System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting information of an startup company; means for transmitting the information of the startup company to a generative AI model; means for analyzing a business plan of the startup company by the generative AI model; means for providing an analytical result by the generative AI model as feedback to the startup company; means for providing an enterprise analytical report created by the generative AI model to an investment agency; and means for managing interaction with the investment agency.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Startups often have groundbreaking ideas and technologies, but face challenges such as difficulty in raising funds and a lack of knowledge about business plans. Meanwhile, investment institutions have difficulty efficiently finding promising investment opportunities, which is time-consuming and costly. To solve these challenges, it is necessary to provide a platform that efficiently connects startups and investment institutions and supports the growth and success of each. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including a means for inputting information about a startup company, a means for transmitting the information about the startup company to a generative AI model, a means for analyzing the business plan of the startup company using the generative AI model, a means for providing the analysis results of the generative AI model as feedback to the startup company, a means for providing a company analysis report created by the generative AI model to an investment institution, and a means for managing interactions with investment institutions, thereby enabling startup companies to receive professional feedback and develop effective business strategies and fundraising, and enabling investment institutions to efficiently find promising investment targets.

[0006] A "startup" is a small, newly established company that aims to grow based on innovative ideas and new technologies.

[0007] "Means for inputting information" refers to the interfaces and devices that startups use to input their business plans, technical details, financial information, etc. into the system.

[0008] A "generative AI model" refers to an algorithm or system that uses machine learning and artificial intelligence techniques to analyze input data and provide specialized feedback and analysis.

[0009] "Means of analysis" refers to the functions and processes for using generative AI models to evaluate and analyze startup companies' business plans, technologies, and financial information from multiple perspectives.

[0010] "Feedback" refers to improvement suggestions and advice provided to startup companies based on the results of analysis by the generative AI model.

[0011] A "Company Analysis Report" is a detailed report created by a generative AI model, including information such as market analysis, competitive analysis, financial forecasts, and risk assessment.

[0012] "Investment institutions" refer to companies and organizations, such as venture capital firms and investment funds, that provide funding to startup companies and support their growth.

[0013] "Evaluation criteria" refers to the standards and indicators used to determine whether a startup company has reached a certain analytical level.

[0014] "Means for managing interactions" refers to mechanisms that provide messaging systems and video conferencing functions to enable startups and investment institutions to communicate efficiently.

[0015] The "Specialized AI Team" is a group of AI systems specializing in various fields, such as technology, law, and corporate strategy, and will utilize their respective expertise to analyze startup companies' business plans from multiple angles. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention provides an innovation platform that effectively connects startup companies with investment institutions, and is a system that uses generative AI to perform professional analysis and feedback. Specific embodiments and program processing for implementing this system are described below.

[0038] System Overview

[0039] This system consists of the following main components:

[0040] 1. User Device

[0041] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[0042] 2. Server

[0043] It plays a central role in receiving data, sending it to generative AI models, and managing and delivering analytical results.

[0044] 3. Generative AI models and specialized AI teams

[0045] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[0046] 4. Investment institution terminal

[0047] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[0048] Program processing

[0049] User registration and information entry

[0050] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[0051] Example: A startup company, XYZ Tech, enters its development plan for a new AI product, registering technical specifications, market forecasts, and budget plans in the system.

[0052] Data analysis and feedback

[0053] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server.

[0054] Example: An AI model evaluates the technical specifications of "XYZ Tech," identifies technical risks and legal issues at the time of market launch, and makes improvement proposals.

[0055] Creation of company analysis reports

[0056] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[0057] Example: The report on "XYZ Tech" includes a technology comparison with key competitors, projected revenue models, and detailed risk factors.

[0058] Identifying investment opportunities

[0059] Investors can access the server and view analytical reports on startups they are interested in. They can use search and filtering functions to find promising investment opportunities in specific industries and technologies.

[0060] Example: An investment institution sees a report on "XYZ Tech," becomes interested in the business plan, and begins detailed due diligence.

[0061] Exchange and growth support

[0062] Users and investment institutions can interact directly within the platform using a messaging system and video conferencing functions, with the server monitoring the interaction and providing additional support when needed.

[0063] Example: XYZ Tech holds a video conference with an investment institution to discuss specific terms of funding and future developments.

[0064] As described above, the system of the present invention can bring benefits to both start-up companies and investment institutions, and can support efficient and effective business development and fundraising.

[0065] The processing flow will be explained below.

[0066] Step 1:

[0067] A user accesses the platform using a device and creates an account, entering the company name, contact information, and business overview as registration information, which is then sent to the server.

[0068] Step 2:

[0069] The user inputs detailed data such as business plans, technical specifications, and financial information via a terminal and sends it to the server, which stores the received information in a database.

[0070] Step 3:

[0071] The server sends the stored startup company information to the generative AI model, which then sends the data to specialized AI teams in each field, who then begin their analysis.

[0072] Step 4:

[0073] The generative AI model analyzes data from technical, legal, and corporate strategy fields and sends the results to a server, which then integrates the results and generates feedback.

[0074] Step 5:

[0075] The server sends the generated feedback to the user's device and notifies the user, who then checks the feedback and uses it to revise and improve their business plan.

[0076] Step 6:

[0077] For startup companies that meet certain criteria, the generative AI model creates a detailed company analysis report and sends it to the server.

[0078] Step 7:

[0079] The server transmits the company analysis report to the user terminal and also makes it accessible to the investment institution terminal.

[0080] Step 8:

[0081] Investors access the platform using their devices to view company analysis reports for startups they are interested in. They can use search and filtering functions to find promising investment targets in specific industries and technologies.

[0082] Step 9:

[0083] If an investment institution shows interest in the startup, the server receives the investment institution's feedback and notifies the user, who then begins interacting with the investment institution.

[0084] Step 10:

[0085] Users and investment institutions communicate directly using messaging systems and video conferencing, with the server recording the conversation and providing additional support from generative AI models where necessary.

[0086] Step 11:

[0087] If the investment goes through and the startup moves towards growth and market expansion, Sarver will monitor the company's progress and provide further support as needed.

[0088] Example 1

[0089] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0090] Modern startups need to connect with investors quickly and efficiently. However, they often miss investment opportunities due to a lack of proper feedback and analysis. Furthermore, startups need a neutral, professional platform to effectively interact with investors. However, such platforms either do not exist or function poorly.

[0091] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0092] In this invention, the server includes a means for inputting startup company information, a means for transmitting the startup company information to a generative AI model, a means for analyzing the startup company's business plan using the generative AI model, a means for providing the startup company with the analysis results of the generative AI model as feedback, a means for providing the investment institution with a company analysis report created by the generative AI model, a means for the investment institution to view and search the startup company's company analysis report, a means for the startup company and the investment institution to interact within the platform, a means for sending a prompt to the generative AI model, and a means for the server to instruct the generative AI model to perform an analysis based on the generated prompt. This allows startup companies to receive professional feedback and analysis, and investment institutions to consider investments based on reliable information. Furthermore, both parties can interact efficiently and obtain optimal investment opportunities.

[0093] A "startup company" is a newly emerging company that aims to develop innovative business models and technologies and provide new value to the market.

[0094] "Investment institutions" are organizations such as financial institutions, venture capital firms, and angel investors that aim to earn profits through investments in startup companies.

[0095] A "generative AI model" is an algorithm or system that uses techniques such as machine learning and deep learning to analyze data and generate feedback, predictions, and suggestions.

[0096] A "prompt sentence" is an instruction sentence entered to instruct the generative AI model to perform specific analysis or evaluation.

[0097] "Feedback" refers to the evaluation, suggestions, and improvements provided by the generative AI model based on the analysis results.

[0098] A "Company Analysis Report" is a detailed analytical document created by a generative AI model by analyzing a startup company's business plan, technical specifications, financial information, etc.

[0099] The "platform" is an online system that allows startups and investment institutions to input information, analyze it, provide feedback, and communicate with each other.

[0100] The "server" is a central processing unit that receives data from user terminals and investment institution terminals, and works with the generative AI model to analyze the data and provide feedback.

[0101] A "user terminal" is a device used by a startup company to input information and receive analysis results.

[0102] An "investor's terminal" is a device used by an investment institution to access the server and view and interact with startup companies' corporate analysis reports.

[0103] The present invention provides an innovation platform that effectively connects startup companies with investment institutions, and provides specialized analysis and feedback using generative AI models. Specific embodiments and program processing for implementing this system are described below.

[0104] System Overview

[0105] The system consists of the following major components:

[0106] 1. User Device

[0107] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[0108] 2. Server

[0109] It plays a central role in receiving data, sending it to generative AI models, and managing and delivering analytical results.

[0110] 3. Generative AI models and specialized AI teams

[0111] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[0112] 4. Investment institution terminal

[0113] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[0114] User registration and information entry

[0115] Users (startup companies) first create an account using their device. They enter their company name, contact information, business overview, etc. into the registration form, and then enter a detailed business plan, technical specifications, and financial information into the system. The entered data is sent to the server and stored in a database.

[0116] Example: A startup company inputs a new business plan on the theme of "application of AI technology" and registers technical specifications, market forecasts, and budget plans in the system. This data is sent to the server by pressing the "Submit" button.

[0117] Data analysis and feedback

[0118] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives and generates feedback. The results are then provided back to the user via the server.

[0119] Example: The server sends the technical specifications for "application of AI technology" to a generative AI model, which generates a prompt saying, "Evaluate technical risk and market risk." The generative AI model performs analysis and returns the results to the server. The server then notifies the user with feedback such as, "Technical risk is low, but market risk is high."

[0120] Creation of company analysis reports

[0121] Based on data that meets certain criteria, the generative AI model creates a company analysis report, including market analysis, competitive analysis, financial forecasts, and risk assessment, and the server then stores the report for viewing by users and investment institutions.

[0122] Example: The report contains detailed information about the market analysis of "AI technology applications," a technical comparison with major competitors, a projected revenue model, and risk factors. The server saves this in PDF format and notifies users and investment institutions.

[0123] Identifying investment opportunities

[0124] Investors can access the server using their terminals to view company analysis reports on startups, and can use search and filtering functions to find promising investment targets in specific industries and technologies.

[0125] Example: An investment institution searches for the keyword "application of AI technology" and obtains and views company analysis reports. For example, an investment institution interested in "technology application" considers specific business plans.

[0126] Exchange and growth support

[0127] Users and investment institutions communicate directly within the platform, which provides messaging and video conferencing functions, and the server monitors communication logs and provides additional support when needed.

[0128] Example: A user holds a video conference with an investment institution to discuss the specifics of funding and future developments. The server records the meeting and makes it available for later reference.

[0129] Examples of prompt statements

[0130] Below are some example prompts to be input to the generative AI model:

[0131] Example prompt 1:

[0132] "AI model, please assess the technical and market risks based on the business plan below and create improvement proposals."

[0133] Business plan: "The startup is developing AI technology that uses cutting-edge machine learning algorithms..."

[0134] Example prompt 2:

[0135] "Please evaluate the AI ​​model and the technical specifications of the startup company, identify legal risks at the time of market launch, and propose countermeasures."

[0136] Technical specifications: "The startup's AI technology features facial and voice recognition..."

[0137] In this way, startups and investment institutions can be effectively connected, enabling business development and fundraising through professional feedback and analysis.

[0138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0139] Step 1:

[0140] User creates an account

[0141] Input: Company name, contact information, business summary.

[0142] A user accesses the system using a user terminal and enters the company name, contact information, and business overview.

[0143] When the user presses the "Send" button, this data is sent to the server.

[0144] Output: User account information is saved in the database.

[0145] Step 2:

[0146] User enters detailed business information

[0147] Input: Business plan, technical specifications, financial information.

[0148] Users use their devices to input business plans, technical specifications, and financial information, such as technical specifications that "use the latest machine learning algorithms," market forecasts, and budget plans.

[0149] When the user has finished entering data, he or she presses the "Submit" button, which sends the entered data to the server.

[0150] Output: The business information is saved in the server database.

[0151] Step 3:

[0152] Send the data to a generative AI model for analysis

[0153] Input: Business plan, technical specifications, financial information.

[0154] The server sends the business information received from the user to the generative AI model, generating a prompt such as "Evaluate technical and market risks."

[0155] The server sends the data along with the prompt to the generative AI model.

[0156] Output: Analysis begins with a generative AI model.

[0157] Step 4:

[0158] Data analysis and feedback generation

[0159] Input: Prompt statement, business plan, technical specifications, financial information.

[0160] Based on the prompt, the generative AI model analyzes the input business information from various perspectives, including technical, legal, and business strategy.

[0161] As a result, analytical data is generated.

[0162] Output: The generative AI model returns the analysis results to the server.

[0163] Step 5:

[0164] Providing Feedback

[0165] Input: Analysis results.

[0166] The server receives the analysis results returned by the generative AI model and provides them to the user as feedback.

[0167] The server notifies the user terminal of the analysis results, such as "Technical risk is low, but market risk is high."

[0168] Output: The feedback is sent to the user.

[0169] Step 6:

[0170] Creation and provision of corporate analysis reports

[0171] Input: Analysis results.

[0172] The server generates data that meets certain criteria and then generates a company analysis report based on the AI ​​model, which includes market analysis, competitive analysis, financial forecasts, and risk assessment.

[0173] The report is saved in PDF format.

[0174] Output: Company analysis reports are provided to users and investment institutions.

[0175] Step 7:

[0176] Viewing reports by investment institutions

[0177] Input: Corporate analysis report.

[0178] Investment institutions can access the server using their terminals to view and search for company analysis reports. For example, if they search for the keyword "application of AI technology," related reports will be displayed.

[0179] Investment institutions can view the reports and find interesting investment opportunities.

[0180] Output: The browsing log is saved on the server.

[0181] Step 8:

[0182] Interaction between users and investment institutions

[0183] Input: A request for interaction.

[0184] Users and investment institutions communicate within the platform using messaging and video conferencing functions.

[0185] The server monitors the logs of interactions and provides additional support as needed.

[0186] Output: A record of the interaction is stored on the server.

[0187] In this way, a system is realized that effectively connects users and investment institutions and allows them to make the most of investment opportunities.

[0188] (Application example 1)

[0189] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0190] It is extremely important for startups to effectively communicate their business plans and technical information to investment institutions and receive appropriate feedback. However, with traditional methods, this process is extremely time-consuming and costly, and opportunities to connect with investment institutions with specialized knowledge are limited. Investors also face challenges in efficiently identifying promising startups. A system that solves these problems and more effectively connects startups and investment institutions is needed.

[0191] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0192] In this invention, the server includes means for inputting information about a startup company, means for transmitting the information about the startup company to a generative AI model, means for analyzing the business plan of the startup company using the generative AI model, means for providing the analysis results of the generative AI model as feedback to the startup company, means for providing a company analysis report created by the generative AI model to an investment institution, means for the investment institution to search and filter the analysis report and identify investment opportunities, means for managing interactions with the investment institution, and means for messaging and video conferencing between the startup company and the investment institution, thereby enabling startup companies and investment institutions to collaborate efficiently and effectively and quickly obtain appropriate feedback and investment opportunities.

[0193] A "startup company" is a newly emerging company that aims for rapid growth in a short period of time based on new business ideas or technologies.

[0194] A "generative AI model" is a collection of algorithms and systems that use artificial intelligence techniques to analyze input data and automatically generate analytical results and proposals.

[0195] The "means for inputting information" is an interface that allows users to register necessary data such as business plans, technical information, and financial information into the system.

[0196] "Means for sending information to the generative AI model" refers to the process for transferring input data to the generative AI model and starting analysis.

[0197] "Means for analyzing business plans" refers to the process of using a generative AI model to evaluate input business plans from technical, financial, market, and other perspectives.

[0198] "Means for providing feedback" refers to the process of returning the results of the analysis by the generative AI model to the user in visual or written form.

[0199] A "Company Analysis Report" is a document summarizing the results of the generative AI model's analysis, including details such as market analysis, competitive analysis, financial forecasts, and risk assessment.

[0200] "Investment institutions" are institutions that provide funding to emerging companies, and primarily include venture capitalists and angel investors.

[0201] "Search and filtering means" refers to a function that allows investment institutions to easily search for company analysis reports based on specific criteria.

[0202] "Means for identifying investment opportunities" refers to the process by which investment institutions find promising investment targets based on the corporate analysis reports of startup companies.

[0203] "Interaction management tools" are the processes that provide and monitor the features, such as messaging and video conferencing, that startups and investment institutions need to communicate effectively.

[0204] "Messaging and video conferencing tools" refers to online tools and platforms that enable startups and investment institutions to exchange information and hold consultations in real time.

[0205] This invention is an innovation system that connects startup companies with investment institutions, and uses generative AI models to analyze startup companies' business plans, technical information, and financial information, and provides analytical results.

[0206] 1. User registration and information entry:

[0207] Users first create an account and enter the necessary data, such as company name, contact information, business overview, technical specifications, and financial information. This information is sent from the front end (e.g., a smartphone app or web interface) to the server, which stores it in a database and prepares it for analysis by the generative AI model.

[0208] 2. Data analysis and feedback:

[0209] The server sends the data entered by the user to a generative AI model. The generative AI model uses AI frameworks such as TensorFlow and PyTorch to analyze the data from multiple perspectives. This analysis includes technical risks, legal issues, and strategic proposals. The server receives the results and provides them to the user as feedback. Specific examples of feedback include "Technical risks: Medium," "Legal issues: Low," and "Strategic proposal: Consider partnerships with overseas companies."

[0210] 3. Creating a company analysis report:

[0211] The company analysis report created by the generative AI model includes detailed market analysis, competitive analysis, financial forecasts, and risk assessment. The server generates and manages this report and provides it through an interface for investment institutions. The report includes specific data and graphs in a format that is easy for investment institutions to understand.

[0212] 4. Search, filter, and identify investment opportunities:

[0213] Investors can use the provided interface to search and filter analytical reports to find promising investment opportunities in specific industries and technologies. For example, they can search for startups based on specific technology areas, geographies, and growth forecasts.

[0214] 5. Interaction and communication:

[0215] The server provides messaging and video conferencing features to help startups and investors collaborate effectively, using real-time communication technologies such as WebRTC. Users and investors can send messages directly to each other or hold online meetings to discuss details.

[0216] Examples of specific examples and prompts

[0217] Examples:

[0218] A startup company, Acme Tech, registers on the app and inputs its business plan and technical information, which the generative AI model analyzes and provides feedback. An investment firm, Venture Capital A, searches and filters Acme Tech's reports, becomes interested, and begins business negotiations via video conference.

[0219] Example prompt sentence:

[0220] User registration prompt: "Please enter your startup name, contact information, business description, technical specifications, and financial information."

[0221] Confirmation prompt: "Are you done entering information? Do you want to move on?"

[0222] Analysis result feedback: "Technical risk is medium, legal challenges are low. Consider partnerships with overseas companies."

[0223] Report Search Prompt: "Search for startups based on specific technology areas and growth forecasts."

[0224] Communication prompts: "Send a message? Start a video conference?"

[0225] The above is a specific embodiment of the present invention. This system enables startup companies and investment institutions to collaborate more effectively and efficiently, enabling them to quickly obtain appropriate feedback and investment opportunities.

[0226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0227] Step 1:

[0228] A user creates an account.

[0229] Input: Company name, contact information, business overview, technical specifications, financial information.

[0230] Operation: The user enters the necessary information on their device (smartphone app or web interface) and sends this data to the server.

[0231] Output: The user's information is saved in the database and an account is created.

[0232] Step 2:

[0233] The server sends the received data to the generative AI model.

[0234] Input: Your business plan, technical details, and financial information.

[0235] How it works: The server extracts user information stored in a database and calls an API to send it to a generative AI model.

[0236] Output: The data is ready for a generative AI model to analyze.

[0237] Step 3:

[0238] A generative AI model analyzes user data.

[0239] Input: User's business plan, technical details, and financial information sent by the server.

[0240] How it works: Generative AI models (using TensorFlow and PyTorch) analyze data to generate technical risks, legal issues, and strategic recommendations.

[0241] Output: Analysis results (e.g., technical risk: medium; legal challenges: low; strategic proposals: consider partnerships with overseas companies).

[0242] Step 4:

[0243] The server provides the analysis results of the generated AI model to the user as feedback.

[0244] Input: Analysis results of the generative AI model.

[0245] How it works: The server receives the analysis results and sends them to the user's device in visual or document form.

[0246] Output: Users receive feedback to improve business plans and assess risks.

[0247] Step 5:

[0248] The server generates a company analysis report and provides it to the investment institution.

[0249] Input: Analysis results of the generative AI model.

[0250] How it works: The server generates a detailed company analysis report based on the analysis results and saves it in the investment institution interface.

[0251] Output: Reports (market analysis, competitive analysis, financial forecasts, risk assessment) are generated and made accessible to investment institutions.

[0252] Step 6:

[0253] Investment institutions search and filter analytical reports.

[0254] Input: Search criteria for the investor (technology area, growth forecast, etc.).

[0255] Operation: Search criteria are entered from the investment institution's terminal, and the server extracts and provides company analysis reports that match the criteria.

[0256] Output: Find analytical reports on startups that are of interest to investment institutions.

[0257] Step 7:

[0258] Investment institutions identify investment opportunities and work with startups.

[0259] Input: Company analysis reports selected by investment institutions.

[0260] How it works: An investment institution selects a particular startup, and the server provides messaging and video conferencing capabilities to facilitate communication between the investment institution and the startup.

[0261] Output: The investment institution and the startup company begin communication, and investment negotiations progress.

[0262] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0263] The present invention provides an innovation platform that effectively connects startup companies and investment institutions, and is a system that utilizes generative AI for professional analysis and feedback, and an emotion engine to recognize and analyze user emotions. Specific embodiments and program processing for implementing this system are described below.

[0264] System Overview

[0265] This system consists of the following main components:

[0266] 1. User Device

[0267] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[0268] 2. Server

[0269] It plays a central role in receiving data, sending it to the generative AI model, managing and providing the analysis results, and also managing the sentiment analysis data from the sentiment engine.

[0270] 3. Generative AI models and specialized AI teams

[0271] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[0272] 4. Emotion Engine

[0273] This system analyzes emotions from user input data and real-time data during interactions, and optimizes feedback and interaction content based on that information.

[0274] 5. Investment institution terminal

[0275] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[0276] Program processing

[0277] User registration and information entry

[0278] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[0279] Example: A startup company, XYZ Tech, enters its development plan for a new AI product, registering technical specifications, market forecasts, and budget plans in the system.

[0280] Data analysis and feedback

[0281] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server. The emotion engine also analyzes user input data and understands emotional responses.

[0282] Example: An AI model evaluates the technical specifications of "XYZ Tech," identifies technical risks and legal issues at the time of market launch, and proposes improvements. At the same time, an emotion engine analyzes the emotional reactions of users based on their input data and reflects them in the feedback.

[0283] Creation of company analysis reports

[0284] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[0285] Example: The report on "XYZ Tech" includes a technology comparison with key competitors, projected revenue models, and detailed risk factors.

[0286] Identifying investment opportunities

[0287] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[0288] Example: An investment institution sees a report on "XYZ Tech," becomes interested in the business plan, and begins detailed due diligence.

[0289] Exchange and growth support

[0290] Users and investment institutions can interact directly within the platform using a messaging system and video conferencing functions. The server monitors the interaction and provides additional support when necessary. The emotion engine analyzes real-time data during the interaction and supports optimal interactions based on the user's emotional state.

[0291] Example: XYZ Tech is holding a video conference with an investment institution to discuss the terms of funding and future developments. During the conversation, the emotion engine monitors the user's stress level and suggests taking a break at the appropriate time.

[0292] As described above, the system of the present invention can bring benefits to both startup companies and investment institutions, supporting efficient and effective business development and fundraising. Furthermore, the introduction of an emotion engine provides optimal support that takes into account the user's emotional state.

[0293] The processing flow will be explained below.

[0294] Step 1:

[0295] A user accesses the platform using a device and creates an account, entering the company name, contact information, and business overview as registration information, which is then sent to the server.

[0296] Step 2:

[0297] A user uses a terminal to input data such as a detailed business plan, technical specifications, and financial information, and then sends it to a server, which stores the information in a database.

[0298] Step 3:

[0299] The server sends the stored startup company information to the generative AI model, which then sends the data to specialized AI teams in each field, who then begin their analysis.

[0300] Step 4:

[0301] The generative AI model analyzes data from technical, legal, and corporate strategy fields and sends the results to a server, which then integrates the results and generates feedback. The emotion engine also analyzes user input data and recognizes emotional states.

[0302] Step 5:

[0303] The server sends the generated feedback and the results of the emotion engine analysis to the user's device and notifies them. The user can then check the feedback and emotion analysis and use it to revise and improve their business plan.

[0304] Step 6:

[0305] For startup companies that meet certain criteria, the generative AI model creates a detailed company analysis report and sends it to the server.

[0306] Step 7:

[0307] The server transmits the company analysis report to the user terminal and also makes it accessible to the investment institution terminal.

[0308] Step 8:

[0309] Investors access the platform using their devices to view company analysis reports for startups they are interested in. They can use search and filtering functions to find promising investment targets in specific industries and technologies.

[0310] Step 9:

[0311] If an investment institution shows interest in the startup, the server receives the investment institution's feedback and notifies the user, who then begins interacting with the investment institution.

[0312] Step 10:

[0313] Users and investment institutions communicate directly using messaging and video conferencing. The server records the content of the interaction and provides additional support from generative AI models as needed. The emotion engine analyzes real-time data during the interaction and monitors the user's emotional state.

[0314] Step 11:

[0315] During the interaction, the emotion engine analyzes the user's emotional state, and if, for example, a high stress level is detected, the server suggests the user take a break and adjusts the progress of the interaction.

[0316] Step 12:

[0317] If the investment is successful and the startup aims to grow and expand into the market, the server will monitor the company's progress and provide further support as needed, taking into account user sentiment analysis data to provide support at the appropriate time.

[0318] Example 2

[0319] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0320] Traditional methods for connecting startups with investment institutions are often inefficient due to information asymmetry and lack of communication. Furthermore, if a startup's business plan, technical specifications, and financial information are not fully analyzed, it can be difficult to provide appropriate feedback or identify investment opportunities. Furthermore, the process often ignores the emotional state of the users involved, which can hinder effective communication.

[0321] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about a startup company; means for transmitting the information about the startup company to a generative AI model; means for multifacetedly analyzing the business plan, technical specifications, and financial information of the startup company using the generative AI model; means for providing the startup company with the analysis results by the generative AI model and the emotion analysis results by the emotion engine as feedback; means for providing the investment institution with a company analysis report created by the generative AI model; and means for managing interactions with the investment institution and analyzing emotion data in real time to support optimal interactions. This enables effective connection between startup companies and investment institutions, information symmetry, and effective communication through real-time emotion analysis.

[0322] A "startup company" is a newly established company that generally has innovative technology or a business model.

[0323] "Means for inputting information" refers to the interface through which users input company information, business plans, technical specifications, financial information, etc. into the system.

[0324] A "generative AI model" is an artificial intelligence model that analyzes input data and generates feedback and improvement suggestions from a multifaceted perspective.

[0325] "Means" refers to a device, system, or method designed to perform a particular function or process.

[0326] "Means for multifaceted analysis of business plans, technical specifications, and financial information" refers to a function that uses a generative AI model to analyze input business plans, technical specifications, and financial information from various perspectives, including technology, law, and corporate strategy.

[0327] The "emotion engine" is a system that analyzes emotions from user input data and real-time interaction data.

[0328] "Means for providing feedback" is a function that presents useful information and improvement suggestions to users based on the analysis results and sentiment analysis results.

[0329] A "Company Analysis Report" is a detailed report that includes market analysis, competitive analysis, financial forecasts, risk assessment, etc. for a startup company.

[0330] "Investment institutions" are companies or organizations that invest in startup companies.

[0331] "Means for managing interactions with investment institutions" refers to functions that support and manage messaging, video conferencing, and other interactions with investment institutions within the platform.

[0332] "Means for analyzing emotional data in real time" refers to a function that analyzes data during interaction in real time, evaluates the user's emotional state, and provides appropriate feedback.

[0333] The present invention is a system that provides a platform that effectively connects startup companies and investment institutions, and uses a generative AI model to perform specialized analysis and feedback, as well as an emotion engine to analyze user emotions.

[0334] System Configuration

[0335] The system consists of the following main components:

[0336] 1. User Device

[0337] A device that allows startup companies to access the system and input business plans, technical specifications, and financial information; typically a PC or smartphone.

[0338] 2. Server

[0339] It serves as a central point for receiving data, sending it to generative AI models, and managing and providing analysis results. It also manages sentiment analysis data from the sentiment engine. This server often uses cloud-based infrastructure (e.g., AWS, Google Cloud, etc.).

[0340] 3. Generative AI models and specialized AI teams

[0341] It is a collection of algorithms and systems that analyze business plans, technical, and financial information and provide feedback from multiple perspectives. Generative AI models use natural language processing (NLP) and machine learning algorithms (e.g., GPT-3, BERT, etc.).

[0342] 4. Emotion Engine

[0343] This system analyzes emotions from user input data and real-time data during interactions, and optimizes feedback and interaction content based on that information. The emotion engine uses an emotion analysis algorithm (e.g., Emotion AI).

[0344] 5. Investment institution terminal

[0345] This is a device that investment institutions use to access the system, view analytical reports on startup companies, and communicate with each other; it is usually a PC or smartphone.

[0346] User registration and information entry

[0347] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[0348] Example: A startup company enters its development plans for a new AI product, registering technical specifications, market forecasts, and budget plans into the system.

[0349] Example prompt: "Please provide a business plan for your new startup company. Please include company name, business overview, technical specifications, and financial information."

[0350] Data analysis and feedback

[0351] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server, and the emotion engine also analyzes the user input data to understand emotional responses.

[0352] Example: A generative AI model evaluates a startup's technical specifications, identifies technical risks and legal issues at the time of market launch, and proposes improvements. At the same time, an emotion engine analyzes the emotional reactions of users based on their input data and reflects them in the feedback.

[0353] Example prompt: "Conduct a go-to-market risk assessment based on the technical specifications. Also, analyze the user's emotional response based on the input data."

[0354] Creation of company analysis reports

[0355] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[0356] Example: The risk assessment report includes a technical comparison with key competitors and details of the expected revenue model.

[0357] Example prompt: "Please prepare a company analysis report. Include market analysis, competitive analysis, financial forecasts, and risk assessment."

[0358] Identifying investment opportunities and supporting exchanges

[0359] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[0360] Example: An investment institution sees a company's report, becomes interested in the business, and begins detailed due diligence.

[0361] Example prompt: "Browse startup company analysis reports and search for investment opportunities in industries and technologies that interest you."

[0362] Users and investment institutions can interact directly within the platform, using a messaging system and video conferencing functions. The server monitors the interaction and provides additional support when needed. An emotion engine analyzes real-time data and supports optimal interactions based on the user's emotional state.

[0363] Example: A startup company holds a video conference with an investment institution to discuss the terms of funding and future developments. An emotion engine monitors the user's stress level and suggests taking a break at the appropriate time.

[0364] Example prompt: "Start a video conference with an investment institution, analyze sentiment data in real time, and suggest breaks at appropriate times."

[0365] In this way, the present invention benefits both start-up companies and investment institutions, supporting efficient and effective business development and fundraising. Furthermore, the introduction of an emotion engine provides optimal support that takes into account the user's emotional state.

[0366] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0367] Step 1:

[0368] User registration and information entry

[0369] Users access the system, create an account, enter their company name, contact information, and business summary in the input form, and then press the "Submit" button to send the information to the server. Detailed business plans, technical specifications, financial information, and other information are also sent to the server.

[0370] Input: Company name, contact details, business overview, business plan, technical specifications, financial information

[0371] Output: Company information and business data stored on the server

[0372] Specific operation: The user accesses the web application on their device, enters the required information into the input form, and clicks the "Submit" button. The data sent from the user device is stored on the server.

[0373] Step 2:

[0374] Data Receipt and Storage

[0375] The server receives the information sent by the user and temporarily stores it in a database, after which it prepares this data to be sent to the generative AI model.

[0376] Input: Information sent from the user's device (company name, contact information, business overview, business plan, technical specifications, financial information)

[0377] Output: Company information and business data stored in a database, ready to be sent to a generative AI model

[0378] Specific operation: On the server side, the data reception API receives the data, stores it in the database, and then converts it into a data format for sending to the generative AI model.

[0379] Step 3:

[0380] Data transmission and analysis

[0381] The server sends the stored data to the generative AI model, which analyzes the data from technical, legal, and corporate strategy perspectives and generates results. At the same time, the emotion engine performs sentiment analysis.

[0382] Input: Company information and business data stored in a database

[0383] Output: Analysis results by the generative AI model and emotion analysis results by the emotion engine

[0384] How it works: The server sends an API request to the generative AI model, which then analyzes the received data. The analysis results are then sent back to the server. The emotion engine then analyzes the emotion data in a similar manner and returns it to the server.

[0385] Step 4:

[0386] Providing Feedback

[0387] The server aggregates the results from the generative AI model and emotion engine and provides it as feedback to the user, displaying the feedback through a dashboard and notification mechanism.

[0388] Input: Analysis results of the generative AI model, emotion analysis results of the emotion engine

[0389] Output: Feedback provided to the user

[0390] What it does: The server aggregates the results from the generative AI model and the emotion engine and generates data to display on the user dashboard. When a user logs in, new feedback is displayed on the dashboard.

[0391] Step 5:

[0392] Creation of company analysis reports

[0393] The generative AI model creates detailed company analysis reports for startups that meet certain criteria, including market analysis, competitive analysis, financial forecasts, and risk assessments. The server stores the report data and makes it accessible to users and investment institutions.

[0394] Input: Analysis results of the generative AI model

[0395] Output: Detailed company analysis report

[0396] Specific operation: The server automatically generates a company analysis report based on the analysis results and saves it in the database. The saved report is provided as a link for users and investment institutions to download.

[0397] Step 6:

[0398] Read reports and identify investment opportunities

[0399] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[0400] Input: Data for company analysis report

[0401] Output: Company analysis report for investment institutions

[0402] Specific operation: Log in to the system on the investment institution's terminal and use the search filter function to search and view reports on startup companies that meet specific criteria. Detailed information on companies that match the criteria will be displayed.

[0403] Step 7:

[0404] Communication and Support

[0405] Users and investment institutions can interact directly within the platform through messaging and video conferencing, with the server managing these interactions, analyzing sentiment data in real time, and providing additional support when needed.

[0406] Input: Real-time data from the interaction and emotion engine analysis data

[0407] Output: Optimize exchanges and support feedback

[0408] How it works: Users and investment institutions start interacting using messaging systems or video conferencing. The emotion engine analyzes participants' emotions in real time, and the server provides appropriate notifications (e.g., break suggestions).

[0409] (Application example 2)

[0410] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0411] In recent years, there has been a growing need to improve engagement between startups and investment institutions. However, conventional platforms have proven difficult to provide appropriate feedback on startups' business plans and technologies. Furthermore, even in brick-and-mortar stores, customer service can be inconsistent, making it particularly difficult to understand customer sentiment and respond appropriately in real time. The present invention aims to provide a system that simultaneously solves these issues.

[0412] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for sending information about the startup company to the generative AI model, means for analyzing the business plan using the generative AI model, and means for providing the startup company with the analysis results of the generative AI model as feedback. This allows the startup company to receive professional feedback in real time. The server also includes means for analyzing customer behavior, comments, and facial expressions, means for providing customer service advice in real time based on the analysis results, and means for analyzing the customer's emotional state and suggesting the optimal response method. This enables advanced responses that correspond to customer emotions to be realized even in physical stores.

[0413] "Means for inputting startup company information" refers to an interface that allows startup companies to input their business plans, technical details, and financial information into the system.

[0414] "Means for sending startup company information to the generative AI model" refers to the process of sending the input startup company information to the generative AI model and providing data for analysis.

[0415] The "means of analyzing the business plan of the startup company using a generative AI model" refers to the process of using a generative AI model to analyze the business plan and technical information of the startup company and generate professional feedback.

[0416] "Means for providing the startup company with the analysis results generated by the generative AI model as feedback" refers to the process of returning the analysis results generated by the generative AI model to the startup company, providing insights for improving business plans and formulating strategies.

[0417] "Means of providing investment institutions with company analysis reports created by generative AI models" refers to the process of sharing detailed analysis reports of startup companies created by generative AI models with investment institutions, providing them with information for making investment decisions.

[0418] "Means for managing interactions with investment institutions" refers to a system that manages information exchanges and meetings between startups and investment institutions, and supports efficient communication.

[0419] "Means for analyzing customer behavior, remarks, and facial expressions" refers to technology that analyzes the behavior, remarks, and facial expressions of customers in physical stores in real time to understand their behavioral patterns and emotions.

[0420] "Means for providing customer service advice in real time based on analysis results" refers to technology that presents appropriate customer service methods to store staff in real time based on the results of an analysis of customer behavior and emotions.

[0421] "Means of analyzing the customer's emotional state and suggesting the most appropriate way to respond" refers to technology that senses the customer's emotions in real time and suggests the most appropriate way to respond to staff.

[0422] The embodiment of the present invention is a system that is based on an innovation platform that connects startup companies and investment institutions, incorporates a generative AI model and a sentiment analysis engine, and further optimizes customer service in physical stores. The specific system configuration and implementation method are described below.

[0423] System Overview

[0424] The system consists of the following major components:

[0425] 1. User Device

[0426] A device that allows startups to enter business plans, technical details, and financial information, and allows investment institutions to view company analysis reports. Examples include PCs and tablets.

[0427] 2. Server

[0428] It plays a central role, analyzing input data using generative AI models and generating feedback. It also performs real-time emotional data analysis using an emotion analysis engine. Specific examples of its use include cloud-based servers such as AWS (Amazon Web Services).

[0429] 3. Generative AI Models

[0430] Algorithms for analyzing startup companies' business plans, technical details, and financial information from multiple angles. For example, OpenAI's GPT model is used.

[0431] 4. Sentiment Analysis Engine

[0432] This system analyzes emotions from user input data and real-time interactions and reflects them in feedback. It uses Affectiva's emotion engine and other technologies.

[0433] 5. Smart Glasses

[0434] Devices used to optimize customer interactions in physical stores. An example is Google Glass.

[0435] Program Description

[0436] The server receives the startup company information entered by the user and sends it to the generative AI model. The generative AI model analyzes the data from perspectives such as technology, corporate strategy, and law, and generates multifaceted feedback. The results of this analysis are provided to the user via the server.

[0437] Furthermore, the server analyzes the customer's behavior, remarks, and facial expressions in real time, and sends the input data to an emotion analysis engine. The emotion analysis engine analyzes the customer's emotional state and displays the optimal response on the smart glasses. This process allows the user to respond more accurately and with consideration for their emotions.

[0438] Specific examples

[0439] Startup companies, which are users, input their business plans and technical information into the system. This data is sent via the server to the generative AI model, where it is analyzed. As a result of the analysis, investment risks and market development proposals are generated and provided to the user as feedback.

[0440] In brick-and-mortar stores, store clerks wearing smart glasses will serve customers. Data on the customer's facial expressions and comments is sent to an emotion analysis engine in real time, and the optimal way to serve them is displayed on the screen of the smart glasses based on the analysis results.

[0441] Prompt Sentence Examples

[0442] Analyze the customer's emotions from their facial expressions and behavior and suggest the best way to respond.

[0443] Customer profile: Name: Taro Yamada, Age: 35, Purchase history: Home appliances, Interests: Smart devices

[0444] Current state: Unhappy expression

[0445] Expected Output: The customer is stressed, so please provide suggestions to help them relax. If possible, provide more details about specific products.

[0446] In this way, the system of the present invention not only strengthens engagement between startup companies and investment institutions, but can also be effective in customer service at physical stores.

[0447] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0448] Step 1:

[0449] A user (startup company) creates an account and enters company information, business plan, technical details, and financial information. The entered data is sent from the user's device to the server. Specifically, the user enters data using a PC or tablet, and this data is sent to the server as an HTTP request.

[0450] Step 2:

[0451] The server sends the received startup company information to the generative AI model. At this time, the data is passed to the generative AI model in an appropriate format. The server then sends the data to the generative AI model (e.g., OpenAI's GPT model) via an API and requests analysis.

[0452] Step 3:

[0453] The generative AI model analyzes business plans, technical details, and financial information to generate multifaceted feedback. It receives startup details as input and produces market forecasts, technology assessments, risk analyses, and other outputs. It uses natural language processing and machine learning algorithms in the analysis process.

[0454] Step 4:

[0455] The server provides the analysis results received from the generative AI model as feedback to the user. Specifically, it notifies the user of the generated report via a web dashboard or email. The feedback includes suggestions for improving the business plan and an assessment of technical risks.

[0456] Step 5:

[0457] An investment institution accesses the system and views the generated company analysis report. The investment institution's terminal sends a request to the server, and the server provides the appropriate report to the investment institution. In this step, the investment institution can efficiently obtain the information of interest by using the report's filtering and search functions.

[0458] Step 6:

[0459] Users (store staff) wear smart glasses and interact with customers. When a customer visits the store, the smart glasses' sensors capture the customer's behavior, remarks, and facial expressions, and the data is sent to the server. The input includes time-stamped behavioral data and facial expression data of the customer.

[0460] Step 7:

[0461] The server sends the received customer data to a sentiment analysis engine, which analyzes customer sentiment in real time and returns the analysis results to the server, including stress levels and satisfaction levels.

[0462] Step 8:

[0463] The server provides real-time customer service advice to store staff based on the analysis results from the emotion analysis engine. The appropriate response is displayed on the smart glasses' display. For example, if a customer appears dissatisfied, "suggestions to help them relax" are presented to the staff.

[0464] Step 9:

[0465] The user (store staff) responds to the customer based on the advice provided, improving customer satisfaction and optimizing the customer experience.

[0466] Through these processing steps, startups receive professional feedback, investment institutions receive detailed company analysis reports, and brick-and-mortar stores can respond appropriately to customer sentiment.

[0467] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0468] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0469] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0470] [Second embodiment]

[0471] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0472] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0473] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0474] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0475] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0476] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0477] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0478] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0479] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0480] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0481] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0482] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0483] The present invention provides an innovation platform that effectively connects startup companies with investment institutions, and is a system that uses generative AI to perform professional analysis and feedback. Specific embodiments and program processing for implementing this system are described below.

[0484] System Overview

[0485] This system consists of the following main components:

[0486] 1. User Device

[0487] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[0488] 2. Server

[0489] It plays a central role in receiving data, sending it to generative AI models, and managing and delivering analytical results.

[0490] 3. Generative AI models and specialized AI teams

[0491] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[0492] 4. Investment institution terminal

[0493] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[0494] Program processing

[0495] User registration and information entry

[0496] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[0497] Example: A startup company, XYZ Tech, enters its development plan for a new AI product, registering technical specifications, market forecasts, and budget plans in the system.

[0498] Data analysis and feedback

[0499] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server.

[0500] Example: An AI model evaluates the technical specifications of "XYZ Tech," identifies technical risks and legal issues at the time of market launch, and makes improvement proposals.

[0501] Creation of company analysis reports

[0502] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[0503] Example: The report on "XYZ Tech" includes a technology comparison with key competitors, projected revenue models, and detailed risk factors.

[0504] Identifying investment opportunities

[0505] Investors can access the server and view analytical reports on startups they are interested in. They can use search and filtering functions to find promising investment opportunities in specific industries and technologies.

[0506] Example: An investment institution sees a report on "XYZ Tech," becomes interested in the business plan, and begins detailed due diligence.

[0507] Exchange and growth support

[0508] Users and investment institutions can interact directly within the platform using a messaging system and video conferencing functions, with the server monitoring the interaction and providing additional support when needed.

[0509] Example: XYZ Tech holds a video conference with an investment institution to discuss specific terms of funding and future developments.

[0510] As described above, the system of the present invention can bring benefits to both start-up companies and investment institutions, and can support efficient and effective business development and fundraising.

[0511] The processing flow will be explained below.

[0512] Step 1:

[0513] A user accesses the platform using a device and creates an account, entering the company name, contact information, and business overview as registration information, which is then sent to the server.

[0514] Step 2:

[0515] The user inputs detailed data such as business plans, technical specifications, and financial information via a terminal and sends it to the server, which stores the received information in a database.

[0516] Step 3:

[0517] The server sends the stored startup company information to the generative AI model, which then sends the data to specialized AI teams in each field, who then begin their analysis.

[0518] Step 4:

[0519] The generative AI model analyzes data from technical, legal, and corporate strategy fields and sends the results to a server, which then integrates the results and generates feedback.

[0520] Step 5:

[0521] The server sends the generated feedback to the user's device and notifies the user, who then checks the feedback and uses it to revise and improve their business plan.

[0522] Step 6:

[0523] For startup companies that meet certain criteria, the generative AI model creates a detailed company analysis report and sends it to the server.

[0524] Step 7:

[0525] The server transmits the company analysis report to the user terminal and also makes it accessible to the investment institution terminal.

[0526] Step 8:

[0527] Investors access the platform using their devices to view company analysis reports for startups they are interested in. They can use search and filtering functions to find promising investment targets in specific industries and technologies.

[0528] Step 9:

[0529] If an investment institution shows interest in the startup, the server receives the investment institution's feedback and notifies the user, who then begins interacting with the investment institution.

[0530] Step 10:

[0531] Users and investment institutions communicate directly using messaging systems and video conferencing, with the server recording the conversation and providing additional support from generative AI models where necessary.

[0532] Step 11:

[0533] If the investment goes through and the startup moves towards growth and market expansion, Sarver will monitor the company's progress and provide further support as needed.

[0534] Example 1

[0535] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0536] Modern startups need to connect with investors quickly and efficiently. However, they often miss investment opportunities due to a lack of proper feedback and analysis. Furthermore, startups need a neutral, professional platform to effectively interact with investors. However, such platforms either do not exist or function poorly.

[0537] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0538] In this invention, the server includes a means for inputting startup company information, a means for transmitting the startup company information to a generative AI model, a means for analyzing the startup company's business plan using the generative AI model, a means for providing the startup company with the analysis results of the generative AI model as feedback, a means for providing the investment institution with a company analysis report created by the generative AI model, a means for the investment institution to view and search the startup company's company analysis report, a means for the startup company and the investment institution to interact within the platform, a means for sending a prompt to the generative AI model, and a means for the server to instruct the generative AI model to perform an analysis based on the generated prompt. This allows startup companies to receive professional feedback and analysis, and investment institutions to consider investments based on reliable information. Furthermore, both parties can interact efficiently and obtain optimal investment opportunities.

[0539] A "startup company" is a newly emerging company that aims to develop innovative business models and technologies and provide new value to the market.

[0540] "Investment institutions" are organizations such as financial institutions, venture capital firms, and angel investors that aim to earn profits through investments in startup companies.

[0541] A "generative AI model" is an algorithm or system that uses techniques such as machine learning and deep learning to analyze data and generate feedback, predictions, and suggestions.

[0542] A "prompt sentence" is an instruction sentence entered to instruct the generative AI model to perform specific analysis or evaluation.

[0543] "Feedback" refers to the evaluation, suggestions, and improvements provided by the generative AI model based on the analysis results.

[0544] A "Company Analysis Report" is a detailed analytical document created by a generative AI model by analyzing a startup company's business plan, technical specifications, financial information, etc.

[0545] The "platform" is an online system that allows startups and investment institutions to input information, analyze it, provide feedback, and communicate with each other.

[0546] The "server" is a central processing unit that receives data from user terminals and investment institution terminals, and works with the generative AI model to analyze the data and provide feedback.

[0547] A "user terminal" is a device used by a startup company to input information and receive analysis results.

[0548] An "investor's terminal" is a device used by an investment institution to access the server and view and interact with startup companies' corporate analysis reports.

[0549] The present invention provides an innovation platform that effectively connects startup companies with investment institutions, and provides specialized analysis and feedback using generative AI models. Specific embodiments and program processing for implementing this system are described below.

[0550] System Overview

[0551] The system consists of the following major components:

[0552] 1. User Device

[0553] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[0554] 2. Server

[0555] It plays a central role in receiving data, sending it to generative AI models, and managing and delivering analytical results.

[0556] 3. Generative AI models and specialized AI teams

[0557] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[0558] 4. Investment institution terminal

[0559] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[0560] User registration and information entry

[0561] Users (startup companies) first create an account using their device. They enter their company name, contact information, business overview, etc. into the registration form, and then enter a detailed business plan, technical specifications, and financial information into the system. The entered data is sent to the server and stored in a database.

[0562] Example: A startup company inputs a new business plan on the theme of "application of AI technology" and registers technical specifications, market forecasts, and budget plans in the system. This data is sent to the server by pressing the "Submit" button.

[0563] Data analysis and feedback

[0564] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives and generates feedback. The results are then provided back to the user via the server.

[0565] Example: The server sends the technical specifications for "application of AI technology" to a generative AI model, which generates a prompt saying, "Evaluate technical risk and market risk." The generative AI model performs analysis and returns the results to the server. The server then notifies the user with feedback such as, "Technical risk is low, but market risk is high."

[0566] Creation of company analysis reports

[0567] Based on data that meets certain criteria, the generative AI model creates a company analysis report, including market analysis, competitive analysis, financial forecasts, and risk assessment, and the server then stores the report for viewing by users and investment institutions.

[0568] Example: The report contains detailed information about the market analysis of "AI technology applications," a technical comparison with major competitors, a projected revenue model, and risk factors. The server saves this in PDF format and notifies users and investment institutions.

[0569] Identifying investment opportunities

[0570] Investors can access the server using their terminals to view company analysis reports on startups, and can use search and filtering functions to find promising investment targets in specific industries and technologies.

[0571] Example: An investment institution searches for the keyword "application of AI technology" and obtains and views company analysis reports. For example, an investment institution interested in "technology application" considers specific business plans.

[0572] Exchange and growth support

[0573] Users and investment institutions communicate directly within the platform, which provides messaging and video conferencing functions, and the server monitors communication logs and provides additional support when needed.

[0574] Example: A user holds a video conference with an investment institution to discuss the specifics of funding and future developments. The server records the meeting and makes it available for later reference.

[0575] Examples of prompt statements

[0576] Below are some example prompts to be input to the generative AI model:

[0577] Example prompt 1:

[0578] "AI model, please assess the technical and market risks based on the business plan below and create improvement proposals."

[0579] Business plan: "The startup is developing AI technology that uses cutting-edge machine learning algorithms..."

[0580] Example prompt 2:

[0581] "Please evaluate the AI ​​model and the technical specifications of the startup company, identify legal risks at the time of market launch, and propose countermeasures."

[0582] Technical specifications: "The startup's AI technology features facial and voice recognition..."

[0583] In this way, startups and investment institutions can be effectively connected, enabling business development and fundraising through professional feedback and analysis.

[0584] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0585] Step 1:

[0586] User creates an account

[0587] Input: Company name, contact information, business summary.

[0588] A user accesses the system using a user terminal and enters the company name, contact information, and business overview.

[0589] When the user presses the "Send" button, this data is sent to the server.

[0590] Output: User account information is saved in the database.

[0591] Step 2:

[0592] User enters detailed business information

[0593] Input: Business plan, technical specifications, financial information.

[0594] Users use their devices to input business plans, technical specifications, and financial information, such as technical specifications that "use the latest machine learning algorithms," market forecasts, and budget plans.

[0595] When the user has finished entering data, he or she presses the "Submit" button, which sends the entered data to the server.

[0596] Output: The business information is saved in the server database.

[0597] Step 3:

[0598] Send the data to a generative AI model for analysis

[0599] Input: Business plan, technical specifications, financial information.

[0600] The server sends the business information received from the user to the generative AI model, generating a prompt such as "Evaluate technical and market risks."

[0601] The server sends the data along with the prompt to the generative AI model.

[0602] Output: Analysis begins with a generative AI model.

[0603] Step 4:

[0604] Data analysis and feedback generation

[0605] Input: Prompt statement, business plan, technical specifications, financial information.

[0606] Based on the prompt, the generative AI model analyzes the input business information from various perspectives, including technical, legal, and business strategy.

[0607] As a result, analytical data is generated.

[0608] Output: The generative AI model returns the analysis results to the server.

[0609] Step 5:

[0610] Providing Feedback

[0611] Input: Analysis results.

[0612] The server receives the analysis results returned by the generative AI model and provides them to the user as feedback.

[0613] The server notifies the user terminal of the analysis results, such as "Technical risk is low, but market risk is high."

[0614] Output: The feedback is sent to the user.

[0615] Step 6:

[0616] Creation and provision of corporate analysis reports

[0617] Input: Analysis results.

[0618] The server generates data that meets certain criteria and then generates a company analysis report based on the AI ​​model, which includes market analysis, competitive analysis, financial forecasts, and risk assessment.

[0619] The report is saved in PDF format.

[0620] Output: Company analysis reports are provided to users and investment institutions.

[0621] Step 7:

[0622] Viewing reports by investment institutions

[0623] Input: Corporate analysis report.

[0624] Investment institutions can access the server using their terminals to view and search for company analysis reports. For example, if they search for the keyword "application of AI technology," related reports will be displayed.

[0625] Investment institutions can view the reports and find interesting investment opportunities.

[0626] Output: The browsing log is saved on the server.

[0627] Step 8:

[0628] Interaction between users and investment institutions

[0629] Input: A request for interaction.

[0630] Users and investment institutions communicate within the platform using messaging and video conferencing functions.

[0631] The server monitors the logs of interactions and provides additional support as needed.

[0632] Output: A record of the interaction is stored on the server.

[0633] In this way, a system is realized that effectively connects users and investment institutions and allows them to make the most of investment opportunities.

[0634] (Application example 1)

[0635] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0636] It is extremely important for startups to effectively communicate their business plans and technical information to investment institutions and receive appropriate feedback. However, with traditional methods, this process is extremely time-consuming and costly, and opportunities to connect with investment institutions with specialized knowledge are limited. Investors also face challenges in efficiently identifying promising startups. A system that solves these problems and more effectively connects startups and investment institutions is needed.

[0637] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0638] In this invention, the server includes means for inputting information about a startup company, means for transmitting the information about the startup company to a generative AI model, means for analyzing the business plan of the startup company using the generative AI model, means for providing the analysis results of the generative AI model as feedback to the startup company, means for providing a company analysis report created by the generative AI model to an investment institution, means for the investment institution to search and filter the analysis report and identify investment opportunities, means for managing interactions with the investment institution, and means for messaging and video conferencing between the startup company and the investment institution, thereby enabling startup companies and investment institutions to collaborate efficiently and effectively and quickly obtain appropriate feedback and investment opportunities.

[0639] A "startup company" is a newly emerging company that aims for rapid growth in a short period of time based on new business ideas or technologies.

[0640] A "generative AI model" is a collection of algorithms and systems that use artificial intelligence techniques to analyze input data and automatically generate analytical results and proposals.

[0641] The "means for inputting information" is an interface that allows users to register necessary data such as business plans, technical information, and financial information into the system.

[0642] "Means for sending information to the generative AI model" refers to the process for transferring input data to the generative AI model and starting analysis.

[0643] "Means for analyzing business plans" refers to the process of using a generative AI model to evaluate input business plans from technical, financial, market, and other perspectives.

[0644] "Means for providing feedback" refers to the process of returning the results of the analysis by the generative AI model to the user in visual or written form.

[0645] A "Company Analysis Report" is a document summarizing the results of the generative AI model's analysis, including details such as market analysis, competitive analysis, financial forecasts, and risk assessment.

[0646] "Investment institutions" are institutions that provide funding to emerging companies, and primarily include venture capitalists and angel investors.

[0647] "Search and filtering means" refers to a function that allows investment institutions to easily search for company analysis reports based on specific criteria.

[0648] "Means for identifying investment opportunities" refers to the process by which investment institutions find promising investment targets based on the corporate analysis reports of startup companies.

[0649] "Interaction management tools" are the processes that provide and monitor the features, such as messaging and video conferencing, that startups and investment institutions need to communicate effectively.

[0650] "Messaging and video conferencing tools" refers to online tools and platforms that enable startups and investment institutions to exchange information and hold consultations in real time.

[0651] This invention is an innovation system that connects startup companies with investment institutions, and uses generative AI models to analyze startup companies' business plans, technical information, and financial information, and provides analytical results.

[0652] 1. User registration and information entry:

[0653] Users first create an account and enter the necessary data, such as company name, contact information, business overview, technical specifications, and financial information. This information is sent from the front end (e.g., a smartphone app or web interface) to the server, which stores it in a database and prepares it for analysis by the generative AI model.

[0654] 2. Data analysis and feedback:

[0655] The server sends the data entered by the user to a generative AI model. The generative AI model uses AI frameworks such as TensorFlow and PyTorch to analyze the data from multiple perspectives. This analysis includes technical risks, legal issues, and strategic proposals. The server receives the results and provides them to the user as feedback. Specific examples of feedback include "Technical risks: Medium," "Legal issues: Low," and "Strategic proposal: Consider partnerships with overseas companies."

[0656] 3. Creating a company analysis report:

[0657] The company analysis report created by the generative AI model includes detailed market analysis, competitive analysis, financial forecasts, and risk assessment. The server generates and manages this report and provides it through an interface for investment institutions. The report includes specific data and graphs in a format that is easy for investment institutions to understand.

[0658] 4. Search, filter, and identify investment opportunities:

[0659] Investors can use the provided interface to search and filter analytical reports to find promising investment opportunities in specific industries and technologies. For example, they can search for startups based on specific technology areas, geographies, and growth forecasts.

[0660] 5. Interaction and communication:

[0661] The server provides messaging and video conferencing features to help startups and investors collaborate effectively, using real-time communication technologies such as WebRTC. Users and investors can send messages directly to each other or hold online meetings to discuss details.

[0662] Examples of specific examples and prompts

[0663] Examples:

[0664] A startup company, Acme Tech, registers on the app and inputs its business plan and technical information, which the generative AI model analyzes and provides feedback. An investment firm, Venture Capital A, searches and filters Acme Tech's reports, becomes interested, and begins business negotiations via video conference.

[0665] Example prompt sentence:

[0666] User registration prompt: "Please enter your startup name, contact information, business description, technical specifications, and financial information."

[0667] Confirmation prompt: "Are you done entering information? Do you want to move on?"

[0668] Analysis result feedback: "Technical risk is medium, legal challenges are low. Consider partnerships with overseas companies."

[0669] Report Search Prompt: "Search for startups based on specific technology areas and growth forecasts."

[0670] Communication prompts: "Send a message? Start a video conference?"

[0671] The above is a specific embodiment of the present invention. This system enables startup companies and investment institutions to collaborate more effectively and efficiently, enabling them to quickly obtain appropriate feedback and investment opportunities.

[0672] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0673] Step 1:

[0674] A user creates an account.

[0675] Input: Company name, contact information, business overview, technical specifications, financial information.

[0676] Operation: The user enters the necessary information on their device (smartphone app or web interface) and sends this data to the server.

[0677] Output: The user's information is saved in the database and an account is created.

[0678] Step 2:

[0679] The server sends the received data to the generative AI model.

[0680] Input: Your business plan, technical details, and financial information.

[0681] How it works: The server extracts user information stored in a database and calls an API to send it to a generative AI model.

[0682] Output: The data is ready for a generative AI model to analyze.

[0683] Step 3:

[0684] A generative AI model analyzes user data.

[0685] Input: User's business plan, technical details, and financial information sent by the server.

[0686] How it works: Generative AI models (using TensorFlow and PyTorch) analyze data to generate technical risks, legal issues, and strategic recommendations.

[0687] Output: Analysis results (e.g., technical risk: medium; legal challenges: low; strategic proposals: consider partnerships with overseas companies).

[0688] Step 4:

[0689] The server provides the analysis results of the generated AI model to the user as feedback.

[0690] Input: Analysis results of the generative AI model.

[0691] How it works: The server receives the analysis results and sends them to the user's device in visual or document form.

[0692] Output: Users receive feedback to improve business plans and assess risks.

[0693] Step 5:

[0694] The server generates a company analysis report and provides it to the investment institution.

[0695] Input: Analysis results of the generative AI model.

[0696] How it works: The server generates a detailed company analysis report based on the analysis results and saves it in the investment institution interface.

[0697] Output: Reports (market analysis, competitive analysis, financial forecasts, risk assessment) are generated and made accessible to investment institutions.

[0698] Step 6:

[0699] Investment institutions search and filter analytical reports.

[0700] Input: Search criteria for the investor (technology area, growth forecast, etc.).

[0701] Operation: Search criteria are entered from the investment institution's terminal, and the server extracts and provides company analysis reports that match the criteria.

[0702] Output: Find analytical reports on startups that are of interest to investment institutions.

[0703] Step 7:

[0704] Investment institutions identify investment opportunities and work with startups.

[0705] Input: Company analysis reports selected by investment institutions.

[0706] How it works: An investment institution selects a particular startup, and the server provides messaging and video conferencing capabilities to facilitate communication between the investment institution and the startup.

[0707] Output: The investment institution and the startup company begin communication, and investment negotiations progress.

[0708] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0709] The present invention provides an innovation platform that effectively connects startup companies and investment institutions, and is a system that utilizes generative AI for professional analysis and feedback, and an emotion engine to recognize and analyze user emotions. Specific embodiments and program processing for implementing this system are described below.

[0710] System Overview

[0711] This system consists of the following main components:

[0712] 1. User Device

[0713] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[0714] 2. Server

[0715] It plays a central role in receiving data, sending it to the generative AI model, managing and providing the analysis results, and also managing the sentiment analysis data from the sentiment engine.

[0716] 3. Generative AI models and specialized AI teams

[0717] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[0718] 4. Emotion Engine

[0719] This system analyzes emotions from user input data and real-time data during interactions, and optimizes feedback and interaction content based on that information.

[0720] 5. Investment institution terminal

[0721] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[0722] Program processing

[0723] User registration and information entry

[0724] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[0725] Example: A startup company, XYZ Tech, enters its development plan for a new AI product, registering technical specifications, market forecasts, and budget plans in the system.

[0726] Data analysis and feedback

[0727] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server. The emotion engine also analyzes user input data and understands emotional responses.

[0728] Example: An AI model evaluates the technical specifications of "XYZ Tech," identifies technical risks and legal issues at the time of market launch, and proposes improvements. At the same time, an emotion engine analyzes the emotional reactions of users based on their input data and reflects them in the feedback.

[0729] Creation of company analysis reports

[0730] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[0731] Example: The report on "XYZ Tech" includes a technology comparison with key competitors, projected revenue models, and detailed risk factors.

[0732] Identifying investment opportunities

[0733] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[0734] Example: An investment institution sees a report on "XYZ Tech," becomes interested in the business plan, and begins detailed due diligence.

[0735] Exchange and growth support

[0736] Users and investment institutions can interact directly within the platform using a messaging system and video conferencing functions. The server monitors the interaction and provides additional support when necessary. The emotion engine analyzes real-time data during the interaction and supports optimal interactions based on the user's emotional state.

[0737] Example: XYZ Tech is holding a video conference with an investment institution to discuss the terms of funding and future developments. During the conversation, the emotion engine monitors the user's stress level and suggests taking a break at the appropriate time.

[0738] As described above, the system of the present invention can bring benefits to both startup companies and investment institutions, supporting efficient and effective business development and fundraising. Furthermore, the introduction of an emotion engine provides optimal support that takes into account the user's emotional state.

[0739] The processing flow will be explained below.

[0740] Step 1:

[0741] A user accesses the platform using a device and creates an account, entering the company name, contact information, and business overview as registration information, which is then sent to the server.

[0742] Step 2:

[0743] A user uses a terminal to input data such as a detailed business plan, technical specifications, and financial information, and then sends it to a server, which stores the information in a database.

[0744] Step 3:

[0745] The server sends the stored startup company information to the generative AI model, which then sends the data to specialized AI teams in each field, who then begin their analysis.

[0746] Step 4:

[0747] The generative AI model analyzes data from technical, legal, and corporate strategy fields and sends the results to a server, which then integrates the results and generates feedback. The emotion engine also analyzes user input data and recognizes emotional states.

[0748] Step 5:

[0749] The server sends the generated feedback and the results of the emotion engine analysis to the user's device and notifies them. The user can then check the feedback and emotion analysis and use it to revise and improve their business plan.

[0750] Step 6:

[0751] For startup companies that meet certain criteria, the generative AI model creates a detailed company analysis report and sends it to the server.

[0752] Step 7:

[0753] The server transmits the company analysis report to the user terminal and also makes it accessible to the investment institution terminal.

[0754] Step 8:

[0755] Investors access the platform using their devices to view company analysis reports for startups they are interested in. They can use search and filtering functions to find promising investment targets in specific industries and technologies.

[0756] Step 9:

[0757] If an investment institution shows interest in the startup, the server receives the investment institution's feedback and notifies the user, who then begins interacting with the investment institution.

[0758] Step 10:

[0759] Users and investment institutions communicate directly using messaging and video conferencing. The server records the content of the interaction and provides additional support from generative AI models as needed. The emotion engine analyzes real-time data during the interaction and monitors the user's emotional state.

[0760] Step 11:

[0761] During the interaction, the emotion engine analyzes the user's emotional state, and if, for example, a high stress level is detected, the server suggests the user take a break and adjusts the progress of the interaction.

[0762] Step 12:

[0763] If the investment is successful and the startup aims to grow and expand into the market, the server will monitor the company's progress and provide further support as needed, taking into account user sentiment analysis data to provide support at the appropriate time.

[0764] Example 2

[0765] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0766] Traditional methods for connecting startups with investment institutions are often inefficient due to information asymmetry and lack of communication. Furthermore, if a startup's business plan, technical specifications, and financial information are not fully analyzed, it can be difficult to provide appropriate feedback or identify investment opportunities. Furthermore, the process often ignores the emotional state of the users involved, which can hinder effective communication.

[0767] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about a startup company; means for transmitting the information about the startup company to a generative AI model; means for multifacetedly analyzing the business plan, technical specifications, and financial information of the startup company using the generative AI model; means for providing the startup company with the analysis results by the generative AI model and the emotion analysis results by the emotion engine as feedback; means for providing the investment institution with a company analysis report created by the generative AI model; and means for managing interactions with the investment institution and analyzing emotion data in real time to support optimal interactions. This enables effective connection between startup companies and investment institutions, information symmetry, and effective communication through real-time emotion analysis.

[0768] A "startup company" is a newly established company that generally has innovative technology or a business model.

[0769] "Means for inputting information" refers to the interface through which users input company information, business plans, technical specifications, financial information, etc. into the system.

[0770] A "generative AI model" is an artificial intelligence model that analyzes input data and generates feedback and improvement suggestions from a multifaceted perspective.

[0771] "Means" refers to a device, system, or method designed to perform a particular function or process.

[0772] "Means for multifaceted analysis of business plans, technical specifications, and financial information" refers to a function that uses a generative AI model to analyze input business plans, technical specifications, and financial information from various perspectives, including technology, law, and corporate strategy.

[0773] The "emotion engine" is a system that analyzes emotions from user input data and real-time interaction data.

[0774] "Means for providing feedback" is a function that presents useful information and improvement suggestions to users based on the analysis results and sentiment analysis results.

[0775] A "Company Analysis Report" is a detailed report that includes market analysis, competitive analysis, financial forecasts, risk assessment, etc. for a startup company.

[0776] "Investment institutions" are companies or organizations that invest in startup companies.

[0777] "Means for managing interactions with investment institutions" refers to functions that support and manage messaging, video conferencing, and other interactions with investment institutions within the platform.

[0778] "Means for analyzing emotional data in real time" refers to a function that analyzes data during interaction in real time, evaluates the user's emotional state, and provides appropriate feedback.

[0779] The present invention is a system that provides a platform that effectively connects startup companies and investment institutions, and uses a generative AI model to perform specialized analysis and feedback, as well as an emotion engine to analyze user emotions.

[0780] System Configuration

[0781] The system consists of the following main components:

[0782] 1. User Device

[0783] A device that allows startup companies to access the system and input business plans, technical specifications, and financial information; typically a PC or smartphone.

[0784] 2. Server

[0785] It serves as a central point for receiving data, sending it to generative AI models, and managing and providing analysis results. It also manages sentiment analysis data from the sentiment engine. This server often uses cloud-based infrastructure (e.g., AWS, Google Cloud, etc.).

[0786] 3. Generative AI models and specialized AI teams

[0787] It is a collection of algorithms and systems that analyze business plans, technical, and financial information and provide feedback from multiple perspectives. Generative AI models use natural language processing (NLP) and machine learning algorithms (e.g., GPT-3, BERT, etc.).

[0788] 4. Emotion Engine

[0789] This system analyzes emotions from user input data and real-time data during interactions, and optimizes feedback and interaction content based on that information. The emotion engine uses an emotion analysis algorithm (e.g., Emotion AI).

[0790] 5. Investment institution terminal

[0791] This is a device that investment institutions use to access the system, view analytical reports on startup companies, and communicate with each other; it is usually a PC or smartphone.

[0792] User registration and information entry

[0793] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[0794] Example: A startup company enters its development plans for a new AI product, registering technical specifications, market forecasts, and budget plans into the system.

[0795] Example prompt: "Please provide a business plan for your new startup company. Please include company name, business overview, technical specifications, and financial information."

[0796] Data analysis and feedback

[0797] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server, and the emotion engine also analyzes the user input data to understand emotional responses.

[0798] Example: A generative AI model evaluates a startup's technical specifications, identifies technical risks and legal issues at the time of market launch, and proposes improvements. At the same time, an emotion engine analyzes the emotional reactions of users based on their input data and reflects them in the feedback.

[0799] Example prompt: "Conduct a go-to-market risk assessment based on the technical specifications. Also, analyze the user's emotional response based on the input data."

[0800] Creation of company analysis reports

[0801] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[0802] Example: The risk assessment report includes a technical comparison with key competitors and details of the expected revenue model.

[0803] Example prompt: "Please prepare a company analysis report. Include market analysis, competitive analysis, financial forecasts, and risk assessment."

[0804] Identifying investment opportunities and supporting exchanges

[0805] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[0806] Example: An investment institution sees a company's report, becomes interested in the business, and begins detailed due diligence.

[0807] Example prompt: "Browse startup company analysis reports and search for investment opportunities in industries and technologies that interest you."

[0808] Users and investment institutions can interact directly within the platform, using a messaging system and video conferencing functions. The server monitors the interaction and provides additional support when needed. An emotion engine analyzes real-time data and supports optimal interactions based on the user's emotional state.

[0809] Example: A startup company holds a video conference with an investment institution to discuss the terms of funding and future developments. An emotion engine monitors the user's stress level and suggests taking a break at the appropriate time.

[0810] Example prompt: "Start a video conference with an investment institution, analyze sentiment data in real time, and suggest breaks at appropriate times."

[0811] In this way, the present invention benefits both start-up companies and investment institutions, supporting efficient and effective business development and fundraising. Furthermore, the introduction of an emotion engine provides optimal support that takes into account the user's emotional state.

[0812] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0813] Step 1:

[0814] User registration and information entry

[0815] Users access the system, create an account, enter their company name, contact information, and business summary in the input form, and then press the "Submit" button to send the information to the server. Detailed business plans, technical specifications, financial information, and other information are also sent to the server.

[0816] Input: Company name, contact details, business overview, business plan, technical specifications, financial information

[0817] Output: Company information and business data stored on the server

[0818] Specific operation: The user accesses the web application on their device, enters the required information into the input form, and clicks the "Submit" button. The data sent from the user device is stored on the server.

[0819] Step 2:

[0820] Data Receipt and Storage

[0821] The server receives the information sent by the user and temporarily stores it in a database, after which it prepares this data to be sent to the generative AI model.

[0822] Input: Information sent from the user's device (company name, contact information, business overview, business plan, technical specifications, financial information)

[0823] Output: Company information and business data stored in a database, ready to be sent to a generative AI model

[0824] Specific operation: On the server side, the data reception API receives the data, stores it in the database, and then converts it into a data format for sending to the generative AI model.

[0825] Step 3:

[0826] Data transmission and analysis

[0827] The server sends the stored data to the generative AI model, which analyzes the data from technical, legal, and corporate strategy perspectives and generates results. At the same time, the emotion engine performs sentiment analysis.

[0828] Input: Company information and business data stored in a database

[0829] Output: Analysis results by the generative AI model and emotion analysis results by the emotion engine

[0830] How it works: The server sends an API request to the generative AI model, which then analyzes the received data. The analysis results are then sent back to the server. The emotion engine then analyzes the emotion data in a similar manner and returns it to the server.

[0831] Step 4:

[0832] Providing Feedback

[0833] The server aggregates the results from the generative AI model and emotion engine and provides it as feedback to the user, displaying the feedback through a dashboard and notification mechanism.

[0834] Input: Analysis results of the generative AI model, emotion analysis results of the emotion engine

[0835] Output: Feedback provided to the user

[0836] What it does: The server aggregates the results from the generative AI model and the emotion engine and generates data to display on the user dashboard. When a user logs in, new feedback is displayed on the dashboard.

[0837] Step 5:

[0838] Creation of company analysis reports

[0839] The generative AI model creates detailed company analysis reports for startups that meet certain criteria, including market analysis, competitive analysis, financial forecasts, and risk assessments. The server stores the report data and makes it accessible to users and investment institutions.

[0840] Input: Analysis results of the generative AI model

[0841] Output: Detailed company analysis report

[0842] Specific operation: The server automatically generates a company analysis report based on the analysis results and saves it in the database. The saved report is provided as a link for users and investment institutions to download.

[0843] Step 6:

[0844] Read reports and identify investment opportunities

[0845] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[0846] Input: Data for company analysis report

[0847] Output: Company analysis report for investment institutions

[0848] Specific operation: Log in to the system on the investment institution's terminal and use the search filter function to search and view reports on startup companies that meet specific criteria. Detailed information on companies that match the criteria will be displayed.

[0849] Step 7:

[0850] Communication and Support

[0851] Users and investment institutions can interact directly within the platform through messaging and video conferencing, with the server managing these interactions, analyzing sentiment data in real time, and providing additional support when needed.

[0852] Input: Real-time data from the interaction and emotion engine analysis data

[0853] Output: Optimize exchanges and support feedback

[0854] How it works: Users and investment institutions start interacting using messaging systems or video conferencing. The emotion engine analyzes participants' emotions in real time, and the server provides appropriate notifications (e.g., break suggestions).

[0855] (Application example 2)

[0856] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0857] In recent years, there has been a growing need to improve engagement between startups and investment institutions. However, conventional platforms have proven difficult to provide appropriate feedback on startups' business plans and technologies. Furthermore, even in brick-and-mortar stores, customer service can be inconsistent, making it particularly difficult to understand customer sentiment and respond appropriately in real time. The present invention aims to provide a system that simultaneously solves these issues.

[0858] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for sending information about the startup company to the generative AI model, means for analyzing the business plan using the generative AI model, and means for providing the startup company with the analysis results of the generative AI model as feedback. This allows the startup company to receive professional feedback in real time. The server also includes means for analyzing customer behavior, comments, and facial expressions, means for providing customer service advice in real time based on the analysis results, and means for analyzing the customer's emotional state and suggesting the optimal response method. This enables advanced responses that correspond to customer emotions to be realized even in physical stores.

[0859] "Means for inputting startup company information" refers to an interface that allows startup companies to input their business plans, technical details, and financial information into the system.

[0860] "Means for sending startup company information to the generative AI model" refers to the process of sending the input startup company information to the generative AI model and providing data for analysis.

[0861] The "means of analyzing the business plan of the startup company using a generative AI model" refers to the process of using a generative AI model to analyze the business plan and technical information of the startup company and generate professional feedback.

[0862] "Means for providing the startup company with the analysis results generated by the generative AI model as feedback" refers to the process of returning the analysis results generated by the generative AI model to the startup company, providing insights for improving business plans and formulating strategies.

[0863] "Means of providing investment institutions with company analysis reports created by generative AI models" refers to the process of sharing detailed analysis reports of startup companies created by generative AI models with investment institutions, providing them with information for making investment decisions.

[0864] "Means for managing interactions with investment institutions" refers to a system that manages information exchanges and meetings between startups and investment institutions, and supports efficient communication.

[0865] "Means for analyzing customer behavior, remarks, and facial expressions" refers to technology that analyzes the behavior, remarks, and facial expressions of customers in physical stores in real time to understand their behavioral patterns and emotions.

[0866] "Means for providing customer service advice in real time based on analysis results" refers to technology that presents appropriate customer service methods to store staff in real time based on the results of an analysis of customer behavior and emotions.

[0867] "Means of analyzing the customer's emotional state and suggesting the most appropriate way to respond" refers to technology that senses the customer's emotions in real time and suggests the most appropriate way to respond to staff.

[0868] The embodiment of the present invention is a system that is based on an innovation platform that connects startup companies and investment institutions, incorporates a generative AI model and a sentiment analysis engine, and further optimizes customer service in physical stores. The specific system configuration and implementation method are described below.

[0869] System Overview

[0870] The system consists of the following major components:

[0871] 1. User Device

[0872] A device that allows startups to enter business plans, technical details, and financial information, and allows investment institutions to view company analysis reports. Examples include PCs and tablets.

[0873] 2. Server

[0874] It plays a central role, analyzing input data using generative AI models and generating feedback. It also performs real-time emotional data analysis using an emotion analysis engine. Specific examples of its use include cloud-based servers such as AWS (Amazon Web Services).

[0875] 3. Generative AI Models

[0876] Algorithms for analyzing startup companies' business plans, technical details, and financial information from multiple angles. For example, OpenAI's GPT model is used.

[0877] 4. Sentiment Analysis Engine

[0878] This system analyzes emotions from user input data and real-time interactions and reflects them in feedback. It uses Affectiva's emotion engine and other technologies.

[0879] 5. Smart Glasses

[0880] Devices used to optimize customer interactions in physical stores. An example is Google Glass.

[0881] Program Description

[0882] The server receives the startup company information entered by the user and sends it to the generative AI model. The generative AI model analyzes the data from perspectives such as technology, corporate strategy, and law, and generates multifaceted feedback. The results of this analysis are provided to the user via the server.

[0883] Furthermore, the server analyzes the customer's behavior, remarks, and facial expressions in real time, and sends the input data to an emotion analysis engine. The emotion analysis engine analyzes the customer's emotional state and displays the optimal response on the smart glasses. This process allows the user to respond more accurately and with consideration for their emotions.

[0884] Specific examples

[0885] Startup companies, which are users, input their business plans and technical information into the system. This data is sent via the server to the generative AI model, where it is analyzed. As a result of the analysis, investment risks and market development proposals are generated and provided to the user as feedback.

[0886] In brick-and-mortar stores, store clerks wearing smart glasses will serve customers. Data on the customer's facial expressions and comments is sent to an emotion analysis engine in real time, and the optimal way to serve them is displayed on the screen of the smart glasses based on the analysis results.

[0887] Prompt Sentence Examples

[0888] Analyze the customer's emotions from their facial expressions and behavior and suggest the best way to respond.

[0889] Customer profile: Name: Taro Yamada, Age: 35, Purchase history: Home appliances, Interests: Smart devices

[0890] Current state: Unhappy expression

[0891] Expected Output: The customer is stressed, so please provide suggestions to help them relax. If possible, provide more details about specific products.

[0892] In this way, the system of the present invention not only strengthens engagement between startup companies and investment institutions, but can also be effective in customer service at physical stores.

[0893] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0894] Step 1:

[0895] A user (startup company) creates an account and enters company information, business plan, technical details, and financial information. The entered data is sent from the user's device to the server. Specifically, the user enters data using a PC or tablet, and this data is sent to the server as an HTTP request.

[0896] Step 2:

[0897] The server sends the received startup company information to the generative AI model. At this time, the data is passed to the generative AI model in an appropriate format. The server then sends the data to the generative AI model (e.g., OpenAI's GPT model) via an API and requests analysis.

[0898] Step 3:

[0899] The generative AI model analyzes business plans, technical details, and financial information to generate multifaceted feedback. It receives startup details as input and produces market forecasts, technology assessments, risk analyses, and other outputs. It uses natural language processing and machine learning algorithms in the analysis process.

[0900] Step 4:

[0901] The server provides the analysis results received from the generative AI model as feedback to the user. Specifically, it notifies the user of the generated report via a web dashboard or email. The feedback includes suggestions for improving the business plan and an assessment of technical risks.

[0902] Step 5:

[0903] An investment institution accesses the system and views the generated company analysis report. The investment institution's terminal sends a request to the server, and the server provides the appropriate report to the investment institution. In this step, the investment institution can efficiently obtain the information of interest by using the report's filtering and search functions.

[0904] Step 6:

[0905] Users (store staff) wear smart glasses and interact with customers. When a customer visits the store, the smart glasses' sensors capture the customer's behavior, remarks, and facial expressions, and the data is sent to the server. The input includes time-stamped behavioral data and facial expression data of the customer.

[0906] Step 7:

[0907] The server sends the received customer data to a sentiment analysis engine, which analyzes customer sentiment in real time and returns the analysis results to the server, including stress levels and satisfaction levels.

[0908] Step 8:

[0909] The server provides real-time customer service advice to store staff based on the analysis results from the emotion analysis engine. The appropriate response is displayed on the smart glasses' display. For example, if a customer appears dissatisfied, "suggestions to help them relax" are presented to the staff.

[0910] Step 9:

[0911] The user (store staff) responds to the customer based on the advice provided, improving customer satisfaction and optimizing the customer experience.

[0912] Through these processing steps, startups receive professional feedback, investment institutions receive detailed company analysis reports, and brick-and-mortar stores can respond appropriately to customer sentiment.

[0913] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0914] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0915] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0916] [Third embodiment]

[0917] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0918] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0919] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0920] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0921] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0922] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0923] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0924] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0925] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0926] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0927] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0928] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0929] The present invention provides an innovation platform that effectively connects startup companies with investment institutions, and is a system that uses generative AI to perform professional analysis and feedback. Specific embodiments and program processing for implementing this system are described below.

[0930] System Overview

[0931] This system consists of the following main components:

[0932] 1. User Device

[0933] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[0934] 2. Server

[0935] It plays a central role in receiving data, sending it to generative AI models, and managing and delivering analytical results.

[0936] 3. Generative AI models and specialized AI teams

[0937] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[0938] 4. Investment institution terminal

[0939] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[0940] Program processing

[0941] User registration and information entry

[0942] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[0943] Example: A startup company, XYZ Tech, enters its development plan for a new AI product, registering technical specifications, market forecasts, and budget plans in the system.

[0944] Data analysis and feedback

[0945] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server.

[0946] Example: An AI model evaluates the technical specifications of "XYZ Tech," identifies technical risks and legal issues at the time of market launch, and makes improvement proposals.

[0947] Creation of company analysis reports

[0948] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[0949] Example: The report on "XYZ Tech" includes a technology comparison with key competitors, projected revenue models, and detailed risk factors.

[0950] Identifying investment opportunities

[0951] Investors can access the server and view analytical reports on startups they are interested in. They can use search and filtering functions to find promising investment opportunities in specific industries and technologies.

[0952] Example: An investment institution sees a report on "XYZ Tech," becomes interested in the business plan, and begins detailed due diligence.

[0953] Exchange and growth support

[0954] Users and investment institutions can interact directly within the platform using a messaging system and video conferencing functions, with the server monitoring the interaction and providing additional support when needed.

[0955] Example: XYZ Tech holds a video conference with an investment institution to discuss specific terms of funding and future developments.

[0956] As described above, the system of the present invention can bring benefits to both start-up companies and investment institutions, and can support efficient and effective business development and fundraising.

[0957] The processing flow will be explained below.

[0958] Step 1:

[0959] A user accesses the platform using a device and creates an account, entering the company name, contact information, and business overview as registration information, which is then sent to the server.

[0960] Step 2:

[0961] The user inputs detailed data such as business plans, technical specifications, and financial information via a terminal and sends it to the server, which stores the received information in a database.

[0962] Step 3:

[0963] The server sends the stored startup company information to the generative AI model, which then sends the data to specialized AI teams in each field, who then begin their analysis.

[0964] Step 4:

[0965] The generative AI model analyzes data from technical, legal, and corporate strategy fields and sends the results to a server, which then integrates the results and generates feedback.

[0966] Step 5:

[0967] The server sends the generated feedback to the user's device and notifies the user, who then checks the feedback and uses it to revise and improve their business plan.

[0968] Step 6:

[0969] For startup companies that meet certain criteria, the generative AI model creates a detailed company analysis report and sends it to the server.

[0970] Step 7:

[0971] The server transmits the company analysis report to the user terminal and also makes it accessible to the investment institution terminal.

[0972] Step 8:

[0973] Investors access the platform using their devices to view company analysis reports for startups they are interested in. They can use search and filtering functions to find promising investment targets in specific industries and technologies.

[0974] Step 9:

[0975] If an investment institution shows interest in the startup, the server receives the investment institution's feedback and notifies the user, who then begins interacting with the investment institution.

[0976] Step 10:

[0977] Users and investment institutions communicate directly using messaging systems and video conferencing, with the server recording the conversation and providing additional support from generative AI models where necessary.

[0978] Step 11:

[0979] If the investment goes through and the startup moves towards growth and market expansion, Sarver will monitor the company's progress and provide further support as needed.

[0980] Example 1

[0981] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0982] Modern startups need to connect with investors quickly and efficiently. However, they often miss investment opportunities due to a lack of proper feedback and analysis. Furthermore, startups need a neutral, professional platform to effectively interact with investors. However, such platforms either do not exist or function poorly.

[0983] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0984] In this invention, the server includes a means for inputting startup company information, a means for transmitting the startup company information to a generative AI model, a means for analyzing the startup company's business plan using the generative AI model, a means for providing the startup company with the analysis results of the generative AI model as feedback, a means for providing the investment institution with a company analysis report created by the generative AI model, a means for the investment institution to view and search the startup company's company analysis report, a means for the startup company and the investment institution to interact within the platform, a means for sending a prompt to the generative AI model, and a means for the server to instruct the generative AI model to perform an analysis based on the generated prompt. This allows startup companies to receive professional feedback and analysis, and investment institutions to consider investments based on reliable information. Furthermore, both parties can interact efficiently and obtain optimal investment opportunities.

[0985] A "startup company" is a newly emerging company that aims to develop innovative business models and technologies and provide new value to the market.

[0986] "Investment institutions" are organizations such as financial institutions, venture capital firms, and angel investors that aim to earn profits through investments in startup companies.

[0987] A "generative AI model" is an algorithm or system that uses techniques such as machine learning and deep learning to analyze data and generate feedback, predictions, and suggestions.

[0988] A "prompt sentence" is an instruction sentence entered to instruct the generative AI model to perform specific analysis or evaluation.

[0989] "Feedback" refers to the evaluation, suggestions, and improvements provided by the generative AI model based on the analysis results.

[0990] A "Company Analysis Report" is a detailed analytical document created by a generative AI model by analyzing a startup company's business plan, technical specifications, financial information, etc.

[0991] The "platform" is an online system that allows startups and investment institutions to input information, analyze it, provide feedback, and communicate with each other.

[0992] The "server" is a central processing unit that receives data from user terminals and investment institution terminals, and works with the generative AI model to analyze the data and provide feedback.

[0993] A "user terminal" is a device used by a startup company to input information and receive analysis results.

[0994] An "investor's terminal" is a device used by an investment institution to access the server and view and interact with startup companies' corporate analysis reports.

[0995] The present invention provides an innovation platform that effectively connects startup companies with investment institutions, and provides specialized analysis and feedback using generative AI models. Specific embodiments and program processing for implementing this system are described below.

[0996] System Overview

[0997] The system consists of the following major components:

[0998] 1. User Device

[0999] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[1000] 2. Server

[1001] It plays a central role in receiving data, sending it to generative AI models, and managing and delivering analytical results.

[1002] 3. Generative AI models and specialized AI teams

[1003] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[1004] 4. Investment institution terminal

[1005] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[1006] User registration and information entry

[1007] Users (startup companies) first create an account using their device. They enter their company name, contact information, business overview, etc. into the registration form, and then enter a detailed business plan, technical specifications, and financial information into the system. The entered data is sent to the server and stored in a database.

[1008] Example: A startup company inputs a new business plan on the theme of "application of AI technology" and registers technical specifications, market forecasts, and budget plans in the system. This data is sent to the server by pressing the "Submit" button.

[1009] Data analysis and feedback

[1010] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives and generates feedback. The results are then provided back to the user via the server.

[1011] Example: The server sends the technical specifications for "application of AI technology" to a generative AI model, which generates a prompt saying, "Evaluate technical risk and market risk." The generative AI model performs analysis and returns the results to the server. The server then notifies the user with feedback such as, "Technical risk is low, but market risk is high."

[1012] Creation of company analysis reports

[1013] Based on data that meets certain criteria, the generative AI model creates a company analysis report, including market analysis, competitive analysis, financial forecasts, and risk assessment, and the server then stores the report for viewing by users and investment institutions.

[1014] Example: The report contains detailed information about the market analysis of "AI technology applications," a technical comparison with major competitors, a projected revenue model, and risk factors. The server saves this in PDF format and notifies users and investment institutions.

[1015] Identifying investment opportunities

[1016] Investors can access the server using their terminals to view company analysis reports on startups, and can use search and filtering functions to find promising investment targets in specific industries and technologies.

[1017] Example: An investment institution searches for the keyword "application of AI technology" and obtains and views company analysis reports. For example, an investment institution interested in "technology application" considers specific business plans.

[1018] Exchange and growth support

[1019] Users and investment institutions communicate directly within the platform, which provides messaging and video conferencing functions, and the server monitors communication logs and provides additional support when needed.

[1020] Example: A user holds a video conference with an investment institution to discuss the specifics of funding and future developments. The server records the meeting and makes it available for later reference.

[1021] Examples of prompt statements

[1022] Below are some example prompts to be input to the generative AI model:

[1023] Example prompt 1:

[1024] "AI model, please assess the technical and market risks based on the business plan below and create improvement proposals."

[1025] Business plan: "The startup is developing AI technology that uses cutting-edge machine learning algorithms..."

[1026] Example prompt 2:

[1027] "Please evaluate the AI ​​model and the technical specifications of the startup company, identify legal risks at the time of market launch, and propose countermeasures."

[1028] Technical specifications: "The startup's AI technology features facial and voice recognition..."

[1029] In this way, startups and investment institutions can be effectively connected, enabling business development and fundraising through professional feedback and analysis.

[1030] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1031] Step 1:

[1032] User creates an account

[1033] Input: Company name, contact information, business summary.

[1034] A user accesses the system using a user terminal and enters the company name, contact information, and business overview.

[1035] When the user presses the "Send" button, this data is sent to the server.

[1036] Output: User account information is saved in the database.

[1037] Step 2:

[1038] User enters detailed business information

[1039] Input: Business plan, technical specifications, financial information.

[1040] Users use their devices to input business plans, technical specifications, and financial information, such as technical specifications that "use the latest machine learning algorithms," market forecasts, and budget plans.

[1041] When the user has finished entering data, he or she presses the "Submit" button, which sends the entered data to the server.

[1042] Output: The business information is saved in the server database.

[1043] Step 3:

[1044] Send the data to a generative AI model for analysis

[1045] Input: Business plan, technical specifications, financial information.

[1046] The server sends the business information received from the user to the generative AI model, generating a prompt such as "Evaluate technical and market risks."

[1047] The server sends the data along with the prompt to the generative AI model.

[1048] Output: Analysis begins with a generative AI model.

[1049] Step 4:

[1050] Data analysis and feedback generation

[1051] Input: Prompt statement, business plan, technical specifications, financial information.

[1052] Based on the prompt, the generative AI model analyzes the input business information from various perspectives, including technical, legal, and business strategy.

[1053] As a result, analytical data is generated.

[1054] Output: The generative AI model returns the analysis results to the server.

[1055] Step 5:

[1056] Providing Feedback

[1057] Input: Analysis results.

[1058] The server receives the analysis results returned by the generative AI model and provides them to the user as feedback.

[1059] The server notifies the user terminal of the analysis results, such as "Technical risk is low, but market risk is high."

[1060] Output: The feedback is sent to the user.

[1061] Step 6:

[1062] Creation and provision of corporate analysis reports

[1063] Input: Analysis results.

[1064] The server generates data that meets certain criteria and then generates a company analysis report based on the AI ​​model, which includes market analysis, competitive analysis, financial forecasts, and risk assessment.

[1065] The report is saved in PDF format.

[1066] Output: Company analysis reports are provided to users and investment institutions.

[1067] Step 7:

[1068] Viewing reports by investment institutions

[1069] Input: Corporate analysis report.

[1070] Investment institutions can access the server using their terminals to view and search for company analysis reports. For example, if they search for the keyword "application of AI technology," related reports will be displayed.

[1071] Investment institutions can view the reports and find interesting investment opportunities.

[1072] Output: The browsing log is saved on the server.

[1073] Step 8:

[1074] Interaction between users and investment institutions

[1075] Input: A request for interaction.

[1076] Users and investment institutions communicate within the platform using messaging and video conferencing functions.

[1077] The server monitors the logs of interactions and provides additional support as needed.

[1078] Output: A record of the interaction is stored on the server.

[1079] In this way, a system is realized that effectively connects users and investment institutions and allows them to make the most of investment opportunities.

[1080] (Application example 1)

[1081] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1082] It is extremely important for startups to effectively communicate their business plans and technical information to investment institutions and receive appropriate feedback. However, with traditional methods, this process is extremely time-consuming and costly, and opportunities to connect with investment institutions with specialized knowledge are limited. Investors also face challenges in efficiently identifying promising startups. A system that solves these problems and more effectively connects startups and investment institutions is needed.

[1083] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1084] In this invention, the server includes means for inputting information about a startup company, means for transmitting the information about the startup company to a generative AI model, means for analyzing the business plan of the startup company using the generative AI model, means for providing the analysis results of the generative AI model as feedback to the startup company, means for providing a company analysis report created by the generative AI model to an investment institution, means for the investment institution to search and filter the analysis report and identify investment opportunities, means for managing interactions with the investment institution, and means for messaging and video conferencing between the startup company and the investment institution, thereby enabling startup companies and investment institutions to collaborate efficiently and effectively and quickly obtain appropriate feedback and investment opportunities.

[1085] A "startup company" is a newly emerging company that aims for rapid growth in a short period of time based on new business ideas or technologies.

[1086] A "generative AI model" is a collection of algorithms and systems that use artificial intelligence techniques to analyze input data and automatically generate analytical results and proposals.

[1087] The "means for inputting information" is an interface that allows users to register necessary data such as business plans, technical information, and financial information into the system.

[1088] "Means for sending information to the generative AI model" refers to the process for transferring input data to the generative AI model and starting analysis.

[1089] "Means for analyzing business plans" refers to the process of using a generative AI model to evaluate input business plans from technical, financial, market, and other perspectives.

[1090] "Means for providing feedback" refers to the process of returning the results of the analysis by the generative AI model to the user in visual or written form.

[1091] A "Company Analysis Report" is a document summarizing the results of the generative AI model's analysis, including details such as market analysis, competitive analysis, financial forecasts, and risk assessment.

[1092] "Investment institutions" are institutions that provide funding to emerging companies, and primarily include venture capitalists and angel investors.

[1093] "Search and filtering means" refers to a function that allows investment institutions to easily search for company analysis reports based on specific criteria.

[1094] "Means for identifying investment opportunities" refers to the process by which investment institutions find promising investment targets based on the corporate analysis reports of startup companies.

[1095] "Interaction management tools" are the processes that provide and monitor the features, such as messaging and video conferencing, that startups and investment institutions need to communicate effectively.

[1096] "Messaging and video conferencing tools" refers to online tools and platforms that enable startups and investment institutions to exchange information and hold consultations in real time.

[1097] This invention is an innovation system that connects startup companies with investment institutions, and uses generative AI models to analyze startup companies' business plans, technical information, and financial information, and provides analytical results.

[1098] 1. User registration and information entry:

[1099] Users first create an account and enter the necessary data, such as company name, contact information, business overview, technical specifications, and financial information. This information is sent from the front end (e.g., a smartphone app or web interface) to the server, which stores it in a database and prepares it for analysis by the generative AI model.

[1100] 2. Data analysis and feedback:

[1101] The server sends the data entered by the user to a generative AI model. The generative AI model uses AI frameworks such as TensorFlow and PyTorch to analyze the data from multiple perspectives. This analysis includes technical risks, legal issues, and strategic proposals. The server receives the results and provides them to the user as feedback. Specific examples of feedback include "Technical risks: Medium," "Legal issues: Low," and "Strategic proposal: Consider partnerships with overseas companies."

[1102] 3. Creating a company analysis report:

[1103] The company analysis report created by the generative AI model includes detailed market analysis, competitive analysis, financial forecasts, and risk assessment. The server generates and manages this report and provides it through an interface for investment institutions. The report includes specific data and graphs in a format that is easy for investment institutions to understand.

[1104] 4. Search, filter, and identify investment opportunities:

[1105] Investors can use the provided interface to search and filter analytical reports to find promising investment opportunities in specific industries and technologies. For example, they can search for startups based on specific technology areas, geographies, and growth forecasts.

[1106] 5. Interaction and communication:

[1107] The server provides messaging and video conferencing features to help startups and investors collaborate effectively, using real-time communication technologies such as WebRTC. Users and investors can send messages directly to each other or hold online meetings to discuss details.

[1108] Examples of specific examples and prompts

[1109] Examples:

[1110] A startup company, Acme Tech, registers on the app and inputs its business plan and technical information, which the generative AI model analyzes and provides feedback. An investment firm, Venture Capital A, searches and filters Acme Tech's reports, becomes interested, and begins business negotiations via video conference.

[1111] Example prompt sentence:

[1112] User registration prompt: "Please enter your startup name, contact information, business description, technical specifications, and financial information."

[1113] Confirmation prompt: "Are you done entering information? Do you want to move on?"

[1114] Analysis result feedback: "Technical risk is medium, legal challenges are low. Consider partnerships with overseas companies."

[1115] Report Search Prompt: "Search for startups based on specific technology areas and growth forecasts."

[1116] Communication prompts: "Send a message? Start a video conference?"

[1117] The above is a specific embodiment of the present invention. This system enables startup companies and investment institutions to collaborate more effectively and efficiently, enabling them to quickly obtain appropriate feedback and investment opportunities.

[1118] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1119] Step 1:

[1120] A user creates an account.

[1121] Input: Company name, contact information, business overview, technical specifications, financial information.

[1122] Operation: The user enters the necessary information on their device (smartphone app or web interface) and sends this data to the server.

[1123] Output: The user's information is saved in the database and an account is created.

[1124] Step 2:

[1125] The server sends the received data to the generative AI model.

[1126] Input: Your business plan, technical details, and financial information.

[1127] How it works: The server extracts user information stored in a database and calls an API to send it to a generative AI model.

[1128] Output: The data is ready for a generative AI model to analyze.

[1129] Step 3:

[1130] A generative AI model analyzes user data.

[1131] Input: User's business plan, technical details, and financial information sent by the server.

[1132] How it works: Generative AI models (using TensorFlow and PyTorch) analyze data to generate technical risks, legal issues, and strategic recommendations.

[1133] Output: Analysis results (e.g., technical risk: medium; legal challenges: low; strategic proposals: consider partnerships with overseas companies).

[1134] Step 4:

[1135] The server provides the analysis results of the generated AI model to the user as feedback.

[1136] Input: Analysis results of the generative AI model.

[1137] How it works: The server receives the analysis results and sends them to the user's device in visual or document form.

[1138] Output: Users receive feedback to improve business plans and assess risks.

[1139] Step 5:

[1140] The server generates a company analysis report and provides it to the investment institution.

[1141] Input: Analysis results of the generative AI model.

[1142] How it works: The server generates a detailed company analysis report based on the analysis results and saves it in the investment institution interface.

[1143] Output: Reports (market analysis, competitive analysis, financial forecasts, risk assessment) are generated and made accessible to investment institutions.

[1144] Step 6:

[1145] Investment institutions search and filter analytical reports.

[1146] Input: Search criteria for the investor (technology area, growth forecast, etc.).

[1147] Operation: Search criteria are entered from the investment institution's terminal, and the server extracts and provides company analysis reports that match the criteria.

[1148] Output: Find analytical reports on startups that are of interest to investment institutions.

[1149] Step 7:

[1150] Investment institutions identify investment opportunities and work with startups.

[1151] Input: Company analysis reports selected by investment institutions.

[1152] How it works: An investment institution selects a particular startup, and the server provides messaging and video conferencing capabilities to facilitate communication between the investment institution and the startup.

[1153] Output: The investment institution and the startup company begin communication, and investment negotiations progress.

[1154] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1155] The present invention provides an innovation platform that effectively connects startup companies and investment institutions, and is a system that utilizes generative AI for professional analysis and feedback, and an emotion engine to recognize and analyze user emotions. Specific embodiments and program processing for implementing this system are described below.

[1156] System Overview

[1157] This system consists of the following main components:

[1158] 1. User Device

[1159] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[1160] 2. Server

[1161] It plays a central role in receiving data, sending it to the generative AI model, managing and providing the analysis results, and also managing the sentiment analysis data from the sentiment engine.

[1162] 3. Generative AI models and specialized AI teams

[1163] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[1164] 4. Emotion Engine

[1165] This system analyzes emotions from user input data and real-time data during interactions, and optimizes feedback and interaction content based on that information.

[1166] 5. Investment institution terminal

[1167] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[1168] Program processing

[1169] User registration and information entry

[1170] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[1171] Example: A startup company, XYZ Tech, enters its development plan for a new AI product, registering technical specifications, market forecasts, and budget plans in the system.

[1172] Data analysis and feedback

[1173] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server. The emotion engine also analyzes user input data and understands emotional responses.

[1174] Example: An AI model evaluates the technical specifications of "XYZ Tech," identifies technical risks and legal issues at the time of market launch, and proposes improvements. At the same time, an emotion engine analyzes the emotional reactions of users based on their input data and reflects them in the feedback.

[1175] Creation of company analysis reports

[1176] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[1177] Example: The report on "XYZ Tech" includes a technology comparison with key competitors, projected revenue models, and detailed risk factors.

[1178] Identifying investment opportunities

[1179] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[1180] Example: An investment institution sees a report on "XYZ Tech," becomes interested in the business plan, and begins detailed due diligence.

[1181] Exchange and growth support

[1182] Users and investment institutions can interact directly within the platform using a messaging system and video conferencing functions. The server monitors the interaction and provides additional support when necessary. The emotion engine analyzes real-time data during the interaction and supports optimal interactions based on the user's emotional state.

[1183] Example: XYZ Tech is holding a video conference with an investment institution to discuss the terms of funding and future developments. During the conversation, the emotion engine monitors the user's stress level and suggests taking a break at the appropriate time.

[1184] As described above, the system of the present invention can bring benefits to both startup companies and investment institutions, supporting efficient and effective business development and fundraising. Furthermore, the introduction of an emotion engine provides optimal support that takes into account the user's emotional state.

[1185] The processing flow will be explained below.

[1186] Step 1:

[1187] A user accesses the platform using a device and creates an account, entering the company name, contact information, and business overview as registration information, which is then sent to the server.

[1188] Step 2:

[1189] A user uses a terminal to input data such as a detailed business plan, technical specifications, and financial information, and then sends it to a server, which stores the information in a database.

[1190] Step 3:

[1191] The server sends the stored startup company information to the generative AI model, which then sends the data to specialized AI teams in each field, who then begin their analysis.

[1192] Step 4:

[1193] The generative AI model analyzes data from technical, legal, and corporate strategy fields and sends the results to a server, which then integrates the results and generates feedback. The emotion engine also analyzes user input data and recognizes emotional states.

[1194] Step 5:

[1195] The server sends the generated feedback and the results of the emotion engine analysis to the user's device and notifies them. The user can then check the feedback and emotion analysis and use it to revise and improve their business plan.

[1196] Step 6:

[1197] For startup companies that meet certain criteria, the generative AI model creates a detailed company analysis report and sends it to the server.

[1198] Step 7:

[1199] The server transmits the company analysis report to the user terminal and also makes it accessible to the investment institution terminal.

[1200] Step 8:

[1201] Investors access the platform using their devices to view company analysis reports for startups they are interested in. They can use search and filtering functions to find promising investment targets in specific industries and technologies.

[1202] Step 9:

[1203] If an investment institution shows interest in the startup, the server receives the investment institution's feedback and notifies the user, who then begins interacting with the investment institution.

[1204] Step 10:

[1205] Users and investment institutions communicate directly using messaging and video conferencing. The server records the content of the interaction and provides additional support from generative AI models as needed. The emotion engine analyzes real-time data during the interaction and monitors the user's emotional state.

[1206] Step 11:

[1207] During the interaction, the emotion engine analyzes the user's emotional state, and if, for example, a high stress level is detected, the server suggests the user take a break and adjusts the progress of the interaction.

[1208] Step 12:

[1209] If the investment is successful and the startup aims to grow and expand into the market, the server will monitor the company's progress and provide further support as needed, taking into account user sentiment analysis data to provide support at the appropriate time.

[1210] Example 2

[1211] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1212] Traditional methods for connecting startups with investment institutions are often inefficient due to information asymmetry and lack of communication. Furthermore, if a startup's business plan, technical specifications, and financial information are not fully analyzed, it can be difficult to provide appropriate feedback or identify investment opportunities. Furthermore, the process often ignores the emotional state of the users involved, which can hinder effective communication.

[1213] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about a startup company; means for transmitting the information about the startup company to a generative AI model; means for multifacetedly analyzing the business plan, technical specifications, and financial information of the startup company using the generative AI model; means for providing the startup company with the analysis results by the generative AI model and the emotion analysis results by the emotion engine as feedback; means for providing the investment institution with a company analysis report created by the generative AI model; and means for managing interactions with the investment institution and analyzing emotion data in real time to support optimal interactions. This enables effective connection between startup companies and investment institutions, information symmetry, and effective communication through real-time emotion analysis.

[1214] A "startup company" is a newly established company that generally has innovative technology or a business model.

[1215] "Means for inputting information" refers to the interface through which users input company information, business plans, technical specifications, financial information, etc. into the system.

[1216] A "generative AI model" is an artificial intelligence model that analyzes input data and generates feedback and improvement suggestions from a multifaceted perspective.

[1217] "Means" refers to a device, system, or method designed to perform a particular function or process.

[1218] "Means for multifaceted analysis of business plans, technical specifications, and financial information" refers to a function that uses a generative AI model to analyze input business plans, technical specifications, and financial information from various perspectives, including technology, law, and corporate strategy.

[1219] The "emotion engine" is a system that analyzes emotions from user input data and real-time interaction data.

[1220] "Means for providing feedback" is a function that presents useful information and improvement suggestions to users based on the analysis results and sentiment analysis results.

[1221] A "Company Analysis Report" is a detailed report that includes market analysis, competitive analysis, financial forecasts, risk assessment, etc. for a startup company.

[1222] "Investment institutions" are companies or organizations that invest in startup companies.

[1223] "Means for managing interactions with investment institutions" refers to functions that support and manage messaging, video conferencing, and other interactions with investment institutions within the platform.

[1224] "Means for analyzing emotional data in real time" refers to a function that analyzes data during interaction in real time, evaluates the user's emotional state, and provides appropriate feedback.

[1225] The present invention is a system that provides a platform that effectively connects startup companies and investment institutions, and uses a generative AI model to perform specialized analysis and feedback, as well as an emotion engine to analyze user emotions.

[1226] System Configuration

[1227] The system consists of the following main components:

[1228] 1. User Device

[1229] A device that allows startup companies to access the system and input business plans, technical specifications, and financial information; typically a PC or smartphone.

[1230] 2. Server

[1231] It serves as a central point for receiving data, sending it to generative AI models, and managing and providing analysis results. It also manages sentiment analysis data from the sentiment engine. This server often uses cloud-based infrastructure (e.g., AWS, Google Cloud, etc.).

[1232] 3. Generative AI models and specialized AI teams

[1233] It is a collection of algorithms and systems that analyze business plans, technical, and financial information and provide feedback from multiple perspectives. Generative AI models use natural language processing (NLP) and machine learning algorithms (e.g., GPT-3, BERT, etc.).

[1234] 4. Emotion Engine

[1235] This system analyzes emotions from user input data and real-time data during interactions, and optimizes feedback and interaction content based on that information. The emotion engine uses an emotion analysis algorithm (e.g., Emotion AI).

[1236] 5. Investment institution terminal

[1237] This is a device that investment institutions use to access the system, view analytical reports on startup companies, and communicate with each other; it is usually a PC or smartphone.

[1238] User registration and information entry

[1239] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[1240] Example: A startup company enters its development plans for a new AI product, registering technical specifications, market forecasts, and budget plans into the system.

[1241] Example prompt: "Please provide a business plan for your new startup company. Please include company name, business overview, technical specifications, and financial information."

[1242] Data analysis and feedback

[1243] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server, and the emotion engine also analyzes the user input data to understand emotional responses.

[1244] Example: A generative AI model evaluates a startup's technical specifications, identifies technical risks and legal issues at the time of market launch, and proposes improvements. At the same time, an emotion engine analyzes the emotional reactions of users based on their input data and reflects them in the feedback.

[1245] Example prompt: "Conduct a go-to-market risk assessment based on the technical specifications. Also, analyze the user's emotional response based on the input data."

[1246] Creation of company analysis reports

[1247] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[1248] Example: The risk assessment report includes a technical comparison with key competitors and details of the expected revenue model.

[1249] Example prompt: "Please prepare a company analysis report. Include market analysis, competitive analysis, financial forecasts, and risk assessment."

[1250] Identifying investment opportunities and supporting exchanges

[1251] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[1252] Example: An investment institution sees a company's report, becomes interested in the business, and begins detailed due diligence.

[1253] Example prompt: "Browse startup company analysis reports and search for investment opportunities in industries and technologies that interest you."

[1254] Users and investment institutions can interact directly within the platform, using a messaging system and video conferencing functions. The server monitors the interaction and provides additional support when needed. An emotion engine analyzes real-time data and supports optimal interactions based on the user's emotional state.

[1255] Example: A startup company holds a video conference with an investment institution to discuss the terms of funding and future developments. An emotion engine monitors the user's stress level and suggests taking a break at the appropriate time.

[1256] Example prompt: "Start a video conference with an investment institution, analyze sentiment data in real time, and suggest breaks at appropriate times."

[1257] In this way, the present invention benefits both start-up companies and investment institutions, supporting efficient and effective business development and fundraising. Furthermore, the introduction of an emotion engine provides optimal support that takes into account the user's emotional state.

[1258] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1259] Step 1:

[1260] User registration and information entry

[1261] Users access the system, create an account, enter their company name, contact information, and business summary in the input form, and then press the "Submit" button to send the information to the server. Detailed business plans, technical specifications, financial information, and other information are also sent to the server.

[1262] Input: Company name, contact details, business overview, business plan, technical specifications, financial information

[1263] Output: Company information and business data stored on the server

[1264] Specific operation: The user accesses the web application on their device, enters the required information into the input form, and clicks the "Submit" button. The data sent from the user device is stored on the server.

[1265] Step 2:

[1266] Data Receipt and Storage

[1267] The server receives the information sent by the user and temporarily stores it in a database, after which it prepares this data to be sent to the generative AI model.

[1268] Input: Information sent from the user's device (company name, contact information, business overview, business plan, technical specifications, financial information)

[1269] Output: Company information and business data stored in a database, ready to be sent to a generative AI model

[1270] Specific operation: On the server side, the data reception API receives the data, stores it in the database, and then converts it into a data format for sending to the generative AI model.

[1271] Step 3:

[1272] Data transmission and analysis

[1273] The server sends the stored data to the generative AI model, which analyzes the data from technical, legal, and corporate strategy perspectives and generates results. At the same time, the emotion engine performs sentiment analysis.

[1274] Input: Company information and business data stored in a database

[1275] Output: Analysis results by the generative AI model and emotion analysis results by the emotion engine

[1276] How it works: The server sends an API request to the generative AI model, which then analyzes the received data. The analysis results are then sent back to the server. The emotion engine then analyzes the emotion data in a similar manner and returns it to the server.

[1277] Step 4:

[1278] Providing Feedback

[1279] The server aggregates the results from the generative AI model and emotion engine and provides it as feedback to the user, displaying the feedback through a dashboard and notification mechanism.

[1280] Input: Analysis results of the generative AI model, emotion analysis results of the emotion engine

[1281] Output: Feedback provided to the user

[1282] What it does: The server aggregates the results from the generative AI model and the emotion engine and generates data to display on the user dashboard. When a user logs in, new feedback is displayed on the dashboard.

[1283] Step 5:

[1284] Creation of company analysis reports

[1285] The generative AI model creates detailed company analysis reports for startups that meet certain criteria, including market analysis, competitive analysis, financial forecasts, and risk assessments. The server stores the report data and makes it accessible to users and investment institutions.

[1286] Input: Analysis results of the generative AI model

[1287] Output: Detailed company analysis report

[1288] Specific operation: The server automatically generates a company analysis report based on the analysis results and saves it in the database. The saved report is provided as a link for users and investment institutions to download.

[1289] Step 6:

[1290] Read reports and identify investment opportunities

[1291] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[1292] Input: Data for company analysis report

[1293] Output: Company analysis report for investment institutions

[1294] Specific operation: Log in to the system on the investment institution's terminal and use the search filter function to search and view reports on startup companies that meet specific criteria. Detailed information on companies that match the criteria will be displayed.

[1295] Step 7:

[1296] Communication and Support

[1297] Users and investment institutions can interact directly within the platform through messaging and video conferencing, with the server managing these interactions, analyzing sentiment data in real time, and providing additional support when needed.

[1298] Input: Real-time data from the interaction and emotion engine analysis data

[1299] Output: Optimize exchanges and support feedback

[1300] How it works: Users and investment institutions start interacting using messaging systems or video conferencing. The emotion engine analyzes participants' emotions in real time, and the server provides appropriate notifications (e.g., break suggestions).

[1301] (Application example 2)

[1302] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1303] In recent years, there has been a growing need to improve engagement between startups and investment institutions. However, conventional platforms have proven difficult to provide appropriate feedback on startups' business plans and technologies. Furthermore, even in brick-and-mortar stores, customer service can be inconsistent, making it particularly difficult to understand customer sentiment and respond appropriately in real time. The present invention aims to provide a system that simultaneously solves these issues.

[1304] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for sending information about the startup company to the generative AI model, means for analyzing the business plan using the generative AI model, and means for providing the startup company with the analysis results of the generative AI model as feedback. This allows the startup company to receive professional feedback in real time. The server also includes means for analyzing customer behavior, comments, and facial expressions, means for providing customer service advice in real time based on the analysis results, and means for analyzing the customer's emotional state and suggesting the optimal response method. This enables advanced responses that correspond to customer emotions to be realized even in physical stores.

[1305] "Means for inputting startup company information" refers to an interface that allows startup companies to input their business plans, technical details, and financial information into the system.

[1306] "Means for sending startup company information to the generative AI model" refers to the process of sending the input startup company information to the generative AI model and providing data for analysis.

[1307] The "means of analyzing the business plan of the startup company using a generative AI model" refers to the process of using a generative AI model to analyze the business plan and technical information of the startup company and generate professional feedback.

[1308] "Means for providing the startup company with the analysis results generated by the generative AI model as feedback" refers to the process of returning the analysis results generated by the generative AI model to the startup company, providing insights for improving business plans and formulating strategies.

[1309] "Means of providing investment institutions with company analysis reports created by generative AI models" refers to the process of sharing detailed analysis reports of startup companies created by generative AI models with investment institutions, providing them with information for making investment decisions.

[1310] "Means for managing interactions with investment institutions" refers to a system that manages information exchanges and meetings between startups and investment institutions, and supports efficient communication.

[1311] "Means for analyzing customer behavior, remarks, and facial expressions" refers to technology that analyzes the behavior, remarks, and facial expressions of customers in physical stores in real time to understand their behavioral patterns and emotions.

[1312] "Means for providing customer service advice in real time based on analysis results" refers to technology that presents appropriate customer service methods to store staff in real time based on the results of an analysis of customer behavior and emotions.

[1313] "Means of analyzing the customer's emotional state and suggesting the most appropriate way to respond" refers to technology that senses the customer's emotions in real time and suggests the most appropriate way to respond to staff.

[1314] The embodiment of the present invention is a system that is based on an innovation platform that connects startup companies and investment institutions, incorporates a generative AI model and a sentiment analysis engine, and further optimizes customer service in physical stores. The specific system configuration and implementation method are described below.

[1315] System Overview

[1316] The system consists of the following major components:

[1317] 1. User Device

[1318] A device that allows startups to enter business plans, technical details, and financial information, and allows investment institutions to view company analysis reports. Examples include PCs and tablets.

[1319] 2. Server

[1320] It plays a central role, analyzing input data using generative AI models and generating feedback. It also performs real-time emotional data analysis using an emotion analysis engine. Specific examples of its use include cloud-based servers such as AWS (Amazon Web Services).

[1321] 3. Generative AI Models

[1322] Algorithms for analyzing startup companies' business plans, technical details, and financial information from multiple angles. For example, OpenAI's GPT model is used.

[1323] 4. Sentiment Analysis Engine

[1324] This system analyzes emotions from user input data and real-time interactions and reflects them in feedback. It uses Affectiva's emotion engine and other technologies.

[1325] 5. Smart Glasses

[1326] Devices used to optimize customer interactions in physical stores. An example is Google Glass.

[1327] Program Description

[1328] The server receives the startup company information entered by the user and sends it to the generative AI model. The generative AI model analyzes the data from perspectives such as technology, corporate strategy, and law, and generates multifaceted feedback. The results of this analysis are provided to the user via the server.

[1329] Furthermore, the server analyzes the customer's behavior, remarks, and facial expressions in real time, and sends the input data to an emotion analysis engine. The emotion analysis engine analyzes the customer's emotional state and displays the optimal response on the smart glasses. This process allows the user to respond more accurately and with consideration for their emotions.

[1330] Specific examples

[1331] Startup companies, which are users, input their business plans and technical information into the system. This data is sent via the server to the generative AI model, where it is analyzed. As a result of the analysis, investment risks and market development proposals are generated and provided to the user as feedback.

[1332] In brick-and-mortar stores, store clerks wearing smart glasses will serve customers. Data on the customer's facial expressions and comments is sent to an emotion analysis engine in real time, and the optimal way to serve them is displayed on the screen of the smart glasses based on the analysis results.

[1333] Prompt Sentence Examples

[1334] Analyze the customer's emotions from their facial expressions and behavior and suggest the best way to respond.

[1335] Customer profile: Name: Taro Yamada, Age: 35, Purchase history: Home appliances, Interests: Smart devices

[1336] Current state: Unhappy expression

[1337] Expected Output: The customer is stressed, so please provide suggestions to help them relax. If possible, provide more details about specific products.

[1338] In this way, the system of the present invention not only strengthens engagement between startup companies and investment institutions, but can also be effective in customer service at physical stores.

[1339] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1340] Step 1:

[1341] A user (startup company) creates an account and enters company information, business plan, technical details, and financial information. The entered data is sent from the user's device to the server. Specifically, the user enters data using a PC or tablet, and this data is sent to the server as an HTTP request.

[1342] Step 2:

[1343] The server sends the received startup company information to the generative AI model. At this time, the data is passed to the generative AI model in an appropriate format. The server then sends the data to the generative AI model (e.g., OpenAI's GPT model) via an API and requests analysis.

[1344] Step 3:

[1345] The generative AI model analyzes business plans, technical details, and financial information to generate multifaceted feedback. It receives startup details as input and produces market forecasts, technology assessments, risk analyses, and other outputs. It uses natural language processing and machine learning algorithms in the analysis process.

[1346] Step 4:

[1347] The server provides the analysis results received from the generative AI model as feedback to the user. Specifically, it notifies the user of the generated report via a web dashboard or email. The feedback includes suggestions for improving the business plan and an assessment of technical risks.

[1348] Step 5:

[1349] An investment institution accesses the system and views the generated company analysis report. The investment institution's terminal sends a request to the server, and the server provides the appropriate report to the investment institution. In this step, the investment institution can efficiently obtain the information of interest by using the report's filtering and search functions.

[1350] Step 6:

[1351] Users (store staff) wear smart glasses and interact with customers. When a customer visits the store, the smart glasses' sensors capture the customer's behavior, remarks, and facial expressions, and the data is sent to the server. The input includes time-stamped behavioral data and facial expression data of the customer.

[1352] Step 7:

[1353] The server sends the received customer data to a sentiment analysis engine, which analyzes customer sentiment in real time and returns the analysis results to the server, including stress levels and satisfaction levels.

[1354] Step 8:

[1355] The server provides real-time customer service advice to store staff based on the analysis results from the emotion analysis engine. The appropriate response is displayed on the smart glasses' display. For example, if a customer appears dissatisfied, "suggestions to help them relax" are presented to the staff.

[1356] Step 9:

[1357] The user (store staff) responds to the customer based on the advice provided, improving customer satisfaction and optimizing the customer experience.

[1358] Through these processing steps, startups receive professional feedback, investment institutions receive detailed company analysis reports, and brick-and-mortar stores can respond appropriately to customer sentiment.

[1359] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1360] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1361] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1362] [Fourth embodiment]

[1363] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1364] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1365] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1366] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1367] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1368] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1369] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1370] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1371] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1372] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1373] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1374] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1375] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1376] The present invention provides an innovation platform that effectively connects startup companies with investment institutions, and is a system that uses generative AI to perform professional analysis and feedback. Specific embodiments and program processing for implementing this system are described below.

[1377] System Overview

[1378] This system consists of the following main components:

[1379] 1. User Device

[1380] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[1381] 2. Server

[1382] It plays a central role in receiving data, sending it to generative AI models, and managing and delivering analytical results.

[1383] 3. Generative AI models and specialized AI teams

[1384] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[1385] 4. Investment institution terminal

[1386] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[1387] Program processing

[1388] User registration and information entry

[1389] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[1390] Example: A startup company, XYZ Tech, enters its development plan for a new AI product, registering technical specifications, market forecasts, and budget plans in the system.

[1391] Data analysis and feedback

[1392] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server.

[1393] Example: An AI model evaluates the technical specifications of "XYZ Tech," identifies technical risks and legal issues at the time of market launch, and makes improvement proposals.

[1394] Creation of company analysis reports

[1395] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[1396] Example: The report on "XYZ Tech" includes a technology comparison with key competitors, projected revenue models, and detailed risk factors.

[1397] Identifying investment opportunities

[1398] Investors can access the server and view analytical reports on startups they are interested in. They can use search and filtering functions to find promising investment opportunities in specific industries and technologies.

[1399] Example: An investment institution sees a report on "XYZ Tech," becomes interested in the business plan, and begins detailed due diligence.

[1400] Exchange and growth support

[1401] Users and investment institutions can interact directly within the platform using a messaging system and video conferencing functions, with the server monitoring the interaction and providing additional support when needed.

[1402] Example: XYZ Tech holds a video conference with an investment institution to discuss specific terms of funding and future developments.

[1403] As described above, the system of the present invention can bring benefits to both start-up companies and investment institutions, and can support efficient and effective business development and fundraising.

[1404] The processing flow will be explained below.

[1405] Step 1:

[1406] A user accesses the platform using a device and creates an account, entering the company name, contact information, and business overview as registration information, which is then sent to the server.

[1407] Step 2:

[1408] The user inputs detailed data such as business plans, technical specifications, and financial information via a terminal and sends it to the server, which stores the received information in a database.

[1409] Step 3:

[1410] The server sends the stored startup company information to the generative AI model, which then sends the data to specialized AI teams in each field, who then begin their analysis.

[1411] Step 4:

[1412] The generative AI model analyzes data from technical, legal, and corporate strategy fields and sends the results to a server, which then integrates the results and generates feedback.

[1413] Step 5:

[1414] The server sends the generated feedback to the user's device and notifies the user, who then checks the feedback and uses it to revise and improve their business plan.

[1415] Step 6:

[1416] For startup companies that meet certain criteria, the generative AI model creates a detailed company analysis report and sends it to the server.

[1417] Step 7:

[1418] The server transmits the company analysis report to the user terminal and also makes it accessible to the investment institution terminal.

[1419] Step 8:

[1420] Investors access the platform using their devices to view company analysis reports for startups they are interested in. They can use search and filtering functions to find promising investment targets in specific industries and technologies.

[1421] Step 9:

[1422] If an investment institution shows interest in the startup, the server receives the investment institution's feedback and notifies the user, who then begins interacting with the investment institution.

[1423] Step 10:

[1424] Users and investment institutions communicate directly using messaging systems and video conferencing, with the server recording the conversation and providing additional support from generative AI models where necessary.

[1425] Step 11:

[1426] If the investment goes through and the startup moves towards growth and market expansion, Sarver will monitor the company's progress and provide further support as needed.

[1427] Example 1

[1428] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1429] Modern startups need to connect with investors quickly and efficiently. However, they often miss investment opportunities due to a lack of proper feedback and analysis. Furthermore, startups need a neutral, professional platform to effectively interact with investors. However, such platforms either do not exist or function poorly.

[1430] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1431] In this invention, the server includes a means for inputting startup company information, a means for transmitting the startup company information to a generative AI model, a means for analyzing the startup company's business plan using the generative AI model, a means for providing the startup company with the analysis results of the generative AI model as feedback, a means for providing the investment institution with a company analysis report created by the generative AI model, a means for the investment institution to view and search the startup company's company analysis report, a means for the startup company and the investment institution to interact within the platform, a means for sending a prompt to the generative AI model, and a means for the server to instruct the generative AI model to perform an analysis based on the generated prompt. This allows startup companies to receive professional feedback and analysis, and investment institutions to consider investments based on reliable information. Furthermore, both parties can interact efficiently and obtain optimal investment opportunities.

[1432] A "startup company" is a newly emerging company that aims to develop innovative business models and technologies and provide new value to the market.

[1433] "Investment institutions" are organizations such as financial institutions, venture capital firms, and angel investors that aim to earn profits through investments in startup companies.

[1434] A "generative AI model" is an algorithm or system that uses techniques such as machine learning and deep learning to analyze data and generate feedback, predictions, and suggestions.

[1435] A "prompt sentence" is an instruction sentence entered to instruct the generative AI model to perform specific analysis or evaluation.

[1436] "Feedback" refers to the evaluation, suggestions, and improvements provided by the generative AI model based on the analysis results.

[1437] A "Company Analysis Report" is a detailed analytical document created by a generative AI model by analyzing a startup company's business plan, technical specifications, financial information, etc.

[1438] The "platform" is an online system that allows startups and investment institutions to input information, analyze it, provide feedback, and communicate with each other.

[1439] The "server" is a central processing unit that receives data from user terminals and investment institution terminals, and works with the generative AI model to analyze the data and provide feedback.

[1440] A "user terminal" is a device used by a startup company to input information and receive analysis results.

[1441] An "investor's terminal" is a device used by an investment institution to access the server and view and interact with startup companies' corporate analysis reports.

[1442] The present invention provides an innovation platform that effectively connects startup companies with investment institutions, and provides specialized analysis and feedback using generative AI models. Specific embodiments and program processing for implementing this system are described below.

[1443] System Overview

[1444] The system consists of the following major components:

[1445] 1. User Device

[1446] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[1447] 2. Server

[1448] It plays a central role in receiving data, sending it to generative AI models, and managing and delivering analytical results.

[1449] 3. Generative AI models and specialized AI teams

[1450] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[1451] 4. Investment institution terminal

[1452] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[1453] User registration and information entry

[1454] Users (startup companies) first create an account using their device. They enter their company name, contact information, business overview, etc. into the registration form, and then enter a detailed business plan, technical specifications, and financial information into the system. The entered data is sent to the server and stored in a database.

[1455] Example: A startup company inputs a new business plan on the theme of "application of AI technology" and registers technical specifications, market forecasts, and budget plans in the system. This data is sent to the server by pressing the "Submit" button.

[1456] Data analysis and feedback

[1457] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives and generates feedback. The results are then provided back to the user via the server.

[1458] Example: The server sends the technical specifications for "application of AI technology" to a generative AI model, which generates a prompt saying, "Evaluate technical risk and market risk." The generative AI model performs analysis and returns the results to the server. The server then notifies the user with feedback such as, "Technical risk is low, but market risk is high."

[1459] Creation of company analysis reports

[1460] Based on data that meets certain criteria, the generative AI model creates a company analysis report, including market analysis, competitive analysis, financial forecasts, and risk assessment, and the server then stores the report for viewing by users and investment institutions.

[1461] Example: The report contains detailed information about the market analysis of "AI technology applications," a technical comparison with major competitors, a projected revenue model, and risk factors. The server saves this in PDF format and notifies users and investment institutions.

[1462] Identifying investment opportunities

[1463] Investors can access the server using their terminals to view company analysis reports on startups, and can use search and filtering functions to find promising investment targets in specific industries and technologies.

[1464] Example: An investment institution searches for the keyword "application of AI technology" and obtains and views company analysis reports. For example, an investment institution interested in "technology application" considers specific business plans.

[1465] Exchange and growth support

[1466] Users and investment institutions communicate directly within the platform, which provides messaging and video conferencing functions, and the server monitors communication logs and provides additional support when needed.

[1467] Example: A user holds a video conference with an investment institution to discuss the specifics of funding and future developments. The server records the meeting and makes it available for later reference.

[1468] Examples of prompt statements

[1469] Below are some example prompts to be input to the generative AI model:

[1470] Example prompt 1:

[1471] "AI model, please assess the technical and market risks based on the business plan below and create improvement proposals."

[1472] Business plan: "The startup is developing AI technology that uses cutting-edge machine learning algorithms..."

[1473] Example prompt 2:

[1474] "Please evaluate the AI ​​model and the technical specifications of the startup company, identify legal risks at the time of market launch, and propose countermeasures."

[1475] Technical specifications: "The startup's AI technology features facial and voice recognition..."

[1476] In this way, startups and investment institutions can be effectively connected, enabling business development and fundraising through professional feedback and analysis.

[1477] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1478] Step 1:

[1479] User creates an account

[1480] Input: Company name, contact information, business summary.

[1481] A user accesses the system using a user terminal and enters the company name, contact information, and business overview.

[1482] When the user presses the "Send" button, this data is sent to the server.

[1483] Output: User account information is saved in the database.

[1484] Step 2:

[1485] User enters detailed business information

[1486] Input: Business plan, technical specifications, financial information.

[1487] Users use their devices to input business plans, technical specifications, and financial information, such as technical specifications that "use the latest machine learning algorithms," market forecasts, and budget plans.

[1488] When the user has finished entering data, he or she presses the "Submit" button, which sends the entered data to the server.

[1489] Output: The business information is saved in the server database.

[1490] Step 3:

[1491] Send the data to a generative AI model for analysis

[1492] Input: Business plan, technical specifications, financial information.

[1493] The server sends the business information received from the user to the generative AI model, generating a prompt such as "Evaluate technical and market risks."

[1494] The server sends the data along with the prompt to the generative AI model.

[1495] Output: Analysis begins with a generative AI model.

[1496] Step 4:

[1497] Data analysis and feedback generation

[1498] Input: Prompt statement, business plan, technical specifications, financial information.

[1499] Based on the prompt, the generative AI model analyzes the input business information from various perspectives, including technical, legal, and business strategy.

[1500] As a result, analytical data is generated.

[1501] Output: The generative AI model returns the analysis results to the server.

[1502] Step 5:

[1503] Providing Feedback

[1504] Input: Analysis results.

[1505] The server receives the analysis results returned by the generative AI model and provides them to the user as feedback.

[1506] The server notifies the user terminal of the analysis results, such as "Technical risk is low, but market risk is high."

[1507] Output: The feedback is sent to the user.

[1508] Step 6:

[1509] Creation and provision of corporate analysis reports

[1510] Input: Analysis results.

[1511] The server generates data that meets certain criteria and then generates a company analysis report based on the AI ​​model, which includes market analysis, competitive analysis, financial forecasts, and risk assessment.

[1512] The report is saved in PDF format.

[1513] Output: Company analysis reports are provided to users and investment institutions.

[1514] Step 7:

[1515] Viewing reports by investment institutions

[1516] Input: Corporate analysis report.

[1517] Investment institutions can access the server using their terminals to view and search for company analysis reports. For example, if they search for the keyword "application of AI technology," related reports will be displayed.

[1518] Investment institutions can view the reports and find interesting investment opportunities.

[1519] Output: The browsing log is saved on the server.

[1520] Step 8:

[1521] Interaction between users and investment institutions

[1522] Input: A request for interaction.

[1523] Users and investment institutions communicate within the platform using messaging and video conferencing functions.

[1524] The server monitors the logs of interactions and provides additional support as needed.

[1525] Output: A record of the interaction is stored on the server.

[1526] In this way, a system is realized that effectively connects users and investment institutions and allows them to make the most of investment opportunities.

[1527] (Application example 1)

[1528] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1529] It is extremely important for startups to effectively communicate their business plans and technical information to investment institutions and receive appropriate feedback. However, with traditional methods, this process is extremely time-consuming and costly, and opportunities to connect with investment institutions with specialized knowledge are limited. Investors also face challenges in efficiently identifying promising startups. A system that solves these problems and more effectively connects startups and investment institutions is needed.

[1530] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1531] In this invention, the server includes means for inputting information about a startup company, means for transmitting the information about the startup company to a generative AI model, means for analyzing the business plan of the startup company using the generative AI model, means for providing the analysis results of the generative AI model as feedback to the startup company, means for providing a company analysis report created by the generative AI model to an investment institution, means for the investment institution to search and filter the analysis report and identify investment opportunities, means for managing interactions with the investment institution, and means for messaging and video conferencing between the startup company and the investment institution, thereby enabling startup companies and investment institutions to collaborate efficiently and effectively and quickly obtain appropriate feedback and investment opportunities.

[1532] A "startup company" is a newly emerging company that aims for rapid growth in a short period of time based on new business ideas or technologies.

[1533] A "generative AI model" is a collection of algorithms and systems that use artificial intelligence techniques to analyze input data and automatically generate analytical results and proposals.

[1534] The "means for inputting information" is an interface that allows users to register necessary data such as business plans, technical information, and financial information into the system.

[1535] "Means for sending information to the generative AI model" refers to the process for transferring input data to the generative AI model and starting analysis.

[1536] "Means for analyzing business plans" refers to the process of using a generative AI model to evaluate input business plans from technical, financial, market, and other perspectives.

[1537] "Means for providing feedback" refers to the process of returning the results of the analysis by the generative AI model to the user in visual or written form.

[1538] A "Company Analysis Report" is a document summarizing the results of the generative AI model's analysis, including details such as market analysis, competitive analysis, financial forecasts, and risk assessment.

[1539] "Investment institutions" are institutions that provide funding to emerging companies, and primarily include venture capitalists and angel investors.

[1540] "Search and filtering means" refers to a function that allows investment institutions to easily search for company analysis reports based on specific criteria.

[1541] "Means for identifying investment opportunities" refers to the process by which investment institutions find promising investment targets based on the corporate analysis reports of startup companies.

[1542] "Interaction management tools" are the processes that provide and monitor the features, such as messaging and video conferencing, that startups and investment institutions need to communicate effectively.

[1543] "Messaging and video conferencing tools" refers to online tools and platforms that enable startups and investment institutions to exchange information and hold consultations in real time.

[1544] This invention is an innovation system that connects startup companies with investment institutions, and uses generative AI models to analyze startup companies' business plans, technical information, and financial information, and provides analytical results.

[1545] 1. User registration and information entry:

[1546] Users first create an account and enter the necessary data, such as company name, contact information, business overview, technical specifications, and financial information. This information is sent from the front end (e.g., a smartphone app or web interface) to the server, which stores it in a database and prepares it for analysis by the generative AI model.

[1547] 2. Data analysis and feedback:

[1548] The server sends the data entered by the user to a generative AI model. The generative AI model uses AI frameworks such as TensorFlow and PyTorch to analyze the data from multiple perspectives. This analysis includes technical risks, legal issues, and strategic proposals. The server receives the results and provides them to the user as feedback. Specific examples of feedback include "Technical risks: Medium," "Legal issues: Low," and "Strategic proposal: Consider partnerships with overseas companies."

[1549] 3. Creating a company analysis report:

[1550] The company analysis report created by the generative AI model includes detailed market analysis, competitive analysis, financial forecasts, and risk assessment. The server generates and manages this report and provides it through an interface for investment institutions. The report includes specific data and graphs in a format that is easy for investment institutions to understand.

[1551] 4. Search, filter, and identify investment opportunities:

[1552] Investors can use the provided interface to search and filter analytical reports to find promising investment opportunities in specific industries and technologies. For example, they can search for startups based on specific technology areas, geographies, and growth forecasts.

[1553] 5. Interaction and communication:

[1554] The server provides messaging and video conferencing features to help startups and investors collaborate effectively, using real-time communication technologies such as WebRTC. Users and investors can send messages directly to each other or hold online meetings to discuss details.

[1555] Examples of specific examples and prompts

[1556] Examples:

[1557] A startup company, Acme Tech, registers on the app and inputs its business plan and technical information, which the generative AI model analyzes and provides feedback. An investment firm, Venture Capital A, searches and filters Acme Tech's reports, becomes interested, and begins business negotiations via video conference.

[1558] Example prompt sentence:

[1559] User registration prompt: "Please enter your startup name, contact information, business description, technical specifications, and financial information."

[1560] Confirmation prompt: "Are you done entering information? Do you want to move on?"

[1561] Analysis result feedback: "Technical risk is medium, legal challenges are low. Consider partnerships with overseas companies."

[1562] Report Search Prompt: "Search for startups based on specific technology areas and growth forecasts."

[1563] Communication prompts: "Send a message? Start a video conference?"

[1564] The above is a specific embodiment of the present invention. This system enables startup companies and investment institutions to collaborate more effectively and efficiently, enabling them to quickly obtain appropriate feedback and investment opportunities.

[1565] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1566] Step 1:

[1567] A user creates an account.

[1568] Input: Company name, contact information, business overview, technical specifications, financial information.

[1569] Operation: The user enters the necessary information on their device (smartphone app or web interface) and sends this data to the server.

[1570] Output: The user's information is saved in the database and an account is created.

[1571] Step 2:

[1572] The server sends the received data to the generative AI model.

[1573] Input: Your business plan, technical details, and financial information.

[1574] How it works: The server extracts user information stored in a database and calls an API to send it to a generative AI model.

[1575] Output: The data is ready for a generative AI model to analyze.

[1576] Step 3:

[1577] A generative AI model analyzes user data.

[1578] Input: User's business plan, technical details, and financial information sent by the server.

[1579] How it works: Generative AI models (using TensorFlow and PyTorch) analyze data to generate technical risks, legal issues, and strategic recommendations.

[1580] Output: Analysis results (e.g., technical risk: medium; legal challenges: low; strategic proposals: consider partnerships with overseas companies).

[1581] Step 4:

[1582] The server provides the analysis results of the generated AI model to the user as feedback.

[1583] Input: Analysis results of the generative AI model.

[1584] How it works: The server receives the analysis results and sends them to the user's device in visual or document form.

[1585] Output: Users receive feedback to improve business plans and assess risks.

[1586] Step 5:

[1587] The server generates a company analysis report and provides it to the investment institution.

[1588] Input: Analysis results of the generative AI model.

[1589] How it works: The server generates a detailed company analysis report based on the analysis results and saves it in the investment institution interface.

[1590] Output: Reports (market analysis, competitive analysis, financial forecasts, risk assessment) are generated and made accessible to investment institutions.

[1591] Step 6:

[1592] Investment institutions search and filter analytical reports.

[1593] Input: Search criteria for the investor (technology area, growth forecast, etc.).

[1594] Operation: Search criteria are entered from the investment institution's terminal, and the server extracts and provides company analysis reports that match the criteria.

[1595] Output: Find analytical reports on startups that are of interest to investment institutions.

[1596] Step 7:

[1597] Investment institutions identify investment opportunities and work with startups.

[1598] Input: Company analysis reports selected by investment institutions.

[1599] How it works: An investment institution selects a particular startup, and the server provides messaging and video conferencing capabilities to facilitate communication between the investment institution and the startup.

[1600] Output: The investment institution and the startup company begin communication, and investment negotiations progress.

[1601] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1602] The present invention provides an innovation platform that effectively connects startup companies and investment institutions, and is a system that utilizes generative AI for professional analysis and feedback, and an emotion engine to recognize and analyze user emotions. Specific embodiments and program processing for implementing this system are described below.

[1603] System Overview

[1604] This system consists of the following main components:

[1605] 1. User Device

[1606] It is a device that allows startups to access the system and enter business plans, technical details, and financial information.

[1607] 2. Server

[1608] It plays a central role in receiving data, sending it to the generative AI model, managing and providing the analysis results, and also managing the sentiment analysis data from the sentiment engine.

[1609] 3. Generative AI models and specialized AI teams

[1610] It is a collection of algorithms and systems that analyze business plans, technology, and financial information and provide feedback from multiple perspectives.

[1611] 4. Emotion Engine

[1612] This system analyzes emotions from user input data and real-time data during interactions, and optimizes feedback and interaction content based on that information.

[1613] 5. Investment institution terminal

[1614] This device allows investment institutions to access the system, view analytical reports on startup companies, and interact with them.

[1615] Program processing

[1616] User registration and information entry

[1617] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[1618] Example: A startup company, XYZ Tech, enters its development plan for a new AI product, registering technical specifications, market forecasts, and budget plans in the system.

[1619] Data analysis and feedback

[1620] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server. The emotion engine also analyzes user input data and understands emotional responses.

[1621] Example: An AI model evaluates the technical specifications of "XYZ Tech," identifies technical risks and legal issues at the time of market launch, and proposes improvements. At the same time, an emotion engine analyzes the emotional reactions of users based on their input data and reflects them in the feedback.

[1622] Creation of company analysis reports

[1623] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[1624] Example: The report on "XYZ Tech" includes a technology comparison with key competitors, projected revenue models, and detailed risk factors.

[1625] Identifying investment opportunities

[1626] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[1627] Example: An investment institution sees a report on "XYZ Tech," becomes interested in the business plan, and begins detailed due diligence.

[1628] Exchange and growth support

[1629] Users and investment institutions can interact directly within the platform using a messaging system and video conferencing functions. The server monitors the interaction and provides additional support when necessary. The emotion engine analyzes real-time data during the interaction and supports optimal interactions based on the user's emotional state.

[1630] Example: XYZ Tech is holding a video conference with an investment institution to discuss the terms of funding and future developments. During the conversation, the emotion engine monitors the user's stress level and suggests taking a break at the appropriate time.

[1631] As described above, the system of the present invention can bring benefits to both startup companies and investment institutions, supporting efficient and effective business development and fundraising. Furthermore, the introduction of an emotion engine provides optimal support that takes into account the user's emotional state.

[1632] The processing flow will be explained below.

[1633] Step 1:

[1634] A user accesses the platform using a device and creates an account, entering the company name, contact information, and business overview as registration information, which is then sent to the server.

[1635] Step 2:

[1636] A user uses a terminal to input data such as a detailed business plan, technical specifications, and financial information, and then sends it to a server, which stores the information in a database.

[1637] Step 3:

[1638] The server sends the stored startup company information to the generative AI model, which then sends the data to specialized AI teams in each field, who then begin their analysis.

[1639] Step 4:

[1640] The generative AI model analyzes data from technical, legal, and corporate strategy fields and sends the results to a server, which then integrates the results and generates feedback. The emotion engine also analyzes user input data and recognizes emotional states.

[1641] Step 5:

[1642] The server sends the generated feedback and the results of the emotion engine analysis to the user's device and notifies them. The user can then check the feedback and emotion analysis and use it to revise and improve their business plan.

[1643] Step 6:

[1644] For startup companies that meet certain criteria, the generative AI model creates a detailed company analysis report and sends it to the server.

[1645] Step 7:

[1646] The server transmits the company analysis report to the user terminal and also makes it accessible to the investment institution terminal.

[1647] Step 8:

[1648] Investors access the platform using their devices to view company analysis reports for startups they are interested in. They can use search and filtering functions to find promising investment targets in specific industries and technologies.

[1649] Step 9:

[1650] If an investment institution shows interest in the startup, the server receives the investment institution's feedback and notifies the user, who then begins interacting with the investment institution.

[1651] Step 10:

[1652] Users and investment institutions communicate directly using messaging and video conferencing. The server records the content of the interaction and provides additional support from generative AI models as needed. The emotion engine analyzes real-time data during the interaction and monitors the user's emotional state.

[1653] Step 11:

[1654] During the interaction, the emotion engine analyzes the user's emotional state, and if, for example, a high stress level is detected, the server suggests the user take a break and adjusts the progress of the interaction.

[1655] Step 12:

[1656] If the investment is successful and the startup aims to grow and expand into the market, the server will monitor the company's progress and provide further support as needed, taking into account user sentiment analysis data to provide support at the appropriate time.

[1657] Example 2

[1658] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1659] Traditional methods for connecting startups with investment institutions are often inefficient due to information asymmetry and lack of communication. Furthermore, if a startup's business plan, technical specifications, and financial information are not fully analyzed, it can be difficult to provide appropriate feedback or identify investment opportunities. Furthermore, the process often ignores the emotional state of the users involved, which can hinder effective communication.

[1660] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting information about a startup company; means for transmitting the information about the startup company to a generative AI model; means for multifacetedly analyzing the business plan, technical specifications, and financial information of the startup company using the generative AI model; means for providing the startup company with the analysis results by the generative AI model and the emotion analysis results by the emotion engine as feedback; means for providing the investment institution with a company analysis report created by the generative AI model; and means for managing interactions with the investment institution and analyzing emotion data in real time to support optimal interactions. This enables effective connection between startup companies and investment institutions, information symmetry, and effective communication through real-time emotion analysis.

[1661] A "startup company" is a newly established company that generally has innovative technology or a business model.

[1662] "Means for inputting information" refers to the interface through which users input company information, business plans, technical specifications, financial information, etc. into the system.

[1663] A "generative AI model" is an artificial intelligence model that analyzes input data and generates feedback and improvement suggestions from a multifaceted perspective.

[1664] "Means" refers to a device, system, or method designed to perform a particular function or process.

[1665] "Means for multifaceted analysis of business plans, technical specifications, and financial information" refers to a function that uses a generative AI model to analyze input business plans, technical specifications, and financial information from various perspectives, including technology, law, and corporate strategy.

[1666] The "emotion engine" is a system that analyzes emotions from user input data and real-time interaction data.

[1667] "Means for providing feedback" is a function that presents useful information and improvement suggestions to users based on the analysis results and sentiment analysis results.

[1668] A "Company Analysis Report" is a detailed report that includes market analysis, competitive analysis, financial forecasts, risk assessment, etc. for a startup company.

[1669] "Investment institutions" are companies or organizations that invest in startup companies.

[1670] "Means for managing interactions with investment institutions" refers to functions that support and manage messaging, video conferencing, and other interactions with investment institutions within the platform.

[1671] "Means for analyzing emotional data in real time" refers to a function that analyzes data during interaction in real time, evaluates the user's emotional state, and provides appropriate feedback.

[1672] The present invention is a system that provides a platform that effectively connects startup companies and investment institutions, and uses a generative AI model to perform specialized analysis and feedback, as well as an emotion engine to analyze user emotions.

[1673] System Configuration

[1674] The system consists of the following main components:

[1675] 1. User Device

[1676] A device that allows startup companies to access the system and input business plans, technical specifications, and financial information; typically a PC or smartphone.

[1677] 2. Server

[1678] It serves as a central point for receiving data, sending it to generative AI models, and managing and providing analysis results. It also manages sentiment analysis data from the sentiment engine. This server often uses cloud-based infrastructure (e.g., AWS, Google Cloud, etc.).

[1679] 3. Generative AI models and specialized AI teams

[1680] It is a collection of algorithms and systems that analyze business plans, technical, and financial information and provide feedback from multiple perspectives. Generative AI models use natural language processing (NLP) and machine learning algorithms (e.g., GPT-3, BERT, etc.).

[1681] 4. Emotion Engine

[1682] This system analyzes emotions from user input data and real-time data during interactions, and optimizes feedback and interaction content based on that information. The emotion engine uses an emotion analysis algorithm (e.g., Emotion AI).

[1683] 5. Investment institution terminal

[1684] This is a device that investment institutions use to access the system, view analytical reports on startup companies, and communicate with each other; it is usually a PC or smartphone.

[1685] User registration and information entry

[1686] Users (startup companies) first create an account, entering their company name, contact information, business overview, etc. After that, a detailed business plan, technical specifications, and financial information are entered into the system and sent to the server.

[1687] Example: A startup company enters its development plans for a new AI product, registering technical specifications, market forecasts, and budget plans into the system.

[1688] Example prompt: "Please provide a business plan for your new startup company. Please include company name, business overview, technical specifications, and financial information."

[1689] Data analysis and feedback

[1690] The server sends the received data to the generative AI model, which analyzes the data from multiple perspectives, including technology, law, and corporate strategy, and generates feedback. The results are provided to the user via the server, and the emotion engine also analyzes the user input data to understand emotional responses.

[1691] Example: A generative AI model evaluates a startup's technical specifications, identifies technical risks and legal issues at the time of market launch, and proposes improvements. At the same time, an emotion engine analyzes the emotional reactions of users based on their input data and reflects them in the feedback.

[1692] Example prompt: "Conduct a go-to-market risk assessment based on the technical specifications. Also, analyze the user's emotional response based on the input data."

[1693] Creation of company analysis reports

[1694] For startups that meet certain criteria, the generative AI model creates a detailed company analysis report, including market analysis, competitive analysis, financial forecasts, risk assessment, etc. The server provides the report to users and also makes it accessible to investment institutions.

[1695] Example: The risk assessment report includes a technical comparison with key competitors and details of the expected revenue model.

[1696] Example prompt: "Please prepare a company analysis report. Include market analysis, competitive analysis, financial forecasts, and risk assessment."

[1697] Identifying investment opportunities and supporting exchanges

[1698] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[1699] Example: An investment institution sees a company's report, becomes interested in the business, and begins detailed due diligence.

[1700] Example prompt: "Browse startup company analysis reports and search for investment opportunities in industries and technologies that interest you."

[1701] Users and investment institutions can interact directly within the platform, using a messaging system and video conferencing functions. The server monitors the interaction and provides additional support when needed. An emotion engine analyzes real-time data and supports optimal interactions based on the user's emotional state.

[1702] Example: A startup company holds a video conference with an investment institution to discuss the terms of funding and future developments. An emotion engine monitors the user's stress level and suggests taking a break at the appropriate time.

[1703] Example prompt: "Start a video conference with an investment institution, analyze sentiment data in real time, and suggest breaks at appropriate times."

[1704] In this way, the present invention benefits both start-up companies and investment institutions, supporting efficient and effective business development and fundraising. Furthermore, the introduction of an emotion engine provides optimal support that takes into account the user's emotional state.

[1705] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1706] Step 1:

[1707] User registration and information entry

[1708] Users access the system, create an account, enter their company name, contact information, and business summary in the input form, and then press the "Submit" button to send the information to the server. Detailed business plans, technical specifications, financial information, and other information are also sent to the server.

[1709] Input: Company name, contact details, business overview, business plan, technical specifications, financial information

[1710] Output: Company information and business data stored on the server

[1711] Specific operation: The user accesses the web application on their device, enters the required information into the input form, and clicks the "Submit" button. The data sent from the user device is stored on the server.

[1712] Step 2:

[1713] Data Receipt and Storage

[1714] The server receives the information sent by the user and temporarily stores it in a database, after which it prepares this data to be sent to the generative AI model.

[1715] Input: Information sent from the user's device (company name, contact information, business overview, business plan, technical specifications, financial information)

[1716] Output: Company information and business data stored in a database, ready to be sent to a generative AI model

[1717] Specific operation: On the server side, the data reception API receives the data, stores it in the database, and then converts it into a data format for sending to the generative AI model.

[1718] Step 3:

[1719] Data transmission and analysis

[1720] The server sends the stored data to the generative AI model, which analyzes the data from technical, legal, and corporate strategy perspectives and generates results. At the same time, the emotion engine performs sentiment analysis.

[1721] Input: Company information and business data stored in a database

[1722] Output: Analysis results by the generative AI model and emotion analysis results by the emotion engine

[1723] How it works: The server sends an API request to the generative AI model, which then analyzes the received data. The analysis results are then sent back to the server. The emotion engine then analyzes the emotion data in a similar manner and returns it to the server.

[1724] Step 4:

[1725] Providing Feedback

[1726] The server aggregates the results from the generative AI model and emotion engine and provides it as feedback to the user, displaying the feedback through a dashboard and notification mechanism.

[1727] Input: Analysis results of the generative AI model, emotion analysis results of the emotion engine

[1728] Output: Feedback provided to the user

[1729] What it does: The server aggregates the results from the generative AI model and the emotion engine and generates data to display on the user dashboard. When a user logs in, new feedback is displayed on the dashboard.

[1730] Step 5:

[1731] Creation of company analysis reports

[1732] The generative AI model creates detailed company analysis reports for startups that meet certain criteria, including market analysis, competitive analysis, financial forecasts, and risk assessments. The server stores the report data and makes it accessible to users and investment institutions.

[1733] Input: Analysis results of the generative AI model

[1734] Output: Detailed company analysis report

[1735] Specific operation: The server automatically generates a company analysis report based on the analysis results and saves it in the database. The saved report is provided as a link for users and investment institutions to download.

[1736] Step 6:

[1737] Read reports and identify investment opportunities

[1738] Investment institutions access the server to view company analysis reports for startups they are interested in. They use search and filtering functions to find promising investment targets in specific industries and technologies.

[1739] Input: Data for company analysis report

[1740] Output: Company analysis report for investment institutions

[1741] Specific operation: Log in to the system on the investment institution's terminal and use the search filter function to search and view reports on startup companies that meet specific criteria. Detailed information on companies that match the criteria will be displayed.

[1742] Step 7:

[1743] Communication and Support

[1744] Users and investment institutions can interact directly within the platform through messaging and video conferencing, with the server managing these interactions, analyzing sentiment data in real time, and providing additional support when needed.

[1745] Input: Real-time data from the interaction and emotion engine analysis data

[1746] Output: Optimize exchanges and support feedback

[1747] How it works: Users and investment institutions start interacting using messaging systems or video conferencing. The emotion engine analyzes participants' emotions in real time, and the server provides appropriate notifications (e.g., break suggestions).

[1748] (Application example 2)

[1749] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1750] In recent years, there has been a growing need to improve engagement between startups and investment institutions. However, conventional platforms have proven difficult to provide appropriate feedback on startups' business plans and technologies. Furthermore, even in brick-and-mortar stores, customer service can be inconsistent, making it particularly difficult to understand customer sentiment and respond appropriately in real time. The present invention aims to provide a system that simultaneously solves these issues.

[1751] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for sending information about the startup company to the generative AI model, means for analyzing the business plan using the generative AI model, and means for providing the startup company with the analysis results of the generative AI model as feedback. This allows the startup company to receive professional feedback in real time. The server also includes means for analyzing customer behavior, comments, and facial expressions, means for providing customer service advice in real time based on the analysis results, and means for analyzing the customer's emotional state and suggesting the optimal response method. This enables advanced responses that correspond to customer emotions to be realized even in physical stores.

[1752] "Means for inputting startup company information" refers to an interface that allows startup companies to input their business plans, technical details, and financial information into the system.

[1753] "Means for sending startup company information to the generative AI model" refers to the process of sending the input startup company information to the generative AI model and providing data for analysis.

[1754] The "means of analyzing the business plan of the startup company using a generative AI model" refers to the process of using a generative AI model to analyze the business plan and technical information of the startup company and generate professional feedback.

[1755] "Means for providing the startup company with the analysis results generated by the generative AI model as feedback" refers to the process of returning the analysis results generated by the generative AI model to the startup company, providing insights for improving business plans and formulating strategies.

[1756] "Means of providing investment institutions with company analysis reports created by generative AI models" refers to the process of sharing detailed analysis reports of startup companies created by generative AI models with investment institutions, providing them with information for making investment decisions.

[1757] "Means for managing interactions with investment institutions" refers to a system that manages information exchanges and meetings between startups and investment institutions, and supports efficient communication.

[1758] "Means for analyzing customer behavior, remarks, and facial expressions" refers to technology that analyzes the behavior, remarks, and facial expressions of customers in physical stores in real time to understand their behavioral patterns and emotions.

[1759] "Means for providing customer service advice in real time based on analysis results" refers to technology that presents appropriate customer service methods to store staff in real time based on the results of an analysis of customer behavior and emotions.

[1760] "Means of analyzing the customer's emotional state and suggesting the most appropriate way to respond" refers to technology that senses the customer's emotions in real time and suggests the most appropriate way to respond to staff.

[1761] The embodiment of the present invention is a system that is based on an innovation platform that connects startup companies and investment institutions, incorporates a generative AI model and a sentiment analysis engine, and further optimizes customer service in physical stores. The specific system configuration and implementation method are described below.

[1762] System Overview

[1763] The system consists of the following major components:

[1764] 1. User Device

[1765] A device that allows startups to enter business plans, technical details, and financial information, and allows investment institutions to view company analysis reports. Examples include PCs and tablets.

[1766] 2. Server

[1767] It plays a central role, analyzing input data using generative AI models and generating feedback. It also performs real-time emotional data analysis using an emotion analysis engine. Specific examples of its use include cloud-based servers such as AWS (Amazon Web Services).

[1768] 3. Generative AI Models

[1769] Algorithms for analyzing startup companies' business plans, technical details, and financial information from multiple angles. For example, OpenAI's GPT model is used.

[1770] 4. Sentiment Analysis Engine

[1771] This system analyzes emotions from user input data and real-time interactions and reflects them in feedback. It uses Affectiva's emotion engine and other technologies.

[1772] 5. Smart Glasses

[1773] Devices used to optimize customer interactions in physical stores. An example is Google Glass.

[1774] Program Description

[1775] The server receives the startup company information entered by the user and sends it to the generative AI model. The generative AI model analyzes the data from perspectives such as technology, corporate strategy, and law, and generates multifaceted feedback. The results of this analysis are provided to the user via the server.

[1776] Furthermore, the server analyzes the customer's behavior, remarks, and facial expressions in real time, and sends the input data to an emotion analysis engine. The emotion analysis engine analyzes the customer's emotional state and displays the optimal response on the smart glasses. This process allows the user to respond more accurately and with consideration for their emotions.

[1777] Specific examples

[1778] Startup companies, which are users, input their business plans and technical information into the system. This data is sent via the server to the generative AI model, where it is analyzed. As a result of the analysis, investment risks and market development proposals are generated and provided to the user as feedback.

[1779] In brick-and-mortar stores, store clerks wearing smart glasses will serve customers. Data on the customer's facial expressions and comments is sent to an emotion analysis engine in real time, and the optimal way to serve them is displayed on the screen of the smart glasses based on the analysis results.

[1780] Prompt Sentence Examples

[1781] Analyze the customer's emotions from their facial expressions and behavior and suggest the best way to respond.

[1782] Customer profile: Name: Taro Yamada, Age: 35, Purchase history: Home appliances, Interests: Smart devices

[1783] Current state: Unhappy expression

[1784] Expected Output: The customer is stressed, so please provide suggestions to help them relax. If possible, provide more details about specific products.

[1785] In this way, the system of the present invention not only strengthens engagement between startup companies and investment institutions, but can also be effective in customer service at physical stores.

[1786] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1787] Step 1:

[1788] A user (startup company) creates an account and enters company information, business plan, technical details, and financial information. The entered data is sent from the user's device to the server. Specifically, the user enters data using a PC or tablet, and this data is sent to the server as an HTTP request.

[1789] Step 2:

[1790] The server sends the received startup company information to the generative AI model. At this time, the data is passed to the generative AI model in an appropriate format. The server then sends the data to the generative AI model (e.g., OpenAI's GPT model) via an API and requests analysis.

[1791] Step 3:

[1792] The generative AI model analyzes business plans, technical details, and financial information to generate multifaceted feedback. It receives startup details as input and produces market forecasts, technology assessments, risk analyses, and other outputs. It uses natural language processing and machine learning algorithms in the analysis process.

[1793] Step 4:

[1794] The server provides the analysis results received from the generative AI model as feedback to the user. Specifically, it notifies the user of the generated report via a web dashboard or email. The feedback includes suggestions for improving the business plan and an assessment of technical risks.

[1795] Step 5:

[1796] An investment institution accesses the system and views the generated company analysis report. The investment institution's terminal sends a request to the server, and the server provides the appropriate report to the investment institution. In this step, the investment institution can efficiently obtain the information of interest by using the report's filtering and search functions.

[1797] Step 6:

[1798] Users (store staff) wear smart glasses and interact with customers. When a customer visits the store, the smart glasses' sensors capture the customer's behavior, remarks, and facial expressions, and the data is sent to the server. The input includes time-stamped behavioral data and facial expression data of the customer.

[1799] Step 7:

[1800] The server sends the received customer data to a sentiment analysis engine, which analyzes customer sentiment in real time and returns the analysis results to the server, including stress levels and satisfaction levels.

[1801] Step 8:

[1802] The server provides real-time customer service advice to store staff based on the analysis results from the emotion analysis engine. The appropriate response is displayed on the smart glasses' display. For example, if a customer appears dissatisfied, "suggestions to help them relax" are presented to the staff.

[1803] Step 9:

[1804] The user (store staff) responds to the customer based on the advice provided, improving customer satisfaction and optimizing the customer experience.

[1805] Through these processing steps, startups receive professional feedback, investment institutions receive detailed company analysis reports, and brick-and-mortar stores can respond appropriately to customer sentiment.

[1806] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1807] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1808] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1809] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1810] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1811] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1812] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1813] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1814] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1815] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar ...

Claims

1. A means of inputting startup company information, A means for transmitting information about the startup company to a generative AI model; A means for analyzing the business plan of the startup company using a generative AI model; A means for providing the startup company with the analysis results of the generative AI model as feedback; A means for providing a company analysis report created by the generative AI model to an investment institution; a means of managing interactions with investment institutions; A system including:

2. The system according to claim 1, further comprising means for analyzing business plans by a specialized AI team in each field.

3. The system of claim 1 further comprising means for generating improvement suggestions for the startup company based on the analysis results.

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