System

Abstract

To provide a system allowing a user to easily prepare a proposal material of high quality reflecting a market trend in real time.SOLUTION: The system includes: means for a user to input information on requirements for creating a proposal material; means for transmitting the input information to a server; means for the server to analyze the input information received from the user and generate an initial proposal material using a generated AI model; means for the server to collect market information in real time from an open data source on the Internet and analyze the market information using a natural language processing technology; means for the server to update the content of the proposal material based on the extracted market information; means for the user to confirm the proposal material generated and transmit a correction instruction to the server; means for the server to update the proposal material based on a correction request from the user and generate a final version of the proposal material; and means for the terminal to provide the final proposal material to the user and the user to confirm and download the proposal material.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] For businesspeople creating proposal materials for new services, creating high-quality materials in a short amount of time is a major challenge. Currently, there is a lack of resources to understand market trends in real time and revise the materials, making it difficult to create effective proposal materials. Another issue is the lack of means to provide proposal materials that quickly and accurately reflect market information. This makes it difficult for businesspeople to provide competitive proposal materials in a timely manner. [Means for solving the problem]

[0005] The present invention provides a system including a means for a user to input information regarding the requirements for creating proposal materials, a means for transmitting the input information to a server, and a means for the server to analyze the input information received from the user and generate initial proposal materials using a generative AI model. The system further includes a means for the server to collect market information in real time from open data sources on the Internet and analyze it using natural language processing technology, and a means for updating the content of the proposal materials based on the extracted market information. The system also includes a means for the user to review the generated proposal materials and send correction instructions to the server, and a means for the server to update the proposal materials based on the user's correction requests and generate final proposal materials. Finally, the system includes a means for a terminal to provide the final proposal materials to the user, allowing the user to review and download them. This system enables users to easily create high-quality proposal materials that reflect market trends in real time.

[0006] "User" refers to a person or entity who utilizes the system to input requirements for creating proposal materials.

[0007] "Terminal" refers to the device used by the User to enter information, transmit it to the server, and review and download the final proposal materials.

[0008] "Server" refers to the part of the system that analyzes information received from users, generates proposal materials using generative AI models, and collects and analyzes market information in real time.

[0009] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates proposal materials based on information entered by the user.

[0010] "Real-time market information" refers to information collected from open data sources on the Internet, including the latest market trends and competitive information.

[0011] "Natural language processing technology" refers to artificial intelligence technology that analyzes collected market information as text and extracts important information.

[0012] "Proposal materials" refer to business documents created by a generative AI model based on requirements specified by the user and reflected by the server in real-time market information.

[0013] A "request for revision" refers to an action in which a user checks the contents of the generated proposal document and instructs additions or revisions as necessary.

[0014] "Open data sources" refer to information sources such as news articles, blogs, and social media posts that are freely accessible on the internet. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention is a system for efficiently creating proposal materials for new services, which uses a generative AI model based on information entered by the user to generate proposal materials and has the function of reflecting real-time market information. This system provides an environment in which users can efficiently create competitive proposal materials.

[0037] Explanation of program processing

[0038] Proposal material creation phase

[0039] User:

[0040] Users first input information about the requirements for creating a proposal, including the target market, service or product features, proposal design and format, and target audience.

[0041] Device:

[0042] The terminal transmits the information entered by the user to the server.

[0043] server:

[0044] The server analyzes the received information and converts it into a format that can be input to the generative AI model. Based on this information, it creates the structure of an initial proposal document. The generative AI model then automatically generates an initial version of the proposal document. This initial version includes the information entered by the user, past success stories, and related materials.

[0045] Real-time market analysis phase

[0046] server:

[0047] The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.) and analyzes the collected data using natural language processing technology to extract the latest market trends and competitive information.

[0048] Market information integration phase

[0049] server:

[0050] The content of the proposal materials is updated based on the analyzed market information. This update ensures that the proposal materials reflect the latest market trends and competitive information, ensuring that the materials are always up-to-date and persuasive.

[0051] Material review and revision phase

[0052] User:

[0053] The user can review the generated proposal and provide instructions for revisions as necessary, such as adding or correcting specific information or adjusting the document design.

[0054] Device:

[0055] The terminal transmits a modification request from the user to the server.

[0056] server:

[0057] The server updates the proposal documents based on user requests for revisions, and if necessary, performs new market analysis and adds the latest information, making the proposal documents even stronger and more competitive.

[0058] Final material generation phase

[0059] server:

[0060] The server generates a final proposal document incorporating all requested revisions and saves it in a format that users can download and present, such as PDF, PowerPoint, or Google Slides.

[0061] Device:

[0062] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[0063] Specific examples

[0064] For example, consider a case where a user is creating a proposal document for a new product. The user inputs the product's features, target market, and competitive information, and the server generates an initial proposal document using a corresponding template. The server collects market information in real time and adds the latest trends and competitive information to the proposal document. The user then reviews the document and requests revisions, and the server completes the final version of the proposal document. Through this process, the user can quickly create high-quality proposal documents that reflect the latest market information.

[0065] This invention enables users to quickly create high-quality proposal materials that reflect market trends in real time, significantly improving the competitiveness of business proposals.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] The user inputs information about the requirements for creating a proposal into the terminal, including the target market, the characteristics of the proposed product or service, the design and format of the proposal, and the target audience.

[0069] Step 2:

[0070] The terminal transmits the information entered by the user to the server.

[0071] Step 3:

[0072] The server analyzes the received information and converts it into a format that can be input into the generative AI model.

[0073] Step 4:

[0074] The server automatically generates an initial proposal document using a generative AI model based on the analyzed input information, and at this stage, it also references past success stories and related materials to enhance the content.

[0075] Step 5:

[0076] The server collects real-time market information from open data sources on the internet, such as news articles, blogs, and social media.

[0077] Step 6:

[0078] The server analyzes the collected market information using natural language processing technology and extracts the latest market trends and competitive information.

[0079] Step 7:

[0080] The server updates the content of the initial proposal based on the extracted market information, so that the latest market information is reflected in the proposal.

[0081] Step 8:

[0082] The user checks the generated proposal document and, if necessary, gives instructions for modifying the content or design of the document.

[0083] Step 9:

[0084] The terminal transmits a modification request from the user to the server.

[0085] Step 10:

[0086] The server updates the proposal documents based on the user's correction requests, and if necessary, performs new market analysis to further strengthen the proposal documents.

[0087] Step 11:

[0088] The server generates the final proposal document with all requested revisions reflected, and the document is saved in a format such as PDF, PowerPoint, or Google Slides.

[0089] Step 12:

[0090] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[0091] Example 1

[0092] 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."

[0093] With conventional proposal creation systems, users had to create documents from scratch, which required a great deal of time and effort, and it was difficult to quickly reflect real-time market information. As a result, it was not possible to quickly provide proposal documents that offered a competitive advantage. Furthermore, there was a lack of an efficient process for revising or updating documents, which led to problems with the quality and timing of the final proposal documents.

[0094] 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.

[0095] In this invention, the server includes: means for analyzing input information received from a user and generating initial proposal materials using a generative AI model; means for collecting market information in real time from open data sources on the Internet and analyzing it using natural language processing technology; and means for updating the content of the proposal materials based on the extracted market information. This allows users to quickly and efficiently create high-quality proposal materials that reflect the latest market information and quickly reflect correction instructions. Furthermore, by using the generative AI model, it is possible to automatically generate proposal materials based on past success stories and related materials. This significantly improves the competitiveness of business proposals.

[0096] "User" refers to the entity that uses the system to input information to create proposal materials and checks and modifies the generated materials.

[0097] A "proposal document" is a document used to propose a new service or product, and includes information on the target market, competitors, and service features.

[0098] The "server" is the central device of the computer system that analyzes information received from users, automatically generates proposal materials using a generative AI model, collects and analyzes real-time market information, and reflects it in the materials.

[0099] "Terminal" means a device that allows a user to input information and check and modify the generated proposal materials, and communicates with the server to send and receive data.

[0100] A "generative AI model" refers to a machine learning algorithm or model that automatically generates proposal materials based on information entered by the user.

[0101] "Input information" refers to data that a user inputs to create a proposal document, including the target market, the characteristics of the service or product, the design and format of the proposal, and the target audience.

[0102] An "open data source" is a collection of data that is publicly available on the internet, including news articles, blogs, social media, etc.

[0103] "Natural language processing technology" is a technology for analyzing collected text data and extracting important information and trends.

[0104] "Market Intelligence" refers to market trends and competitive information collected and analyzed from data sources on the Internet.

[0105] A "correction instruction" is an instruction that the user uses to specify additions or changes to the generated proposal material, and is transmitted to the server.

[0106] The "final proposal document" is a completed proposal document that reflects all revision requests from the user.

[0107] MODE FOR CARRYING OUT THE INVENTION

[0108] This invention is a system for efficiently creating proposal materials for new services. It uses a generative AI model based on information entered by the user to generate proposal materials, and has the function of reflecting real-time market information. This system provides an environment in which users can efficiently create competitive proposal materials.

[0109] System Overview

[0110] The system consists of a user, a terminal, and a server. The user inputs the information necessary to create a proposal document. The terminal sends this information to the server, which then provides the generated document to the user. The server analyzes the input information and generates the proposal document using a generative AI model. It also collects market information from open data sources on the Internet, analyzes it using natural language processing technology, and reflects that information in the proposal document.

[0111] Hardware and software used

[0112] Terminal: A device such as a personal computer or smartphone that allows users to input information and check and edit materials.

[0113] Server: A high-performance computer system that analyzes information, runs AI models, and collects and analyzes data.

[0114] Software: Word processing software, generative AI models (e.g., GPT), natural language processing techniques (e.g., NLTK, SpaCy)

[0115] Specific examples of creating proposal materials

[0116] For example, consider a case where a user is creating a proposal document for a new product. The user inputs the product's features, target market, and competitive information, and the server generates an initial proposal document using a corresponding template. The server collects market information in real time and adds the latest trends and competitive information to the proposal document. The user then reviews the document and requests revisions, and the server completes the final version of the proposal document. Through this process, the user can quickly create high-quality proposal documents that reflect the latest market information.

[0117] Prompt Sentence Examples

[0118] "To create a proposal for a new product, you enter product features, target market, and competitive information. The server generates an initial proposal based on this information. It also collects market information in real time, adding the latest trends and competitive information to the proposal."

[0119] This system enables users to quickly create high-quality proposal materials that reflect the latest market information, significantly improving the competitiveness of their business proposals.

[0120] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0121] Step 1:

[0122] The user inputs information related to the requirements for creating a proposal document. The information input by the user includes the target market, product or service features, proposal design and format, target audience, etc. Specifically, the user inputs information such as "list of new product features," "target market is North America," and "main competitor is Company X" into the input form. Once the input is complete, the information is saved for the next step.

[0123] Input: User-entered requirements information for proposal materials (e.g., product features, target market, competitive information)

[0124] Output: The input requirements information is saved.

[0125] Step 2:

[0126] The device sends the information entered by the user to the server. When the user clicks the "Send" button, the device calls the API in the backend and passes the input information to the server. The device notifies the user that the sending process was successful.

[0127] Input: User-entered requirements information for the proposal document

[0128] Output: User input sent to the server

[0129] Step 3:

[0130] The server analyzes the information received from the device and converts it into a format suitable for input into the generative AI model. Specifically, it converts the received information into JSON format and organizes it into a structure suitable for the generative AI model. It also pulls past success stories and related materials from a database and integrates this information.

[0131] Input: User input information sent from the device

[0132] Output: Information converted into a format that can be input into a generative AI model

[0133] Step 4:

[0134] The generative AI model generates an initial proposal based on the information prepared by the server, using the basic structure and template of the proposal. The initial version of the proposal reflects the requirements specified by the user.

[0135] Input: Information converted into a format that can be fed into a generative AI model

[0136] Output: Generate initial proposal materials

[0137] Step 5:

[0138] The server collects real-time market information from open data sources on the internet, through APIs and web scraping, retrieving relevant data from news articles, blogs, social media, etc.

[0139] Input: Real-time market data request

[0140] Output: Collected market data

[0141] Step 6:

[0142] The server analyzes the collected market data using natural language processing technology, specifically extracting important keywords and trends from the text data and organizing the information relevant to the proposal materials.

[0143] Input: Collected market data

[0144] Output: Analyzed market information (e.g. trends, competitive intelligence)

[0145] Step 7:

[0146] The server updates the content of the proposal documents based on the analyzed market information. Specifically, it adds the latest market trends and competitive analysis to the proposal documents, thereby enhancing the documents based on the latest information.

[0147] Input: Parsed market information

[0148] Output: Updated proposal

[0149] Step 8:

[0150] The user can check the generated proposal document and input any correction requests they may have. Through the GUI, the user can intuitively add or correct specific information, adjust the document design, and more.

[0151] Input: User requested correction

[0152] Output: Correction request entered

[0153] Step 9:

[0154] The terminal sends the modification request from the user to the server, and the user's modification request is now ready to be processed by the server.

[0155] Input: User's correction request

[0156] Output: The modification request sent to the server

[0157] Step 10:

[0158] The server updates the proposal documents based on the user's correction requests, and if necessary, performs new market analysis and adds the latest information to the documents to generate even stronger proposal documents.

[0159] Input: The modification request sent to the server

[0160] Output: Updated proposal

[0161] Step 11:

[0162] The server generates the final proposal document incorporating all requested revisions and saves it in formats such as PDF, PowerPoint, Google Slides, etc.

[0163] Input: Updated proposal

[0164] Output: Final proposal

[0165] Step 12:

[0166] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials by clicking on the download link.

[0167] Input: Final proposal

[0168] Output: The final proposal provided to the user

[0169] (Application example 1)

[0170] 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."

[0171] Creating proposal materials for advertising campaigns requires a great deal of time and effort, and it is difficult to quickly create materials that reflect the latest market information. The purpose of this invention is to solve these problems by efficiently collecting and analyzing the information necessary for advertising campaigns and automatically creating high-quality proposal materials that always reflect the latest market data.

[0172] 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.

[0173] In this invention, the server includes: means for a user to input information regarding requirements for creating proposal materials; means for transmitting the input information to the server; means for the server to analyze the input information received from the user and generate initial proposal materials using a generative AI model; means for the server to collect market information in real time from open data sources on the Internet and analyze it using natural language processing technology; means for the server to update the content of the proposal materials based on the extracted market information; means for the user to check the generated proposal materials and send correction instructions to the server; means for the server to update the proposal materials based on correction requests from the user and generate final proposal materials; means for the terminal to provide the final proposal materials to the user so that the user can check and download them; means for the user to input information about an advertising campaign and receive proposal materials generated based on this information; and means for collecting real-time market data and reflecting the results of analysis in the advertising campaign materials. This enables users to quickly and efficiently create high-quality proposal materials for their advertising campaigns and always reflect the latest market information.

[0174] A "user" is a person who inputs information required to create a proposal document, and checks and modifies the created document.

[0175] "Pitch deck" means a written or digital file that is used to present an advertising campaign or a product or service to the market.

[0176] "Creation requirements" refer to the information, conditions, specifications, etc. required when creating proposal materials.

[0177] The "server" is a computer system that receives and analyzes information entered by users and creates proposal materials using a generative AI model.

[0178] A "generative AI model" is an artificial intelligence model that automatically generates proposal materials based on input data.

[0179] An "initial proposal" is the first version of a proposal that is automatically created by a generative AI model based on information provided by a user.

[0180] "Open data sources on the Internet" refers to information sources that are publicly available online, such as news articles, blogs, and social media.

[0181] "Real-time market information" refers to the latest market data that changes over time, such as current market trends and competitive information.

[0182] "Natural language processing technology" is a computer science technology for analyzing text data, understanding its meaning, and extracting information.

[0183] "Modification instructions" refer to requests for modifications or additions made by the user to the generated proposal materials.

[0184] The "final version of the proposal material" refers to the proposal material that has been finally completed and that reflects the user's correction requests.

[0185] A "terminal" is a device used by a user to send input information and receive generated materials.

[0186] This invention is a system that efficiently creates proposal materials using a generative AI model based on information about advertising campaigns entered by users. The system generates optimal proposal materials based on initial information provided by users and real-time market data, and provides an environment where users can review and modify them.

[0187] Program Description

[0188] Proposal material creation phase

[0189] 1. The user enters information about the advertising campaign (e.g., product, target market, campaign objectives).

[0190] 2. The device sends the input information to the server.

[0191] 3. The server analyzes this information and converts it into a format suitable for the generative AI model, which then creates an initial proposal document based on this information.

[0192] Real-time market analysis phase

[0193] 1. The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.).

[0194] 2. Analyze the collected data using natural language processing (NLP) technology to extract the latest market trends and competitive information.

[0195] Market information integration phase

[0196] 1. The server updates the content of the proposal materials based on the analyzed market information. This update ensures that the proposal materials reflect the latest market trends and competitive information.

[0197] Material review and revision phase

[0198] 1. The user can review the generated proposal document and provide instructions for revisions as necessary, such as adding or correcting specific information or adjusting the document design.

[0199] 2. The device sends a modification request to the server.

[0200] 3. The server updates the proposal based on the revision request, conducting new market analysis as needed and adding the latest information.

[0201] Final material generation phase

[0202] 1. The server generates the final proposal document incorporating all requested revisions and saves it in a format that users can download or present, such as PDF, PowerPoint, or Google Slides.

[0203] 2. The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[0204] Specific examples

[0205] If a user is planning a social media campaign for a new cosmetics line, they would first enter the following information:

[0206] Product: New skin care line

[0207] Target market: Women aged 20-35

[0208] Campaign Objective: Increase engagement on Instagram and TikTok

[0209] Using this information, the server generates an initial proposal and then uses the following prompt to create a final proposal that reflects market information:

[0210] Create an ad campaign proposal with the following details:

[0211] Product: New skincare line

[0212] Target Audience: Women aged 20-35

[0213] Focus: Social media engagement on Instagram and TikTok

[0214] Real-time market information includes:

[0215] Update the initial ad campaign proposal with the following market trends and data:

[0216] Growing trend of eco-friendly skincare products

[0217] Increasing engagement rates on visual platforms like Instagram and TikTok

[0218] Competitor analysis showing a surge in influencer marketing strategies for similar products

[0219] This system allows users to quickly create high-quality proposal materials that always reflect the latest market data.

[0220] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0221] Step 1:

[0222] The user inputs information related to the requirements for creating an advertising campaign (e.g., product, target market, campaign objectives), including campaign details, target market demographics, goals, budget, etc.

[0223] Enter: Campaign details

[0224] Output: Initial information sent to the server

[0225] Step 2:

[0226] The device sends the information entered by the user to the server, and this data is sent in a standard format such as JSON.

[0227] Input: Campaign information entered by the user

[0228] Output: Campaign information transferred to the server

[0229] Step 3:

[0230] The server analyzes the input information received from the user and converts it into a format suitable for the generative AI model. Specifically, it converts text data into prompt sentences.

[0231] Input: Campaign information

[0232] Output: The prompt sentence that is input to the generative AI model

[0233] Step 4:

[0234] The server automatically generates the initial proposal using a generative AI model, which generates text based on the prompt sentences mentioned above.

[0235] Input: prompt statement

[0236] Output: Initial proposal

[0237] Step 5:

[0238] The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.) using scraping technology and APIs.

[0239] Input: None (automatic collection)

[0240] Output: Real-time market data

[0241] Step 6:

[0242] The server analyzes the collected data using natural language processing (NLP) technology to extract the latest market trends and competitive information, specifically through word analysis, topic modeling, and sentiment analysis.

[0243] Input: Real-time market data

[0244] Output: Analyzed market trend information

[0245] Step 7:

[0246] The server updates the initial proposal based on the analyzed market information, and re-uses the generative AI model to generate more specific proposals.

[0247] Input: Initial proposal materials, analyzed market information

[0248] Output: Updated proposal

[0249] Step 8:

[0250] The user checks the generated proposal document and sends correction instructions to the server as necessary, such as adding or correcting specific information or adjusting the document design.

[0251] Input: Updated proposal

[0252] Output: User's correction instructions

[0253] Step 9:

[0254] The terminal sends the user's revision requests to the server, which then generates the final version of the proposal based on this information.

[0255] Input: User's correction request

[0256] Output: The modification request forwarded to the server

[0257] Step 10:

[0258] The server uses the generative AI model again based on the user's correction requests to generate the final proposal document, and if necessary, performs new market analysis and adds the latest information.

[0259] Input: Correction Request

[0260] Output: Final proposal

[0261] Step 11:

[0262] The terminal provides the final proposal materials to the user and saves them in a format that the user can view and download.

[0263] Input: Final proposal

[0264] Output: A download link or file that is provided to the user

[0265] 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.

[0266] The present invention relates to a system that integrates the creation of proposal materials with real-time market information and further optimizes the content of the proposal materials by recognizing user emotions. The system includes a means for a user to input information required for creating proposal materials and generate the materials using a generative AI model. Furthermore, the system is equipped with an emotion engine that analyzes user emotions and provides more appropriate materials.

[0267] Explanation of program processing

[0268] Proposal material creation phase

[0269] User:

[0270] The user first inputs information about the requirements for creating a proposal document into the device, including the target market, the features of the proposed product or service, the design and format of the proposal document, and the target audience, as well as data for capturing emotions from the user's voice and text input.

[0271] Device:

[0272] The terminal transmits the information and emotion data input by the user to the server.

[0273] Initial Data Preparation Phase

[0274] server:

[0275] The server analyzes the received information and converts it into a format that can be input to the generative AI model. At the same time, it analyzes the user's emotions using an emotion engine and supplies this information to the generative AI model.

[0276] Initial data generation phase

[0277] server:

[0278] The server uses the analyzed input information and emotion data to generate an initial proposal using a generative AI model, which reflects the user's input and emotional adjustments.

[0279] Real-time market analysis phase

[0280] server:

[0281] The server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology. From the analysis results, the latest market trends and competitive information are extracted.

[0282] Market information integration phase

[0283] server:

[0284] The extracted market information is used to update the content of the initial pitch deck, and the tone and messaging of the pitch deck are adjusted based on user sentiment data obtained from the emotion engine.

[0285] Material review and revision phase

[0286] User:

[0287] The user can review the generated proposal and provide instructions for revisions to the content and design, including those based on the user's feelings.

[0288] Device:

[0289] The terminal transmits a modification request from the user to the server.

[0290] server:

[0291] The server updates the proposal materials based on correction requests from users, and reanalyzes and reflects new market information and sentiment data as necessary.

[0292] Final data generation phase

[0293] server:

[0294] Generate a final proposal document that reflects all revision requests, real-time market information, and sentiment data, and save it as a PDF, PowerPoint, Google Slides, etc.

[0295] Proposal materials provision phase

[0296] Device:

[0297] The final proposal will be provided to the user for review and download.

[0298] Specific examples

[0299] For example, when a user creates a proposal document for a new product, they input product features, target market, and competitive information, along with the associated emotions of excitement and anticipation. The server generates an initial proposal document based on this information and emotion data, and then collects real-time market information and integrates it into the document. The user then reviews the document and provides instructions for revision based on their emotions, and the server ultimately generates a high-quality proposal document that reflects the user's emotions.

[0300] This system allows users to efficiently create high-quality proposal materials that reflect real-time market information and their own emotions, significantly improving the competitiveness of business proposals and providing more persuasive materials that are in tune with users' emotions.

[0301] The processing flow will be explained below.

[0302] Step 1:

[0303] The user inputs information about the requirements for creating a proposal document into the terminal, including the target market, the characteristics of the proposed product or service, the design and format of the document, and the target audience.

[0304] Step 2:

[0305] The terminal transmits the information entered by the user and emotion data obtained from voice and text to the server.

[0306] Step 3:

[0307] The server analyzes the received information and converts it into a format that can be input into the generative AI model, while simultaneously analyzing the user's emotions using an emotion engine.

[0308] Step 4:

[0309] The server uses a generative AI model to automatically generate an initial proposal document based on the analyzed input information and emotion data, which includes adjustments based on the information and emotion entered by the user.

[0310] Step 5:

[0311] The server collects real-time market information from open data sources on the internet, such as news articles, blogs, and social media.

[0312] Step 6:

[0313] The server analyzes the collected market information using natural language processing technology and extracts the latest market trends and competitive information.

[0314] Step 7:

[0315] The server updates the content of the initial pitch deck based on the extracted market information, while simultaneously adjusting the pitch deck's tone and messaging based on user emotion data obtained from the emotion engine.

[0316] Step 8:

[0317] The user reviews the generated proposal materials and makes suggestions for revisions to the content and design of the materials, including suggestions for revisions based on the user's feelings.

[0318] Step 9:

[0319] The terminal transmits a modification request from the user to the server.

[0320] Step 10:

[0321] The server updates the proposal materials based on user requests for revisions, and if necessary, re-analyzes market information and sentiment data to reflect these changes.

[0322] Step 11:

[0323] The server generates the final proposal document, incorporating all revision requests, real-time market information, and sentiment data, and saves it in formats such as PDF, PowerPoint, and Google Slides.

[0324] Step 12:

[0325] The terminal provides the final version of the proposal material to the user, allowing the user to check and download the material.

[0326] Example 2

[0327] 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."

[0328] Conventional proposal material creation systems have difficulty fully reflecting user sentiment and real-time market information, resulting in a decline in the persuasiveness and competitiveness of the materials. Furthermore, updating and correcting materials is time-consuming, which can cause delays in a business environment where rapid response is required. Therefore, the present invention solves these problems and enables the efficient creation of high-quality proposal materials.

[0329] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0330] In this invention, the server includes means for analyzing voice and facial expression data to recognize user emotions, means for collecting market information in real time from open data sources on the Internet and analyzing it using natural language processing technology, and means for reanalyzing the emotion data to generate final proposal materials, thereby enabling the creation of high-quality proposal materials that reflect user emotions and the latest market information.

[0331] "User" refers to an individual or organization who inputs the information necessary to create proposal materials and operates the system.

[0332] "Terminal" means an electronic device used by a User to input information or to view and download generated proposal materials.

[0333] "Server" refers to the computer system that receives and analyzes information sent by users and generates and updates proposal materials using generative AI models.

[0334] A "proposal" is a document or presentation that describes the features, target market, and target audience of a particular product or service that a user is aiming to create.

[0335] A "generative AI model" is an artificial intelligence model that generates proposal materials based on information entered by the user.

[0336] "Emotion data" refers to information about emotions acquired from the user's voice and facial expressions.

[0337] "Market intelligence" refers to data such as market trends and competitive information collected from open data sources on the Internet.

[0338] "Natural language processing technology" is a technology used to analyze market information, and is a method for analyzing the meaning of text data and extracting information.

[0339] A "modification instruction" is a request made by a user to change the content or design of the generated proposal material.

[0340] The present invention relates to a system for creating proposal materials, integrating real-time market information, and optimizing the content of the proposal materials by recognizing user emotions. This system is realized by combining multiple means.

[0341] Hardware and software configuration of the proposal document creation system

[0342] User:

[0343] Users input the information required to create proposal materials into a device. The device can be a PC, tablet, smartphone, or other electronic device. Users input using a keyboard, microphone, and camera. Voice input is converted into text using voice recognition software, and facial expression data is acquired using a camera and image analysis software.

[0344] Device:

[0345] The device sends the information and emotion data entered by the user to the server. Data is transferred over an internet connection and encryption technology such as SSL / TLS, using protocols such as HTTP POST requests.

[0346] server:

[0347] The server analyzes the received information and generates initial proposal materials using a generative AI model. A text analysis engine and a sentiment analysis engine run on the server, converting the input information and sentiment data into an appropriate format. This process uses natural language processing models such as BERT and sentiment analysis models.

[0348] The server also collects real-time market information from open data sources on the Internet, using web scraping technology and APIs, and analyzes the market information using natural language processing technology to extract the latest trends and competitive information. The analyzed market information is then integrated into proposal materials and updated.

[0349] Examples of specific examples and prompts

[0350] For example, when a user creates a proposal for a new product, they use their device to input product features, target market, competitive information, etc. The device then sends this information to a server. The server then analyzes the received information, including sentiment data, and generates an initial proposal using a generative AI model (e.g., GPT-4). The server then collects market information and updates the proposal in real time.

[0351] The user reviews the generated proposal document and sends revision instructions from the terminal to the server. The server reanalyzes the revision requests, the latest market information, and sentiment data to generate the final proposal document. The terminal then provides the final proposal document to the user, who then reviews and downloads it.

[0352] Prompt Sentence Examples

[0353] Enter the following prompt into the generative AI model:

[0354] Please enter the features of your new product as follows: The target market is technology startups, and the competitive information is that Company A and Company B are the main competitors. The design of the proposal document should be simple, and the target audience should be engineers. Furthermore, the content should reflect their expectations.

[0355] This system allows users to efficiently create high-quality proposal materials that reflect real-time market information and their own emotions, improving the competitiveness of business proposals and providing persuasive materials that are in tune with users' emotions.

[0356] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0357] Step 1:

[0358] User:

[0359] The user inputs the information necessary to create a proposal document into the device. Specifically, details such as the target market, the features of the proposed product or service, the document design and format, and the target audience are entered as text. Voice input can also be performed using a microphone, and the voice is converted into text by an automatic speech recognition system. Furthermore, a camera is used to capture facial expressions, which are then used as data for emotion analysis. This provides the user's input information and emotion data.

[0360] Step 2:

[0361] Device:

[0362] The device sends the information entered by the user and emotion data to the server. Specifically, the text data, text data obtained by voice recognition, and facial expression data are all sent together via an HTTP POST request. The data is encrypted using SSL / TLS before being sent and is securely transferred to the server.

[0363] Step 3:

[0364] server:

[0365] The server analyzes the received information. First, it uses a text analysis engine to format the information entered by the user into an appropriate format. Next, it uses an emotion analysis engine to extract the user's emotions from the voice data and facial expression data and stores them as numerical data. For example, emotions such as "happiness" and "expectation" are quantified. This step also converts the analysis results into a format that can be applied to a generative AI model. Through this process, the input data is analyzed and a dataset for the AI ​​model is generated.

[0366] Step 4:

[0367] server:

[0368] The server uses a generative AI model to generate an initial proposal. Specifically, the analyzed input information and emotional data are input as prompts into a generative AI model such as OpenAI's GPT-4. The generative AI model then uses this data to generate text and graphic elements for the initial proposal. The result is an initial proposal that reflects the user's input and emotional data.

[0369] Step 5:

[0370] server:

[0371] The server collects market information in real time from open data sources on the Internet. Specifically, it uses web scraping and APIs to obtain the latest market information from news sites and industry reports. This allows for the collection of market trends and competitive information in real time.

[0372] Step 6:

[0373] server:

[0374] The server analyzes the collected market information using natural language processing technology. This analysis uses language models such as BERT to extract trends and competitive information from the collected text data. The analysis results are integrated into proposal materials. Specifically, the market information is summarized and output as text data to be integrated into the strategy section of the proposal materials.

[0375] Step 7:

[0376] server:

[0377] The server updates the content of the initial proposal based on the extracted market information. Furthermore, it adjusts the tone and messaging of the proposal based on the user's emotional data obtained from the emotion engine. For example, it reflects competitive information and uses more positive language in response to the user's expressed expectations. This allows the initial proposal to be shaped by market information and emotional data.

[0378] Step 8:

[0379] User:

[0380] The user can review the generated proposal and make corrections to the content and design. The user can use a terminal to input corrections such as changing the color of a specific graph or requesting additional information. Corrections can also be made based on emotions.

[0381] Step 9:

[0382] Device:

[0383] The terminal transmits a request for modification from the user to the server. Specifically, the modification content made by the user on the terminal is sent to the server in text format, and the server receives it in a format that can be processed.

[0384] Step 10:

[0385] server:

[0386] The server updates the proposal documents based on the user's revision requests. If necessary, it reanalyzes new market information and sentiment data and reflects the revisions. For example, it adds newly collected market information and revise the proposal documents to reflect the sentiment data. This updates the proposal documents to reflect the revision requests.

[0387] Step 11:

[0388] server:

[0389] The server generates the final proposal document, reflecting all revision requests, real-time market information, and sentiment data, and converts and saves the document in formats such as PDF, PowerPoint, Google Slides, etc. This results in a file that can be used as a high-quality presentation document.

[0390] Step 12:

[0391] Device:

[0392] The terminal provides the final proposal materials to the user, allowing the user to review and download them. Specifically, a download link for the materials is displayed on the terminal, and when the user clicks it, the file download begins. This allows the user to review and use the final proposal materials.

[0393] (Application example 2)

[0394] 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."

[0395] Conventional advertising material creation systems have difficulty reflecting real-time changes in market information and user sentiment, resulting in difficulties in creating consistent, high-quality advertising materials. Furthermore, the time-consuming task of manually collecting market trends and competitive information hinders efficient material creation. Furthermore, it is not possible to create advertising materials that reflect user sentiment, making it difficult to increase persuasiveness and empathy among the target audience.

[0396] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0397] In this invention, the server includes: means for a user to input information regarding requirements for creating advertising materials; means for transmitting the input information to the server; means for the server to analyze the input information received from the user and generate initial advertising materials using a generative AI model; means for the server to collect market information in real time from open data sources on the Internet and analyze it using natural language processing technology; means for the server to update the content of the advertising materials based on the extracted market information; means for the server to analyze emotions from user voice input; means for the server to adjust the tone and messaging of the advertising materials based on the emotion analysis results; means for the user to review the generated advertising materials and send correction instructions to the server; means for the server to update the advertising materials based on correction requests from the user and generate final advertising materials; and means for the terminal to provide the final advertising materials to the user so that the user can review and download them. This enables efficient creation of high-quality, consistent advertising materials that reflect real-time market information and user emotions.

[0398] A "user" is a person who uses the system to create advertising materials.

[0399] "Advertising materials" are documents or presentations created to promote a particular product or service.

[0400] "Production requirements" are all the information needed to create advertising materials, including the theme, target market, competitive information, etc.

[0401] An "input means" is an interface or device used by a user to provide information that enters the system.

[0402] A "server" is a central processing unit that receives input information from a user and processes and analyzes it.

[0403] A "generative AI model" is an artificial intelligence model that automatically generates advertising materials based on given input data.

[0404] "Initial Advertising Materials" means the first version of advertising materials created by a generative AI model.

[0405] "Internet open data sources" are publicly available data resources accessible via the Internet, including market information.

[0406] "Natural language processing technology" is a technology for analyzing text data, extracting information, and understanding meaning.

[0407] "Means for collecting market information in real time" refers to a method that allows for the immediate acquisition of dynamically changing market data.

[0408] "Sentiment analysis" is the process of identifying a user's emotions from their voice or text.

[0409] "Means to adjust tone and messaging" refers to methods to optimize the content and presentation of advertising materials based on user emotions.

[0410] "Modification instructions" refer to requests for changes made by a user to generated advertising materials.

[0411] "Final Advertising Materials" means advertising materials in their completed form, incorporating all revision instructions and the latest market information.

[0412] "Terminal" means a device used by a user to operate the system and to view and download advertising materials.

[0413] The present invention is a system for supporting the creation of advertising materials, which includes a user, a terminal, and a server. In this system, the user inputs information and sends it to the server via the terminal, and the server creates the materials using a generative AI model. Furthermore, the server analyzes the user's sentiment and reflects real-time market information in the materials.

[0414] The server receives information entered by the user regarding the requirements for creating advertising materials. For example, the system receives user-entered information such as themes, target markets, and competitive information. This information is sent from the device to the server. Voice data provided by the user is also sent to the server and is subjected to sentiment analysis.

[0415] The server generates initial advertising materials using a generative AI model. The generative AI model creates advertising materials based on information entered by the user. The server also collects market information in real time from open data sources on the Internet. The market information is analyzed using natural language processing technology, and the extracted market information is used to update the content of the advertising materials.

[0416] The server has an emotion engine for analyzing emotions from the user's voice data. The emotion engine analyzes the user's emotion data and uses the results to adjust the tone and messaging of advertising materials. For example, if the user is excited, advertising materials with a positive tone that reflects that emotion are generated.

[0417] The user checks the generated advertising materials on their device and sends correction instructions to the server as necessary. The server updates the advertising materials based on the correction instructions. The final version of the advertising materials is completed by reflecting all correction requests and the latest market information. The final advertising materials are provided to the user via their device, allowing them to check and download them.

[0418] The system operates using the following hardware and software: The hardware includes the user's device (e.g., smartphone or PC) and server. The software includes the OpenAI API, which provides the generative AI model, an internet connection to obtain real-time market information, and an emotion engine for emotion analysis.

[0419] As a concrete example, let's consider the case where a user creates advertising materials for a "new product launch." In this case, the user uses their device to input the following information: the new product's features, target market, competitive information, emotions of excitement and anticipation, etc. This information is sent to the server, where the generative AI model and sentiment analysis engine perform their respective roles to generate the initial advertising materials. The server then collects market information from the Internet and integrates it into the materials. The user reviews the materials and makes corrections as necessary. The final advertising materials are provided with all inputs reflected.

[0420] Example prompt sentence:

[0421] User Input Data: New Product Launch

[0422] User emotion data: excitement, anticipation

[0423] Market intelligence: Competitor A adds new features this month

[0424] Use the information above to create the best advertising materials.

[0425] As described above, by using the system of the present invention, it is possible to efficiently create high-quality, consistent advertising materials that reflect real-time market information and user sentiment.

[0426] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0427] Step 1:

[0428] The user inputs information regarding the requirements for producing advertising materials into the terminal.

[0429] Input: New product features, target market, competitive intelligence, user voice input, etc.

[0430] Processing: The user uses the device to enter the required information and collect data on the device, including voice input.

[0431] Output: Collected data is saved to the device.

[0432] Step 2:

[0433] The terminal transmits the information entered by the user to the server.

[0434] Input: Data about the creation requirements entered by the user into the terminal.

[0435] Processing: The device formats the user's input data and transmits it over the Internet to a server.

[0436] Output: The user input information is sent to the server.

[0437] Step 3:

[0438] The server analyzes the received input information and generates initial advertising materials using a generative AI model.

[0439] Input: Data about the creation requirements submitted by the user.

[0440] Processing: The server analyzes the input information and converts it into an input format for the generative AI model. Based on this format, the generative AI model is called to generate the initial advertising materials.

[0441] Output: Generation of initial advertising materials.

[0442] Step 4:

[0443] The server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology.

[0444] Input: Raw data from open data sources on the internet.

[0445] Processing: The server collects market information in real time, analyzes market trends and competitive information using natural language processing technology, and extracts the required data.

[0446] Output: Extracted market information.

[0447] Step 5:

[0448] The server updates the content of the advertising materials based on the extracted market information.

[0449] Input: Extracted market information, initial advertising materials.

[0450] Processing: Based on market information, the server updates the content of advertising materials, optimizing the tone and messaging of the materials.

[0451] Output: Updated advertising materials reflecting market information.

[0452] Step 6:

[0453] The server uses an emotion analysis engine to analyze the user's emotion data.

[0454] Input: User's voice data.

[0455] Processing: The server performs emotion analysis on the voice input and extracts the user's emotion data.

[0456] Output: Extracted emotion data.

[0457] Step 7:

[0458] The server adjusts the tone and messaging of advertising materials based on the results of sentiment analysis.

[0459] Input: Sentiment data, updated advertising materials.

[0460] Processing: The server uses the emotional data to optimize the content of advertising materials, for example, adding a positive tone if the emotional data is "excited."

[0461] Output: Emotionally corrected advertising materials.

[0462] Step 8:

[0463] The user checks the generated advertising materials and sends correction instructions to the server.

[0464] Input: Emotionally corrected advertising materials.

[0465] Processing: The user checks the advertising materials through the terminal and gives instructions on what needs to be corrected. These instructions are sent from the terminal to the server.

[0466] Output: User correction instructions.

[0467] Step 9:

[0468] The server updates the advertising materials based on the correction requests from the user and generates the final version of the advertising materials.

[0469] Input: User correction instructions, emotion-corrected advertising materials.

[0470] Processing: The server re-updates the advertising materials based on the user's modification requests, and re-reflects the sentiment data and market information to generate the final materials.

[0471] Output: Final, completed advertising materials.

[0472] Step 10:

[0473] The device provides the final advertising material to the user for review and download.

[0474] Input: Final advertising materials.

[0475] Processing: The device receives the final advertising material from the server, stores it and provides it for the user to access.

[0476] Output: Final advertising materials available for user review and download.

[0477] 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.

[0478] 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.

[0479] 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.

[0480] [Second embodiment]

[0481] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0482] 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.

[0483] 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).

[0484] 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.

[0485] 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.

[0486] 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).

[0487] 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.

[0488] 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.

[0489] 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.

[0490] 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.

[0491] 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.

[0492] 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."

[0493] The present invention is a system for efficiently creating proposal materials for new services, which uses a generative AI model based on information entered by the user to generate proposal materials and has the function of reflecting real-time market information. This system provides an environment in which users can efficiently create competitive proposal materials.

[0494] Explanation of program processing

[0495] Proposal material creation phase

[0496] User:

[0497] Users first input information about the requirements for creating a proposal, including the target market, service or product features, proposal design and format, and target audience.

[0498] Device:

[0499] The terminal transmits the information entered by the user to the server.

[0500] server:

[0501] The server analyzes the received information and converts it into a format that can be input to the generative AI model. Based on this information, it creates the structure of an initial proposal document. The generative AI model then automatically generates an initial version of the proposal document. This initial version includes the information entered by the user, past success stories, and related materials.

[0502] Real-time market analysis phase

[0503] server:

[0504] The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.) and analyzes the collected data using natural language processing technology to extract the latest market trends and competitive information.

[0505] Market information integration phase

[0506] server:

[0507] The content of the proposal materials is updated based on the analyzed market information. This update ensures that the proposal materials reflect the latest market trends and competitive information, ensuring that the materials are always up-to-date and persuasive.

[0508] Material review and revision phase

[0509] User:

[0510] The user can review the generated proposal and provide instructions for revisions as necessary, such as adding or correcting specific information or adjusting the document design.

[0511] Device:

[0512] The terminal transmits a modification request from the user to the server.

[0513] server:

[0514] The server updates the proposal documents based on user requests for revisions, and if necessary, performs new market analysis and adds the latest information, making the proposal documents even stronger and more competitive.

[0515] Final material generation phase

[0516] server:

[0517] The server generates a final proposal document incorporating all requested revisions and saves it in a format that users can download and present, such as PDF, PowerPoint, or Google Slides.

[0518] Device:

[0519] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[0520] Specific examples

[0521] For example, consider a case where a user is creating a proposal document for a new product. The user inputs the product's features, target market, and competitive information, and the server generates an initial proposal document using a corresponding template. The server collects market information in real time and adds the latest trends and competitive information to the proposal document. The user then reviews the document and requests revisions, and the server completes the final version of the proposal document. Through this process, the user can quickly create high-quality proposal documents that reflect the latest market information.

[0522] This invention enables users to quickly create high-quality proposal materials that reflect market trends in real time, significantly improving the competitiveness of business proposals.

[0523] The processing flow will be explained below.

[0524] Step 1:

[0525] The user inputs information about the requirements for creating a proposal into the terminal, including the target market, the characteristics of the proposed product or service, the design and format of the proposal, and the target audience.

[0526] Step 2:

[0527] The terminal transmits the information entered by the user to the server.

[0528] Step 3:

[0529] The server analyzes the received information and converts it into a format that can be input into the generative AI model.

[0530] Step 4:

[0531] The server automatically generates an initial proposal document using a generative AI model based on the analyzed input information, and at this stage, it also references past success stories and related materials to enhance the content.

[0532] Step 5:

[0533] The server collects real-time market information from open data sources on the internet, such as news articles, blogs, and social media.

[0534] Step 6:

[0535] The server analyzes the collected market information using natural language processing technology and extracts the latest market trends and competitive information.

[0536] Step 7:

[0537] The server updates the content of the initial proposal based on the extracted market information, so that the latest market information is reflected in the proposal.

[0538] Step 8:

[0539] The user checks the generated proposal document and, if necessary, gives instructions for modifying the content or design of the document.

[0540] Step 9:

[0541] The terminal transmits a modification request from the user to the server.

[0542] Step 10:

[0543] The server updates the proposal documents based on the user's correction requests, and if necessary, performs new market analysis to further strengthen the proposal documents.

[0544] Step 11:

[0545] The server generates the final proposal document with all requested revisions reflected, and the document is saved in a format such as PDF, PowerPoint, or Google Slides.

[0546] Step 12:

[0547] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[0548] Example 1

[0549] 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."

[0550] With conventional proposal creation systems, users had to create documents from scratch, which required a great deal of time and effort, and it was difficult to quickly reflect real-time market information. As a result, it was not possible to quickly provide proposal documents that offered a competitive advantage. Furthermore, there was a lack of an efficient process for revising or updating documents, which led to problems with the quality and timing of the final proposal documents.

[0551] 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.

[0552] In this invention, the server includes: means for analyzing input information received from a user and generating initial proposal materials using a generative AI model; means for collecting market information in real time from open data sources on the Internet and analyzing it using natural language processing technology; and means for updating the content of the proposal materials based on the extracted market information. This allows users to quickly and efficiently create high-quality proposal materials that reflect the latest market information and quickly reflect correction instructions. Furthermore, by using the generative AI model, it is possible to automatically generate proposal materials based on past success stories and related materials. This significantly improves the competitiveness of business proposals.

[0553] "User" refers to the entity that uses the system to input information to create proposal materials and checks and modifies the generated materials.

[0554] A "proposal document" is a document used to propose a new service or product, and includes information on the target market, competitors, and service features.

[0555] The "server" is the central device of the computer system that analyzes information received from users, automatically generates proposal materials using a generative AI model, collects and analyzes real-time market information, and reflects it in the materials.

[0556] "Terminal" means a device that allows a user to input information and check and modify the generated proposal materials, and communicates with the server to send and receive data.

[0557] A "generative AI model" refers to a machine learning algorithm or model that automatically generates proposal materials based on information entered by the user.

[0558] "Input information" refers to data that a user inputs to create a proposal document, including the target market, the characteristics of the service or product, the design and format of the proposal, and the target audience.

[0559] An "open data source" is a collection of data that is publicly available on the internet, including news articles, blogs, social media, etc.

[0560] "Natural language processing technology" is a technology for analyzing collected text data and extracting important information and trends.

[0561] "Market Intelligence" refers to market trends and competitive information collected and analyzed from data sources on the Internet.

[0562] A "correction instruction" is an instruction that the user uses to specify additions or changes to the generated proposal material, and is transmitted to the server.

[0563] The "final proposal document" is a completed proposal document that reflects all revision requests from the user.

[0564] MODE FOR CARRYING OUT THE INVENTION

[0565] This invention is a system for efficiently creating proposal materials for new services. It uses a generative AI model based on information entered by the user to generate proposal materials, and has the function of reflecting real-time market information. This system provides an environment in which users can efficiently create competitive proposal materials.

[0566] System Overview

[0567] The system consists of a user, a terminal, and a server. The user inputs the information necessary to create a proposal document. The terminal sends this information to the server, which then provides the generated document to the user. The server analyzes the input information and generates the proposal document using a generative AI model. It also collects market information from open data sources on the Internet, analyzes it using natural language processing technology, and reflects that information in the proposal document.

[0568] Hardware and software used

[0569] Terminal: A device such as a personal computer or smartphone that allows users to input information and check and edit materials.

[0570] Server: A high-performance computer system that analyzes information, runs AI models, and collects and analyzes data.

[0571] Software: Word processing software, generative AI models (e.g., GPT), natural language processing techniques (e.g., NLTK, SpaCy)

[0572] Specific examples of creating proposal materials

[0573] For example, consider a case where a user is creating a proposal document for a new product. The user inputs the product's features, target market, and competitive information, and the server generates an initial proposal document using a corresponding template. The server collects market information in real time and adds the latest trends and competitive information to the proposal document. The user then reviews the document and requests revisions, and the server completes the final version of the proposal document. Through this process, the user can quickly create high-quality proposal documents that reflect the latest market information.

[0574] Prompt Sentence Examples

[0575] "To create a proposal for a new product, you enter product features, target market, and competitive information. The server generates an initial proposal based on this information. It also collects market information in real time, adding the latest trends and competitive information to the proposal."

[0576] This system enables users to quickly create high-quality proposal materials that reflect the latest market information, significantly improving the competitiveness of their business proposals.

[0577] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0578] Step 1:

[0579] The user inputs information related to the requirements for creating a proposal document. The information input by the user includes the target market, product or service features, proposal design and format, target audience, etc. Specifically, the user inputs information such as "list of new product features," "target market is North America," and "main competitor is Company X" into the input form. Once the input is complete, the information is saved for the next step.

[0580] Input: User-entered requirements information for proposal materials (e.g., product features, target market, competitive information)

[0581] Output: The input requirements information is saved.

[0582] Step 2:

[0583] The device sends the information entered by the user to the server. When the user clicks the "Send" button, the device calls the API in the backend and passes the input information to the server. The device notifies the user that the sending process was successful.

[0584] Input: User-entered requirements information for the proposal document

[0585] Output: User input sent to the server

[0586] Step 3:

[0587] The server analyzes the information received from the device and converts it into a format suitable for input into the generative AI model. Specifically, it converts the received information into JSON format and organizes it into a structure suitable for the generative AI model. It also pulls past success stories and related materials from a database and integrates this information.

[0588] Input: User input information sent from the device

[0589] Output: Information converted into a format that can be input into a generative AI model

[0590] Step 4:

[0591] The generative AI model generates an initial proposal based on the information prepared by the server, using the basic structure and template of the proposal. The initial version of the proposal reflects the requirements specified by the user.

[0592] Input: Information converted into a format that can be fed into a generative AI model

[0593] Output: Generate initial proposal materials

[0594] Step 5:

[0595] The server collects real-time market information from open data sources on the internet, through APIs and web scraping, retrieving relevant data from news articles, blogs, social media, etc.

[0596] Input: Real-time market data request

[0597] Output: Collected market data

[0598] Step 6:

[0599] The server analyzes the collected market data using natural language processing technology, specifically extracting important keywords and trends from the text data and organizing the information relevant to the proposal materials.

[0600] Input: Collected market data

[0601] Output: Analyzed market information (e.g. trends, competitive intelligence)

[0602] Step 7:

[0603] The server updates the content of the proposal documents based on the analyzed market information. Specifically, it adds the latest market trends and competitive analysis to the proposal documents, thereby enhancing the documents based on the latest information.

[0604] Input: Parsed market information

[0605] Output: Updated proposal

[0606] Step 8:

[0607] The user can check the generated proposal document and input any correction requests they may have. Through the GUI, the user can intuitively add or correct specific information, adjust the document design, and more.

[0608] Input: User requested correction

[0609] Output: Correction request entered

[0610] Step 9:

[0611] The terminal sends the modification request from the user to the server, and the user's modification request is now ready to be processed by the server.

[0612] Input: User's correction request

[0613] Output: The modification request sent to the server

[0614] Step 10:

[0615] The server updates the proposal documents based on the user's correction requests, and if necessary, performs new market analysis and adds the latest information to the documents to generate even stronger proposal documents.

[0616] Input: The modification request sent to the server

[0617] Output: Updated proposal

[0618] Step 11:

[0619] The server generates the final proposal document incorporating all requested revisions and saves it in formats such as PDF, PowerPoint, Google Slides, etc.

[0620] Input: Updated proposal

[0621] Output: Final proposal

[0622] Step 12:

[0623] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials by clicking on the download link.

[0624] Input: Final proposal

[0625] Output: The final proposal provided to the user

[0626] (Application example 1)

[0627] 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."

[0628] Creating proposal materials for advertising campaigns requires a great deal of time and effort, and it is difficult to quickly create materials that reflect the latest market information. The purpose of this invention is to solve these problems by efficiently collecting and analyzing the information necessary for advertising campaigns and automatically creating high-quality proposal materials that always reflect the latest market data.

[0629] 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.

[0630] In this invention, the server includes: means for a user to input information regarding requirements for creating proposal materials; means for transmitting the input information to the server; means for the server to analyze the input information received from the user and generate initial proposal materials using a generative AI model; means for the server to collect market information in real time from open data sources on the Internet and analyze it using natural language processing technology; means for the server to update the content of the proposal materials based on the extracted market information; means for the user to check the generated proposal materials and send correction instructions to the server; means for the server to update the proposal materials based on correction requests from the user and generate final proposal materials; means for the terminal to provide the final proposal materials to the user so that the user can check and download them; means for the user to input information about an advertising campaign and receive proposal materials generated based on this information; and means for collecting real-time market data and reflecting the results of analysis in the advertising campaign materials. This enables users to quickly and efficiently create high-quality proposal materials for their advertising campaigns and always reflect the latest market information.

[0631] A "user" is a person who inputs information required to create a proposal document, and checks and modifies the created document.

[0632] "Pitch deck" means a written or digital file that is used to present an advertising campaign or a product or service to the market.

[0633] "Creation requirements" refer to the information, conditions, specifications, etc. required when creating proposal materials.

[0634] The "server" is a computer system that receives and analyzes information entered by users and creates proposal materials using a generative AI model.

[0635] A "generative AI model" is an artificial intelligence model that automatically generates proposal materials based on input data.

[0636] An "initial proposal" is the first version of a proposal that is automatically created by a generative AI model based on information provided by a user.

[0637] "Open data sources on the Internet" refers to information sources that are publicly available online, such as news articles, blogs, and social media.

[0638] "Real-time market information" refers to the latest market data that changes over time, such as current market trends and competitive information.

[0639] "Natural language processing technology" is a computer science technology for analyzing text data, understanding its meaning, and extracting information.

[0640] "Modification instructions" refer to requests for modifications or additions made by the user to the generated proposal materials.

[0641] The "final version of the proposal material" refers to the proposal material that has been finally completed and that reflects the user's correction requests.

[0642] A "terminal" is a device used by a user to send input information and receive generated materials.

[0643] This invention is a system that efficiently creates proposal materials using a generative AI model based on information about advertising campaigns entered by users. The system generates optimal proposal materials based on initial information provided by users and real-time market data, and provides an environment where users can review and modify them.

[0644] Program Description

[0645] Proposal material creation phase

[0646] 1. The user enters information about the advertising campaign (e.g., product, target market, campaign objectives).

[0647] 2. The device sends the input information to the server.

[0648] 3. The server analyzes this information and converts it into a format suitable for the generative AI model, which then creates an initial proposal document based on this information.

[0649] Real-time market analysis phase

[0650] 1. The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.).

[0651] 2. Analyze the collected data using natural language processing (NLP) technology to extract the latest market trends and competitive information.

[0652] Market information integration phase

[0653] 1. The server updates the content of the proposal materials based on the analyzed market information. This update ensures that the proposal materials reflect the latest market trends and competitive information.

[0654] Material review and revision phase

[0655] 1. The user can review the generated proposal document and provide instructions for revisions as necessary, such as adding or correcting specific information or adjusting the document design.

[0656] 2. The device sends a modification request to the server.

[0657] 3. The server updates the proposal based on the revision request, conducting new market analysis as needed and adding the latest information.

[0658] Final material generation phase

[0659] 1. The server generates the final proposal document incorporating all requested revisions and saves it in a format that users can download or present, such as PDF, PowerPoint, or Google Slides.

[0660] 2. The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[0661] Specific examples

[0662] If a user is planning a social media campaign for a new cosmetics line, they would first enter the following information:

[0663] Product: New skin care line

[0664] Target market: Women aged 20-35

[0665] Campaign Objective: Increase engagement on Instagram and TikTok

[0666] Using this information, the server generates an initial proposal and then uses the following prompt to create a final proposal that reflects market information:

[0667] Create an ad campaign proposal with the following details:

[0668] Product: New skincare line

[0669] Target Audience: Women aged 20-35

[0670] Focus: Social media engagement on Instagram and TikTok

[0671] Real-time market information includes:

[0672] Update the initial ad campaign proposal with the following market trends and data:

[0673] Growing trend of eco-friendly skincare products

[0674] Increasing engagement rates on visual platforms like Instagram and TikTok

[0675] Competitor analysis showing a surge in influencer marketing strategies for similar products

[0676] This system allows users to quickly create high-quality proposal materials that always reflect the latest market data.

[0677] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0678] Step 1:

[0679] The user inputs information related to the requirements for creating an advertising campaign (e.g., product, target market, campaign objectives), including campaign details, target market demographics, goals, budget, etc.

[0680] Enter: Campaign details

[0681] Output: Initial information sent to the server

[0682] Step 2:

[0683] The device sends the information entered by the user to the server, and this data is sent in a standard format such as JSON.

[0684] Input: Campaign information entered by the user

[0685] Output: Campaign information transferred to the server

[0686] Step 3:

[0687] The server analyzes the input information received from the user and converts it into a format suitable for the generative AI model. Specifically, it converts text data into prompt sentences.

[0688] Input: Campaign information

[0689] Output: The prompt sentence that is input to the generative AI model

[0690] Step 4:

[0691] The server automatically generates the initial proposal using a generative AI model, which generates text based on the prompt sentences mentioned above.

[0692] Input: prompt statement

[0693] Output: Initial proposal

[0694] Step 5:

[0695] The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.) using scraping technology and APIs.

[0696] Input: None (automatic collection)

[0697] Output: Real-time market data

[0698] Step 6:

[0699] The server analyzes the collected data using natural language processing (NLP) technology to extract the latest market trends and competitive information, specifically through word analysis, topic modeling, and sentiment analysis.

[0700] Input: Real-time market data

[0701] Output: Analyzed market trend information

[0702] Step 7:

[0703] The server updates the initial proposal based on the analyzed market information, and re-uses the generative AI model to generate more specific proposals.

[0704] Input: Initial proposal materials, analyzed market information

[0705] Output: Updated proposal

[0706] Step 8:

[0707] The user checks the generated proposal document and sends correction instructions to the server as necessary, such as adding or correcting specific information or adjusting the document design.

[0708] Input: Updated proposal

[0709] Output: User's correction instructions

[0710] Step 9:

[0711] The terminal sends the user's revision requests to the server, which then generates the final version of the proposal based on this information.

[0712] Input: User's correction request

[0713] Output: The modification request forwarded to the server

[0714] Step 10:

[0715] The server uses the generative AI model again based on the user's correction requests to generate the final proposal document, and if necessary, performs new market analysis and adds the latest information.

[0716] Input: Correction Request

[0717] Output: Final proposal

[0718] Step 11:

[0719] The terminal provides the final proposal materials to the user and saves them in a format that the user can view and download.

[0720] Input: Final proposal

[0721] Output: A download link or file that is provided to the user

[0722] 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.

[0723] The present invention relates to a system that integrates the creation of proposal materials with real-time market information and further optimizes the content of the proposal materials by recognizing user emotions. The system includes a means for a user to input information required for creating proposal materials and generate the materials using a generative AI model. Furthermore, the system is equipped with an emotion engine that analyzes user emotions and provides more appropriate materials.

[0724] Explanation of program processing

[0725] Proposal material creation phase

[0726] User:

[0727] The user first inputs information about the requirements for creating a proposal document into the device, including the target market, the features of the proposed product or service, the design and format of the proposal document, and the target audience, as well as data for capturing emotions from the user's voice and text input.

[0728] Device:

[0729] The terminal transmits the information and emotion data input by the user to the server.

[0730] Initial Data Preparation Phase

[0731] server:

[0732] The server analyzes the received information and converts it into a format that can be input to the generative AI model. At the same time, it analyzes the user's emotions using an emotion engine and supplies this information to the generative AI model.

[0733] Initial data generation phase

[0734] server:

[0735] The server uses the analyzed input information and emotion data to generate an initial proposal using a generative AI model, which reflects the user's input and emotional adjustments.

[0736] Real-time market analysis phase

[0737] server:

[0738] The server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology. From the analysis results, the latest market trends and competitive information are extracted.

[0739] Market information integration phase

[0740] server:

[0741] The extracted market information is used to update the content of the initial pitch deck, and the tone and messaging of the pitch deck are adjusted based on user sentiment data obtained from the emotion engine.

[0742] Material review and revision phase

[0743] User:

[0744] The user can review the generated proposal and provide instructions for revisions to the content and design, including those based on the user's feelings.

[0745] Device:

[0746] The terminal transmits a modification request from the user to the server.

[0747] server:

[0748] The server updates the proposal materials based on correction requests from users, and reanalyzes and reflects new market information and sentiment data as necessary.

[0749] Final data generation phase

[0750] server:

[0751] Generate a final proposal document that reflects all revision requests, real-time market information, and sentiment data, and save it as a PDF, PowerPoint, Google Slides, etc.

[0752] Proposal materials provision phase

[0753] Device:

[0754] The final proposal will be provided to the user for review and download.

[0755] Specific examples

[0756] For example, when a user creates a proposal document for a new product, they input product features, target market, and competitive information, along with the associated emotions of excitement and anticipation. The server generates an initial proposal document based on this information and emotion data, and then collects real-time market information and integrates it into the document. The user then reviews the document and provides instructions for revision based on their emotions, and the server ultimately generates a high-quality proposal document that reflects the user's emotions.

[0757] This system allows users to efficiently create high-quality proposal materials that reflect real-time market information and their own emotions, significantly improving the competitiveness of business proposals and providing more persuasive materials that are in tune with users' emotions.

[0758] The processing flow will be explained below.

[0759] Step 1:

[0760] The user inputs information about the requirements for creating a proposal document into the terminal, including the target market, the characteristics of the proposed product or service, the design and format of the document, and the target audience.

[0761] Step 2:

[0762] The terminal transmits the information entered by the user and emotion data obtained from voice and text to the server.

[0763] Step 3:

[0764] The server analyzes the received information and converts it into a format that can be input into the generative AI model, while simultaneously analyzing the user's emotions using an emotion engine.

[0765] Step 4:

[0766] The server uses a generative AI model to automatically generate an initial proposal document based on the analyzed input information and emotion data, which includes adjustments based on the information and emotion entered by the user.

[0767] Step 5:

[0768] The server collects real-time market information from open data sources on the internet, such as news articles, blogs, and social media.

[0769] Step 6:

[0770] The server analyzes the collected market information using natural language processing technology and extracts the latest market trends and competitive information.

[0771] Step 7:

[0772] The server updates the content of the initial pitch deck based on the extracted market information, while simultaneously adjusting the pitch deck's tone and messaging based on user emotion data obtained from the emotion engine.

[0773] Step 8:

[0774] The user reviews the generated proposal materials and makes suggestions for revisions to the content and design of the materials, including suggestions for revisions based on the user's feelings.

[0775] Step 9:

[0776] The terminal transmits a modification request from the user to the server.

[0777] Step 10:

[0778] The server updates the proposal materials based on user requests for revisions, and if necessary, re-analyzes market information and sentiment data to reflect these changes.

[0779] Step 11:

[0780] The server generates the final proposal document, incorporating all revision requests, real-time market information, and sentiment data, and saves it in formats such as PDF, PowerPoint, and Google Slides.

[0781] Step 12:

[0782] The terminal provides the final version of the proposal material to the user, allowing the user to check and download the material.

[0783] Example 2

[0784] 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."

[0785] Conventional proposal material creation systems have difficulty fully reflecting user sentiment and real-time market information, resulting in a decline in the persuasiveness and competitiveness of the materials. Furthermore, updating and correcting materials is time-consuming, which can cause delays in a business environment where rapid response is required. Therefore, the present invention solves these problems and enables the efficient creation of high-quality proposal materials.

[0786] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0787] In this invention, the server includes means for analyzing voice and facial expression data to recognize user emotions, means for collecting market information in real time from open data sources on the Internet and analyzing it using natural language processing technology, and means for reanalyzing the emotion data to generate final proposal materials, thereby enabling the creation of high-quality proposal materials that reflect user emotions and the latest market information.

[0788] "User" refers to an individual or organization who inputs the information necessary to create proposal materials and operates the system.

[0789] "Terminal" means an electronic device used by a User to input information or to view and download generated proposal materials.

[0790] "Server" refers to the computer system that receives and analyzes information sent by users and generates and updates proposal materials using generative AI models.

[0791] A "proposal" is a document or presentation that describes the features, target market, and target audience of a particular product or service that a user is aiming to create.

[0792] A "generative AI model" is an artificial intelligence model that generates proposal materials based on information entered by the user.

[0793] "Emotion data" refers to information about emotions acquired from the user's voice and facial expressions.

[0794] "Market intelligence" refers to data such as market trends and competitive information collected from open data sources on the Internet.

[0795] "Natural language processing technology" is a technology used to analyze market information, and is a method for analyzing the meaning of text data and extracting information.

[0796] A "modification instruction" is a request made by a user to change the content or design of the generated proposal material.

[0797] The present invention relates to a system for creating proposal materials, integrating real-time market information, and optimizing the content of the proposal materials by recognizing user emotions. This system is realized by combining multiple means.

[0798] Hardware and software configuration of the proposal document creation system

[0799] User:

[0800] Users input the information required to create proposal materials into a device. The device can be a PC, tablet, smartphone, or other electronic device. Users input using a keyboard, microphone, and camera. Voice input is converted into text using voice recognition software, and facial expression data is acquired using a camera and image analysis software.

[0801] Device:

[0802] The device sends the information and emotion data entered by the user to the server. Data is transferred over an internet connection and encryption technology such as SSL / TLS, using protocols such as HTTP POST requests.

[0803] server:

[0804] The server analyzes the received information and generates initial proposal materials using a generative AI model. A text analysis engine and a sentiment analysis engine run on the server, converting the input information and sentiment data into an appropriate format. This process uses natural language processing models such as BERT and sentiment analysis models.

[0805] The server also collects real-time market information from open data sources on the Internet, using web scraping technology and APIs, and analyzes the market information using natural language processing technology to extract the latest trends and competitive information. The analyzed market information is then integrated into proposal materials and updated.

[0806] Examples of specific examples and prompts

[0807] For example, when a user creates a proposal for a new product, they use their device to input product features, target market, competitive information, etc. The device then sends this information to a server. The server then analyzes the received information, including sentiment data, and generates an initial proposal using a generative AI model (e.g., GPT-4). The server then collects market information and updates the proposal in real time.

[0808] The user reviews the generated proposal document and sends revision instructions from the terminal to the server. The server reanalyzes the revision requests, the latest market information, and sentiment data to generate the final proposal document. The terminal then provides the final proposal document to the user, who then reviews and downloads it.

[0809] Prompt Sentence Examples

[0810] Enter the following prompt into the generative AI model:

[0811] Please enter the features of your new product as follows: The target market is technology startups, and the competitive information is that Company A and Company B are the main competitors. The design of the proposal document should be simple, and the target audience should be engineers. Furthermore, the content should reflect their expectations.

[0812] This system allows users to efficiently create high-quality proposal materials that reflect real-time market information and their own emotions, improving the competitiveness of business proposals and providing persuasive materials that are in tune with users' emotions.

[0813] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0814] Step 1:

[0815] User:

[0816] The user inputs the information necessary to create a proposal document into the device. Specifically, details such as the target market, the features of the proposed product or service, the document design and format, and the target audience are entered as text. Voice input can also be performed using a microphone, and the voice is converted into text by an automatic speech recognition system. Furthermore, a camera is used to capture facial expressions, which are then used as data for emotion analysis. This provides the user's input information and emotion data.

[0817] Step 2:

[0818] Device:

[0819] The device sends the information entered by the user and emotion data to the server. Specifically, the text data, text data obtained by voice recognition, and facial expression data are all sent together via an HTTP POST request. The data is encrypted using SSL / TLS before being sent and is securely transferred to the server.

[0820] Step 3:

[0821] server:

[0822] The server analyzes the received information. First, it uses a text analysis engine to format the information entered by the user into an appropriate format. Next, it uses an emotion analysis engine to extract the user's emotions from the voice data and facial expression data and stores them as numerical data. For example, emotions such as "happiness" and "expectation" are quantified. This step also converts the analysis results into a format that can be applied to a generative AI model. Through this process, the input data is analyzed and a dataset for the AI ​​model is generated.

[0823] Step 4:

[0824] server:

[0825] The server uses a generative AI model to generate an initial proposal. Specifically, the analyzed input information and emotional data are input as prompts into a generative AI model such as OpenAI's GPT-4. The generative AI model then uses this data to generate text and graphic elements for the initial proposal. The result is an initial proposal that reflects the user's input and emotional data.

[0826] Step 5:

[0827] server:

[0828] The server collects market information in real time from open data sources on the Internet. Specifically, it uses web scraping and APIs to obtain the latest market information from news sites and industry reports. This allows for the collection of market trends and competitive information in real time.

[0829] Step 6:

[0830] server:

[0831] The server analyzes the collected market information using natural language processing technology. This analysis uses language models such as BERT to extract trends and competitive information from the collected text data. The analysis results are integrated into proposal materials. Specifically, the market information is summarized and output as text data to be integrated into the strategy section of the proposal materials.

[0832] Step 7:

[0833] server:

[0834] The server updates the content of the initial proposal based on the extracted market information. Furthermore, it adjusts the tone and messaging of the proposal based on the user's emotional data obtained from the emotion engine. For example, it reflects competitive information and uses more positive language in response to the user's expressed expectations. This allows the initial proposal to be shaped by market information and emotional data.

[0835] Step 8:

[0836] User:

[0837] The user can review the generated proposal and make corrections to the content and design. The user can use a terminal to input corrections such as changing the color of a specific graph or requesting additional information. Corrections can also be made based on emotions.

[0838] Step 9:

[0839] Device:

[0840] The terminal transmits a request for modification from the user to the server. Specifically, the modification content made by the user on the terminal is sent to the server in text format, and the server receives it in a format that can be processed.

[0841] Step 10:

[0842] server:

[0843] The server updates the proposal documents based on the user's revision requests. If necessary, it reanalyzes new market information and sentiment data and reflects the revisions. For example, it adds newly collected market information and revise the proposal documents to reflect the sentiment data. This updates the proposal documents to reflect the revision requests.

[0844] Step 11:

[0845] server:

[0846] The server generates the final proposal document, reflecting all revision requests, real-time market information, and sentiment data, and converts and saves the document in formats such as PDF, PowerPoint, Google Slides, etc. This results in a file that can be used as a high-quality presentation document.

[0847] Step 12:

[0848] Device:

[0849] The terminal provides the final proposal materials to the user, allowing the user to review and download them. Specifically, a download link for the materials is displayed on the terminal, and when the user clicks it, the file download begins. This allows the user to review and use the final proposal materials.

[0850] (Application example 2)

[0851] 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."

[0852] Conventional advertising material creation systems have difficulty reflecting real-time changes in market information and user sentiment, resulting in difficulties in creating consistent, high-quality advertising materials. Furthermore, the time-consuming task of manually collecting market trends and competitive information hinders efficient material creation. Furthermore, it is not possible to create advertising materials that reflect user sentiment, making it difficult to increase persuasiveness and empathy among the target audience.

[0853] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0854] In this invention, the server includes: means for a user to input information regarding requirements for creating advertising materials; means for transmitting the input information to the server; means for the server to analyze the input information received from the user and generate initial advertising materials using a generative AI model; means for the server to collect market information in real time from open data sources on the Internet and analyze it using natural language processing technology; means for the server to update the content of the advertising materials based on the extracted market information; means for the server to analyze emotions from user voice input; means for the server to adjust the tone and messaging of the advertising materials based on the emotion analysis results; means for the user to review the generated advertising materials and send correction instructions to the server; means for the server to update the advertising materials based on correction requests from the user and generate final advertising materials; and means for the terminal to provide the final advertising materials to the user so that the user can review and download them. This enables efficient creation of high-quality, consistent advertising materials that reflect real-time market information and user emotions.

[0855] A "user" is a person who uses the system to create advertising materials.

[0856] "Advertising materials" are documents or presentations created to promote a particular product or service.

[0857] "Production requirements" are all the information needed to create advertising materials, including the theme, target market, competitive information, etc.

[0858] An "input means" is an interface or device used by a user to provide information that enters the system.

[0859] A "server" is a central processing unit that receives input information from a user and processes and analyzes it.

[0860] A "generative AI model" is an artificial intelligence model that automatically generates advertising materials based on given input data.

[0861] "Initial Advertising Materials" means the first version of advertising materials created by a generative AI model.

[0862] "Internet open data sources" are publicly available data resources accessible via the Internet, including market information.

[0863] "Natural language processing technology" is a technology for analyzing text data, extracting information, and understanding meaning.

[0864] "Means for collecting market information in real time" refers to a method that allows for the immediate acquisition of dynamically changing market data.

[0865] "Sentiment analysis" is the process of identifying a user's emotions from their voice or text.

[0866] "Means to adjust tone and messaging" refers to methods to optimize the content and presentation of advertising materials based on user emotions.

[0867] "Modification instructions" refer to requests for changes made by a user to generated advertising materials.

[0868] "Final Advertising Materials" means advertising materials in their completed form, incorporating all revision instructions and the latest market information.

[0869] "Terminal" means a device used by a user to operate the system and to view and download advertising materials.

[0870] The present invention is a system for supporting the creation of advertising materials, which includes a user, a terminal, and a server. In this system, the user inputs information and sends it to the server via the terminal, and the server creates the materials using a generative AI model. Furthermore, the server analyzes the user's sentiment and reflects real-time market information in the materials.

[0871] The server receives information entered by the user regarding the requirements for creating advertising materials. For example, the system receives user-entered information such as themes, target markets, and competitive information. This information is sent from the device to the server. Voice data provided by the user is also sent to the server and is subjected to sentiment analysis.

[0872] The server generates initial advertising materials using a generative AI model. The generative AI model creates advertising materials based on information entered by the user. The server also collects market information in real time from open data sources on the Internet. The market information is analyzed using natural language processing technology, and the extracted market information is used to update the content of the advertising materials.

[0873] The server has an emotion engine for analyzing emotions from the user's voice data. The emotion engine analyzes the user's emotion data and uses the results to adjust the tone and messaging of advertising materials. For example, if the user is excited, advertising materials with a positive tone that reflects that emotion are generated.

[0874] The user checks the generated advertising materials on their device and sends correction instructions to the server as necessary. The server updates the advertising materials based on the correction instructions. The final version of the advertising materials is completed by reflecting all correction requests and the latest market information. The final advertising materials are provided to the user via their device, allowing them to check and download them.

[0875] The system operates using the following hardware and software: The hardware includes the user's device (e.g., smartphone or PC) and server. The software includes the OpenAI API, which provides the generative AI model, an internet connection to obtain real-time market information, and an emotion engine for emotion analysis.

[0876] As a concrete example, let's consider the case where a user creates advertising materials for a "new product launch." In this case, the user uses their device to input the following information: the new product's features, target market, competitive information, emotions of excitement and anticipation, etc. This information is sent to the server, where the generative AI model and sentiment analysis engine perform their respective roles to generate the initial advertising materials. The server then collects market information from the Internet and integrates it into the materials. The user reviews the materials and makes corrections as necessary. The final advertising materials are provided with all inputs reflected.

[0877] Example prompt sentence:

[0878] User Input Data: New Product Launch

[0879] User emotion data: excitement, anticipation

[0880] Market intelligence: Competitor A adds new features this month

[0881] Use the information above to create the best advertising materials.

[0882] As described above, by using the system of the present invention, it is possible to efficiently create high-quality, consistent advertising materials that reflect real-time market information and user sentiment.

[0883] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0884] Step 1:

[0885] The user inputs information regarding the requirements for producing advertising materials into the terminal.

[0886] Input: New product features, target market, competitive intelligence, user voice input, etc.

[0887] Processing: The user uses the device to enter the required information and collect data on the device, including voice input.

[0888] Output: Collected data is saved to the device.

[0889] Step 2:

[0890] The terminal transmits the information entered by the user to the server.

[0891] Input: Data about the creation requirements entered by the user into the terminal.

[0892] Processing: The device formats the user's input data and transmits it over the Internet to a server.

[0893] Output: The user input information is sent to the server.

[0894] Step 3:

[0895] The server analyzes the received input information and generates initial advertising materials using a generative AI model.

[0896] Input: Data about the creation requirements submitted by the user.

[0897] Processing: The server analyzes the input information and converts it into an input format for the generative AI model. Based on this format, the generative AI model is called to generate the initial advertising materials.

[0898] Output: Generation of initial advertising materials.

[0899] Step 4:

[0900] The server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology.

[0901] Input: Raw data from open data sources on the internet.

[0902] Processing: The server collects market information in real time, analyzes market trends and competitive information using natural language processing technology, and extracts the required data.

[0903] Output: Extracted market information.

[0904] Step 5:

[0905] The server updates the content of the advertising materials based on the extracted market information.

[0906] Input: Extracted market information, initial advertising materials.

[0907] Processing: Based on market information, the server updates the content of advertising materials, optimizing the tone and messaging of the materials.

[0908] Output: Updated advertising materials reflecting market information.

[0909] Step 6:

[0910] The server uses an emotion analysis engine to analyze the user's emotion data.

[0911] Input: User's voice data.

[0912] Processing: The server performs emotion analysis on the voice input and extracts the user's emotion data.

[0913] Output: Extracted emotion data.

[0914] Step 7:

[0915] The server adjusts the tone and messaging of advertising materials based on the results of sentiment analysis.

[0916] Input: Sentiment data, updated advertising materials.

[0917] Processing: The server uses the emotional data to optimize the content of advertising materials, for example, adding a positive tone if the emotional data is "excited."

[0918] Output: Emotionally corrected advertising materials.

[0919] Step 8:

[0920] The user checks the generated advertising materials and sends correction instructions to the server.

[0921] Input: Emotionally corrected advertising materials.

[0922] Processing: The user checks the advertising materials through the terminal and gives instructions on what needs to be corrected. These instructions are sent from the terminal to the server.

[0923] Output: User correction instructions.

[0924] Step 9:

[0925] The server updates the advertising materials based on the correction requests from the user and generates the final version of the advertising materials.

[0926] Input: User correction instructions, emotion-corrected advertising materials.

[0927] Processing: The server re-updates the advertising materials based on the user's modification requests, and re-reflects the sentiment data and market information to generate the final materials.

[0928] Output: Final, completed advertising materials.

[0929] Step 10:

[0930] The device provides the final advertising material to the user for review and download.

[0931] Input: Final advertising materials.

[0932] Processing: The device receives the final advertising material from the server, stores it and provides it for the user to access.

[0933] Output: Final advertising materials available for user review and download.

[0934] 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.

[0935] 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.

[0936] 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.

[0937] [Third embodiment]

[0938] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0939] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0940] 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).

[0941] 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.

[0942] 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.

[0943] 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).

[0944] 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.

[0945] 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.

[0946] 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.

[0947] 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.

[0948] 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.

[0949] 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."

[0950] The present invention is a system for efficiently creating proposal materials for new services, which uses a generative AI model based on information entered by the user to generate proposal materials and has the function of reflecting real-time market information. This system provides an environment in which users can efficiently create competitive proposal materials.

[0951] Explanation of program processing

[0952] Proposal material creation phase

[0953] User:

[0954] Users first input information about the requirements for creating a proposal, including the target market, service or product features, proposal design and format, and target audience.

[0955] Device:

[0956] The terminal transmits the information entered by the user to the server.

[0957] server:

[0958] The server analyzes the received information and converts it into a format that can be input to the generative AI model. Based on this information, it creates the structure of an initial proposal document. The generative AI model then automatically generates an initial version of the proposal document. This initial version includes the information entered by the user, past success stories, and related materials.

[0959] Real-time market analysis phase

[0960] server:

[0961] The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.) and analyzes the collected data using natural language processing technology to extract the latest market trends and competitive information.

[0962] Market information integration phase

[0963] server:

[0964] The content of the proposal materials is updated based on the analyzed market information. This update ensures that the proposal materials reflect the latest market trends and competitive information, ensuring that the materials are always up-to-date and persuasive.

[0965] Material review and revision phase

[0966] User:

[0967] The user can review the generated proposal and provide instructions for revisions as necessary, such as adding or correcting specific information or adjusting the document design.

[0968] Device:

[0969] The terminal transmits a modification request from the user to the server.

[0970] server:

[0971] The server updates the proposal documents based on user requests for revisions, and if necessary, performs new market analysis and adds the latest information, making the proposal documents even stronger and more competitive.

[0972] Final material generation phase

[0973] server:

[0974] The server generates a final proposal document incorporating all requested revisions and saves it in a format that users can download and present, such as PDF, PowerPoint, or Google Slides.

[0975] Device:

[0976] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[0977] Specific examples

[0978] For example, consider a case where a user is creating a proposal document for a new product. The user inputs the product's features, target market, and competitive information, and the server generates an initial proposal document using a corresponding template. The server collects market information in real time and adds the latest trends and competitive information to the proposal document. The user then reviews the document and requests revisions, and the server completes the final version of the proposal document. Through this process, the user can quickly create high-quality proposal documents that reflect the latest market information.

[0979] This invention enables users to quickly create high-quality proposal materials that reflect market trends in real time, significantly improving the competitiveness of business proposals.

[0980] The processing flow will be explained below.

[0981] Step 1:

[0982] The user inputs information about the requirements for creating a proposal into the terminal, including the target market, the characteristics of the proposed product or service, the design and format of the proposal, and the target audience.

[0983] Step 2:

[0984] The terminal transmits the information entered by the user to the server.

[0985] Step 3:

[0986] The server analyzes the received information and converts it into a format that can be input into the generative AI model.

[0987] Step 4:

[0988] The server automatically generates an initial proposal document using a generative AI model based on the analyzed input information, and at this stage, it also references past success stories and related materials to enhance the content.

[0989] Step 5:

[0990] The server collects real-time market information from open data sources on the internet, such as news articles, blogs, and social media.

[0991] Step 6:

[0992] The server analyzes the collected market information using natural language processing technology and extracts the latest market trends and competitive information.

[0993] Step 7:

[0994] The server updates the content of the initial proposal based on the extracted market information, so that the latest market information is reflected in the proposal.

[0995] Step 8:

[0996] The user checks the generated proposal document and, if necessary, gives instructions for modifying the content or design of the document.

[0997] Step 9:

[0998] The terminal transmits a modification request from the user to the server.

[0999] Step 10:

[1000] The server updates the proposal documents based on the user's correction requests, and if necessary, performs new market analysis to further strengthen the proposal documents.

[1001] Step 11:

[1002] The server generates the final proposal document with all requested revisions reflected, and the document is saved in a format such as PDF, PowerPoint, or Google Slides.

[1003] Step 12:

[1004] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[1005] Example 1

[1006] 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."

[1007] With conventional proposal creation systems, users had to create documents from scratch, which required a great deal of time and effort, and it was difficult to quickly reflect real-time market information. As a result, it was not possible to quickly provide proposal documents that offered a competitive advantage. Furthermore, there was a lack of an efficient process for revising or updating documents, which led to problems with the quality and timing of the final proposal documents.

[1008] 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.

[1009] In this invention, the server includes: means for analyzing input information received from a user and generating initial proposal materials using a generative AI model; means for collecting market information in real time from open data sources on the Internet and analyzing it using natural language processing technology; and means for updating the content of the proposal materials based on the extracted market information. This allows users to quickly and efficiently create high-quality proposal materials that reflect the latest market information and quickly reflect correction instructions. Furthermore, by using the generative AI model, it is possible to automatically generate proposal materials based on past success stories and related materials. This significantly improves the competitiveness of business proposals.

[1010] "User" refers to the entity that uses the system to input information to create proposal materials and checks and modifies the generated materials.

[1011] A "proposal document" is a document used to propose a new service or product, and includes information on the target market, competitors, and service features.

[1012] The "server" is the central device of the computer system that analyzes information received from users, automatically generates proposal materials using a generative AI model, collects and analyzes real-time market information, and reflects it in the materials.

[1013] "Terminal" means a device that allows a user to input information and check and modify the generated proposal materials, and communicates with the server to send and receive data.

[1014] A "generative AI model" refers to a machine learning algorithm or model that automatically generates proposal materials based on information entered by the user.

[1015] "Input information" refers to data that a user inputs to create a proposal document, including the target market, the characteristics of the service or product, the design and format of the proposal, and the target audience.

[1016] An "open data source" is a collection of data that is publicly available on the internet, including news articles, blogs, social media, etc.

[1017] "Natural language processing technology" is a technology for analyzing collected text data and extracting important information and trends.

[1018] "Market Intelligence" refers to market trends and competitive information collected and analyzed from data sources on the Internet.

[1019] A "correction instruction" is an instruction that the user uses to specify additions or changes to the generated proposal material, and is transmitted to the server.

[1020] The "final proposal document" is a completed proposal document that reflects all revision requests from the user.

[1021] MODE FOR CARRYING OUT THE INVENTION

[1022] This invention is a system for efficiently creating proposal materials for new services. It uses a generative AI model based on information entered by the user to generate proposal materials, and has the function of reflecting real-time market information. This system provides an environment in which users can efficiently create competitive proposal materials.

[1023] System Overview

[1024] The system consists of a user, a terminal, and a server. The user inputs the information necessary to create a proposal document. The terminal sends this information to the server, which then provides the generated document to the user. The server analyzes the input information and generates the proposal document using a generative AI model. It also collects market information from open data sources on the Internet, analyzes it using natural language processing technology, and reflects that information in the proposal document.

[1025] Hardware and software used

[1026] Terminal: A device such as a personal computer or smartphone that allows users to input information and check and edit materials.

[1027] Server: A high-performance computer system that analyzes information, runs AI models, and collects and analyzes data.

[1028] Software: Word processing software, generative AI models (e.g., GPT), natural language processing techniques (e.g., NLTK, SpaCy)

[1029] Specific examples of creating proposal materials

[1030] For example, consider a case where a user is creating a proposal document for a new product. The user inputs the product's features, target market, and competitive information, and the server generates an initial proposal document using a corresponding template. The server collects market information in real time and adds the latest trends and competitive information to the proposal document. The user then reviews the document and requests revisions, and the server completes the final version of the proposal document. Through this process, the user can quickly create high-quality proposal documents that reflect the latest market information.

[1031] Prompt Sentence Examples

[1032] "To create a proposal for a new product, you enter product features, target market, and competitive information. The server generates an initial proposal based on this information. It also collects market information in real time, adding the latest trends and competitive information to the proposal."

[1033] This system enables users to quickly create high-quality proposal materials that reflect the latest market information, significantly improving the competitiveness of their business proposals.

[1034] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1035] Step 1:

[1036] The user inputs information related to the requirements for creating a proposal document. The information input by the user includes the target market, product or service features, proposal design and format, target audience, etc. Specifically, the user inputs information such as "list of new product features," "target market is North America," and "main competitor is Company X" into the input form. Once the input is complete, the information is saved for the next step.

[1037] Input: User-entered requirements information for proposal materials (e.g., product features, target market, competitive information)

[1038] Output: The input requirements information is saved.

[1039] Step 2:

[1040] The device sends the information entered by the user to the server. When the user clicks the "Send" button, the device calls the API in the backend and passes the input information to the server. The device notifies the user that the sending process was successful.

[1041] Input: User-entered requirements information for the proposal document

[1042] Output: User input sent to the server

[1043] Step 3:

[1044] The server analyzes the information received from the device and converts it into a format suitable for input into the generative AI model. Specifically, it converts the received information into JSON format and organizes it into a structure suitable for the generative AI model. It also pulls past success stories and related materials from a database and integrates this information.

[1045] Input: User input information sent from the device

[1046] Output: Information converted into a format that can be input into a generative AI model

[1047] Step 4:

[1048] The generative AI model generates an initial proposal based on the information prepared by the server, using the basic structure and template of the proposal. The initial version of the proposal reflects the requirements specified by the user.

[1049] Input: Information converted into a format that can be fed into a generative AI model

[1050] Output: Generate initial proposal materials

[1051] Step 5:

[1052] The server collects real-time market information from open data sources on the internet, through APIs and web scraping, retrieving relevant data from news articles, blogs, social media, etc.

[1053] Input: Real-time market data request

[1054] Output: Collected market data

[1055] Step 6:

[1056] The server analyzes the collected market data using natural language processing technology, specifically extracting important keywords and trends from the text data and organizing the information relevant to the proposal materials.

[1057] Input: Collected market data

[1058] Output: Analyzed market information (e.g. trends, competitive intelligence)

[1059] Step 7:

[1060] The server updates the content of the proposal documents based on the analyzed market information. Specifically, it adds the latest market trends and competitive analysis to the proposal documents, thereby enhancing the documents based on the latest information.

[1061] Input: Parsed market information

[1062] Output: Updated proposal

[1063] Step 8:

[1064] The user can check the generated proposal document and input any correction requests they may have. Through the GUI, the user can intuitively add or correct specific information, adjust the document design, and more.

[1065] Input: User requested correction

[1066] Output: Correction request entered

[1067] Step 9:

[1068] The terminal sends the modification request from the user to the server, and the user's modification request is now ready to be processed by the server.

[1069] Input: User's correction request

[1070] Output: The modification request sent to the server

[1071] Step 10:

[1072] The server updates the proposal documents based on the user's correction requests, and if necessary, performs new market analysis and adds the latest information to the documents to generate even stronger proposal documents.

[1073] Input: The modification request sent to the server

[1074] Output: Updated proposal

[1075] Step 11:

[1076] The server generates the final proposal document incorporating all requested revisions and saves it in formats such as PDF, PowerPoint, Google Slides, etc.

[1077] Input: Updated proposal

[1078] Output: Final proposal

[1079] Step 12:

[1080] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials by clicking on the download link.

[1081] Input: Final proposal

[1082] Output: The final proposal provided to the user

[1083] (Application example 1)

[1084] 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."

[1085] Creating proposal materials for advertising campaigns requires a great deal of time and effort, and it is difficult to quickly create materials that reflect the latest market information. The purpose of this invention is to solve these problems by efficiently collecting and analyzing the information necessary for advertising campaigns and automatically creating high-quality proposal materials that always reflect the latest market data.

[1086] 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.

[1087] In this invention, the server includes: means for a user to input information regarding requirements for creating proposal materials; means for transmitting the input information to the server; means for the server to analyze the input information received from the user and generate initial proposal materials using a generative AI model; means for the server to collect market information in real time from open data sources on the Internet and analyze it using natural language processing technology; means for the server to update the content of the proposal materials based on the extracted market information; means for the user to check the generated proposal materials and send correction instructions to the server; means for the server to update the proposal materials based on correction requests from the user and generate final proposal materials; means for the terminal to provide the final proposal materials to the user so that the user can check and download them; means for the user to input information about an advertising campaign and receive proposal materials generated based on this information; and means for collecting real-time market data and reflecting the results of analysis in the advertising campaign materials. This enables users to quickly and efficiently create high-quality proposal materials for their advertising campaigns and always reflect the latest market information.

[1088] A "user" is a person who inputs information required to create a proposal document, and checks and modifies the created document.

[1089] "Pitch deck" means a written or digital file that is used to present an advertising campaign or a product or service to the market.

[1090] "Creation requirements" refer to the information, conditions, specifications, etc. required when creating proposal materials.

[1091] The "server" is a computer system that receives and analyzes information entered by users and creates proposal materials using a generative AI model.

[1092] A "generative AI model" is an artificial intelligence model that automatically generates proposal materials based on input data.

[1093] An "initial proposal" is the first version of a proposal that is automatically created by a generative AI model based on information provided by a user.

[1094] "Open data sources on the Internet" refers to information sources that are publicly available online, such as news articles, blogs, and social media.

[1095] "Real-time market information" refers to the latest market data that changes over time, such as current market trends and competitive information.

[1096] "Natural language processing technology" is a computer science technology for analyzing text data, understanding its meaning, and extracting information.

[1097] "Modification instructions" refer to requests for modifications or additions made by the user to the generated proposal materials.

[1098] The "final version of the proposal material" refers to the proposal material that has been finally completed and that reflects the user's correction requests.

[1099] A "terminal" is a device used by a user to send input information and receive generated materials.

[1100] This invention is a system that efficiently creates proposal materials using a generative AI model based on information about advertising campaigns entered by users. The system generates optimal proposal materials based on initial information provided by users and real-time market data, and provides an environment where users can review and modify them.

[1101] Program Description

[1102] Proposal material creation phase

[1103] 1. The user enters information about the advertising campaign (e.g., product, target market, campaign objectives).

[1104] 2. The device sends the input information to the server.

[1105] 3. The server analyzes this information and converts it into a format suitable for the generative AI model, which then creates an initial proposal document based on this information.

[1106] Real-time market analysis phase

[1107] 1. The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.).

[1108] 2. Analyze the collected data using natural language processing (NLP) technology to extract the latest market trends and competitive information.

[1109] Market information integration phase

[1110] 1. The server updates the content of the proposal materials based on the analyzed market information. This update ensures that the proposal materials reflect the latest market trends and competitive information.

[1111] Material review and revision phase

[1112] 1. The user can review the generated proposal document and provide instructions for revisions as necessary, such as adding or correcting specific information or adjusting the document design.

[1113] 2. The device sends a modification request to the server.

[1114] 3. The server updates the proposal based on the revision request, conducting new market analysis as needed and adding the latest information.

[1115] Final material generation phase

[1116] 1. The server generates the final proposal document incorporating all requested revisions and saves it in a format that users can download or present, such as PDF, PowerPoint, or Google Slides.

[1117] 2. The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[1118] Specific examples

[1119] If a user is planning a social media campaign for a new cosmetics line, they would first enter the following information:

[1120] Product: New skin care line

[1121] Target market: Women aged 20-35

[1122] Campaign Objective: Increase engagement on Instagram and TikTok

[1123] Using this information, the server generates an initial proposal and then uses the following prompt to create a final proposal that reflects market information:

[1124] Create an ad campaign proposal with the following details:

[1125] Product: New skincare line

[1126] Target Audience: Women aged 20-35

[1127] Focus: Social media engagement on Instagram and TikTok

[1128] Real-time market information includes:

[1129] Update the initial ad campaign proposal with the following market trends and data:

[1130] Growing trend of eco-friendly skincare products

[1131] Increasing engagement rates on visual platforms like Instagram and TikTok

[1132] Competitor analysis showing a surge in influencer marketing strategies for similar products

[1133] This system allows users to quickly create high-quality proposal materials that always reflect the latest market data.

[1134] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1135] Step 1:

[1136] The user inputs information related to the requirements for creating an advertising campaign (e.g., product, target market, campaign objectives), including campaign details, target market demographics, goals, budget, etc.

[1137] Enter: Campaign details

[1138] Output: Initial information sent to the server

[1139] Step 2:

[1140] The device sends the information entered by the user to the server, and this data is sent in a standard format such as JSON.

[1141] Input: Campaign information entered by the user

[1142] Output: Campaign information transferred to the server

[1143] Step 3:

[1144] The server analyzes the input information received from the user and converts it into a format suitable for the generative AI model. Specifically, it converts text data into prompt sentences.

[1145] Input: Campaign information

[1146] Output: The prompt sentence that is input to the generative AI model

[1147] Step 4:

[1148] The server automatically generates the initial proposal using a generative AI model, which generates text based on the prompt sentences mentioned above.

[1149] Input: prompt statement

[1150] Output: Initial proposal

[1151] Step 5:

[1152] The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.) using scraping technology and APIs.

[1153] Input: None (automatic collection)

[1154] Output: Real-time market data

[1155] Step 6:

[1156] The server analyzes the collected data using natural language processing (NLP) technology to extract the latest market trends and competitive information, specifically through word analysis, topic modeling, and sentiment analysis.

[1157] Input: Real-time market data

[1158] Output: Analyzed market trend information

[1159] Step 7:

[1160] The server updates the initial proposal based on the analyzed market information, and re-uses the generative AI model to generate more specific proposals.

[1161] Input: Initial proposal materials, analyzed market information

[1162] Output: Updated proposal

[1163] Step 8:

[1164] The user checks the generated proposal document and sends correction instructions to the server as necessary, such as adding or correcting specific information or adjusting the document design.

[1165] Input: Updated proposal

[1166] Output: User's correction instructions

[1167] Step 9:

[1168] The terminal sends the user's revision requests to the server, which then generates the final version of the proposal based on this information.

[1169] Input: User's correction request

[1170] Output: The modification request forwarded to the server

[1171] Step 10:

[1172] The server uses the generative AI model again based on the user's correction requests to generate the final proposal document, and if necessary, performs new market analysis and adds the latest information.

[1173] Input: Correction Request

[1174] Output: Final proposal

[1175] Step 11:

[1176] The terminal provides the final proposal materials to the user and saves them in a format that the user can view and download.

[1177] Input: Final proposal

[1178] Output: A download link or file that is provided to the user

[1179] 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.

[1180] The present invention relates to a system that integrates the creation of proposal materials with real-time market information and further optimizes the content of the proposal materials by recognizing user emotions. The system includes a means for a user to input information required for creating proposal materials and generate the materials using a generative AI model. Furthermore, the system is equipped with an emotion engine that analyzes user emotions and provides more appropriate materials.

[1181] Explanation of program processing

[1182] Proposal material creation phase

[1183] User:

[1184] The user first inputs information about the requirements for creating a proposal document into the device, including the target market, the features of the proposed product or service, the design and format of the proposal document, and the target audience, as well as data for capturing emotions from the user's voice and text input.

[1185] Device:

[1186] The terminal transmits the information and emotion data input by the user to the server.

[1187] Initial Data Preparation Phase

[1188] server:

[1189] The server analyzes the received information and converts it into a format that can be input to the generative AI model. At the same time, it analyzes the user's emotions using an emotion engine and supplies this information to the generative AI model.

[1190] Initial data generation phase

[1191] server:

[1192] The server uses the analyzed input information and emotion data to generate an initial proposal using a generative AI model, which reflects the user's input and emotional adjustments.

[1193] Real-time market analysis phase

[1194] server:

[1195] The server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology. From the analysis results, the latest market trends and competitive information are extracted.

[1196] Market information integration phase

[1197] server:

[1198] The extracted market information is used to update the content of the initial pitch deck, and the tone and messaging of the pitch deck are adjusted based on user sentiment data obtained from the emotion engine.

[1199] Material review and revision phase

[1200] User:

[1201] The user can review the generated proposal and provide instructions for revisions to the content and design, including those based on the user's feelings.

[1202] Device:

[1203] The terminal transmits a modification request from the user to the server.

[1204] server:

[1205] The server updates the proposal materials based on correction requests from users, and reanalyzes and reflects new market information and sentiment data as necessary.

[1206] Final data generation phase

[1207] server:

[1208] Generate a final proposal document that reflects all revision requests, real-time market information, and sentiment data, and save it as a PDF, PowerPoint, Google Slides, etc.

[1209] Proposal materials provision phase

[1210] Device:

[1211] The final proposal will be provided to the user for review and download.

[1212] Specific examples

[1213] For example, when a user creates a proposal document for a new product, they input product features, target market, and competitive information, along with the associated emotions of excitement and anticipation. The server generates an initial proposal document based on this information and emotion data, and then collects real-time market information and integrates it into the document. The user then reviews the document and provides instructions for revision based on their emotions, and the server ultimately generates a high-quality proposal document that reflects the user's emotions.

[1214] This system allows users to efficiently create high-quality proposal materials that reflect real-time market information and their own emotions, significantly improving the competitiveness of business proposals and providing more persuasive materials that are in tune with users' emotions.

[1215] The processing flow will be explained below.

[1216] Step 1:

[1217] The user inputs information about the requirements for creating a proposal document into the terminal, including the target market, the characteristics of the proposed product or service, the design and format of the document, and the target audience.

[1218] Step 2:

[1219] The terminal transmits the information entered by the user and emotion data obtained from voice and text to the server.

[1220] Step 3:

[1221] The server analyzes the received information and converts it into a format that can be input into the generative AI model, while simultaneously analyzing the user's emotions using an emotion engine.

[1222] Step 4:

[1223] The server uses a generative AI model to automatically generate an initial proposal document based on the analyzed input information and emotion data, which includes adjustments based on the information and emotion entered by the user.

[1224] Step 5:

[1225] The server collects real-time market information from open data sources on the internet, such as news articles, blogs, and social media.

[1226] Step 6:

[1227] The server analyzes the collected market information using natural language processing technology and extracts the latest market trends and competitive information.

[1228] Step 7:

[1229] The server updates the content of the initial pitch deck based on the extracted market information, while simultaneously adjusting the pitch deck's tone and messaging based on user emotion data obtained from the emotion engine.

[1230] Step 8:

[1231] The user reviews the generated proposal materials and makes suggestions for revisions to the content and design of the materials, including suggestions for revisions based on the user's feelings.

[1232] Step 9:

[1233] The terminal transmits a modification request from the user to the server.

[1234] Step 10:

[1235] The server updates the proposal materials based on user requests for revisions, and if necessary, re-analyzes market information and sentiment data to reflect these changes.

[1236] Step 11:

[1237] The server generates the final proposal document, incorporating all revision requests, real-time market information, and sentiment data, and saves it in formats such as PDF, PowerPoint, and Google Slides.

[1238] Step 12:

[1239] The terminal provides the final version of the proposal material to the user, allowing the user to check and download the material.

[1240] Example 2

[1241] 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."

[1242] Conventional proposal material creation systems have difficulty fully reflecting user sentiment and real-time market information, resulting in a decline in the persuasiveness and competitiveness of the materials. Furthermore, updating and correcting materials is time-consuming, which can cause delays in a business environment where rapid response is required. Therefore, the present invention solves these problems and enables the efficient creation of high-quality proposal materials.

[1243] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1244] In this invention, the server includes means for analyzing voice and facial expression data to recognize user emotions, means for collecting market information in real time from open data sources on the Internet and analyzing it using natural language processing technology, and means for reanalyzing the emotion data to generate final proposal materials, thereby enabling the creation of high-quality proposal materials that reflect user emotions and the latest market information.

[1245] "User" refers to an individual or organization who inputs the information necessary to create proposal materials and operates the system.

[1246] "Terminal" means an electronic device used by a User to input information or to view and download generated proposal materials.

[1247] "Server" refers to the computer system that receives and analyzes information sent by users and generates and updates proposal materials using generative AI models.

[1248] A "proposal" is a document or presentation that describes the features, target market, and target audience of a particular product or service that a user is aiming to create.

[1249] A "generative AI model" is an artificial intelligence model that generates proposal materials based on information entered by the user.

[1250] "Emotion data" refers to information about emotions acquired from the user's voice and facial expressions.

[1251] "Market intelligence" refers to data such as market trends and competitive information collected from open data sources on the Internet.

[1252] "Natural language processing technology" is a technology used to analyze market information, and is a method for analyzing the meaning of text data and extracting information.

[1253] A "modification instruction" is a request made by a user to change the content or design of the generated proposal material.

[1254] The present invention relates to a system for creating proposal materials, integrating real-time market information, and optimizing the content of the proposal materials by recognizing user emotions. This system is realized by combining multiple means.

[1255] Hardware and software configuration of the proposal document creation system

[1256] User:

[1257] Users input the information required to create proposal materials into a device. The device can be a PC, tablet, smartphone, or other electronic device. Users input using a keyboard, microphone, and camera. Voice input is converted into text using voice recognition software, and facial expression data is acquired using a camera and image analysis software.

[1258] Device:

[1259] The device sends the information and emotion data entered by the user to the server. Data is transferred over an internet connection and encryption technology such as SSL / TLS, using protocols such as HTTP POST requests.

[1260] server:

[1261] The server analyzes the received information and generates initial proposal materials using a generative AI model. A text analysis engine and a sentiment analysis engine run on the server, converting the input information and sentiment data into an appropriate format. This process uses natural language processing models such as BERT and sentiment analysis models.

[1262] The server also collects real-time market information from open data sources on the Internet, using web scraping technology and APIs, and analyzes the market information using natural language processing technology to extract the latest trends and competitive information. The analyzed market information is then integrated into proposal materials and updated.

[1263] Examples of specific examples and prompts

[1264] For example, when a user creates a proposal for a new product, they use their device to input product features, target market, competitive information, etc. The device then sends this information to a server. The server then analyzes the received information, including sentiment data, and generates an initial proposal using a generative AI model (e.g., GPT-4). The server then collects market information and updates the proposal in real time.

[1265] The user reviews the generated proposal document and sends revision instructions from the terminal to the server. The server reanalyzes the revision requests, the latest market information, and sentiment data to generate the final proposal document. The terminal then provides the final proposal document to the user, who then reviews and downloads it.

[1266] Prompt Sentence Examples

[1267] Enter the following prompt into the generative AI model:

[1268] Please enter the features of your new product as follows: The target market is technology startups, and the competitive information is that Company A and Company B are the main competitors. The design of the proposal document should be simple, and the target audience should be engineers. Furthermore, the content should reflect their expectations.

[1269] This system allows users to efficiently create high-quality proposal materials that reflect real-time market information and their own emotions, improving the competitiveness of business proposals and providing persuasive materials that are in tune with users' emotions.

[1270] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1271] Step 1:

[1272] User:

[1273] The user inputs the information necessary to create a proposal document into the device. Specifically, details such as the target market, the features of the proposed product or service, the document design and format, and the target audience are entered as text. Voice input can also be performed using a microphone, and the voice is converted into text by an automatic speech recognition system. Furthermore, a camera is used to capture facial expressions, which are then used as data for emotion analysis. This provides the user's input information and emotion data.

[1274] Step 2:

[1275] Device:

[1276] The device sends the information entered by the user and emotion data to the server. Specifically, the text data, text data obtained by voice recognition, and facial expression data are all sent together via an HTTP POST request. The data is encrypted using SSL / TLS before being sent and is securely transferred to the server.

[1277] Step 3:

[1278] server:

[1279] The server analyzes the received information. First, it uses a text analysis engine to format the information entered by the user into an appropriate format. Next, it uses an emotion analysis engine to extract the user's emotions from the voice data and facial expression data and stores them as numerical data. For example, emotions such as "happiness" and "expectation" are quantified. This step also converts the analysis results into a format that can be applied to a generative AI model. Through this process, the input data is analyzed and a dataset for the AI ​​model is generated.

[1280] Step 4:

[1281] server:

[1282] The server uses a generative AI model to generate an initial proposal. Specifically, the analyzed input information and emotional data are input as prompts into a generative AI model such as OpenAI's GPT-4. The generative AI model then uses this data to generate text and graphic elements for the initial proposal. The result is an initial proposal that reflects the user's input and emotional data.

[1283] Step 5:

[1284] server:

[1285] The server collects market information in real time from open data sources on the Internet. Specifically, it uses web scraping and APIs to obtain the latest market information from news sites and industry reports. This allows for the collection of market trends and competitive information in real time.

[1286] Step 6:

[1287] server:

[1288] The server analyzes the collected market information using natural language processing technology. This analysis uses language models such as BERT to extract trends and competitive information from the collected text data. The analysis results are integrated into proposal materials. Specifically, the market information is summarized and output as text data to be integrated into the strategy section of the proposal materials.

[1289] Step 7:

[1290] server:

[1291] The server updates the content of the initial proposal based on the extracted market information. Furthermore, it adjusts the tone and messaging of the proposal based on the user's emotional data obtained from the emotion engine. For example, it reflects competitive information and uses more positive language in response to the user's expressed expectations. This allows the initial proposal to be shaped by market information and emotional data.

[1292] Step 8:

[1293] User:

[1294] The user can review the generated proposal and make corrections to the content and design. The user can use a terminal to input corrections such as changing the color of a specific graph or requesting additional information. Corrections can also be made based on emotions.

[1295] Step 9:

[1296] Device:

[1297] The terminal transmits a request for modification from the user to the server. Specifically, the modification content made by the user on the terminal is sent to the server in text format, and the server receives it in a format that can be processed.

[1298] Step 10:

[1299] server:

[1300] The server updates the proposal documents based on the user's revision requests. If necessary, it reanalyzes new market information and sentiment data and reflects the revisions. For example, it adds newly collected market information and revise the proposal documents to reflect the sentiment data. This updates the proposal documents to reflect the revision requests.

[1301] Step 11:

[1302] server:

[1303] The server generates the final proposal document, reflecting all revision requests, real-time market information, and sentiment data, and converts and saves the document in formats such as PDF, PowerPoint, Google Slides, etc. This results in a file that can be used as a high-quality presentation document.

[1304] Step 12:

[1305] Device:

[1306] The terminal provides the final proposal materials to the user, allowing the user to review and download them. Specifically, a download link for the materials is displayed on the terminal, and when the user clicks it, the file download begins. This allows the user to review and use the final proposal materials.

[1307] (Application example 2)

[1308] 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."

[1309] Conventional advertising material creation systems have difficulty reflecting real-time changes in market information and user sentiment, resulting in difficulties in creating consistent, high-quality advertising materials. Furthermore, the time-consuming task of manually collecting market trends and competitive information hinders efficient material creation. Furthermore, it is not possible to create advertising materials that reflect user sentiment, making it difficult to increase persuasiveness and empathy among the target audience.

[1310] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1311] In this invention, the server includes: means for a user to input information regarding requirements for creating advertising materials; means for transmitting the input information to the server; means for the server to analyze the input information received from the user and generate initial advertising materials using a generative AI model; means for the server to collect market information in real time from open data sources on the Internet and analyze it using natural language processing technology; means for the server to update the content of the advertising materials based on the extracted market information; means for the server to analyze emotions from user voice input; means for the server to adjust the tone and messaging of the advertising materials based on the emotion analysis results; means for the user to review the generated advertising materials and send correction instructions to the server; means for the server to update the advertising materials based on correction requests from the user and generate final advertising materials; and means for the terminal to provide the final advertising materials to the user so that the user can review and download them. This enables efficient creation of high-quality, consistent advertising materials that reflect real-time market information and user emotions.

[1312] A "user" is a person who uses the system to create advertising materials.

[1313] "Advertising materials" are documents or presentations created to promote a particular product or service.

[1314] "Production requirements" are all the information needed to create advertising materials, including the theme, target market, competitive information, etc.

[1315] An "input means" is an interface or device used by a user to provide information that enters the system.

[1316] A "server" is a central processing unit that receives input information from a user and processes and analyzes it.

[1317] A "generative AI model" is an artificial intelligence model that automatically generates advertising materials based on given input data.

[1318] "Initial Advertising Materials" means the first version of advertising materials created by a generative AI model.

[1319] "Internet open data sources" are publicly available data resources accessible via the Internet, including market information.

[1320] "Natural language processing technology" is a technology for analyzing text data, extracting information, and understanding meaning.

[1321] "Means for collecting market information in real time" refers to a method that allows for the immediate acquisition of dynamically changing market data.

[1322] "Sentiment analysis" is the process of identifying a user's emotions from their voice or text.

[1323] "Means to adjust tone and messaging" refers to methods to optimize the content and presentation of advertising materials based on user emotions.

[1324] "Modification instructions" refer to requests for changes made by a user to generated advertising materials.

[1325] "Final Advertising Materials" means advertising materials in their completed form, incorporating all revision instructions and the latest market information.

[1326] "Terminal" means a device used by a user to operate the system and to view and download advertising materials.

[1327] The present invention is a system for supporting the creation of advertising materials, which includes a user, a terminal, and a server. In this system, the user inputs information and sends it to the server via the terminal, and the server creates the materials using a generative AI model. Furthermore, the server analyzes the user's sentiment and reflects real-time market information in the materials.

[1328] The server receives information entered by the user regarding the requirements for creating advertising materials. For example, the system receives user-entered information such as themes, target markets, and competitive information. This information is sent from the device to the server. Voice data provided by the user is also sent to the server and is subjected to sentiment analysis.

[1329] The server generates initial advertising materials using a generative AI model. The generative AI model creates advertising materials based on information entered by the user. The server also collects market information in real time from open data sources on the Internet. The market information is analyzed using natural language processing technology, and the extracted market information is used to update the content of the advertising materials.

[1330] The server has an emotion engine for analyzing emotions from the user's voice data. The emotion engine analyzes the user's emotion data and uses the results to adjust the tone and messaging of advertising materials. For example, if the user is excited, advertising materials with a positive tone that reflects that emotion are generated.

[1331] The user checks the generated advertising materials on their device and sends correction instructions to the server as necessary. The server updates the advertising materials based on the correction instructions. The final version of the advertising materials is completed by reflecting all correction requests and the latest market information. The final advertising materials are provided to the user via their device, allowing them to check and download them.

[1332] The system operates using the following hardware and software: The hardware includes the user's device (e.g., smartphone or PC) and server. The software includes the OpenAI API, which provides the generative AI model, an internet connection to obtain real-time market information, and an emotion engine for emotion analysis.

[1333] As a concrete example, let's consider the case where a user creates advertising materials for a "new product launch." In this case, the user uses their device to input the following information: the new product's features, target market, competitive information, emotions of excitement and anticipation, etc. This information is sent to the server, where the generative AI model and sentiment analysis engine perform their respective roles to generate the initial advertising materials. The server then collects market information from the Internet and integrates it into the materials. The user reviews the materials and makes corrections as necessary. The final advertising materials are provided with all inputs reflected.

[1334] Example prompt sentence:

[1335] User Input Data: New Product Launch

[1336] User emotion data: excitement, anticipation

[1337] Market intelligence: Competitor A adds new features this month

[1338] Use the information above to create the best advertising materials.

[1339] As described above, by using the system of the present invention, it is possible to efficiently create high-quality, consistent advertising materials that reflect real-time market information and user sentiment.

[1340] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1341] Step 1:

[1342] The user inputs information regarding the requirements for producing advertising materials into the terminal.

[1343] Input: New product features, target market, competitive intelligence, user voice input, etc.

[1344] Processing: The user uses the device to enter the required information and collect data on the device, including voice input.

[1345] Output: Collected data is saved to the device.

[1346] Step 2:

[1347] The terminal transmits the information entered by the user to the server.

[1348] Input: Data about the creation requirements entered by the user into the terminal.

[1349] Processing: The device formats the user's input data and transmits it over the Internet to a server.

[1350] Output: The user input information is sent to the server.

[1351] Step 3:

[1352] The server analyzes the received input information and generates initial advertising materials using a generative AI model.

[1353] Input: Data about the creation requirements submitted by the user.

[1354] Processing: The server analyzes the input information and converts it into an input format for the generative AI model. Based on this format, the generative AI model is called to generate the initial advertising materials.

[1355] Output: Generation of initial advertising materials.

[1356] Step 4:

[1357] The server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology.

[1358] Input: Raw data from open data sources on the internet.

[1359] Processing: The server collects market information in real time, analyzes market trends and competitive information using natural language processing technology, and extracts the required data.

[1360] Output: Extracted market information.

[1361] Step 5:

[1362] The server updates the content of the advertising materials based on the extracted market information.

[1363] Input: Extracted market information, initial advertising materials.

[1364] Processing: Based on market information, the server updates the content of advertising materials, optimizing the tone and messaging of the materials.

[1365] Output: Updated advertising materials reflecting market information.

[1366] Step 6:

[1367] The server uses an emotion analysis engine to analyze the user's emotion data.

[1368] Input: User's voice data.

[1369] Processing: The server performs emotion analysis on the voice input and extracts the user's emotion data.

[1370] Output: Extracted emotion data.

[1371] Step 7:

[1372] The server adjusts the tone and messaging of advertising materials based on the results of sentiment analysis.

[1373] Input: Sentiment data, updated advertising materials.

[1374] Processing: The server uses the emotional data to optimize the content of advertising materials, for example, adding a positive tone if the emotional data is "excited."

[1375] Output: Emotionally corrected advertising materials.

[1376] Step 8:

[1377] The user checks the generated advertising materials and sends correction instructions to the server.

[1378] Input: Emotionally corrected advertising materials.

[1379] Processing: The user checks the advertising materials through the terminal and gives instructions on what needs to be corrected. These instructions are sent from the terminal to the server.

[1380] Output: User correction instructions.

[1381] Step 9:

[1382] The server updates the advertising materials based on the correction requests from the user and generates the final version of the advertising materials.

[1383] Input: User correction instructions, emotion-corrected advertising materials.

[1384] Processing: The server re-updates the advertising materials based on the user's modification requests, and re-reflects the sentiment data and market information to generate the final materials.

[1385] Output: Final, completed advertising materials.

[1386] Step 10:

[1387] The device provides the final advertising material to the user for review and download.

[1388] Input: Final advertising materials.

[1389] Processing: The device receives the final advertising material from the server, stores it and provides it for the user to access.

[1390] Output: Final advertising materials available for user review and download.

[1391] 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.

[1392] 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.

[1393] 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.

[1394] [Fourth embodiment]

[1395] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1396] 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.

[1397] 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).

[1398] 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.

[1399] 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.

[1400] 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).

[1401] 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.

[1402] 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.

[1403] 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.

[1404] 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.

[1405] 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.

[1406] 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.

[1407] 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."

[1408] The present invention is a system for efficiently creating proposal materials for new services, which uses a generative AI model based on information entered by the user to generate proposal materials and has the function of reflecting real-time market information. This system provides an environment in which users can efficiently create competitive proposal materials.

[1409] Explanation of program processing

[1410] Proposal material creation phase

[1411] User:

[1412] Users first input information about the requirements for creating a proposal, including the target market, service or product features, proposal design and format, and target audience.

[1413] Device:

[1414] The terminal transmits the information entered by the user to the server.

[1415] server:

[1416] The server analyzes the received information and converts it into a format that can be input to the generative AI model. Based on this information, it creates the structure of an initial proposal document. The generative AI model then automatically generates an initial version of the proposal document. This initial version includes the information entered by the user, past success stories, and related materials.

[1417] Real-time market analysis phase

[1418] server:

[1419] The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.) and analyzes the collected data using natural language processing technology to extract the latest market trends and competitive information.

[1420] Market information integration phase

[1421] server:

[1422] The content of the proposal materials is updated based on the analyzed market information. This update ensures that the proposal materials reflect the latest market trends and competitive information, ensuring that the materials are always up-to-date and persuasive.

[1423] Material review and revision phase

[1424] User:

[1425] The user can review the generated proposal and provide instructions for revisions as necessary, such as adding or correcting specific information or adjusting the document design.

[1426] Device:

[1427] The terminal transmits a modification request from the user to the server.

[1428] server:

[1429] The server updates the proposal documents based on user requests for revisions, and if necessary, performs new market analysis and adds the latest information, making the proposal documents even stronger and more competitive.

[1430] Final material generation phase

[1431] server:

[1432] The server generates a final proposal document incorporating all requested revisions and saves it in a format that users can download and present, such as PDF, PowerPoint, or Google Slides.

[1433] Device:

[1434] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[1435] Specific examples

[1436] For example, consider a case where a user is creating a proposal document for a new product. The user inputs the product's features, target market, and competitive information, and the server generates an initial proposal document using a corresponding template. The server collects market information in real time and adds the latest trends and competitive information to the proposal document. The user then reviews the document and requests revisions, and the server completes the final version of the proposal document. Through this process, the user can quickly create high-quality proposal documents that reflect the latest market information.

[1437] This invention enables users to quickly create high-quality proposal materials that reflect market trends in real time, significantly improving the competitiveness of business proposals.

[1438] The processing flow will be explained below.

[1439] Step 1:

[1440] The user inputs information about the requirements for creating a proposal into the terminal, including the target market, the characteristics of the proposed product or service, the design and format of the proposal, and the target audience.

[1441] Step 2:

[1442] The terminal transmits the information entered by the user to the server.

[1443] Step 3:

[1444] The server analyzes the received information and converts it into a format that can be input into the generative AI model.

[1445] Step 4:

[1446] The server automatically generates an initial proposal document using a generative AI model based on the analyzed input information, and at this stage, it also references past success stories and related materials to enhance the content.

[1447] Step 5:

[1448] The server collects real-time market information from open data sources on the internet, such as news articles, blogs, and social media.

[1449] Step 6:

[1450] The server analyzes the collected market information using natural language processing technology and extracts the latest market trends and competitive information.

[1451] Step 7:

[1452] The server updates the content of the initial proposal based on the extracted market information, so that the latest market information is reflected in the proposal.

[1453] Step 8:

[1454] The user checks the generated proposal document and, if necessary, gives instructions for modifying the content or design of the document.

[1455] Step 9:

[1456] The terminal transmits a modification request from the user to the server.

[1457] Step 10:

[1458] The server updates the proposal documents based on the user's correction requests, and if necessary, performs new market analysis to further strengthen the proposal documents.

[1459] Step 11:

[1460] The server generates the final proposal document with all requested revisions reflected, and the document is saved in a format such as PDF, PowerPoint, or Google Slides.

[1461] Step 12:

[1462] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[1463] Example 1

[1464] 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."

[1465] With conventional proposal creation systems, users had to create documents from scratch, which required a great deal of time and effort, and it was difficult to quickly reflect real-time market information. As a result, it was not possible to quickly provide proposal documents that offered a competitive advantage. Furthermore, there was a lack of an efficient process for revising or updating documents, which led to problems with the quality and timing of the final proposal documents.

[1466] 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.

[1467] In this invention, the server includes: means for analyzing input information received from a user and generating initial proposal materials using a generative AI model; means for collecting market information in real time from open data sources on the Internet and analyzing it using natural language processing technology; and means for updating the content of the proposal materials based on the extracted market information. This allows users to quickly and efficiently create high-quality proposal materials that reflect the latest market information and quickly reflect correction instructions. Furthermore, by using the generative AI model, it is possible to automatically generate proposal materials based on past success stories and related materials. This significantly improves the competitiveness of business proposals.

[1468] "User" refers to the entity that uses the system to input information to create proposal materials and checks and modifies the generated materials.

[1469] A "proposal document" is a document used to propose a new service or product, and includes information on the target market, competitors, and service features.

[1470] The "server" is the central device of the computer system that analyzes information received from users, automatically generates proposal materials using a generative AI model, collects and analyzes real-time market information, and reflects it in the materials.

[1471] "Terminal" means a device that allows a user to input information and check and modify the generated proposal materials, and communicates with the server to send and receive data.

[1472] A "generative AI model" refers to a machine learning algorithm or model that automatically generates proposal materials based on information entered by the user.

[1473] "Input information" refers to data that a user inputs to create a proposal document, including the target market, the characteristics of the service or product, the design and format of the proposal, and the target audience.

[1474] An "open data source" is a collection of data that is publicly available on the internet, including news articles, blogs, social media, etc.

[1475] "Natural language processing technology" is a technology for analyzing collected text data and extracting important information and trends.

[1476] "Market Intelligence" refers to market trends and competitive information collected and analyzed from data sources on the Internet.

[1477] A "correction instruction" is an instruction that the user uses to specify additions or changes to the generated proposal material, and is transmitted to the server.

[1478] The "final proposal document" is a completed proposal document that reflects all revision requests from the user.

[1479] MODE FOR CARRYING OUT THE INVENTION

[1480] This invention is a system for efficiently creating proposal materials for new services. It uses a generative AI model based on information entered by the user to generate proposal materials, and has the function of reflecting real-time market information. This system provides an environment in which users can efficiently create competitive proposal materials.

[1481] System Overview

[1482] The system consists of a user, a terminal, and a server. The user inputs the information necessary to create a proposal document. The terminal sends this information to the server, which then provides the generated document to the user. The server analyzes the input information and generates the proposal document using a generative AI model. It also collects market information from open data sources on the Internet, analyzes it using natural language processing technology, and reflects that information in the proposal document.

[1483] Hardware and software used

[1484] Terminal: A device such as a personal computer or smartphone that allows users to input information and check and edit materials.

[1485] Server: A high-performance computer system that analyzes information, runs AI models, and collects and analyzes data.

[1486] Software: Word processing software, generative AI models (e.g., GPT), natural language processing techniques (e.g., NLTK, SpaCy)

[1487] Specific examples of creating proposal materials

[1488] For example, consider a case where a user is creating a proposal document for a new product. The user inputs the product's features, target market, and competitive information, and the server generates an initial proposal document using a corresponding template. The server collects market information in real time and adds the latest trends and competitive information to the proposal document. The user then reviews the document and requests revisions, and the server completes the final version of the proposal document. Through this process, the user can quickly create high-quality proposal documents that reflect the latest market information.

[1489] Prompt Sentence Examples

[1490] "To create a proposal for a new product, you enter product features, target market, and competitive information. The server generates an initial proposal based on this information. It also collects market information in real time, adding the latest trends and competitive information to the proposal."

[1491] This system enables users to quickly create high-quality proposal materials that reflect the latest market information, significantly improving the competitiveness of their business proposals.

[1492] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1493] Step 1:

[1494] The user inputs information related to the requirements for creating a proposal document. The information input by the user includes the target market, product or service features, proposal design and format, target audience, etc. Specifically, the user inputs information such as "list of new product features," "target market is North America," and "main competitor is Company X" into the input form. Once the input is complete, the information is saved for the next step.

[1495] Input: User-entered requirements information for proposal materials (e.g., product features, target market, competitive information)

[1496] Output: The input requirements information is saved.

[1497] Step 2:

[1498] The device sends the information entered by the user to the server. When the user clicks the "Send" button, the device calls the API in the backend and passes the input information to the server. The device notifies the user that the sending process was successful.

[1499] Input: User-entered requirements information for the proposal document

[1500] Output: User input sent to the server

[1501] Step 3:

[1502] The server analyzes the information received from the device and converts it into a format suitable for input into the generative AI model. Specifically, it converts the received information into JSON format and organizes it into a structure suitable for the generative AI model. It also pulls past success stories and related materials from a database and integrates this information.

[1503] Input: User input information sent from the device

[1504] Output: Information converted into a format that can be input into a generative AI model

[1505] Step 4:

[1506] The generative AI model generates an initial proposal based on the information prepared by the server, using the basic structure and template of the proposal. The initial version of the proposal reflects the requirements specified by the user.

[1507] Input: Information converted into a format that can be fed into a generative AI model

[1508] Output: Generate initial proposal materials

[1509] Step 5:

[1510] The server collects real-time market information from open data sources on the internet, through APIs and web scraping, retrieving relevant data from news articles, blogs, social media, etc.

[1511] Input: Real-time market data request

[1512] Output: Collected market data

[1513] Step 6:

[1514] The server analyzes the collected market data using natural language processing technology, specifically extracting important keywords and trends from the text data and organizing the information relevant to the proposal materials.

[1515] Input: Collected market data

[1516] Output: Analyzed market information (e.g. trends, competitive intelligence)

[1517] Step 7:

[1518] The server updates the content of the proposal documents based on the analyzed market information. Specifically, it adds the latest market trends and competitive analysis to the proposal documents, thereby enhancing the documents based on the latest information.

[1519] Input: Parsed market information

[1520] Output: Updated proposal

[1521] Step 8:

[1522] The user can check the generated proposal document and input any correction requests they may have. Through the GUI, the user can intuitively add or correct specific information, adjust the document design, and more.

[1523] Input: User requested correction

[1524] Output: Correction request entered

[1525] Step 9:

[1526] The terminal sends the modification request from the user to the server, and the user's modification request is now ready to be processed by the server.

[1527] Input: User's correction request

[1528] Output: The modification request sent to the server

[1529] Step 10:

[1530] The server updates the proposal documents based on the user's correction requests, and if necessary, performs new market analysis and adds the latest information to the documents to generate even stronger proposal documents.

[1531] Input: The modification request sent to the server

[1532] Output: Updated proposal

[1533] Step 11:

[1534] The server generates the final proposal document incorporating all requested revisions and saves it in formats such as PDF, PowerPoint, Google Slides, etc.

[1535] Input: Updated proposal

[1536] Output: Final proposal

[1537] Step 12:

[1538] The terminal provides the final proposal materials to the user, allowing the user to review and download the materials by clicking on the download link.

[1539] Input: Final proposal

[1540] Output: The final proposal provided to the user

[1541] (Application example 1)

[1542] 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."

[1543] Creating proposal materials for advertising campaigns requires a great deal of time and effort, and it is difficult to quickly create materials that reflect the latest market information. The purpose of this invention is to solve these problems by efficiently collecting and analyzing the information necessary for advertising campaigns and automatically creating high-quality proposal materials that always reflect the latest market data.

[1544] 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.

[1545] In this invention, the server includes: means for a user to input information regarding requirements for creating proposal materials; means for transmitting the input information to the server; means for the server to analyze the input information received from the user and generate initial proposal materials using a generative AI model; means for the server to collect market information in real time from open data sources on the Internet and analyze it using natural language processing technology; means for the server to update the content of the proposal materials based on the extracted market information; means for the user to check the generated proposal materials and send correction instructions to the server; means for the server to update the proposal materials based on correction requests from the user and generate final proposal materials; means for the terminal to provide the final proposal materials to the user so that the user can check and download them; means for the user to input information about an advertising campaign and receive proposal materials generated based on this information; and means for collecting real-time market data and reflecting the results of analysis in the advertising campaign materials. This enables users to quickly and efficiently create high-quality proposal materials for their advertising campaigns and always reflect the latest market information.

[1546] A "user" is a person who inputs information required to create a proposal document, and checks and modifies the created document.

[1547] "Pitch deck" means a written or digital file that is used to present an advertising campaign or a product or service to the market.

[1548] "Creation requirements" refer to the information, conditions, specifications, etc. required when creating proposal materials.

[1549] The "server" is a computer system that receives and analyzes information entered by users and creates proposal materials using a generative AI model.

[1550] A "generative AI model" is an artificial intelligence model that automatically generates proposal materials based on input data.

[1551] An "initial proposal" is the first version of a proposal that is automatically created by a generative AI model based on information provided by a user.

[1552] "Open data sources on the Internet" refers to information sources that are publicly available online, such as news articles, blogs, and social media.

[1553] "Real-time market information" refers to the latest market data that changes over time, such as current market trends and competitive information.

[1554] "Natural language processing technology" is a computer science technology for analyzing text data, understanding its meaning, and extracting information.

[1555] "Modification instructions" refer to requests for modifications or additions made by the user to the generated proposal materials.

[1556] The "final version of the proposal material" refers to the proposal material that has been finally completed and that reflects the user's correction requests.

[1557] A "terminal" is a device used by a user to send input information and receive generated materials.

[1558] This invention is a system that efficiently creates proposal materials using a generative AI model based on information about advertising campaigns entered by users. The system generates optimal proposal materials based on initial information provided by users and real-time market data, and provides an environment where users can review and modify them.

[1559] Program Description

[1560] Proposal material creation phase

[1561] 1. The user enters information about the advertising campaign (e.g., product, target market, campaign objectives).

[1562] 2. The device sends the input information to the server.

[1563] 3. The server analyzes this information and converts it into a format suitable for the generative AI model, which then creates an initial proposal document based on this information.

[1564] Real-time market analysis phase

[1565] 1. The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.).

[1566] 2. Analyze the collected data using natural language processing (NLP) technology to extract the latest market trends and competitive information.

[1567] Market information integration phase

[1568] 1. The server updates the content of the proposal materials based on the analyzed market information. This update ensures that the proposal materials reflect the latest market trends and competitive information.

[1569] Material review and revision phase

[1570] 1. The user can review the generated proposal document and provide instructions for revisions as necessary, such as adding or correcting specific information or adjusting the document design.

[1571] 2. The device sends a modification request to the server.

[1572] 3. The server updates the proposal based on the revision request, conducting new market analysis as needed and adding the latest information.

[1573] Final material generation phase

[1574] 1. The server generates the final proposal document incorporating all requested revisions and saves it in a format that users can download or present, such as PDF, PowerPoint, or Google Slides.

[1575] 2. The terminal provides the final proposal materials to the user, allowing the user to review and download the materials.

[1576] Specific examples

[1577] If a user is planning a social media campaign for a new cosmetics line, they would first enter the following information:

[1578] Product: New skin care line

[1579] Target market: Women aged 20-35

[1580] Campaign Objective: Increase engagement on Instagram and TikTok

[1581] Using this information, the server generates an initial proposal and then uses the following prompt to create a final proposal that reflects market information:

[1582] Create an ad campaign proposal with the following details:

[1583] Product: New skincare line

[1584] Target Audience: Women aged 20-35

[1585] Focus: Social media engagement on Instagram and TikTok

[1586] Real-time market information includes:

[1587] Update the initial ad campaign proposal with the following market trends and data:

[1588] Growing trend of eco-friendly skincare products

[1589] Increasing engagement rates on visual platforms like Instagram and TikTok

[1590] Competitor analysis showing a surge in influencer marketing strategies for similar products

[1591] This system allows users to quickly create high-quality proposal materials that always reflect the latest market data.

[1592] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1593] Step 1:

[1594] The user inputs information related to the requirements for creating an advertising campaign (e.g., product, target market, campaign objectives), including campaign details, target market demographics, goals, budget, etc.

[1595] Enter: Campaign details

[1596] Output: Initial information sent to the server

[1597] Step 2:

[1598] The device sends the information entered by the user to the server, and this data is sent in a standard format such as JSON.

[1599] Input: Campaign information entered by the user

[1600] Output: Campaign information transferred to the server

[1601] Step 3:

[1602] The server analyzes the input information received from the user and converts it into a format suitable for the generative AI model. Specifically, it converts text data into prompt sentences.

[1603] Input: Campaign information

[1604] Output: The prompt sentence that is input to the generative AI model

[1605] Step 4:

[1606] The server automatically generates the initial proposal using a generative AI model, which generates text based on the prompt sentences mentioned above.

[1607] Input: prompt statement

[1608] Output: Initial proposal

[1609] Step 5:

[1610] The server collects market information in real time from open data sources on the Internet (news articles, blogs, social media, etc.) using scraping technology and APIs.

[1611] Input: None (automatic collection)

[1612] Output: Real-time market data

[1613] Step 6:

[1614] The server analyzes the collected data using natural language processing (NLP) technology to extract the latest market trends and competitive information, specifically through word analysis, topic modeling, and sentiment analysis.

[1615] Input: Real-time market data

[1616] Output: Analyzed market trend information

[1617] Step 7:

[1618] The server updates the initial proposal based on the analyzed market information, and re-uses the generative AI model to generate more specific proposals.

[1619] Input: Initial proposal materials, analyzed market information

[1620] Output: Updated proposal

[1621] Step 8:

[1622] The user checks the generated proposal document and sends correction instructions to the server as necessary, such as adding or correcting specific information or adjusting the document design.

[1623] Input: Updated proposal

[1624] Output: User's correction instructions

[1625] Step 9:

[1626] The terminal sends the user's revision requests to the server, which then generates the final version of the proposal based on this information.

[1627] Input: User's correction request

[1628] Output: The modification request forwarded to the server

[1629] Step 10:

[1630] The server uses the generative AI model again based on the user's correction requests to generate the final proposal document, and if necessary, performs new market analysis and adds the latest information.

[1631] Input: Correction Request

[1632] Output: Final proposal

[1633] Step 11:

[1634] The terminal provides the final proposal materials to the user and saves them in a format that the user can view and download.

[1635] Input: Final proposal

[1636] Output: A download link or file that is provided to the user

[1637] 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.

[1638] The present invention relates to a system that integrates the creation of proposal materials with real-time market information and further optimizes the content of the proposal materials by recognizing user emotions. The system includes a means for a user to input information required for creating proposal materials and generate the materials using a generative AI model. Furthermore, the system is equipped with an emotion engine that analyzes user emotions and provides more appropriate materials.

[1639] Explanation of program processing

[1640] Proposal material creation phase

[1641] User:

[1642] The user first inputs information about the requirements for creating a proposal document into the device, including the target market, the features of the proposed product or service, the design and format of the proposal document, and the target audience, as well as data for capturing emotions from the user's voice and text input.

[1643] Device:

[1644] The terminal transmits the information and emotion data input by the user to the server.

[1645] Initial Data Preparation Phase

[1646] server:

[1647] The server analyzes the received information and converts it into a format that can be input to the generative AI model. At the same time, it analyzes the user's emotions using an emotion engine and supplies this information to the generative AI model.

[1648] Initial data generation phase

[1649] server:

[1650] The server uses the analyzed input information and emotion data to generate an initial proposal using a generative AI model, which reflects the user's input and emotional adjustments.

[1651] Real-time market analysis phase

[1652] server:

[1653] The server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology. From the analysis results, the latest market trends and competitive information are extracted.

[1654] Market information integration phase

[1655] server:

[1656] The extracted market information is used to update the content of the initial pitch deck, and the tone and messaging of the pitch deck are adjusted based on user sentiment data obtained from the emotion engine.

[1657] Material review and revision phase

[1658] User:

[1659] The user can review the generated proposal and provide instructions for revisions to the content and design, including those based on the user's feelings.

[1660] Device:

[1661] The terminal transmits a modification request from the user to the server.

[1662] server:

[1663] The server updates the proposal materials based on correction requests from users, and reanalyzes and reflects new market information and sentiment data as necessary.

[1664] Final data generation phase

[1665] server:

[1666] Generate a final proposal document that reflects all revision requests, real-time market information, and sentiment data, and save it as a PDF, PowerPoint, Google Slides, etc.

[1667] Proposal materials provision phase

[1668] Device:

[1669] The final proposal will be provided to the user for review and download.

[1670] Specific examples

[1671] For example, when a user creates a proposal document for a new product, they input product features, target market, and competitive information, along with the associated emotions of excitement and anticipation. The server generates an initial proposal document based on this information and emotion data, and then collects real-time market information and integrates it into the document. The user then reviews the document and provides instructions for revision based on their emotions, and the server ultimately generates a high-quality proposal document that reflects the user's emotions.

[1672] This system allows users to efficiently create high-quality proposal materials that reflect real-time market information and their own emotions, significantly improving the competitiveness of business proposals and providing more persuasive materials that are in tune with users' emotions.

[1673] The processing flow will be explained below.

[1674] Step 1:

[1675] The user inputs information about the requirements for creating a proposal document into the terminal, including the target market, the characteristics of the proposed product or service, the design and format of the document, and the target audience.

[1676] Step 2:

[1677] The terminal transmits the information entered by the user and emotion data obtained from voice and text to the server.

[1678] Step 3:

[1679] The server analyzes the received information and converts it into a format that can be input into the generative AI model, while simultaneously analyzing the user's emotions using an emotion engine.

[1680] Step 4:

[1681] The server uses a generative AI model to automatically generate an initial proposal document based on the analyzed input information and emotion data, which includes adjustments based on the information and emotion entered by the user.

[1682] Step 5:

[1683] The server collects real-time market information from open data sources on the internet, such as news articles, blogs, and social media.

[1684] Step 6:

[1685] The server analyzes the collected market information using natural language processing technology and extracts the latest market trends and competitive information.

[1686] Step 7:

[1687] The server updates the content of the initial pitch deck based on the extracted market information, while simultaneously adjusting the pitch deck's tone and messaging based on user emotion data obtained from the emotion engine.

[1688] Step 8:

[1689] The user reviews the generated proposal materials and makes suggestions for revisions to the content and design of the materials, including suggestions for revisions based on the user's feelings.

[1690] Step 9:

[1691] The terminal transmits a modification request from the user to the server.

[1692] Step 10:

[1693] The server updates the proposal materials based on user requests for revisions, and if necessary, re-analyzes market information and sentiment data to reflect these changes.

[1694] Step 11:

[1695] The server generates the final proposal document, incorporating all revision requests, real-time market information, and sentiment data, and saves it in formats such as PDF, PowerPoint, and Google Slides.

[1696] Step 12:

[1697] The terminal provides the final version of the proposal material to the user, allowing the user to check and download the material.

[1698] Example 2

[1699] 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."

[1700] Conventional proposal material creation systems have difficulty fully reflecting user sentiment and real-time market information, resulting in a decline in the persuasiveness and competitiveness of the materials. Furthermore, updating and correcting materials is time-consuming, which can cause delays in a business environment where rapid response is required. Therefore, the present invention solves these problems and enables the efficient creation of high-quality proposal materials.

[1701] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1702] In this invention, the server includes means for analyzing voice and facial expression data to recognize user emotions, means for collecting market information in real time from open data sources on the Internet and analyzing it using natural language processing technology, and means for reanalyzing the emotion data to generate final proposal materials, thereby enabling the creation of high-quality proposal materials that reflect user emotions and the latest market information.

[1703] "User" refers to an individual or organization who inputs the information necessary to create proposal materials and operates the system.

[1704] "Terminal" means an electronic device used by a User to input information or to view and download generated proposal materials.

[1705] "Server" refers to the computer system that receives and analyzes information sent by users and generates and updates proposal materials using generative AI models.

[1706] A "proposal" is a document or presentation that describes the features, target market, and target audience of a particular product or service that a user is aiming to create.

[1707] A "generative AI model" is an artificial intelligence model that generates proposal materials based on information entered by the user.

[1708] "Emotion data" refers to information about emotions acquired from the user's voice and facial expressions.

[1709] "Market intelligence" refers to data such as market trends and competitive information collected from open data sources on the Internet.

[1710] "Natural language processing technology" is a technology used to analyze market information, and is a method for analyzing the meaning of text data and extracting information.

[1711] A "modification instruction" is a request made by a user to change the content or design of the generated proposal material.

[1712] The present invention relates to a system for creating proposal materials, integrating real-time market information, and optimizing the content of the proposal materials by recognizing user emotions. This system is realized by combining multiple means.

[1713] Hardware and software configuration of the proposal document creation system

[1714] User:

[1715] Users input the information required to create proposal materials into a device. The device can be a PC, tablet, smartphone, or other electronic device. Users input using a keyboard, microphone, and camera. Voice input is converted into text using voice recognition software, and facial expression data is acquired using a camera and image analysis software.

[1716] Device:

[1717] The device sends the information and emotion data entered by the user to the server. Data is transferred over an internet connection and encryption technology such as SSL / TLS, using protocols such as HTTP POST requests.

[1718] server:

[1719] The server analyzes the received information and generates initial proposal materials using a generative AI model. A text analysis engine and a sentiment analysis engine run on the server, converting the input information and sentiment data into an appropriate format. This process uses natural language processing models such as BERT and sentiment analysis models.

[1720] The server also collects real-time market information from open data sources on the Internet, using web scraping technology and APIs, and analyzes the market information using natural language processing technology to extract the latest trends and competitive information. The analyzed market information is then integrated into proposal materials and updated.

[1721] Examples of specific examples and prompts

[1722] For example, when a user creates a proposal for a new product, they use their device to input product features, target market, competitive information, etc. The device then sends this information to a server. The server then analyzes the received information, including sentiment data, and generates an initial proposal using a generative AI model (e.g., GPT-4). The server then collects market information and updates the proposal in real time.

[1723] The user reviews the generated proposal document and sends revision instructions from the terminal to the server. The server reanalyzes the revision requests, the latest market information, and sentiment data to generate the final proposal document. The terminal then provides the final proposal document to the user, who then reviews and downloads it.

[1724] Prompt Sentence Examples

[1725] Enter the following prompt into the generative AI model:

[1726] Please enter the features of your new product as follows: The target market is technology startups, and the competitive information is that Company A and Company B are the main competitors. The design of the proposal document should be simple, and the target audience should be engineers. Furthermore, the content should reflect their expectations.

[1727] This system allows users to efficiently create high-quality proposal materials that reflect real-time market information and their own emotions, improving the competitiveness of business proposals and providing persuasive materials that are in tune with users' emotions.

[1728] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1729] Step 1:

[1730] User:

[1731] The user inputs the information necessary to create a proposal document into the device. Specifically, details such as the target market, the features of the proposed product or service, the document design and format, and the target audience are entered as text. Voice input can also be performed using a microphone, and the voice is converted into text by an automatic speech recognition system. Furthermore, a camera is used to capture facial expressions, which are then used as data for emotion analysis. This provides the user's input information and emotion data.

[1732] Step 2:

[1733] Device:

[1734] The device sends the information entered by the user and emotion data to the server. Specifically, the text data, text data obtained by voice recognition, and facial expression data are all sent together via an HTTP POST request. The data is encrypted using SSL / TLS before being sent and is securely transferred to the server.

[1735] Step 3:

[1736] server:

[1737] The server analyzes the received information. First, it uses a text analysis engine to format the information entered by the user into an appropriate format. Next, it uses an emotion analysis engine to extract the user's emotions from the voice data and facial expression data and stores them as numerical data. For example, emotions such as "happiness" and "expectation" are quantified. This step also converts the analysis results into a format that can be applied to a generative AI model. Through this process, the input data is analyzed and a dataset for the AI ​​model is generated.

[1738] Step 4:

[1739] server:

[1740] The server uses a generative AI model to generate an initial proposal. Specifically, the analyzed input information and emotional data are input as prompts into a generative AI model such as OpenAI's GPT-4. The generative AI model then uses this data to generate text and graphic elements for the initial proposal. The result is an initial proposal that reflects the user's input and emotional data.

[1741] Step 5:

[1742] server:

[1743] The server collects market information in real time from open data sources on the Internet. Specifically, it uses web scraping and APIs to obtain the latest market information from news sites and industry reports. This allows for the collection of market trends and competitive information in real time.

[1744] Step 6:

[1745] server:

[1746] The server analyzes the collected market information using natural language processing technology. This analysis uses language models such as BERT to extract trends and competitive information from the collected text data. The analysis results are integrated into proposal materials. Specifically, the market information is summarized and output as text data to be integrated into the strategy section of the proposal materials.

[1747] Step 7:

[1748] server:

[1749] The server updates the content of the initial proposal based on the extracted market information. Furthermore, it adjusts the tone and messaging of the proposal based on the user's emotional data obtained from the emotion engine. For example, it reflects competitive information and uses more positive language in response to the user's expressed expectations. This allows the initial proposal to be shaped by market information and emotional data.

[1750] Step 8:

[1751] User:

[1752] The user can review the generated proposal and make corrections to the content and design. The user can use a terminal to input corrections such as changing the color of a specific graph or requesting additional information. Corrections can also be made based on emotions.

[1753] Step 9:

[1754] Device:

[1755] The terminal transmits a request for modification from the user to the server. Specifically, the modification content made by the user on the terminal is sent to the server in text format, and the server receives it in a format that can be processed.

[1756] Step 10:

[1757] server:

[1758] The server updates the proposal documents based on the user's revision requests. If necessary, it reanalyzes new market information and sentiment data and reflects the revisions. For example, it adds newly collected market information and revise the proposal documents to reflect the sentiment data. This updates the proposal documents to reflect the revision requests.

[1759] Step 11:

[1760] server:

[1761] The server generates the final proposal document, reflecting all revision requests, real-time market information, and sentiment data, and converts and saves the document in formats such as PDF, PowerPoint, Google Slides, etc. This results in a file that can be used as a high-quality presentation document.

[1762] Step 12:

[1763] Device:

[1764] The terminal provides the final proposal materials to the user, allowing the user to review and download them. Specifically, a download link for the materials is displayed on the terminal, and when the user clicks it, the file download begins. This allows the user to review and use the final proposal materials.

[1765] (Application example 2)

[1766] 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."

[1767] Conventional advertising material creation systems have difficulty reflecting real-time changes in market information and user sentiment, resulting in difficulties in creating consistent, high-quality advertising materials. Furthermore, the time-consuming task of manually collecting market trends and competitive information hinders efficient material creation. Furthermore, it is not possible to create advertising materials that reflect user sentiment, making it difficult to increase persuasiveness and empathy among the target audience.

[1768] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1769] In this invention, the server includes: means for a user to input information regarding requirements for creating advertising materials; means for transmitting the input information to the server; means for the server to analyze the input information received from the user and generate initial advertising materials using a generative AI model; means for the server to collect market information in real time from open data sources on the Internet and analyze it using natural language processing technology; means for the server to update the content of the advertising materials based on the extracted market information; means for the server to analyze emotions from user voice input; means for the server to adjust the tone and messaging of the advertising materials based on the emotion analysis results; means for the user to review the generated advertising materials and send correction instructions to the server; means for the server to update the advertising materials based on correction requests from the user and generate final advertising materials; and means for the terminal to provide the final advertising materials to the user so that the user can review and download them. This enables efficient creation of high-quality, consistent advertising materials that reflect real-time market information and user emotions.

[1770] A "user" is a person who uses the system to create advertising materials.

[1771] "Advertising materials" are documents or presentations created to promote a particular product or service.

[1772] "Production requirements" are all the information needed to create advertising materials, including the theme, target market, competitive information, etc.

[1773] An "input means" is an interface or device used by a user to provide information that enters the system.

[1774] A "server" is a central processing unit that receives input information from a user and processes and analyzes it.

[1775] A "generative AI model" is an artificial intelligence model that automatically generates advertising materials based on given input data.

[1776] "Initial Advertising Materials" means the first version of advertising materials created by a generative AI model.

[1777] "Internet open data sources" are publicly available data resources accessible via the Internet, including market information.

[1778] "Natural language processing technology" is a technology for analyzing text data, extracting information, and understanding meaning.

[1779] "Means for collecting market information in real time" refers to a method that allows for the immediate acquisition of dynamically changing market data.

[1780] "Sentiment analysis" is the process of identifying a user's emotions from their voice or text.

[1781] "Means to adjust tone and messaging" refers to methods to optimize the content and presentation of advertising materials based on user emotions.

[1782] "Modification instructions" refer to requests for changes made by a user to generated advertising materials.

[1783] "Final Advertising Materials" means advertising materials in their completed form, incorporating all revision instructions and the latest market information.

[1784] "Terminal" means a device used by a user to operate the system and to view and download advertising materials.

[1785] The present invention is a system for supporting the creation of advertising materials, which includes a user, a terminal, and a server. In this system, the user inputs information and sends it to the server via the terminal, and the server creates the materials using a generative AI model. Furthermore, the server analyzes the user's sentiment and reflects real-time market information in the materials.

[1786] The server receives information entered by the user regarding the requirements for creating advertising materials. For example, the system receives user-entered information such as themes, target markets, and competitive information. This information is sent from the device to the server. Voice data provided by the user is also sent to the server and is subjected to sentiment analysis.

[1787] The server generates initial advertising materials using a generative AI model. The generative AI model creates advertising materials based on information entered by the user. The server also collects market information in real time from open data sources on the Internet. The market information is analyzed using natural language processing technology, and the extracted market information is used to update the content of the advertising materials.

[1788] The server has an emotion engine for analyzing emotions from the user's voice data. The emotion engine analyzes the user's emotion data and uses the results to adjust the tone and messaging of advertising materials. For example, if the user is excited, advertising materials with a positive tone that reflects that emotion are generated.

[1789] The user checks the generated advertising materials on their device and sends correction instructions to the server as necessary. The server updates the advertising materials based on the correction instructions. The final version of the advertising materials is completed by reflecting all correction requests and the latest market information. The final advertising materials are provided to the user via their device, allowing them to check and download them.

[1790] The system operates using the following hardware and software: The hardware includes the user's device (e.g., smartphone or PC) and server. The software includes the OpenAI API, which provides the generative AI model, an internet connection to obtain real-time market information, and an emotion engine for emotion analysis.

[1791] As a concrete example, let's consider the case where a user creates advertising materials for a "new product launch." In this case, the user uses their device to input the following information: the new product's features, target market, competitive information, emotions of excitement and anticipation, etc. This information is sent to the server, where the generative AI model and sentiment analysis engine perform their respective roles to generate the initial advertising materials. The server then collects market information from the Internet and integrates it into the materials. The user reviews the materials and makes corrections as necessary. The final advertising materials are provided with all inputs reflected.

[1792] Example prompt sentence:

[1793] User Input Data: New Product Launch

[1794] User emotion data: excitement, anticipation

[1795] Market intelligence: Competitor A adds new features this month

[1796] Use the information above to create the best advertising materials.

[1797] As described above, by using the system of the present invention, it is possible to efficiently create high-quality, consistent advertising materials that reflect real-time market information and user sentiment.

[1798] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1799] Step 1:

[1800] The user inputs information regarding the requirements for producing advertising materials into the terminal.

[1801] Input: New product features, target market, competitive intelligence, user voice input, etc.

[1802] Processing: The user uses the device to enter the required information and collect data on the device, including voice input.

[1803] Output: Collected data is saved to the device.

[1804] Step 2:

[1805] The terminal transmits the information entered by the user to the server.

[1806] Input: Data about the creation requirements entered by the user into the terminal.

[1807] Processing: The device formats the user's input data and transmits it over the Internet to a server.

[1808] Output: The user input information is sent to the server.

[1809] Step 3:

[1810] The server analyzes the received input information and generates initial advertising materials using a generative AI model.

[1811] Input: Data about the creation requirements submitted by the user.

[1812] Processing: The server analyzes the input information and converts it into an input format for the generative AI model. Based on this format, the generative AI model is called to generate the initial advertising materials.

[1813] Output: Generation of initial advertising materials.

[1814] Step 4:

[1815] The server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology.

[1816] Input: Raw data from open data sources on the internet.

[1817] Processing: The server collects market information in real time, analyzes market trends and competitive information using natural language processing technology, and extracts the required data.

[1818] Output: Extracted market information.

[1819] Step 5:

[1820] The server updates the content of the advertising materials based on the extracted market information.

[1821] Input: Extracted market information, initial advertising materials.

[1822] Processing: Based on market information, the server updates the content of advertising materials, optimizing the tone and messaging of the materials.

[1823] Output: Updated advertising materials reflecting market information.

[1824] Step 6:

[1825] The server uses an emotion analysis engine to analyze the user's emotion data.

[1826] Input: User's voice data.

[1827] Processing: The server performs emotion analysis on the voice input and extracts the user's emotion data.

[1828] Output: Extracted emotion data.

[1829] Step 7:

[1830] The server adjusts the tone and messaging of advertising materials based on the results of sentiment analysis.

[1831] Input: Sentiment data, updated advertising materials.

[1832] Processing: The server uses the emotional data to optimize the content of advertising materials, for example, adding a positive tone if the emotional data is "excited."

[1833] Output: Emotionally corrected advertising materials.

[1834] Step 8:

[1835] The user checks the generated advertising materials and sends correction instructions to the server.

[1836] Input: Emotionally corrected advertising materials.

[1837] Processing: The user checks the advertising materials through the terminal and gives instructions on what needs to be corrected. These instructions are sent from the terminal to the server.

[1838] Output: User correction instructions.

[1839] Step 9:

[1840] The server updates the advertising materials based on the correction requests from the user and generates the final version of the advertising materials.

[1841] Input: User correction instructions, emotion-corrected advertising materials.

[1842] Processing: The server re-updates the advertising materials based on the user's modification requests, and re-reflects the sentiment data and market information to generate the final materials.

[1843] Output: Final, completed advertising materials.

[1844] Step 10:

[1845] The device provides the final advertising material to the user for review and download.

[1846] Input: Final advertising materials.

[1847] Processing: The device receives the final advertising material from the server, stores it and provides it for the user to access.

[1848] Output: Final advertising materials available for user review and download.

[1849] 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.

[1850] 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.

[1851] 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.

[1852] 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.

[1853] 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.

[1854] 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.

[1855] 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).

[1856] 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.

[1857] 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."

[1858] 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 emotion values.

[1859] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1860] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1861] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1862] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1863] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1864] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1865] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1866] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1867] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1868] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1869] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1870] The following is further disclosed regarding the above embodiment.

[1871] (Claim 1)

[1872] a means for a user to input information regarding requirements for creating a proposal document;

[1873] means for transmitting the input information to a server;

[1874] A means for the server to analyze input information received from the user and generate initial proposal materials using a generative AI model;

[1875] A server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology.

[1876] A means for the server to update the content of the proposal materials based on the extracted market information;

[1877] A means for a user to check the generated proposal material and send correction instructions to the server;

[1878] a means for the server to update the proposal document based on a correction request from the user and generate a final version of the proposal document;

[1879] A means for the terminal to provide the final proposal materials to the user and allow the user to review and download them;

[1880] A system including:

[1881] (Claim 2)

[1882] 10. The system of claim 1, further comprising means for the server to analyze historical data and current trends to predict market growth patterns and integrate growth market information into the strategy portion of the proposal deck.

[1883] (Claim 3)

[1884] 2. The system according to claim 1, further comprising means for the server to update the contents of the proposal materials in real time, providing an environment in which the user can revise the materials at any time based on the latest information.

[1885] "Example 1"

[1886] (Claim 1)

[1887] a means for a user to input information regarding requirements for creating a proposal document;

[1888] means for transmitting the input information to a server;

[1889] A means for the server to analyze input information received from the user and generate initial proposal materials using a generative AI model;

[1890] A server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology.

[1891] A means for the server to update the content of the proposal materials based on the extracted market information;

[1892] A means for a user to check the generated proposal material and send correction instructions to the server;

[1893] a means for the server to update the proposal document based on a correction request from the user and generate a final version of the proposal document;

[1894] A means for the terminal to provide the final proposal materials to the user and allow the user to review and download them;

[1895] means for the terminal to send a user's correction instruction;

[1896] A means for the server to convert the input information into a format for input to the generative AI model;

[1897] A means for the server to analyze the collected data using natural language processing technology;

[1898] A system including:

[1899] (Claim 2)

[1900] 10. The system of claim 1, further comprising means for the server to analyze historical data and current trends to predict market growth patterns and integrate growth market information into the strategy portion of the proposal deck.

[1901] (Claim 3)

[1902] 2. The system according to claim 1, further comprising means for the server to update the contents of the proposal materials in real time, providing an environment in which the user can revise the materials at any time based on the latest information.

[1903] "Application Example 1"

[1904] (Claim 1)

[1905] a means for a user to input information regarding requirements for creating a proposal document;

[1906] means for transmitting the input information to a server;

[1907] A means for the server to analyze input information received from the user and generate initial proposal materials using a generative AI model;

[1908] A server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology.

[1909] A means for the server to update the content of the proposal materials based on the extracted market information;

[1910] A means for a user to check the generated proposal material and send correction instructions to the server;

[1911] a means for the server to update the proposal document based on a correction request from the user and generate a final version of the proposal document;

[1912] A means for the terminal to provide the final proposal materials to the user and allow the user to review and download them;

[1913] a means for a user to input information about an advertising campaign and receive proposal materials generated based on that information;

[1914] A means of collecting real-time market data and incorporating the results of analysis into advertising campaign materials.

[1915] A system including:

[1916] (Claim 2)

[1917] 10. The system of claim 1, further comprising means for the server to analyze historical data and current trends to predict market growth patterns and integrate growth market information into the strategy portion of the proposal deck.

[1918] (Claim 3)

[1919] 2. The system according to claim 1, further comprising means for the server to update the contents of the proposal materials in real time, providing an environment in which the user can revise the materials at any time based on the latest information.

[1920] "Example 2: Combining Emotion Engines"

[1921] (Claim 1)

[1922] a means for a user to input information regarding requirements for creating a proposal document;

[1923] means for transmitting the input information to a server;

[1924] A means for analyzing voice and facial expression data to recognize the user's emotions;

[1925] A means for the server to analyze input information received from the user and generate initial proposal materials using a generative AI model;

[1926] A server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology.

[1927] A means for the server to update the content of the proposal materials based on the extracted market information;

[1928] A means for a user to check the generated proposal material and send correction instructions to the server;

[1929] a means for the server to update the proposal document based on a correction request from the user and reanalyze the emotion data to generate a final version of the proposal document;

[1930] A means for the terminal to provide the final proposal materials to the user and allow the user to review and download them;

[1931] A system including:

[1932] (Claim 2)

[1933] 10. The system of claim 1, further comprising means for the server to analyze historical data and current trends to predict market growth patterns and integrate growth market information into the strategy portion of the proposal deck.

[1934] (Claim 3)

[1935] 2. The system according to claim 1, further comprising means for the server to update the contents of the proposal materials in real time, providing an environment in which the user can revise the materials at any time based on the latest information.

[1936] "Application example 2 when combining emotion engines"

[1937] (Claim 1)

[1938] means for a user to input information regarding the requirements for producing advertising materials;

[1939] means for transmitting the input information to a server;

[1940] a means for the server to analyze input information received from the user and generate initial advertising materials using a generative AI model;

[1941] A server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology.

[1942] a means for the server to update the content of the advertising materials based on the extracted market information;

[1943] a means for the server to analyze emotions from a user's voice input;

[1944] A means for the server to adjust the tone and messaging of advertising materials based on the results of the sentiment analysis;

[1945] A means for a user to review the generated advertising materials and send correction instructions to the server;

[1946] a means for the server to update the advertising materials based on the correction request from the user and generate the final version of the advertising materials;

[1947] A means for the terminal to provide the final advertising material to the user and allow the user to review and download it;

[1948] A system including:

[1949] (Claim 2)

[1950] 10. The system of claim 1, further comprising means for the server to analyze historical data and current trends to predict market growth patterns and integrate growth market information into strategic portions of advertising materials.

[1951] (Claim 3)

[1952] 10. The system of claim 1, further comprising means for the server to update the content of the advertising materials in real time, providing an environment in which the user can modify the materials at any time based on the latest information. [Explanation of symbols]

[1953] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for a user to input information regarding requirements for creating a proposal document; means for transmitting the input information to a server; A means for the server to analyze input information received from the user and generate initial proposal materials using a generative AI model; A server collects market information in real time from open data sources on the Internet and analyzes it using natural language processing technology. A means for the server to update the content of the proposal materials based on the extracted market information; A means for a user to check the generated proposal material and send correction instructions to the server; a means for the server to update the proposal document based on a correction request from the user and generate a final version of the proposal document; A means for the terminal to provide the final proposal materials to the user and enable the user to review and download them; A system including:

2. 10. The system of claim 1, further comprising means for the server to analyze historical data and current trends to predict market growth patterns and integrate growth market information into the strategy portion of the proposal deck.

3. 2. The system according to claim 1, further comprising means for the server to update the contents of the proposal materials in real time, providing an environment in which the user can revise the materials at any time based on the latest information.

Images