system

Abstract

We provide the system. [Solution] A method for automatically generating a contract based on the entered contract information, A method for checking the legal risks of generated contracts using an AI agent, AI tools for monitoring project schedules and prioritizing tasks, A method for analyzing images of receipts, converting them into text data, and automatically calculating expenses, A means of generating an automated response to customer inquiries, A business management system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Freelancers and small - scale business operators need to efficiently perform a wide range of operations, such as contract management, project schedule adjustment, expense management, and customer response. However, there is a lack of comprehensive systems to support these operations, and there is a problem that more time and labor are spent on individual operations. As a result, the productivity of operations decreases, and there are also situations where potential problems arising from legal risks and inadequacies in expense management cannot be avoided.

Means for Solving the Problems

[0005] The present invention solves the above problems by providing a business management system that includes means for automatically generating contracts based on input contract information, means for checking the legal risks of the generated contracts using an AI agent, means for monitoring project schedules and setting task priorities using AI, means for analyzing receipt images, converting them into text data, and automatically aggregating expenses, and means for generating automatic replies to customer inquiries. With this system, freelancers and small businesses can efficiently manage their work, mitigate legal risks, and properly manage expenses.

[0006] "Contract information" refers to information that includes details such as the conditions, content, duration, and amount between the parties necessary to conclude a contract.

[0007] A "contract" is a legally binding document created based on contractual information, which documents the agreement between the parties involved.

[0008] "Legal risk" refers to the risk of legal problems or lawsuits that may arise in connection with contracts or business operations.

[0009] An "AI agent" is a program that uses artificial intelligence technology to analyze information, make decisions, and assist in problem-solving.

[0010] A "project schedule" is a timeline that outlines the start date, end date, and deadline for each task in a project.

[0011] "Task prioritization" is an indicator that shows the most effective order in which to execute multiple tasks within a project.

[0012] A "receipt" is a document that proves that payment for a transaction was received.

[0013] "Expenses" refer to money spent for business activities and are costs that a company or business operator should bear.

[0014] An "automatic reply" is a response message that is automatically sent in response to a received message or inquiry, with pre-set content.

[0015] A "marketing campaign" is a series of promotional activities planned to increase awareness of a particular product or service and encourage purchases. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

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

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

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

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

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

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

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

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

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0037] This invention is a system designed to solve the diverse business management challenges faced by freelancers and small business owners. This system comprehensively handles contract management, project scheduling, expense management, customer service, and even marketing support.

[0038] In contract management, users input the necessary contract information using a terminal, and the server automatically generates the contract. The server also uses an AI agent to check the legal risks of the generated contract and confirm its safety.

[0039] In project scheduling, users input each project task from their terminal. Based on this information, the server monitors the progress of the tasks and sets priorities using AI. For tasks with approaching deadlines, the server sends reminders to the user.

[0040] In expense management, users scan receipts using their device's camera. The server captures the image data, converts it to text data, and automatically aggregates it to support proper expense management.

[0041] In customer support, the user's device receives inquiries from customers, and the server generates an automated response. If necessary, a chatbot handles customer support, and the server suggests response options.

[0042] For example, when a user starts a new project, they input all related tasks from their terminal. The server receives this information, calculates the optimal order for task progress, and sends notifications as the tasks progress. This entire process allows the user to manage their projects more efficiently.

[0043] Furthermore, in marketing campaigns, the server analyzes customer data and proposes targeted marketing strategies. Campaign text is automatically generated by AI, and the server executes the campaign with user approval. This method allows users to conduct marketing activities efficiently.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user enters contract information using a terminal. They fill in details such as the contracting party, contract amount, and contract period in a form.

[0047] Step 2:

[0048] The terminal sends the entered contract information to the server. This information is then incorporated into the contract management program.

[0049] Step 3:

[0050] The server automatically generates a contract by combining the entered information based on a contract template.

[0051] Step 4:

[0052] The generated contract is analyzed for legal risks by an AI agent on the server. If risks are identified, proposed revisions are generated.

[0053] Step 5:

[0054] The server sends the completed contract to the user's terminal and requests the user to review it. Instructions for revisions are received as needed.

[0055] Step 6:

[0056] Users input project task information from their devices, providing task names, deadlines, priority levels, and other details.

[0057] Step 7:

[0058] The server receives task information and activates a function to monitor progress. It tracks the progress of each task.

[0059] Step 8:

[0060] The server's AI module analyzes task priorities and notifies the user's device of the tasks they should be working on.

[0061] Step 9:

[0062] To manage expense information, users scan receipts with their device's camera and generate image data.

[0063] Step 10:

[0064] The terminal sends scanned images to the server, which analyzes the images, converts them to text, and compiles the expenses.

[0065] Step 11:

[0066] The user receives customer inquiries on their device, the server automatically generates a reply, and sends the suggested response to the user's device.

[0067] Step 12:

[0068] The server analyzes customer data and devises targeted marketing strategies. AI generates campaign text.

[0069] Step 13:

[0070] The server sends the proposed campaign details to the user's device, and after obtaining approval, the marketing campaign is implemented.

[0071] (Example 1)

[0072] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0073] In today's diverse business management landscape, there is a demand for effective contract document creation and progress management, expense processing, customer service, and marketing strategy implementation. However, these tasks are complex, and the lack of efficiency and automation in each process makes it difficult to respond quickly to these challenges.

[0074] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0075] In this invention, the server includes means for automatically generating contract documents based on input business information, artificial intelligence means for analyzing the legal risks of the generated contract documents, artificial intelligence means for monitoring the progress of work and setting work priorities, means for analyzing images of paper documents to convert them into text information and automatically compile expenses, means for generating automatic replies to customer inquiries, and means for automatically generating and proposing targeted marketing strategies based on customer data. As a result, each process of the business is automated, enabling efficient management and rapid response.

[0076] "Business information" is a general term for all data related to contracts, work, expenses, customer service, and marketing activities.

[0077] A "contract document" is a document created to formally record a transaction or agreement.

[0078] "Artificial intelligence tools" refer to technologies that utilize machine learning and data analysis techniques to automatically analyze data and make decisions.

[0079] "Progress status" refers to information indicating the current stage of a project or task.

[0080] "Priority" refers to the criteria used to rearrange tasks and work based on their importance and urgency.

[0081] "Characterization" is the process of recognizing characters from image data and converting them into text data.

[0082] "Automatic aggregation" refers to the process of automating the collection of data based on input data and calculating the total.

[0083] "Automatic reply" is a function that allows the system to send a response to received messages or inquiries based on predefined rules.

[0084] A "target marketing strategy" is a set of policies and plans for efficient marketing activities aimed at a specific customer segment or market.

[0085] This system is designed to effectively solve the diverse business management challenges faced by freelancers and small business owners. To implement the invention, a network-connected server and user-operated terminals are required.

[0086] The server is equipped with high-performance computing power and AI models to perform key business processes. These AI models are used for automatically generating contract documents, analyzing legal risks, monitoring and prioritizing tasks, managing expenses, automatically responding to inquiries, and proposing marketing strategies.

[0087] The terminal provides an interface for users to input business information. This allows users to easily input contract information, project tasks, expense information, and more. By utilizing the terminal's camera function, it is also possible to easily scan and digitize paper receipts.

[0088] Users can initiate the necessary processing on the server side by entering a prompt into the system, such as, "I would like to create a contract for a new project. Please use the following conditions: (details of conditions)." In response to this prompt, the system selects an appropriate contract template and automatically generates the contract. The generated contract is then analyzed for legal risks by an AI agent.

[0089] Furthermore, in marketing activities, prompts such as "Please propose a marketing campaign for our new product. The target customer segment is: (details of the customer segment)" can be used to allow the server to analyze customer data and propose an efficient campaign strategy.

[0090] This system allows users to automate many business programs, enabling them to manage their operations effectively and efficiently. In this way, the aim is to improve the overall efficiency of business management and reduce the workload on users.

[0091] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0092] Step 1:

[0093] Users use terminals to input information related to their work. For example, when entering contract information, they meticulously enter details such as the contractor's name, contract amount, and contract period into the terminal. The entered data is then transmitted to the server via the network.

[0094] Step 2:

[0095] The server automatically generates contract documents based on the received business information. Using a generation AI model, the server creates the contract by embedding data into a pre-configured contract template. The contract generated through this process is output as a formatted digital document.

[0096] Step 3:

[0097] The server utilizes an AI agent to check the legal risks of the generated contracts. It analyzes the contract content to verify that there are no legal issues. This analysis includes cross-referencing with a legal database, and the results are output as a risk assessment report.

[0098] Step 4:

[0099] Users use their device's scheduling function to enter each task in the project. After entering the task name, start date, end date, and required resources, this information is also sent to the server.

[0100] Step 5:

[0101] The server monitors the progress of project tasks and uses AI to prioritize them. The server analyzes data for each task and determines priorities based on urgency and importance. As a result of this data processing, priority information is notified to the user's device.

[0102] Step 6:

[0103] The server monitors project task deadlines and generates reminders for tasks approaching their due dates. This allows users to receive timely notifications about tasks with approaching deadlines. Notifications are sent via email or as app notifications on the device.

[0104] Step 7:

[0105] The user uses their device's camera to scan the receipt and sends the image data to the server. The server reads this data using OCR technology and converts the contents of the document into text data.

[0106] Step 8:

[0107] The server analyzes the text data obtained by OCR and automatically aggregates expenses. Based on the expense information stored in the database, it classifies the data by category and outputs the aggregated results to the user as a monthly report.

[0108] Step 9:

[0109] When a user's device receives an inquiry from a customer, it sends the data to the server. The server uses AI to analyze the inquiry and generate an appropriate automated response.

[0110] Step 10:

[0111] The server analyzes customer data and devises targeted marketing strategies. This process involves clustering based on purchase history and behavioral patterns to propose the most suitable campaign. The proposed campaign is reviewed and approved by the user before being implemented.

[0112] (Application Example 1)

[0113] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0114] For freelancers and small businesses, managing operations has become increasingly complex, making efficient business operations difficult. For these businesses, individually managing diverse tasks such as contract management, project scheduling, expense management, customer service, and marketing support is a significant burden. To address this challenge, a system that integrates and manages these functions is necessary.

[0115] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0116] In this invention, the server includes means for automatically generating a contract based on input contract information, means for checking the legal risks of the generated contract using an intelligent agent, and intelligent means for tracking the progress of work and setting work priorities. This enables freelancers and small business owners to efficiently manage multiple tasks and improve the productivity and accuracy of their work.

[0117] "Contract information" refers to data related to contracts that a business enters into with its business partners, employees, etc., and is necessary when creating contract documents.

[0118] An "intelligent agent" is a program that uses artificial intelligence technology to automatically perform specific tasks, and is used for evaluating the legal risks of contracts and generating proposals.

[0119] "Work progress" refers to information indicating the current stage of a task in a project or business, and is important for efficient schedule management.

[0120] "Task prioritization" refers to the criteria used to assess the importance and urgency of multiple ongoing tasks and determine the order in which they should be performed.

[0121] "Textual information" refers to text data extracted from image data, which is useful for expense management and digital processing of forms.

[0122] "User inquiries" refer to communications where customers or clients seek information about products or services or request solutions to problems.

[0123] A "commercial strategy" is a set of marketing activities and campaigns designed to analyze customer behavior and market trends and drive business growth.

[0124] A "notification" is a means of communication used to convey important business information to relevant parties, and is useful for improving work efficiency and information sharing.

[0125] This invention provides a platform for centrally managing contracts, scheduling, expense management, customer service, and marketing support as a business management system. Specific embodiments of this system are described below.

[0126] The server provides core functions for managing various types of business information. When contract information is entered, the server executes an automated generation program to generate the contract. Furthermore, an intelligent agent checks the legal risks of the contract using a generation AI model. In project scheduling, the server monitors progress based on task information entered by the user and sets task priorities using intelligent means.

[0127] For expense management, users upload receipts as images using their smartphone cameras. The server converts these images into text information and automatically performs aggregation. The technology used for text extraction is the Google® Cloud Vision API. For customer support, the server generates an automated response whenever the user's device receives an inquiry from a customer. This response is generated by an AI model based on predefined prompt phrases.

[0128] In marketing support, the server analyzes customer data and automatically generates and proposes commercial strategies. For this purpose, it utilizes Python's pandas and scikit-learn as data analysis techniques. The proposed commercial strategies are implemented after user approval. This entire process allows the server to manage multiple business functions simultaneously, significantly improving the operational efficiency of freelancers and small businesses.

[0129] As a concrete example, when launching a new commercial campaign, the server analyzes past sales data and automatically suggests the most effective strategy. Then, based on the generated prompt, it automatically generates the campaign text. An example of this automatically generated prompt could be: "Based on this month's sales data, please suggest the most effective measures for the next promotion."

[0130] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0131] Step 1:

[0132] The user enters contract information and sends it to the server. This input includes detailed information such as the name of the contracting party and the contract details. Based on this input data, the server runs a program that automatically generates a contract and outputs a draft of the contract. A template is used to generate the contract, and the input information is filled in to create a document that conforms to the format.

[0133] Step 2:

[0134] The server passes the generated contract to an intelligent agent for security verification. The entire contract is provided to the AI ​​agent as input. The intelligent agent uses a generation AI model to evaluate the legal risks and points out any problematic areas. This result is output as a risk assessment report and returned to the user.

[0135] Step 3:

[0136] The user inputs project task information and sends it from their terminal to the server. The server analyzes the progress of each task based on this data and sets priorities. A schedule management algorithm is used to process this input data and output the optimal schedule. A list of prioritized tasks is output and displayed to the user.

[0137] Step 4:

[0138] The user scans a receipt using their smartphone camera and uploads the image data to the server. The server converts the image into text data via the Google Cloud Vision API. By analyzing this input image, the date, amount, and breakdown of the expenditure are extracted, and based on this, the expenditure record is automatically compiled and an expense report is generated.

[0139] Step 5:

[0140] The terminal receives an inquiry from a customer and sends the inquiry details to the server. Based on this information, the server uses a generation AI model to automatically generate a reply message according to the prompts. Utilizing the input inquiry and related prompts, an appropriate reply is output and sent to the customer.

[0141] Step 6:

[0142] The server collects historical customer data and performs analysis based on it to generate commercial strategies. Using sales history and customer attribute information as input data, it applies data analysis methods to output the optimal promotional strategy. This strategy is then proposed to the user and implemented after approval.

[0143] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0144] This invention aims to integrate an emotion engine into a business management system for freelancers and small businesses to recognize users' emotional states and provide more personalized responses. In addition to contract management, project scheduling, expense management, and customer support, this system includes functions to improve business efficiency by recognizing users' emotions.

[0145] This system has a function that automatically generates contracts on the server based on contract information entered via a terminal. The generated contracts are checked for legal risks by an AI agent on the server to ensure their safety. In the project schedule, the server monitors tasks entered by the user, and the AI ​​sets priorities. In particular, when the user's emotional state influences decisions, the emotion engine adjusts priorities and schedules.

[0146] The user's device scans receipts and sends the image data to the server. The server analyzes this data and aggregates it into necessary text, streamlining expense management. Furthermore, in customer support, the server receives customer inquiries and generates automated replies. This is where the emotion engine comes in, selecting responses that are appropriate to the user's or customer's emotions.

[0147] As an example, if a user is experiencing stress, the emotion engine can detect this and re-evaluate the task priorities. Similarly, if a customer is dissatisfied, the emotion engine can automatically generate a more polite response from the server, communicating in a way that soothes the customer's emotions. In this way, the introduction of an emotion engine can improve the quality of business management and enhance user and customer satisfaction.

[0148] The following describes the processing flow.

[0149] Step 1:

[0150] The user uses a terminal to enter contract information and begin creating the contract. The contract details include information such as the business partner, agreed terms, and submission deadline.

[0151] Step 2:

[0152] The terminal sends the entered contract information to the server. The server automatically generates a contract based on that information and constructs the document using a template.

[0153] Step 3:

[0154] The server uses an AI agent to check the legal risks of automatically generated contracts. The AI ​​agent identifies potential risks and generates suggestions as needed.

[0155] Step 4:

[0156] The device analyzes the user's emotional state through an emotion engine. The emotion engine infers the emotional state based on factors such as the user's voice tone and input speed.

[0157] Step 5:

[0158] The server receives the results analyzed by the emotion engine and adjusts priorities and procedures in the contract process. In particular, it adjusts notifications and reminders if the user is experiencing stress.

[0159] Step 6:

[0160] The user inputs information for each project task on their device. The server creates a schedule based on this data, and the AI ​​sets the task priorities.

[0161] Step 7:

[0162] The server dynamically changes task priorities while considering the user's emotions. This action helps the user maintain focus.

[0163] Step 8:

[0164] For expense management, users scan receipts with their device's camera, and the device sends the image to a server. The server analyzes the image and automatically compiles expense items.

[0165] Step 9:

[0166] When a customer inquiry is received on a terminal, the server generates an automated response. The emotion engine analyzes the customer's emotional state and adjusts the response accordingly.

[0167] Step 10:

[0168] Based on the analysis results from the emotion engine, the server creates personalized follow-ups for customers and develops content to improve the quality of service.

[0169] (Example 2)

[0170] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0171] Freelancers and small business owners often face inefficiencies due to the significant amount of manual work required for business management. Furthermore, accurately understanding and appropriately responding to the nuances of customer emotions is challenging. In addition, integrated management and utilization of individual business data is difficult, highlighting the need for increased productivity and improved customer satisfaction.

[0172] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0173] This invention includes a server that automatically generates contract documents based on input contract information, a means for evaluating the legal risks of the generated contract documents using an artificial intelligence agent, and a means for monitoring project schedules, setting work priorities, and adjusting them according to the user's emotional state using an emotion recognition engine. This enables more efficient business management, improved customer service quality, and increased user and customer satisfaction.

[0174] A "contract document" is a written document that formally records the terms and conditions of a transaction or agreement, and has legal effect.

[0175] An "artificial intelligence agent" is a program that autonomously learns knowledge and solves specific tasks or problems.

[0176] A "project schedule" is a plan that outlines the work schedule from the start to the end of a project.

[0177] "Task prioritization" refers to the criteria used to determine which tasks should be handled first when performing work.

[0178] An "emotion recognition engine" is a program that has the function of analyzing and recognizing a person's emotional state.

[0179] "Expenses" refer to the economic expenditures necessary for business activities.

[0180] "Customer inquiries" refer to questions and requests sent by customers seeking information or support regarding products or services.

[0181] An "automatic reply" is a response message that a system automatically generates and sends based on specific conditions or triggers.

[0182] This invention is a system designed for freelancers and small businesses to streamline work management and improve the quality of their work. The system includes contract information management, project scheduling, expense management, customer support, and sentiment recognition.

[0183] First, the user enters contract information using a terminal. This information is sent to a server, which automatically generates a contract document based on it. A generation AI model is used for the automatic generation of the contract, which creates a standard contract template. The generated contract is then evaluated for legal risks by an artificial intelligence agent on the server. This ensures that a legally secure contract document is provided.

[0184] In project management, tasks entered by users via terminals are recorded on a server. The server incorporates an emotion recognition engine and monitors the project schedule. Based on the user's emotional state, the server automatically adjusts task priorities. This reduces user stress and enables efficient schedule management.

[0185] Regarding expense management, users scan receipts using their devices and send the images to the server. The received image data is analyzed by the server, and text information is extracted. This allows for automatic expense aggregation and efficient accounting processing.

[0186] In customer support, customer inquiries are sent to a server. The server uses an emotion recognition engine to analyze the customer's emotional state and generates an automated response. This enables responses that are appropriate to the customer's emotions, which is expected to improve customer satisfaction.

[0187] For example, a prompt for responding to a user feeling anxious about their work might be, "If the user is feeling stressed, how should task priorities be adjusted?" Another example prompt for responding to a customer expressing dissatisfaction with a product might be, "Please provide a response that alleviates the customer's dissatisfaction." These prompts are generated using a generative AI model to facilitate the most appropriate response for each situation.

[0188] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0189] Step 1:

[0190] The user enters contract information using a terminal. The user enters details such as the name of the contracting party, the contract details, and the start and end dates into the terminal. The terminal converts this information into a structured data format and sends it to the server.

[0191] Step 2:

[0192] The server receives the entered contract information and automatically generates a contract document using a generation AI model. The server inputs the received data into the model and embeds the information into a standard contract template. The generated contract is stored on the server.

[0193] Step 3:

[0194] The server uses an artificial intelligence agent to assess the legal risks of the generated contract. The agent analyzes the content of the contract and checks whether the legal terminology and conditions are appropriate. The output of this process is a contract document that has been confirmed to be safe.

[0195] Step 4:

[0196] The user enters project-related tasks from their terminal. The user fills in task details and deadlines. The terminal then sends this task information directly to the server.

[0197] Step 5:

[0198] The server receives task information and uses an emotion recognition engine to monitor and adjust the project schedule. The server receives emotion data as input and controls task priorities based on the user's emotional state. The output is the adjusted schedule.

[0199] Step 6:

[0200] The user scans the receipt using the terminal. The terminal takes a picture of the receipt and prepares to send it to the server.

[0201] Step 7:

[0202] The server analyzes the received receipt image and extracts text information. The server processes the data using an image analysis algorithm and converts it into text format. As a result, the expense data is organized and can be automatically aggregated.

[0203] Step 8:

[0204] A customer submits an inquiry about a product or service. The server receives the customer's message and analyzes their emotional state through an emotion recognition engine.

[0205] Step 9:

[0206] The server generates an automated response based on the analysis results. The server then constructs the most appropriate response based on the sentiment analysis and sends it to the customer. This process aims to increase customer satisfaction.

[0207] (Application Example 2)

[0208] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0209] While conventional business management systems contribute to improving operational efficiency in areas such as contract and expense management, they have the challenge of making it difficult to provide personalized responses that take into account the emotions of users and customers. In particular, for small businesses and households, providing appropriate responses that address individual emotional states is crucial for improving the quality of work and daily life.

[0210] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0211] In this invention, the server includes means for automatically generating contracts based on input contract data, means for checking the legal risks of the generated contracts using an AI agent, AI means for monitoring work schedules and setting task priorities, means for analyzing receipt images and converting them into text data to automatically aggregate expenses, means for generating automatic replies to customer inquiries, means for recognizing the user's emotional state and adjusting schedules and priorities based on those emotions, means for managing household tasks and adjusting task priorities based on the individual's emotional state, and means for analyzing visitors' emotions and adjusting responses to visitors. This makes it possible to manage work and household tasks more efficiently and effectively according to individual emotional states.

[0212] "Contract data" refers to information related to business contracts, and is the input information necessary for creating a contract.

[0213] "Automatic contract generation method" refers to a technology that has the function of automatically creating a contract based on input contract data.

[0214] The "legal risk check mechanism" is a function that uses an AI agent to verify the legal risks of generated contracts.

[0215] A "work schedule monitoring tool" is a function that observes and tracks time management related to projects and tasks, and uses that information to enable efficient management.

[0216] "Priority setting AI means" refers to a function that uses artificial intelligence to optimize the execution order of tasks according to their importance and urgency.

[0217] A "receipt analysis method" is a technology that extracts text information from images of paper or electronic receipts and converts it into text data that can be used for subsequent processing.

[0218] The "automatic expense aggregation method" is a function that automatically aggregates expenses based on analyzed receipt data, thereby supporting financial management.

[0219] An "automatic reply generation method" is a technology that automatically generates replies to customer inquiries, enabling timely and efficient customer service.

[0220] "Emotional state recognition means" refers to technology for analyzing the emotions of a user or customer and providing information based on those emotions.

[0221] "Household task management tools" are technologies that provide the functionality to manage schedules and resources in order to effectively plan and execute various tasks within the household.

[0222] "Visitor emotion analysis tools" are technologies that evaluate and analyze visitors' emotions and take appropriate action based on the results.

[0223] This invention realizes a system that recognizes the user's emotional state and provides personalized support for work management and household tasks. By utilizing data communication between the server and terminal and AI, it enables effective work management.

[0224] The server receives contract data and automatically generates contracts based on it. The generated contracts have a function to check legal risks using an AI agent. Furthermore, it monitors the work schedule and sets task priorities using AI. This AI analyzes the user's emotional state using an emotion recognition library developed in Python. The terminal processes images acquired by smartphones or home robot cameras, recognizes the user's emotions, and sends them to the server.

[0225] Receipts are scanned at the terminal, and the image data is sent to the server. The server analyzes the image data, converts it into the necessary text data, and automatically calculates expenses. When there is a customer inquiry, the server generates an automated reply, but here again, the sentiment engine comes into play, adjusting the reply based on the user's or customer's emotions. By also performing sentiment analysis of visitors, it optimizes how you handle visitors in your home.

[0226] For example, a server can analyze a user's stress levels and reduce their workload by readjusting important tasks. Furthermore, within a home, it's possible to analyze whether a visitor is relaxed and suggest appropriate hospitality. An example of a prompt for a generative AI model might be, "Classify the user's emotions into anger, sadness, and joy, and consider appropriate responses for each."

[0227] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0228] Step 1:

[0229] The device recognizes the user's emotions and sends them to the server as image data. The user's facial expressions are read through the camera of their smartphone or a robot, and the images are analyzed in real time. An emotion recognition library is used to process the image data and generate emotional state data. The generated emotional state data is then sent to the server.

[0230] Step 2:

[0231] The server analyzes the received emotional state data and re-evaluates task priorities. Based on the input emotional state data, the AI ​​calculates the importance of work tasks, taking emotional impact into account, and adjusts the schedule accordingly. The output is a task list with adjusted priorities.

[0232] Step 3:

[0233] The terminal scans expense-related receipts and sends them to the server as image data. The user scans the receipts, and the resulting image data is transferred to the server. The server uses OCR technology to convert the images into text data and extracts and aggregates expense items. The output is an aggregated expense list.

[0234] Step 4:

[0235] When the server receives a customer inquiry, it generates an automated response. When a user submits an inquiry, an AI agent analyzes the content and generates an appropriate response. The emotion engine adjusts the wording according to the user's emotional state, enabling a personalized response. The output is the automated response message.

[0236] Step 5:

[0237] The server analyzes the visitor's emotions and determines how to respond within the home. If there is a visitor at the user's home, the facial expression images captured by the device are analyzed. Based on a generated AI model, the visitor's emotions are classified, and information is generated and provided to suggest appropriate hospitality. The output is the suggested hospitality plan.

[0238] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0239] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0240] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0241] [Second Embodiment]

[0242] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0243] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0244] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0245] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0246] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0247] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0248] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0249] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0250] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0251] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0252] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0253] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0254] This invention is a system designed to solve the diverse business management challenges faced by freelancers and small business owners. This system comprehensively handles contract management, project scheduling, expense management, customer service, and even marketing support.

[0255] In contract management, users input the necessary contract information using a terminal, and the server automatically generates the contract. The server also uses an AI agent to check the legal risks of the generated contract and confirm its safety.

[0256] In project scheduling, users input each project task from their terminal. Based on this information, the server monitors the progress of the tasks and sets priorities using AI. For tasks with approaching deadlines, the server sends reminders to the user.

[0257] In expense management, users scan receipts using their device's camera. The server captures the image data, converts it to text data, and automatically aggregates it to support proper expense management.

[0258] In customer support, the user's device receives inquiries from customers, and the server generates an automated response. If necessary, a chatbot handles customer support, and the server suggests response options.

[0259] For example, when a user starts a new project, they input all related tasks from their terminal. The server receives this information, calculates the optimal order for task progress, and sends notifications as the tasks progress. This entire process allows the user to manage their projects more efficiently.

[0260] Furthermore, in marketing campaigns, the server analyzes customer data and proposes targeted marketing strategies. Campaign text is automatically generated by AI, and the server executes the campaign with user approval. This method allows users to conduct marketing activities efficiently.

[0261] The following describes the processing flow.

[0262] Step 1:

[0263] The user enters contract information using a terminal. They fill in details such as the contracting party, contract amount, and contract period in a form.

[0264] Step 2:

[0265] The terminal sends the entered contract information to the server. This information is then incorporated into the contract management program.

[0266] Step 3:

[0267] The server automatically generates a contract by combining the entered information based on a contract template.

[0268] Step 4:

[0269] The generated contract is analyzed for legal risks by an AI agent on the server. If risks are identified, proposed revisions are generated.

[0270] Step 5:

[0271] The server sends the completed contract to the user's terminal and requests the user to review it. Instructions for revisions are received as needed.

[0272] Step 6:

[0273] Users input project task information from their devices, providing task names, deadlines, priority levels, and other details.

[0274] Step 7:

[0275] The server receives task information and activates a function to monitor progress. It tracks the progress of each task.

[0276] Step 8:

[0277] The server's AI module analyzes task priorities and notifies the user's device of the tasks they should be working on.

[0278] Step 9:

[0279] To manage expense information, users scan receipts with their device's camera and generate image data.

[0280] Step 10:

[0281] The terminal sends the scanned image to the server, and the server analyzes the image, converts it into text, and aggregates the expenses.

[0282] Step 11:

[0283] The user receives an inquiry from a customer on the terminal, and the server creates an automatic reply and sends the proposed reply to the terminal.

[0284] Step 12:

[0285] The server analyzes customer data and devises a target marketing strategy. The content of the campaign is generated by AI.

[0286] Step 13:

[0287] The server sends the content of the proposed campaign to the terminal. After obtaining approval, it implements the marketing campaign.

[0288] (Example 1)

[0289] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0290] In modern diverse business management, effective creation of contract documents, management of progress, expense processing, customer response, and implementation of marketing strategies are required. However, these operations are complex, and since the efficiency and automation of each process have not been achieved, there is a problem that it is difficult to respond quickly to business.

[0291] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0292] In this invention, the server includes means for automatically generating contract documents based on input business information, artificial intelligence means for analyzing the legal risks of the generated contract documents, artificial intelligence means for monitoring the progress of work and setting work priorities, means for analyzing images of paper documents to convert them into text information and automatically compile expenses, means for generating automatic replies to customer inquiries, and means for automatically generating and proposing targeted marketing strategies based on customer data. As a result, each process of the business is automated, enabling efficient management and rapid response.

[0293] "Business information" is a general term for all data related to contracts, work, expenses, customer service, and marketing activities.

[0294] A "contract document" is a document created to formally record a transaction or agreement.

[0295] "Artificial intelligence tools" refer to technologies that utilize machine learning and data analysis techniques to automatically analyze data and make decisions.

[0296] "Progress status" refers to information indicating the current stage of a project or task.

[0297] "Priority" refers to the criteria used to rearrange tasks and work based on their importance and urgency.

[0298] "Characterization" is the process of recognizing characters from image data and converting them into text data.

[0299] "Automatic aggregation" refers to the process of automating the collection of data based on input data and calculating the total.

[0300] "Automatic reply" is a function that allows the system to send a response to received messages or inquiries based on predefined rules.

[0301] A "target marketing strategy" is a set of policies and plans for efficient marketing activities aimed at a specific customer segment or market.

[0302] This system is designed to effectively solve the diverse business management challenges faced by freelancers and small business owners. To implement the invention, a network-connected server and user-operated terminals are required.

[0303] The server is equipped with high-performance computing power and AI models to perform key business processes. These AI models are used for automatically generating contract documents, analyzing legal risks, monitoring and prioritizing tasks, managing expenses, automatically responding to inquiries, and proposing marketing strategies.

[0304] The terminal provides an interface for users to input business information. This allows users to easily input contract information, project tasks, expense information, and more. By utilizing the terminal's camera function, it is also possible to easily scan and digitize paper receipts.

[0305] Users can initiate the necessary processing on the server side by entering a prompt into the system, such as, "I would like to create a contract for a new project. Please use the following conditions: (details of conditions)." In response to this prompt, the system selects an appropriate contract template and automatically generates the contract. The generated contract is then analyzed for legal risks by an AI agent.

[0306] Furthermore, in marketing activities, prompts such as "Please propose a marketing campaign for our new product. The target customer segment is: (details of the customer segment)" can be used to allow the server to analyze customer data and propose an efficient campaign strategy.

[0307] With this system, users can automatically process many business programs and manage their businesses effectively and efficiently. The aim is to improve the overall efficiency of business management and reduce the users' business burden in this way.

[0308] The flow of the specific process in Example 1 will be described using FIG. 11.

[0309] Step 1:

[0310] The user uses a terminal to input information related to the business. For example, when inputting contract information, details such as the contractor name, contract amount, and contract period are entered into the terminal. The input data is sent to the server via the network.

[0311] Step 2:

[0312] The server automatically generates a contract document based on the received business information. The server uses a generation AI model to create a contract document by embedding data into a pre-set contract template. The contract document generated in this process is output as a formatted digital document.

[0313] Step 3:

[0314] The server utilizes an AI agent to check the legal risks of the generated contract document. It analyzes the content of the contract document to confirm whether there are any legal issues. This analysis includes comparison with a legal database, and the result is output as a risk assessment report.

[0315] Step 4:

[0316] The user uses the scheduling function of the terminal to input each task of the project. After inputting the task name, start date, end date, and required resources, this information is also sent to the server.

[0317] Step 5:

[0318] The server monitors the progress of project tasks and uses AI to prioritize them. The server analyzes data for each task and determines priorities based on urgency and importance. As a result of this data processing, priority information is notified to the user's device.

[0319] Step 6:

[0320] The server monitors project task deadlines and generates reminders for tasks approaching their due dates. This allows users to receive timely notifications about tasks with approaching deadlines. Notifications are sent via email or as app notifications on the device.

[0321] Step 7:

[0322] The user uses their device's camera to scan the receipt and sends the image data to the server. The server reads this data using OCR technology and converts the contents of the document into text data.

[0323] Step 8:

[0324] The server analyzes the text data obtained by OCR and automatically aggregates expenses. Based on the expense information stored in the database, it classifies the data by category and outputs the aggregated results to the user as a monthly report.

[0325] Step 9:

[0326] When a user's device receives an inquiry from a customer, it sends the data to the server. The server uses AI to analyze the inquiry and generate an appropriate automated response.

[0327] Step 10:

[0328] The server analyzes customer data and devises targeted marketing strategies. This process involves clustering based on purchase history and behavioral patterns to propose the most suitable campaign. The proposed campaign is reviewed and approved by the user before being implemented.

[0329] (Application Example 1)

[0330] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0331] For freelancers and small businesses, managing operations has become increasingly complex, making efficient business operations difficult. For these businesses, individually managing diverse tasks such as contract management, project scheduling, expense management, customer service, and marketing support is a significant burden. To address this challenge, a system that integrates and manages these functions is necessary.

[0332] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0333] In this invention, the server includes means for automatically generating a contract based on input contract information, means for checking the legal risks of the generated contract using an intelligent agent, and intelligent means for tracking the progress of work and setting work priorities. This enables freelancers and small business owners to efficiently manage multiple tasks and improve the productivity and accuracy of their work.

[0334] "Contract information" refers to data related to contracts that a business enters into with its business partners, employees, etc., and is necessary when creating contract documents.

[0335] An "intelligent agent" is a program that uses artificial intelligence technology to automatically perform specific tasks, and is used for evaluating the legal risks of contracts and generating proposals.

[0336] "Work progress" refers to information indicating the current stage of a task in a project or business, and is important for efficient schedule management.

[0337] "Task prioritization" refers to the criteria used to assess the importance and urgency of multiple ongoing tasks and determine the order in which they should be performed.

[0338] "Textual information" refers to text data extracted from image data, which is useful for expense management and digital processing of forms.

[0339] "User inquiries" refer to communications where customers or clients seek information about products or services or request solutions to problems.

[0340] A "commercial strategy" is a set of marketing activities and campaigns designed to analyze customer behavior and market trends and drive business growth.

[0341] A "notification" is a means of communication used to convey important business information to relevant parties, and is useful for improving work efficiency and information sharing.

[0342] This invention provides a platform for centrally managing contracts, scheduling, expense management, customer service, and marketing support as a business management system. Specific embodiments of this system are described below.

[0343] The server provides core functions for managing various types of business information. When contract information is entered, the server executes an automated generation program to generate the contract. Furthermore, an intelligent agent checks the legal risks of the contract using a generation AI model. In project scheduling, the server monitors progress based on task information entered by the user and sets task priorities using intelligent means.

[0344] For expense management, users upload receipts as images using their smartphone cameras. The server converts these images into text information and automatically performs aggregation. The technology used is the Google Cloud Vision API for text extraction. For customer support, the server generates an automated response whenever the user's device receives an inquiry from a customer. This response is generated by a generation AI model based on predefined prompt phrases.

[0345] In marketing support, the server analyzes customer data and automatically generates and proposes commercial strategies. For this purpose, it utilizes Python's pandas and scikit-learn as data analysis techniques. The proposed commercial strategies are implemented after user approval. This entire process allows the server to manage multiple business functions simultaneously, significantly improving the operational efficiency of freelancers and small businesses.

[0346] As a concrete example, when launching a new commercial campaign, the server analyzes past sales data and automatically suggests the most effective strategy. Then, based on the generated prompt, it automatically generates the campaign text. An example of this automatically generated prompt could be: "Based on this month's sales data, please suggest the most effective measures for the next promotion."

[0347] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0348] Step 1:

[0349] The user enters contract information and sends it to the server. This input includes detailed information such as the name of the contracting party and the contract details. Based on this input data, the server runs a program that automatically generates a contract and outputs a draft of the contract. A template is used to generate the contract, and the input information is filled in to create a document that conforms to the format.

[0350] Step 2:

[0351] The server passes the generated contract to an intelligent agent for security verification. The entire contract is provided to the AI ​​agent as input. The intelligent agent uses a generation AI model to evaluate the legal risks and points out any problematic areas. This result is output as a risk assessment report and returned to the user.

[0352] Step 3:

[0353] The user inputs project task information and sends it from their terminal to the server. The server analyzes the progress of each task based on this data and sets priorities. A schedule management algorithm is used to process this input data and output the optimal schedule. A list of prioritized tasks is output and displayed to the user.

[0354] Step 4:

[0355] The user scans a receipt using their smartphone camera and uploads the image data to the server. The server converts the image into text data via the Google Cloud Vision API. By analyzing this input image, the date, amount, and breakdown of the expenditure are extracted, and based on this, the expenditure record is automatically compiled and an expense report is generated.

[0356] Step 5:

[0357] The terminal receives an inquiry from a customer and sends the inquiry details to the server. Based on this information, the server uses a generation AI model to automatically generate a reply message according to the prompts. Utilizing the input inquiry and related prompts, an appropriate reply is output and sent to the customer.

[0358] Step 6:

[0359] The server collects historical customer data and performs analysis based on it to generate commercial strategies. Using sales history and customer attribute information as input data, it applies data analysis methods to output the optimal promotional strategy. This strategy is then proposed to the user and implemented after approval.

[0360] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0361] This invention aims to integrate an emotion engine into a business management system for freelancers and small businesses to recognize users' emotional states and provide more personalized responses. In addition to contract management, project scheduling, expense management, and customer support, this system includes functions to improve business efficiency by recognizing users' emotions.

[0362] This system has a function that automatically generates contracts on the server based on contract information entered via a terminal. The generated contracts are checked for legal risks by an AI agent on the server to ensure their safety. In the project schedule, the server monitors tasks entered by the user, and the AI ​​sets priorities. In particular, when the user's emotional state influences decisions, the emotion engine adjusts priorities and schedules.

[0363] The user's device scans receipts and sends the image data to the server. The server analyzes this data and aggregates it into necessary text, streamlining expense management. Furthermore, in customer support, the server receives customer inquiries and generates automated replies. This is where the emotion engine comes in, selecting responses that are appropriate to the user's or customer's emotions.

[0364] As an example, if a user is experiencing stress, the emotion engine can detect this and re-evaluate the task priorities. Similarly, if a customer is dissatisfied, the emotion engine can automatically generate a more polite response from the server, communicating in a way that soothes the customer's emotions. In this way, the introduction of an emotion engine can improve the quality of business management and enhance user and customer satisfaction.

[0365] The following describes the processing flow.

[0366] Step 1:

[0367] The user uses a terminal to enter contract information and begin creating the contract. The contract details include information such as the business partner, agreed terms, and submission deadline.

[0368] Step 2:

[0369] The terminal sends the entered contract information to the server. The server automatically generates a contract based on that information and constructs the document using a template.

[0370] Step 3:

[0371] The server uses an AI agent to check the legal risks of automatically generated contracts. The AI ​​agent identifies potential risks and generates suggestions as needed.

[0372] Step 4:

[0373] The device analyzes the user's emotional state through an emotion engine. The emotion engine infers the emotional state based on factors such as the user's voice tone and input speed.

[0374] Step 5:

[0375] The server receives the results analyzed by the emotion engine and adjusts priorities and procedures in the contract process. In particular, it adjusts notifications and reminders if the user is experiencing stress.

[0376] Step 6:

[0377] The user inputs information for each project task on their device. The server creates a schedule based on this data, and the AI ​​sets the task priorities.

[0378] Step 7:

[0379] The server dynamically changes task priorities while considering the user's emotions. This action helps the user maintain focus.

[0380] Step 8:

[0381] For expense management, users scan receipts with their device's camera, and the device sends the image to a server. The server analyzes the image and automatically compiles expense items.

[0382] Step 9:

[0383] When a customer inquiry is received on a terminal, the server generates an automated response. The emotion engine analyzes the customer's emotional state and adjusts the response accordingly.

[0384] Step 10:

[0385] Based on the analysis results from the emotion engine, the server creates personalized follow-ups for customers and develops content to improve the quality of service.

[0386] (Example 2)

[0387] Next, we will describe Example 2. 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".

[0388] Freelancers and small business owners often face inefficiencies due to the significant amount of manual work required for business management. Furthermore, accurately understanding and appropriately responding to the nuances of customer emotions is challenging. In addition, integrated management and utilization of individual business data is difficult, highlighting the need for increased productivity and improved customer satisfaction.

[0389] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0390] This invention includes a server that automatically generates contract documents based on input contract information, a means for evaluating the legal risks of the generated contract documents using an artificial intelligence agent, and a means for monitoring project schedules, setting work priorities, and adjusting them according to the user's emotional state using an emotion recognition engine. This enables more efficient business management, improved customer service quality, and increased user and customer satisfaction.

[0391] A "contract document" is a written document that formally records the terms and conditions of a transaction or agreement, and has legal effect.

[0392] An "artificial intelligence agent" is a program that autonomously learns knowledge and solves specific tasks or problems.

[0393] A "project schedule" is a plan that outlines the work schedule from the start to the end of a project.

[0394] "Task prioritization" refers to the criteria used to determine which tasks should be handled first when performing work.

[0395] An "emotion recognition engine" is a program that has the function of analyzing and recognizing a person's emotional state.

[0396] "Expenses" refer to the economic expenditures necessary for business activities.

[0397] "Customer inquiries" refer to questions and requests sent by customers seeking information or support regarding products or services.

[0398] An "automatic reply" is a response message that a system automatically generates and sends based on specific conditions or triggers.

[0399] This invention is a system designed for freelancers and small businesses to streamline work management and improve the quality of their work. The system includes contract information management, project scheduling, expense management, customer support, and sentiment recognition.

[0400] First, the user enters contract information using a terminal. This information is sent to a server, which automatically generates a contract document based on it. A generation AI model is used for the automatic generation of the contract, which creates a standard contract template. The generated contract is then evaluated for legal risks by an artificial intelligence agent on the server. This ensures that a legally secure contract document is provided.

[0401] In project management, tasks entered by users via terminals are recorded on a server. The server incorporates an emotion recognition engine and monitors the project schedule. Based on the user's emotional state, the server automatically adjusts task priorities. This reduces user stress and enables efficient schedule management.

[0402] Regarding expense management, users scan receipts using their devices and send the images to the server. The received image data is analyzed by the server, and text information is extracted. This allows for automatic expense aggregation and efficient accounting processing.

[0403] In customer support, customer inquiries are sent to a server. The server uses an emotion recognition engine to analyze the customer's emotional state and generates an automated response. This enables responses that are appropriate to the customer's emotions, which is expected to improve customer satisfaction.

[0404] For example, a prompt for responding to a user feeling anxious about their work might be, "If the user is feeling stressed, how should task priorities be adjusted?" Another example prompt for responding to a customer expressing dissatisfaction with a product might be, "Please provide a response that alleviates the customer's dissatisfaction." These prompts are generated using a generative AI model to facilitate the most appropriate response for each situation.

[0405] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0406] Step 1:

[0407] The user enters contract information using a terminal. The user enters details such as the name of the contracting party, the contract details, and the start and end dates into the terminal. The terminal converts this information into a structured data format and sends it to the server.

[0408] Step 2:

[0409] The server receives the entered contract information and automatically generates a contract document using a generation AI model. The server inputs the received data into the model and embeds the information into a standard contract template. The generated contract is stored on the server.

[0410] Step 3:

[0411] The server uses an artificial intelligence agent to assess the legal risks of the generated contract. The agent analyzes the content of the contract and checks whether the legal terminology and conditions are appropriate. The output of this process is a contract document that has been confirmed to be safe.

[0412] Step 4:

[0413] The user enters project-related tasks from their terminal. The user fills in task details and deadlines. The terminal then sends this task information directly to the server.

[0414] Step 5:

[0415] The server receives task information and uses an emotion recognition engine to monitor and adjust the project schedule. The server receives emotion data as input and controls task priorities based on the user's emotional state. The output is the adjusted schedule.

[0416] Step 6:

[0417] The user scans the receipt using the terminal. The terminal takes a picture of the receipt and prepares to send it to the server.

[0418] Step 7:

[0419] The server analyzes the received receipt image and extracts text information. The server processes the data using an image analysis algorithm and converts it into text format. As a result, the expense data is organized and can be automatically aggregated.

[0420] Step 8:

[0421] A customer submits an inquiry about a product or service. The server receives the customer's message and analyzes their emotional state through an emotion recognition engine.

[0422] Step 9:

[0423] The server generates an automated response based on the analysis results. The server then constructs the most appropriate response based on the sentiment analysis and sends it to the customer. This process aims to increase customer satisfaction.

[0424] (Application Example 2)

[0425] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0426] While conventional business management systems contribute to improving operational efficiency in areas such as contract and expense management, they have the challenge of making it difficult to provide personalized responses that take into account the emotions of users and customers. In particular, for small businesses and households, providing appropriate responses that address individual emotional states is crucial for improving the quality of work and daily life.

[0427] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0428] In this invention, the server includes means for automatically generating contracts based on input contract data, means for checking the legal risks of the generated contracts using an AI agent, AI means for monitoring work schedules and setting task priorities, means for analyzing receipt images and converting them into text data to automatically aggregate expenses, means for generating automatic replies to customer inquiries, means for recognizing the user's emotional state and adjusting schedules and priorities based on those emotions, means for managing household tasks and adjusting task priorities based on the individual's emotional state, and means for analyzing visitors' emotions and adjusting responses to visitors. This makes it possible to manage work and household tasks more efficiently and effectively according to individual emotional states.

[0429] "Contract data" refers to information related to business contracts, and is the input information necessary for creating a contract.

[0430] "Automatic contract generation method" refers to a technology that has the function of automatically creating a contract based on input contract data.

[0431] The "legal risk check mechanism" is a function that uses an AI agent to verify the legal risks of generated contracts.

[0432] A "work schedule monitoring tool" is a function that observes and tracks time management related to projects and tasks, and uses that information to enable efficient management.

[0433] "Priority setting AI means" refers to a function that uses artificial intelligence to optimize the execution order of tasks according to their importance and urgency.

[0434] A "receipt analysis method" is a technology that extracts text information from images of paper or electronic receipts and converts it into text data that can be used for subsequent processing.

[0435] The "automatic expense aggregation method" is a function that automatically aggregates expenses based on analyzed receipt data, thereby supporting financial management.

[0436] An "automatic reply generation method" is a technology that automatically generates replies to customer inquiries, enabling timely and efficient customer service.

[0437] "Emotional state recognition means" refers to technology for analyzing the emotions of a user or customer and providing information based on those emotions.

[0438] "Household task management tools" are technologies that provide the functionality to manage schedules and resources in order to effectively plan and execute various tasks within the household.

[0439] "Visitor emotion analysis tools" are technologies that evaluate and analyze visitors' emotions and take appropriate action based on the results.

[0440] This invention realizes a system that recognizes the user's emotional state and provides personalized support for work management and household tasks. By utilizing data communication between the server and terminal and AI, it enables effective work management.

[0441] The server receives contract data and automatically generates contracts based on it. The generated contracts have a function to check legal risks using an AI agent. Furthermore, it monitors the work schedule and sets task priorities using AI. This AI analyzes the user's emotional state using an emotion recognition library developed in Python. The terminal processes images acquired by smartphones or home robot cameras, recognizes the user's emotions, and sends them to the server.

[0442] Receipts are scanned at the terminal, and the image data is sent to the server. The server analyzes the image data, converts it into the necessary text data, and automatically calculates expenses. When there is a customer inquiry, the server generates an automated reply, but here again, the sentiment engine comes into play, adjusting the reply based on the user's or customer's emotions. By also performing sentiment analysis of visitors, it optimizes how you handle visitors in your home.

[0443] For example, a server can analyze a user's stress levels and reduce their workload by readjusting important tasks. Furthermore, within a home, it's possible to analyze whether a visitor is relaxed and suggest appropriate hospitality. An example of a prompt for a generative AI model might be, "Classify the user's emotions into anger, sadness, and joy, and consider appropriate responses for each."

[0444] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0445] Step 1:

[0446] The device recognizes the user's emotions and sends them to the server as image data. The user's facial expressions are read through the camera of their smartphone or a robot, and the images are analyzed in real time. An emotion recognition library is used to process the image data and generate emotional state data. The generated emotional state data is then sent to the server.

[0447] Step 2:

[0448] The server analyzes the received emotional state data and re-evaluates task priorities. Based on the input emotional state data, the AI ​​calculates the importance of work tasks, taking emotional impact into account, and adjusts the schedule accordingly. The output is a task list with adjusted priorities.

[0449] Step 3:

[0450] The terminal scans expense-related receipts and sends them to the server as image data. The user scans the receipts, and the resulting image data is transferred to the server. The server uses OCR technology to convert the images into text data and extracts and aggregates expense items. The output is an aggregated expense list.

[0451] Step 4:

[0452] When the server receives a customer inquiry, it generates an automated response. When a user submits an inquiry, an AI agent analyzes the content and generates an appropriate response. The emotion engine adjusts the wording according to the user's emotional state, enabling a personalized response. The output is the automated response message.

[0453] Step 5:

[0454] The server analyzes the visitor's emotions and determines how to respond within the home. If there is a visitor at the user's home, the facial expression images captured by the device are analyzed. Based on a generated AI model, the visitor's emotions are classified, and information is generated and provided to suggest appropriate hospitality. The output is the suggested hospitality plan.

[0455] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0456] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0457] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0458] [Third Embodiment]

[0459] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0460] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0461] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0462] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0463] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0464] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0465] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0466] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0467] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0468] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0469] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0470] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0471] This invention is a system designed to solve the diverse business management challenges faced by freelancers and small business owners. This system comprehensively handles contract management, project scheduling, expense management, customer service, and even marketing support.

[0472] In contract management, users input the necessary contract information using a terminal, and the server automatically generates the contract. The server also uses an AI agent to check the legal risks of the generated contract and confirm its safety.

[0473] In project scheduling, users input each project task from their terminal. Based on this information, the server monitors the progress of the tasks and sets priorities using AI. For tasks with approaching deadlines, the server sends reminders to the user.

[0474] In expense management, users scan receipts using their device's camera. The server captures the image data, converts it to text data, and automatically aggregates it to support proper expense management.

[0475] In customer support, the user's device receives inquiries from customers, and the server generates an automated response. If necessary, a chatbot handles customer support, and the server suggests response options.

[0476] For example, when a user starts a new project, they input all related tasks from their terminal. The server receives this information, calculates the optimal order for task progress, and sends notifications as the tasks progress. This entire process allows the user to manage their projects more efficiently.

[0477] Furthermore, in marketing campaigns, the server analyzes customer data and proposes targeted marketing strategies. Campaign text is automatically generated by AI, and the server executes the campaign with user approval. This method allows users to conduct marketing activities efficiently.

[0478] The following describes the processing flow.

[0479] Step 1:

[0480] The user enters contract information using a terminal. They fill in details such as the contracting party, contract amount, and contract period in a form.

[0481] Step 2:

[0482] The terminal sends the entered contract information to the server. This information is then incorporated into the contract management program.

[0483] Step 3:

[0484] The server automatically generates a contract by combining the entered information based on a contract template.

[0485] Step 4:

[0486] The generated contract is analyzed for legal risks by an AI agent on the server. If risks are identified, proposed revisions are generated.

[0487] Step 5:

[0488] The server sends the completed contract to the user's terminal and requests the user to review it. Instructions for revisions are received as needed.

[0489] Step 6:

[0490] Users input project task information from their devices, providing task names, deadlines, priority levels, and other details.

[0491] Step 7:

[0492] The server receives task information and activates a function to monitor progress. It tracks the progress of each task.

[0493] Step 8:

[0494] The server's AI module analyzes task priorities and notifies the user's device of the tasks they should be working on.

[0495] Step 9:

[0496] To manage expense information, users scan receipts with their device's camera and generate image data.

[0497] Step 10:

[0498] The terminal sends scanned images to the server, which analyzes the images, converts them to text, and compiles the expenses.

[0499] Step 11:

[0500] The user receives customer inquiries on their device, the server automatically generates a reply, and sends the suggested response to the user's device.

[0501] Step 12:

[0502] The server analyzes customer data and devises targeted marketing strategies. AI generates campaign text.

[0503] Step 13:

[0504] The server sends the proposed campaign details to the user's device, and after obtaining approval, the marketing campaign is implemented.

[0505] (Example 1)

[0506] Next, we will describe Example 1. 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."

[0507] In today's diverse business management landscape, there is a demand for effective contract document creation and progress management, expense processing, customer service, and marketing strategy implementation. However, these tasks are complex, and the lack of efficiency and automation in each process makes it difficult to respond quickly to these challenges.

[0508] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0509] In this invention, the server includes means for automatically generating contract documents based on input business information, artificial intelligence means for analyzing the legal risks of the generated contract documents, artificial intelligence means for monitoring the progress of work and setting work priorities, means for analyzing images of paper documents to convert them into text information and automatically compile expenses, means for generating automatic replies to customer inquiries, and means for automatically generating and proposing targeted marketing strategies based on customer data. As a result, each process of the business is automated, enabling efficient management and rapid response.

[0510] "Business information" is a general term for all data related to contracts, work, expenses, customer service, and marketing activities.

[0511] A "contract document" is a document created to formally record a transaction or agreement.

[0512] "Artificial intelligence tools" refer to technologies that utilize machine learning and data analysis techniques to automatically analyze data and make decisions.

[0513] "Progress status" refers to information indicating the current stage of a project or task.

[0514] "Priority" refers to the criteria used to rearrange tasks and work based on their importance and urgency.

[0515] "Characterization" is the process of recognizing characters from image data and converting them into text data.

[0516] "Automatic aggregation" refers to the process of automating the collection of data based on input data and calculating the total.

[0517] "Automatic reply" is a function that allows the system to send a response to received messages or inquiries based on predefined rules.

[0518] A "target marketing strategy" is a set of policies and plans for efficient marketing activities aimed at a specific customer segment or market.

[0519] This system is designed to effectively solve the diverse business management challenges faced by freelancers and small business owners. To implement the invention, a network-connected server and user-operated terminals are required.

[0520] The server is equipped with high-performance computing power and AI models to perform key business processes. These AI models are used for automatically generating contract documents, analyzing legal risks, monitoring and prioritizing tasks, managing expenses, automatically responding to inquiries, and proposing marketing strategies.

[0521] The terminal provides an interface for users to input business information. This allows users to easily input contract information, project tasks, expense information, and more. By utilizing the terminal's camera function, it is also possible to easily scan and digitize paper receipts.

[0522] Users can initiate the necessary processing on the server side by entering a prompt into the system, such as, "I would like to create a contract for a new project. Please use the following conditions: (details of conditions)." In response to this prompt, the system selects an appropriate contract template and automatically generates the contract. The generated contract is then analyzed for legal risks by an AI agent.

[0523] Furthermore, in marketing activities, prompts such as "Please propose a marketing campaign for our new product. The target customer segment is: (details of the customer segment)" can be used to allow the server to analyze customer data and propose an efficient campaign strategy.

[0524] This system allows users to automate many business programs, enabling them to manage their operations effectively and efficiently. In this way, the aim is to improve the overall efficiency of business management and reduce the workload on users.

[0525] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0526] Step 1:

[0527] Users use terminals to input information related to their work. For example, when entering contract information, they meticulously enter details such as the contractor's name, contract amount, and contract period into the terminal. The entered data is then transmitted to the server via the network.

[0528] Step 2:

[0529] The server automatically generates contract documents based on the received business information. Using a generation AI model, the server creates the contract by embedding data into a pre-configured contract template. The contract generated through this process is output as a formatted digital document.

[0530] Step 3:

[0531] The server utilizes an AI agent to check the legal risks of the generated contracts. It analyzes the contract content to verify that there are no legal issues. This analysis includes cross-referencing with a legal database, and the results are output as a risk assessment report.

[0532] Step 4:

[0533] Users use their device's scheduling function to enter each task in the project. After entering the task name, start date, end date, and required resources, this information is also sent to the server.

[0534] Step 5:

[0535] The server monitors the progress of project tasks and uses AI to prioritize them. The server analyzes data for each task and determines priorities based on urgency and importance. As a result of this data processing, priority information is notified to the user's device.

[0536] Step 6:

[0537] The server monitors project task deadlines and generates reminders for tasks approaching their due dates. This allows users to receive timely notifications about tasks with approaching deadlines. Notifications are sent via email or as app notifications on the device.

[0538] Step 7:

[0539] The user uses their device's camera to scan the receipt and sends the image data to the server. The server reads this data using OCR technology and converts the contents of the document into text data.

[0540] Step 8:

[0541] The server analyzes the text data obtained by OCR and automatically aggregates expenses. Based on the expense information stored in the database, it classifies the data by category and outputs the aggregated results to the user as a monthly report.

[0542] Step 9:

[0543] When a user's device receives an inquiry from a customer, it sends the data to the server. The server uses AI to analyze the inquiry and generate an appropriate automated response.

[0544] Step 10:

[0545] The server analyzes customer data and devises targeted marketing strategies. This process involves clustering based on purchase history and behavioral patterns to propose the most suitable campaign. The proposed campaign is reviewed and approved by the user before being implemented.

[0546] (Application Example 1)

[0547] Next, we will explain Application Example 1. In the following explanation, 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."

[0548] For freelancers and small businesses, managing operations has become increasingly complex, making efficient business operations difficult. For these businesses, individually managing diverse tasks such as contract management, project scheduling, expense management, customer service, and marketing support is a significant burden. To address this challenge, a system that integrates and manages these functions is necessary.

[0549] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0550] In this invention, the server includes means for automatically generating a contract based on input contract information, means for checking the legal risks of the generated contract using an intelligent agent, and intelligent means for tracking the progress of work and setting work priorities. This enables freelancers and small business owners to efficiently manage multiple tasks and improve the productivity and accuracy of their work.

[0551] "Contract information" refers to data related to contracts that a business enters into with its business partners, employees, etc., and is necessary when creating contract documents.

[0552] An "intelligent agent" is a program that uses artificial intelligence technology to automatically perform specific tasks, and is used for evaluating the legal risks of contracts and generating proposals.

[0553] "Work progress" refers to information indicating the current stage of a task in a project or business, and is important for efficient schedule management.

[0554] "Task prioritization" refers to the criteria used to assess the importance and urgency of multiple ongoing tasks and determine the order in which they should be performed.

[0555] "Textual information" refers to text data extracted from image data, which is useful for expense management and digital processing of forms.

[0556] "User inquiries" refer to communications where customers or clients seek information about products or services or request solutions to problems.

[0557] A "commercial strategy" is a set of marketing activities and campaigns designed to analyze customer behavior and market trends and drive business growth.

[0558] A "notification" is a means of communication used to convey important business information to relevant parties, and is useful for improving work efficiency and information sharing.

[0559] This invention provides a platform for centrally managing contracts, scheduling, expense management, customer service, and marketing support as a business management system. Specific embodiments of this system are described below.

[0560] The server provides core functions for managing various types of business information. When contract information is entered, the server executes an automated generation program to generate the contract. Furthermore, an intelligent agent checks the legal risks of the contract using a generation AI model. In project scheduling, the server monitors progress based on task information entered by the user and sets task priorities using intelligent means.

[0561] For expense management, users upload receipts as images using their smartphone cameras. The server converts these images into text information and automatically performs aggregation. The technology used is the Google Cloud Vision API for text extraction. For customer support, the server generates an automated response whenever the user's device receives an inquiry from a customer. This response is generated by a generation AI model based on predefined prompt phrases.

[0562] In marketing support, the server analyzes customer data and automatically generates and proposes commercial strategies. For this purpose, it utilizes Python's pandas and scikit-learn as data analysis techniques. The proposed commercial strategies are implemented after user approval. This entire process allows the server to manage multiple business functions simultaneously, significantly improving the operational efficiency of freelancers and small businesses.

[0563] As a concrete example, when launching a new commercial campaign, the server analyzes past sales data and automatically suggests the most effective strategy. Then, based on the generated prompt, it automatically generates the campaign text. An example of this automatically generated prompt could be: "Based on this month's sales data, please suggest the most effective measures for the next promotion."

[0564] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0565] Step 1:

[0566] The user enters contract information and sends it to the server. This input includes detailed information such as the name of the contracting party and the contract details. Based on this input data, the server runs a program that automatically generates a contract and outputs a draft of the contract. A template is used to generate the contract, and the input information is filled in to create a document that conforms to the format.

[0567] Step 2:

[0568] The server passes the generated contract to an intelligent agent for security verification. The entire contract is provided to the AI ​​agent as input. The intelligent agent uses a generation AI model to evaluate the legal risks and points out any problematic areas. This result is output as a risk assessment report and returned to the user.

[0569] Step 3:

[0570] The user inputs project task information and sends it from their terminal to the server. The server analyzes the progress of each task based on this data and sets priorities. A schedule management algorithm is used to process this input data and output the optimal schedule. A list of prioritized tasks is output and displayed to the user.

[0571] Step 4:

[0572] The user scans a receipt using their smartphone camera and uploads the image data to the server. The server converts the image into text data via the Google Cloud Vision API. By analyzing this input image, the date, amount, and breakdown of the expenditure are extracted, and based on this, the expenditure record is automatically compiled and an expense report is generated.

[0573] Step 5:

[0574] The terminal receives an inquiry from a customer and sends the inquiry details to the server. Based on this information, the server uses a generation AI model to automatically generate a reply message according to the prompts. Utilizing the input inquiry and related prompts, an appropriate reply is output and sent to the customer.

[0575] Step 6:

[0576] The server collects historical customer data and performs analysis based on it to generate commercial strategies. Using sales history and customer attribute information as input data, it applies data analysis methods to output the optimal promotional strategy. This strategy is then proposed to the user and implemented after approval.

[0577] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0578] This invention aims to integrate an emotion engine into a business management system for freelancers and small businesses to recognize users' emotional states and provide more personalized responses. In addition to contract management, project scheduling, expense management, and customer support, this system includes functions to improve business efficiency by recognizing users' emotions.

[0579] This system has a function that automatically generates contracts on the server based on contract information entered via a terminal. The generated contracts are checked for legal risks by an AI agent on the server to ensure their safety. In the project schedule, the server monitors tasks entered by the user, and the AI ​​sets priorities. In particular, when the user's emotional state influences decisions, the emotion engine adjusts priorities and schedules.

[0580] The user's device scans receipts and sends the image data to the server. The server analyzes this data and aggregates it into necessary text, streamlining expense management. Furthermore, in customer support, the server receives customer inquiries and generates automated replies. This is where the emotion engine comes in, selecting responses that are appropriate to the user's or customer's emotions.

[0581] As an example, if a user is experiencing stress, the emotion engine can detect this and re-evaluate the task priorities. Similarly, if a customer is dissatisfied, the emotion engine can automatically generate a more polite response from the server, communicating in a way that soothes the customer's emotions. In this way, the introduction of an emotion engine can improve the quality of business management and enhance user and customer satisfaction.

[0582] The following describes the processing flow.

[0583] Step 1:

[0584] The user uses a terminal to enter contract information and begin creating the contract. The contract details include information such as the business partner, agreed terms, and submission deadline.

[0585] Step 2:

[0586] The terminal sends the entered contract information to the server. The server automatically generates a contract based on that information and constructs the document using a template.

[0587] Step 3:

[0588] The server uses an AI agent to check the legal risks of automatically generated contracts. The AI ​​agent identifies potential risks and generates suggestions as needed.

[0589] Step 4:

[0590] The device analyzes the user's emotional state through an emotion engine. The emotion engine infers the emotional state based on factors such as the user's voice tone and input speed.

[0591] Step 5:

[0592] The server receives the results analyzed by the emotion engine and adjusts priorities and procedures in the contract process. In particular, it adjusts notifications and reminders if the user is experiencing stress.

[0593] Step 6:

[0594] The user inputs information for each project task on their device. The server creates a schedule based on this data, and the AI ​​sets the task priorities.

[0595] Step 7:

[0596] The server dynamically changes task priorities while considering the user's emotions. This action helps the user maintain focus.

[0597] Step 8:

[0598] For expense management, users scan receipts with their device's camera, and the device sends the image to a server. The server analyzes the image and automatically compiles expense items.

[0599] Step 9:

[0600] When a customer inquiry is received on a terminal, the server generates an automated response. The emotion engine analyzes the customer's emotional state and adjusts the response accordingly.

[0601] Step 10:

[0602] Based on the analysis results from the emotion engine, the server creates personalized follow-ups for customers and develops content to improve the quality of service.

[0603] (Example 2)

[0604] Next, we will describe Example 2. 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."

[0605] Freelancers and small business owners often face inefficiencies due to the significant amount of manual work required for business management. Furthermore, accurately understanding and appropriately responding to the nuances of customer emotions is challenging. In addition, integrated management and utilization of individual business data is difficult, highlighting the need for increased productivity and improved customer satisfaction.

[0606] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0607] This invention includes a server that automatically generates contract documents based on input contract information, a means for evaluating the legal risks of the generated contract documents using an artificial intelligence agent, and a means for monitoring project schedules, setting work priorities, and adjusting them according to the user's emotional state using an emotion recognition engine. This enables more efficient business management, improved customer service quality, and increased user and customer satisfaction.

[0608] A "contract document" is a written document that formally records the terms and conditions of a transaction or agreement, and has legal effect.

[0609] An "artificial intelligence agent" is a program that autonomously learns knowledge and solves specific tasks or problems.

[0610] A "project schedule" is a plan that outlines the work schedule from the start to the end of a project.

[0611] "Task prioritization" refers to the criteria used to determine which tasks should be handled first when performing work.

[0612] An "emotion recognition engine" is a program that has the function of analyzing and recognizing a person's emotional state.

[0613] "Expenses" refer to the economic expenditures necessary for business activities.

[0614] "Customer inquiries" refer to questions and requests sent by customers seeking information or support regarding products or services.

[0615] An "automatic reply" is a response message that a system automatically generates and sends based on specific conditions or triggers.

[0616] This invention is a system designed for freelancers and small businesses to streamline work management and improve the quality of their work. The system includes contract information management, project scheduling, expense management, customer support, and sentiment recognition.

[0617] First, the user enters contract information using a terminal. This information is sent to a server, which automatically generates a contract document based on it. A generation AI model is used for the automatic generation of the contract, which creates a standard contract template. The generated contract is then evaluated for legal risks by an artificial intelligence agent on the server. This ensures that a legally secure contract document is provided.

[0618] In project management, tasks entered by users via terminals are recorded on a server. The server incorporates an emotion recognition engine and monitors the project schedule. Based on the user's emotional state, the server automatically adjusts task priorities. This reduces user stress and enables efficient schedule management.

[0619] Regarding expense management, users scan receipts using their devices and send the images to the server. The received image data is analyzed by the server, and text information is extracted. This allows for automatic expense aggregation and efficient accounting processing.

[0620] In customer support, customer inquiries are sent to a server. The server uses an emotion recognition engine to analyze the customer's emotional state and generates an automated response. This enables responses that are appropriate to the customer's emotions, which is expected to improve customer satisfaction.

[0621] For example, a prompt for responding to a user feeling anxious about their work might be, "If the user is feeling stressed, how should task priorities be adjusted?" Another example prompt for responding to a customer expressing dissatisfaction with a product might be, "Please provide a response that alleviates the customer's dissatisfaction." These prompts are generated using a generative AI model to facilitate the most appropriate response for each situation.

[0622] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0623] Step 1:

[0624] The user enters contract information using a terminal. The user enters details such as the name of the contracting party, the contract details, and the start and end dates into the terminal. The terminal converts this information into a structured data format and sends it to the server.

[0625] Step 2:

[0626] The server receives the entered contract information and automatically generates a contract document using a generation AI model. The server inputs the received data into the model and embeds the information into a standard contract template. The generated contract is stored on the server.

[0627] Step 3:

[0628] The server uses an artificial intelligence agent to assess the legal risks of the generated contract. The agent analyzes the content of the contract and checks whether the legal terminology and conditions are appropriate. The output of this process is a contract document that has been confirmed to be safe.

[0629] Step 4:

[0630] The user enters project-related tasks from their terminal. The user fills in task details and deadlines. The terminal then sends this task information directly to the server.

[0631] Step 5:

[0632] The server receives task information and uses an emotion recognition engine to monitor and adjust the project schedule. The server receives emotion data as input and controls task priorities based on the user's emotional state. The output is the adjusted schedule.

[0633] Step 6:

[0634] The user scans the receipt using the terminal. The terminal takes a picture of the receipt and prepares to send it to the server.

[0635] Step 7:

[0636] The server analyzes the received receipt image and extracts text information. The server processes the data using an image analysis algorithm and converts it into text format. As a result, the expense data is organized and can be automatically aggregated.

[0637] Step 8:

[0638] A customer submits an inquiry about a product or service. The server receives the customer's message and analyzes their emotional state through an emotion recognition engine.

[0639] Step 9:

[0640] The server generates an automated response based on the analysis results. The server then constructs the most appropriate response based on the sentiment analysis and sends it to the customer. This process aims to increase customer satisfaction.

[0641] (Application Example 2)

[0642] Next, we will explain application example 2. In the following explanation, 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."

[0643] While conventional business management systems contribute to improving operational efficiency in areas such as contract and expense management, they have the challenge of making it difficult to provide personalized responses that take into account the emotions of users and customers. In particular, for small businesses and households, providing appropriate responses that address individual emotional states is crucial for improving the quality of work and daily life.

[0644] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0645] In this invention, the server includes means for automatically generating contracts based on input contract data, means for checking the legal risks of the generated contracts using an AI agent, AI means for monitoring work schedules and setting task priorities, means for analyzing receipt images and converting them into text data to automatically aggregate expenses, means for generating automatic replies to customer inquiries, means for recognizing the user's emotional state and adjusting schedules and priorities based on those emotions, means for managing household tasks and adjusting task priorities based on the individual's emotional state, and means for analyzing visitors' emotions and adjusting responses to visitors. This makes it possible to manage work and household tasks more efficiently and effectively according to individual emotional states.

[0646] "Contract data" refers to information related to business contracts, and is the input information necessary for creating a contract.

[0647] "Automatic contract generation method" refers to a technology that has the function of automatically creating a contract based on input contract data.

[0648] The "legal risk check mechanism" is a function that uses an AI agent to verify the legal risks of generated contracts.

[0649] A "work schedule monitoring tool" is a function that observes and tracks time management related to projects and tasks, and uses that information to enable efficient management.

[0650] "Priority setting AI means" refers to a function that uses artificial intelligence to optimize the execution order of tasks according to their importance and urgency.

[0651] A "receipt analysis method" is a technology that extracts text information from images of paper or electronic receipts and converts it into text data that can be used for subsequent processing.

[0652] The "automatic expense aggregation method" is a function that automatically aggregates expenses based on analyzed receipt data, thereby supporting financial management.

[0653] An "automatic reply generation method" is a technology that automatically generates replies to customer inquiries, enabling timely and efficient customer service.

[0654] "Emotional state recognition means" refers to technology for analyzing the emotions of a user or customer and providing information based on those emotions.

[0655] "Household task management tools" are technologies that provide the functionality to manage schedules and resources in order to effectively plan and execute various tasks within the household.

[0656] "Visitor emotion analysis tools" are technologies that evaluate and analyze visitors' emotions and take appropriate action based on the results.

[0657] This invention realizes a system that recognizes the user's emotional state and provides personalized support for work management and household tasks. By utilizing data communication between the server and terminal and AI, it enables effective work management.

[0658] The server receives contract data and automatically generates contracts based on it. The generated contracts have a function to check legal risks using an AI agent. Furthermore, it monitors the work schedule and sets task priorities using AI. This AI analyzes the user's emotional state using an emotion recognition library developed in Python. The terminal processes images acquired by smartphones or home robot cameras, recognizes the user's emotions, and sends them to the server.

[0659] Receipts are scanned at the terminal, and the image data is sent to the server. The server analyzes the image data, converts it into the necessary text data, and automatically calculates expenses. When there is a customer inquiry, the server generates an automated reply, but here again, the sentiment engine comes into play, adjusting the reply based on the user's or customer's emotions. By also performing sentiment analysis of visitors, it optimizes how you handle visitors in your home.

[0660] For example, a server can analyze a user's stress levels and reduce their workload by readjusting important tasks. Furthermore, within a home, it's possible to analyze whether a visitor is relaxed and suggest appropriate hospitality. An example of a prompt for a generative AI model might be, "Classify the user's emotions into anger, sadness, and joy, and consider appropriate responses for each."

[0661] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0662] Step 1:

[0663] The device recognizes the user's emotions and sends them to the server as image data. The user's facial expressions are read through the camera of their smartphone or a robot, and the images are analyzed in real time. An emotion recognition library is used to process the image data and generate emotional state data. The generated emotional state data is then sent to the server.

[0664] Step 2:

[0665] The server analyzes the received emotional state data and re-evaluates task priorities. Based on the input emotional state data, the AI ​​calculates the importance of work tasks, taking emotional impact into account, and adjusts the schedule accordingly. The output is a task list with adjusted priorities.

[0666] Step 3:

[0667] The terminal scans expense-related receipts and sends them to the server as image data. The user scans the receipts, and the resulting image data is transferred to the server. The server uses OCR technology to convert the images into text data and extracts and aggregates expense items. The output is an aggregated expense list.

[0668] Step 4:

[0669] When the server receives a customer inquiry, it generates an automated response. When a user submits an inquiry, an AI agent analyzes the content and generates an appropriate response. The emotion engine adjusts the wording according to the user's emotional state, enabling a personalized response. The output is the automated response message.

[0670] Step 5:

[0671] The server analyzes the visitor's emotions and determines how to respond within the home. If there is a visitor at the user's home, the facial expression images captured by the device are analyzed. Based on a generated AI model, the visitor's emotions are classified, and information is generated and provided to suggest appropriate hospitality. The output is the suggested hospitality plan.

[0672] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0673] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0674] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0675] [Fourth Embodiment]

[0676] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0677] As shown in Figure 7, the 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.

[0678] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0679] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0680] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0681] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0682] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0683] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0684] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0685] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0686] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0687] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0688] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0689] This invention is a system designed to solve the diverse business management challenges faced by freelancers and small business owners. This system comprehensively handles contract management, project scheduling, expense management, customer service, and even marketing support.

[0690] In contract management, users input the necessary contract information using a terminal, and the server automatically generates the contract. The server also uses an AI agent to check the legal risks of the generated contract and confirm its safety.

[0691] In project scheduling, users input each project task from their terminal. Based on this information, the server monitors the progress of the tasks and sets priorities using AI. For tasks with approaching deadlines, the server sends reminders to the user.

[0692] In expense management, users scan receipts using their device's camera. The server captures the image data, converts it to text data, and automatically aggregates it to support proper expense management.

[0693] In customer support, the user's device receives inquiries from customers, and the server generates an automated response. If necessary, a chatbot handles customer support, and the server suggests response options.

[0694] For example, when a user starts a new project, they input all related tasks from their terminal. The server receives this information, calculates the optimal order for task progress, and sends notifications as the tasks progress. This entire process allows the user to manage their projects more efficiently.

[0695] Furthermore, in marketing campaigns, the server analyzes customer data and proposes targeted marketing strategies. Campaign text is automatically generated by AI, and the server executes the campaign with user approval. This method allows users to conduct marketing activities efficiently.

[0696] The following describes the processing flow.

[0697] Step 1:

[0698] The user enters contract information using a terminal. They fill in details such as the contracting party, contract amount, and contract period in a form.

[0699] Step 2:

[0700] The terminal sends the entered contract information to the server. This information is then incorporated into the contract management program.

[0701] Step 3:

[0702] The server automatically generates a contract by combining the entered information based on a contract template.

[0703] Step 4:

[0704] The generated contract is analyzed for legal risks by an AI agent on the server. If risks are identified, proposed revisions are generated.

[0705] Step 5:

[0706] The server sends the completed contract to the user's terminal and requests the user to review it. Instructions for revisions are received as needed.

[0707] Step 6:

[0708] Users input project task information from their devices, providing task names, deadlines, priority levels, and other details.

[0709] Step 7:

[0710] The server receives task information and activates a function to monitor progress. It tracks the progress of each task.

[0711] Step 8:

[0712] The server's AI module analyzes task priorities and notifies the user's device of the tasks they should be working on.

[0713] Step 9:

[0714] To manage expense information, users scan receipts with their device's camera and generate image data.

[0715] Step 10:

[0716] The terminal sends scanned images to the server, which analyzes the images, converts them to text, and compiles the expenses.

[0717] Step 11:

[0718] The user receives customer inquiries on their device, the server automatically generates a reply, and sends the suggested response to the user's device.

[0719] Step 12:

[0720] The server analyzes customer data and devises targeted marketing strategies. AI generates campaign text.

[0721] Step 13:

[0722] The server sends the proposed campaign details to the user's device, and after obtaining approval, the marketing campaign is implemented.

[0723] (Example 1)

[0724] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0725] In today's diverse business management landscape, there is a demand for effective contract document creation and progress management, expense processing, customer service, and marketing strategy implementation. However, these tasks are complex, and the lack of efficiency and automation in each process makes it difficult to respond quickly to these challenges.

[0726] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0727] In this invention, the server includes means for automatically generating contract documents based on input business information, artificial intelligence means for analyzing the legal risks of the generated contract documents, artificial intelligence means for monitoring the progress of work and setting work priorities, means for analyzing images of paper documents to convert them into text information and automatically compile expenses, means for generating automatic replies to customer inquiries, and means for automatically generating and proposing targeted marketing strategies based on customer data. As a result, each process of the business is automated, enabling efficient management and rapid response.

[0728] "Business information" is a general term for all data related to contracts, work, expenses, customer service, and marketing activities.

[0729] A "contract document" is a document created to formally record a transaction or agreement.

[0730] "Artificial intelligence tools" refer to technologies that utilize machine learning and data analysis techniques to automatically analyze data and make decisions.

[0731] "Progress status" refers to information indicating the current stage of a project or task.

[0732] "Priority" refers to the criteria used to rearrange tasks and work based on their importance and urgency.

[0733] "Characterization" is the process of recognizing characters from image data and converting them into text data.

[0734] "Automatic aggregation" refers to the process of automating the collection of data based on input data and calculating the total.

[0735] "Automatic reply" is a function that allows the system to send a response to received messages or inquiries based on predefined rules.

[0736] A "target marketing strategy" is a set of policies and plans for efficient marketing activities aimed at a specific customer segment or market.

[0737] This system is designed to effectively solve the diverse business management challenges faced by freelancers and small business owners. To implement the invention, a network-connected server and user-operated terminals are required.

[0738] The server is equipped with high-performance computing power and AI models to perform key business processes. These AI models are used for automatically generating contract documents, analyzing legal risks, monitoring and prioritizing tasks, managing expenses, automatically responding to inquiries, and proposing marketing strategies.

[0739] The terminal provides an interface for users to input business information. This allows users to easily input contract information, project tasks, expense information, and more. By utilizing the terminal's camera function, it is also possible to easily scan and digitize paper receipts.

[0740] Users can initiate the necessary processing on the server side by entering a prompt into the system, such as, "I would like to create a contract for a new project. Please use the following conditions: (details of conditions)." In response to this prompt, the system selects an appropriate contract template and automatically generates the contract. The generated contract is then analyzed for legal risks by an AI agent.

[0741] Furthermore, in marketing activities, prompts such as "Please propose a marketing campaign for our new product. The target customer segment is: (details of the customer segment)" can be used to allow the server to analyze customer data and propose an efficient campaign strategy.

[0742] This system allows users to automate many business programs, enabling them to manage their operations effectively and efficiently. In this way, the aim is to improve the overall efficiency of business management and reduce the workload on users.

[0743] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0744] Step 1:

[0745] Users use terminals to input information related to their work. For example, when entering contract information, they meticulously enter details such as the contractor's name, contract amount, and contract period into the terminal. The entered data is then transmitted to the server via the network.

[0746] Step 2:

[0747] The server automatically generates contract documents based on the received business information. Using a generation AI model, the server creates the contract by embedding data into a pre-configured contract template. The contract generated through this process is output as a formatted digital document.

[0748] Step 3:

[0749] The server utilizes an AI agent to check the legal risks of the generated contracts. It analyzes the contract content to verify that there are no legal issues. This analysis includes cross-referencing with a legal database, and the results are output as a risk assessment report.

[0750] Step 4:

[0751] Users use their device's scheduling function to enter each task in the project. After entering the task name, start date, end date, and required resources, this information is also sent to the server.

[0752] Step 5:

[0753] The server monitors the progress of project tasks and uses AI to prioritize them. The server analyzes data for each task and determines priorities based on urgency and importance. As a result of this data processing, priority information is notified to the user's device.

[0754] Step 6:

[0755] The server monitors project task deadlines and generates reminders for tasks approaching their due dates. This allows users to receive timely notifications about tasks with approaching deadlines. Notifications are sent via email or as app notifications on the device.

[0756] Step 7:

[0757] The user uses their device's camera to scan the receipt and sends the image data to the server. The server reads this data using OCR technology and converts the contents of the document into text data.

[0758] Step 8:

[0759] The server analyzes the text data obtained by OCR and automatically aggregates expenses. Based on the expense information stored in the database, it classifies the data by category and outputs the aggregated results to the user as a monthly report.

[0760] Step 9:

[0761] When a user's device receives an inquiry from a customer, it sends the data to the server. The server uses AI to analyze the inquiry and generate an appropriate automated response.

[0762] Step 10:

[0763] The server analyzes customer data and devises targeted marketing strategies. This process involves clustering based on purchase history and behavioral patterns to propose the most suitable campaign. The proposed campaign is reviewed and approved by the user before being implemented.

[0764] (Application Example 1)

[0765] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0766] For freelancers and small businesses, managing operations has become increasingly complex, making efficient business operations difficult. For these businesses, individually managing diverse tasks such as contract management, project scheduling, expense management, customer service, and marketing support is a significant burden. To address this challenge, a system that integrates and manages these functions is necessary.

[0767] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0768] In this invention, the server includes means for automatically generating a contract based on input contract information, means for checking the legal risks of the generated contract using an intelligent agent, and intelligent means for tracking the progress of work and setting work priorities. This enables freelancers and small business owners to efficiently manage multiple tasks and improve the productivity and accuracy of their work.

[0769] "Contract information" refers to data related to contracts that a business enters into with its business partners, employees, etc., and is necessary when creating contract documents.

[0770] An "intelligent agent" is a program that uses artificial intelligence technology to automatically perform specific tasks, and is used for evaluating the legal risks of contracts and generating proposals.

[0771] "Work progress" refers to information indicating the current stage of a task in a project or business, and is important for efficient schedule management.

[0772] "Task prioritization" refers to the criteria used to assess the importance and urgency of multiple ongoing tasks and determine the order in which they should be performed.

[0773] "Textual information" refers to text data extracted from image data, which is useful for expense management and digital processing of forms.

[0774] "User inquiries" refer to communications where customers or clients seek information about products or services or request solutions to problems.

[0775] A "commercial strategy" is a set of marketing activities and campaigns designed to analyze customer behavior and market trends and drive business growth.

[0776] A "notification" is a means of communication used to convey important business information to relevant parties, and is useful for improving work efficiency and information sharing.

[0777] This invention provides a platform for centrally managing contracts, scheduling, expense management, customer service, and marketing support as a business management system. Specific embodiments of this system are described below.

[0778] The server provides core functions for managing various types of business information. When contract information is entered, the server executes an automated generation program to generate the contract. Furthermore, an intelligent agent checks the legal risks of the contract using a generation AI model. In project scheduling, the server monitors progress based on task information entered by the user and sets task priorities using intelligent means.

[0779] For expense management, users upload receipts as images using their smartphone cameras. The server converts these images into text information and automatically performs aggregation. The technology used is the Google Cloud Vision API for text extraction. For customer support, the server generates an automated response whenever the user's device receives an inquiry from a customer. This response is generated by a generation AI model based on predefined prompt phrases.

[0780] In marketing support, the server analyzes customer data and automatically generates and proposes commercial strategies. For this purpose, it utilizes Python's pandas and scikit-learn as data analysis techniques. The proposed commercial strategies are implemented after user approval. This entire process allows the server to manage multiple business functions simultaneously, significantly improving the operational efficiency of freelancers and small businesses.

[0781] As a concrete example, when launching a new commercial campaign, the server analyzes past sales data and automatically suggests the most effective strategy. Then, based on the generated prompt, it automatically generates the campaign text. An example of this automatically generated prompt could be: "Based on this month's sales data, please suggest the most effective measures for the next promotion."

[0782] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0783] Step 1:

[0784] The user enters contract information and sends it to the server. This input includes detailed information such as the name of the contracting party and the contract details. Based on this input data, the server runs a program that automatically generates a contract and outputs a draft of the contract. A template is used to generate the contract, and the input information is filled in to create a document that conforms to the format.

[0785] Step 2:

[0786] The server passes the generated contract to an intelligent agent for security verification. The entire contract is provided to the AI ​​agent as input. The intelligent agent uses a generation AI model to evaluate the legal risks and points out any problematic areas. This result is output as a risk assessment report and returned to the user.

[0787] Step 3:

[0788] The user inputs project task information and sends it from their terminal to the server. The server analyzes the progress of each task based on this data and sets priorities. A schedule management algorithm is used to process this input data and output the optimal schedule. A list of prioritized tasks is output and displayed to the user.

[0789] Step 4:

[0790] The user scans a receipt using their smartphone camera and uploads the image data to the server. The server converts the image into text data via the Google Cloud Vision API. By analyzing this input image, the date, amount, and breakdown of the expenditure are extracted, and based on this, the expenditure record is automatically compiled and an expense report is generated.

[0791] Step 5:

[0792] The terminal receives an inquiry from a customer and sends the inquiry details to the server. Based on this information, the server uses a generation AI model to automatically generate a reply message according to the prompts. Utilizing the input inquiry and related prompts, an appropriate reply is output and sent to the customer.

[0793] Step 6:

[0794] The server collects historical customer data and performs analysis based on it to generate commercial strategies. Using sales history and customer attribute information as input data, it applies data analysis methods to output the optimal promotional strategy. This strategy is then proposed to the user and implemented after approval.

[0795] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0796] This invention aims to integrate an emotion engine into a business management system for freelancers and small businesses to recognize users' emotional states and provide more personalized responses. In addition to contract management, project scheduling, expense management, and customer support, this system includes functions to improve business efficiency by recognizing users' emotions.

[0797] This system has a function that automatically generates contracts on the server based on contract information entered via a terminal. The generated contracts are checked for legal risks by an AI agent on the server to ensure their safety. In the project schedule, the server monitors tasks entered by the user, and the AI ​​sets priorities. In particular, when the user's emotional state influences decisions, the emotion engine adjusts priorities and schedules.

[0798] The user's device scans receipts and sends the image data to the server. The server analyzes this data and aggregates it into necessary text, streamlining expense management. Furthermore, in customer support, the server receives customer inquiries and generates automated replies. This is where the emotion engine comes in, selecting responses that are appropriate to the user's or customer's emotions.

[0799] As an example, if a user is experiencing stress, the emotion engine can detect this and re-evaluate the task priorities. Similarly, if a customer is dissatisfied, the emotion engine can automatically generate a more polite response from the server, communicating in a way that soothes the customer's emotions. In this way, the introduction of an emotion engine can improve the quality of business management and enhance user and customer satisfaction.

[0800] The following describes the processing flow.

[0801] Step 1:

[0802] The user uses a terminal to enter contract information and begin creating the contract. The contract details include information such as the business partner, agreed terms, and submission deadline.

[0803] Step 2:

[0804] The terminal sends the entered contract information to the server. The server automatically generates a contract based on that information and constructs the document using a template.

[0805] Step 3:

[0806] The server uses an AI agent to check the legal risks of automatically generated contracts. The AI ​​agent identifies potential risks and generates suggestions as needed.

[0807] Step 4:

[0808] The device analyzes the user's emotional state through an emotion engine. The emotion engine infers the emotional state based on factors such as the user's voice tone and input speed.

[0809] Step 5:

[0810] The server receives the results analyzed by the emotion engine and adjusts priorities and procedures in the contract process. In particular, it adjusts notifications and reminders if the user is experiencing stress.

[0811] Step 6:

[0812] The user inputs information for each project task on their device. The server creates a schedule based on this data, and the AI ​​sets the task priorities.

[0813] Step 7:

[0814] The server dynamically changes task priorities while considering the user's emotions. This action helps the user maintain focus.

[0815] Step 8:

[0816] For expense management, users scan receipts with their device's camera, and the device sends the image to a server. The server analyzes the image and automatically compiles expense items.

[0817] Step 9:

[0818] When a customer inquiry is received on a terminal, the server generates an automated response. The emotion engine analyzes the customer's emotional state and adjusts the response accordingly.

[0819] Step 10:

[0820] Based on the analysis results from the emotion engine, the server creates personalized follow-ups for customers and develops content to improve the quality of service.

[0821] (Example 2)

[0822] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0823] Freelancers and small business owners often face inefficiencies due to the significant amount of manual work required for business management. Furthermore, accurately understanding and appropriately responding to the nuances of customer emotions is challenging. In addition, integrated management and utilization of individual business data is difficult, highlighting the need for increased productivity and improved customer satisfaction.

[0824] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0825] This invention includes a server that automatically generates contract documents based on input contract information, a means for evaluating the legal risks of the generated contract documents using an artificial intelligence agent, and a means for monitoring project schedules, setting work priorities, and adjusting them according to the user's emotional state using an emotion recognition engine. This enables more efficient business management, improved customer service quality, and increased user and customer satisfaction.

[0826] A "contract document" is a written document that formally records the terms and conditions of a transaction or agreement, and has legal effect.

[0827] An "artificial intelligence agent" is a program that autonomously learns knowledge and solves specific tasks or problems.

[0828] A "project schedule" is a plan that outlines the work schedule from the start to the end of a project.

[0829] "Task prioritization" refers to the criteria used to determine which tasks should be handled first when performing work.

[0830] An "emotion recognition engine" is a program that has the function of analyzing and recognizing a person's emotional state.

[0831] "Expenses" refer to the economic expenditures necessary for business activities.

[0832] "Customer inquiries" refer to questions and requests sent by customers seeking information or support regarding products or services.

[0833] An "automatic reply" is a response message that a system automatically generates and sends based on specific conditions or triggers.

[0834] This invention is a system designed for freelancers and small businesses to streamline work management and improve the quality of their work. The system includes contract information management, project scheduling, expense management, customer support, and sentiment recognition.

[0835] First, the user enters contract information using a terminal. This information is sent to a server, which automatically generates a contract document based on it. A generation AI model is used for the automatic generation of the contract, which creates a standard contract template. The generated contract is then evaluated for legal risks by an artificial intelligence agent on the server. This ensures that a legally secure contract document is provided.

[0836] In project management, tasks entered by users via terminals are recorded on a server. The server incorporates an emotion recognition engine and monitors the project schedule. Based on the user's emotional state, the server automatically adjusts task priorities. This reduces user stress and enables efficient schedule management.

[0837] Regarding expense management, users scan receipts using their devices and send the images to the server. The received image data is analyzed by the server, and text information is extracted. This allows for automatic expense aggregation and efficient accounting processing.

[0838] In customer support, customer inquiries are sent to a server. The server uses an emotion recognition engine to analyze the customer's emotional state and generates an automated response. This enables responses that are appropriate to the customer's emotions, which is expected to improve customer satisfaction.

[0839] For example, a prompt for responding to a user feeling anxious about their work might be, "If the user is feeling stressed, how should task priorities be adjusted?" Another example prompt for responding to a customer expressing dissatisfaction with a product might be, "Please provide a response that alleviates the customer's dissatisfaction." These prompts are generated using a generative AI model to facilitate the most appropriate response for each situation.

[0840] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0841] Step 1:

[0842] The user enters contract information using a terminal. The user enters details such as the name of the contracting party, the contract details, and the start and end dates into the terminal. The terminal converts this information into a structured data format and sends it to the server.

[0843] Step 2:

[0844] The server receives the entered contract information and automatically generates a contract document using a generation AI model. The server inputs the received data into the model and embeds the information into a standard contract template. The generated contract is stored on the server.

[0845] Step 3:

[0846] The server uses an artificial intelligence agent to assess the legal risks of the generated contract. The agent analyzes the content of the contract and checks whether the legal terminology and conditions are appropriate. The output of this process is a contract document that has been confirmed to be safe.

[0847] Step 4:

[0848] The user enters project-related tasks from their terminal. The user fills in task details and deadlines. The terminal then sends this task information directly to the server.

[0849] Step 5:

[0850] The server receives task information and uses an emotion recognition engine to monitor and adjust the project schedule. The server receives emotion data as input and controls task priorities based on the user's emotional state. The output is the adjusted schedule.

[0851] Step 6:

[0852] The user scans the receipt using the terminal. The terminal takes a picture of the receipt and prepares to send it to the server.

[0853] Step 7:

[0854] The server analyzes the received receipt image and extracts text information. The server processes the data using an image analysis algorithm and converts it into text format. As a result, the expense data is organized and can be automatically aggregated.

[0855] Step 8:

[0856] A customer submits an inquiry about a product or service. The server receives the customer's message and analyzes their emotional state through an emotion recognition engine.

[0857] Step 9:

[0858] The server generates an automated response based on the analysis results. The server then constructs the most appropriate response based on the sentiment analysis and sends it to the customer. This process aims to increase customer satisfaction.

[0859] (Application Example 2)

[0860] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0861] While conventional business management systems contribute to improving operational efficiency in areas such as contract and expense management, they have the challenge of making it difficult to provide personalized responses that take into account the emotions of users and customers. In particular, for small businesses and households, providing appropriate responses that address individual emotional states is crucial for improving the quality of work and daily life.

[0862] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0863] In this invention, the server includes means for automatically generating contracts based on input contract data, means for checking the legal risks of the generated contracts using an AI agent, AI means for monitoring work schedules and setting task priorities, means for analyzing receipt images and converting them into text data to automatically aggregate expenses, means for generating automatic replies to customer inquiries, means for recognizing the user's emotional state and adjusting schedules and priorities based on those emotions, means for managing household tasks and adjusting task priorities based on the individual's emotional state, and means for analyzing visitors' emotions and adjusting responses to visitors. This makes it possible to manage work and household tasks more efficiently and effectively according to individual emotional states.

[0864] "Contract data" refers to information related to business contracts, and is the input information necessary for creating a contract.

[0865] "Automatic contract generation method" refers to a technology that has the function of automatically creating a contract based on input contract data.

[0866] The "legal risk check mechanism" is a function that uses an AI agent to verify the legal risks of generated contracts.

[0867] A "work schedule monitoring tool" is a function that observes and tracks time management related to projects and tasks, and uses that information to enable efficient management.

[0868] "Priority setting AI means" refers to a function that uses artificial intelligence to optimize the execution order of tasks according to their importance and urgency.

[0869] A "receipt analysis method" is a technology that extracts text information from images of paper or electronic receipts and converts it into text data that can be used for subsequent processing.

[0870] The "automatic expense aggregation method" is a function that automatically aggregates expenses based on analyzed receipt data, thereby supporting financial management.

[0871] An "automatic reply generation method" is a technology that automatically generates replies to customer inquiries, enabling timely and efficient customer service.

[0872] "Emotional state recognition means" refers to technology for analyzing the emotions of a user or customer and providing information based on those emotions.

[0873] "Household task management tools" are technologies that provide the functionality to manage schedules and resources in order to effectively plan and execute various tasks within the household.

[0874] "Visitor emotion analysis tools" are technologies that evaluate and analyze visitors' emotions and take appropriate action based on the results.

[0875] This invention realizes a system that recognizes the user's emotional state and provides personalized support for work management and household tasks. By utilizing data communication between the server and terminal and AI, it enables effective work management.

[0876] The server receives contract data and automatically generates contracts based on it. The generated contracts have a function to check legal risks using an AI agent. Furthermore, it monitors the work schedule and sets task priorities using AI. This AI analyzes the user's emotional state using an emotion recognition library developed in Python. The terminal processes images acquired by smartphones or home robot cameras, recognizes the user's emotions, and sends them to the server.

[0877] Receipts are scanned at the terminal, and the image data is sent to the server. The server analyzes the image data, converts it into the necessary text data, and automatically calculates expenses. When there is a customer inquiry, the server generates an automated reply, but here again, the sentiment engine comes into play, adjusting the reply based on the user's or customer's emotions. By also performing sentiment analysis of visitors, it optimizes how you handle visitors in your home.

[0878] For example, a server can analyze a user's stress levels and reduce their workload by readjusting important tasks. Furthermore, within a home, it's possible to analyze whether a visitor is relaxed and suggest appropriate hospitality. An example of a prompt for a generative AI model might be, "Classify the user's emotions into anger, sadness, and joy, and consider appropriate responses for each."

[0879] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0880] Step 1:

[0881] The device recognizes the user's emotions and sends them to the server as image data. The user's facial expressions are read through the camera of their smartphone or a robot, and the images are analyzed in real time. An emotion recognition library is used to process the image data and generate emotional state data. The generated emotional state data is then sent to the server.

[0882] Step 2:

[0883] The server analyzes the received emotional state data and re-evaluates task priorities. Based on the input emotional state data, the AI ​​calculates the importance of work tasks, taking emotional impact into account, and adjusts the schedule accordingly. The output is a task list with adjusted priorities.

[0884] Step 3:

[0885] The terminal scans expense-related receipts and sends them to the server as image data. The user scans the receipts, and the resulting image data is transferred to the server. The server uses OCR technology to convert the images into text data and extracts and aggregates expense items. The output is an aggregated expense list.

[0886] Step 4:

[0887] When the server receives a customer inquiry, it generates an automated response. When a user submits an inquiry, an AI agent analyzes the content and generates an appropriate response. The emotion engine adjusts the wording according to the user's emotional state, enabling a personalized response. The output is the automated response message.

[0888] Step 5:

[0889] The server analyzes the visitor's emotions and determines how to respond within the home. If there is a visitor at the user's home, the facial expression images captured by the device are analyzed. Based on a generated AI model, the visitor's emotions are classified, and information is generated and provided to suggest appropriate hospitality. The output is the suggested hospitality plan.

[0890] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0891] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0892] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0893] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0894] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0895] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0896] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0897] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0898] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0899] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0900] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0901] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0902] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0903] 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.

[0904] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0905] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0906] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0907] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0908] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0909] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0910] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0911] The following is further disclosed regarding the embodiments described above.

[0912] (Claim 1)

[0913] A method for automatically generating a contract based on the entered contract information,

[0914] A method for checking the legal risks of generated contracts using an AI agent,

[0915] AI tools for monitoring project schedules and prioritizing tasks,

[0916] A method for analyzing images of receipts, converting them into text data, and automatically calculating expenses,

[0917] A means of generating an automated response to customer inquiries,

[0918] A business management system that includes this.

[0919] (Claim 2)

[0920] The system according to claim 1, further comprising means for monitoring the progress of a contract and sending renewal reminders.

[0921] (Claim 3)

[0922] The system according to claim 1, further comprising means for automatically generating and proposing targeted marketing campaigns.

[0923] "Example 1"

[0924] (Claim 1)

[0925] A means of automatically generating contract documents based on the entered business information,

[0926] An artificial intelligence tool for analyzing the legal risks of generated contract documents,

[0927] An artificial intelligence system that monitors the progress of tasks and sets task priorities,

[0928] A method for analyzing images of paper documents, converting them into text information, and automatically calculating expenses,

[0929] A means of generating an automated response to customer inquiries,

[0930] A system that includes this.

[0931] (Claim 2)

[0932] The system according to claim 1, further comprising means for monitoring the progress of a contract and sending renewal notices.

[0933] (Claim 3)

[0934] The system according to claim 1, further comprising means for automatically generating and proposing a targeted marketing strategy based on customer data.

[0935] "Application Example 1"

[0936] (Claim 1)

[0937] A method for automatically generating a contract based on the entered contract information,

[0938] A method for checking the legal risks of generated contracts using intelligent agents,

[0939] An intelligent means for tracking work progress and setting work priorities,

[0940] A method for analyzing images of expense records, converting them into text information, and automatically summarizing expenses,

[0941] A means of generating an automated response to user inquiries,

[0942] A means of automatically generating and proposing commercial strategies by analyzing customer data,

[0943] A means of scheduling certain tasks and notifying the person in charge,

[0944] A business management system that includes this.

[0945] (Claim 2)

[0946] The system according to claim 1, further comprising means for monitoring the progress of a contract and sending renewal notices.

[0947] (Claim 3)

[0948] The system according to claim 1, further comprising means for proposing and implementing a promotion strategy.

[0949] "Example 2 of combining an emotion engine"

[0950] (Claim 1)

[0951] A means of automatically generating contract documents based on entered contract information,

[0952] A method for evaluating the legal risks of generated contract documents using an artificial intelligence agent,

[0953] A method using an emotion recognition engine that monitors the project schedule, sets task priorities, and adjusts them according to the user's emotional state,

[0954] A method for analyzing images of receipts, converting them into text data, and automatically calculating expenses,

[0955] A method for generating automated responses to customer inquiries after analyzing their emotional state,

[0956] A system that includes this.

[0957] (Claim 2)

[0958] The system according to claim 1, further comprising means for monitoring the progress of a contract and sending notifications for renewal.

[0959] (Claim 3)

[0960] The system according to claim 1, further comprising means for automatically generating and proposing sales promotion activities for target customers.

[0961] "Application example 2 when combining with an emotional engine"

[0962] (Claim 1)

[0963] A method for automatically generating a contract based on the entered contract data,

[0964] A method for checking the legal risks of generated contracts using an AI agent,

[0965] AI tools to monitor work schedules and set task priorities,

[0966] A method for analyzing images of receipts, converting them into text data, and automatically calculating expenses,

[0967] A means of generating an automated response to customer inquiries,

[0968] A means of recognizing the user's emotional state and adjusting schedules and priorities based on those emotions,

[0969] A means of managing household tasks and adjusting task priorities based on an individual's emotional state,

[0970] A means of analyzing visitors' emotions and adjusting responses to them,

[0971] A system that includes this.

[0972] (Claim 2)

[0973] The system according to claim 1, further comprising means for monitoring the progress of a contract and sending renewal reminders.

[0974] (Claim 3)

[0975] The system according to claim 1, further comprising means for adjusting the response to visitors based on emotion recognition. [Explanation of symbols]

[0976] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A method for automatically generating a contract based on the entered contract information, A method for checking the legal risks of generated contracts using an AI agent, AI tools for monitoring project schedules and prioritizing tasks, A method for analyzing images of receipts, converting them into text data, and automatically calculating expenses, A means of generating an automated response to customer inquiries, A business management system that includes this.

2. The system according to claim 1, further comprising means for monitoring the progress of a contract and sending renewal reminders.

3. The system according to claim 1, further comprising means for automatically generating and proposing targeted marketing campaigns.

Images