How AI can help with system operations

Abstract

This is a method for supporting system operation work using AI, and its purpose is to improve work efficiency. [Solution] In one aspect of the present invention, there is provided a method for supporting system operation using AI, which is provided to a system that supports system operation, the system including a user terminal of a user who uses an application, a server terminal of a system operation company that performs operation work for the application, and an operator terminal of a person in charge of the operation work, wherein the user terminal, server terminal, and operator terminal are connected via a network, wherein the server terminal receives request information from the user terminal, refers to a natural language analysis model connected to the server terminal based on the request information, searches for knowledge data including an operation flow of the application, receives answer information generated by the natural language analysis model based on the search results, and transmits the generated answer information to the user terminal.

Description

[Technical field]

[0001] The present invention relates to a method for supporting system operation work using AI. [Background technology]

[0002] Conventionally, in response to inquiries from users of an application regarding how to use the application, problems, etc., the person in charge of system operations (operator) would refer to knowledge data each time an inquiry was received as a request, check the operational flow, and send the data to the application to complete the request.

[0003] However, as the number of requests increases, this type of operation becomes difficult, and as one method for improving the efficiency of help desk operations, Patent Document 1 discloses a help desk system that determines FAQs based on user attributes in response to inquiries from users. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2008-046852 Summary of the Invention [Problem to be solved by the invention]

[0005] However, particularly in system operation tasks, the requests made by users are becoming more complex, making it difficult to respond to the requests simply by referring to FAQs as in the technique disclosed in Patent Document 1.

[0006] Therefore, the present invention is a method for supporting system operation work using AI, and aims to achieve further improvement in work efficiency. [Means for solving the problem]

[0007] In one aspect of the present invention, there is provided a method for supporting system operation using AI, which is provided to a system that supports system operation, the system including a user terminal of a user who uses an application, a server terminal of a system operation company that performs operation work for the application, and an operator terminal of a person in charge of the operation work, wherein the user terminal, server terminal, and operator terminal are connected via a network, wherein the server terminal receives request information from the user terminal, refers to a natural language analysis model connected to the server terminal based on the request information, searches for knowledge data including an operation flow of the application, receives answer information generated by the natural language analysis model based on the search results, and transmits the generated answer information to the user terminal. Effect of the Invention

[0008] According to the present invention, a method for supporting system operation work using AI can further improve work efficiency. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram showing a system for supporting system operation work using AI according to a first embodiment of the present invention. [Diagram 2] 2 is a functional block diagram showing the server terminal 100 of FIG. 1. [Diagram 3] 2 is a functional block diagram showing a user terminal 200 of FIG. 1. [Figure 4] FIG. 2 is a diagram showing an example of user data stored in the server 100. [Diagram 5] FIG. 2 is a diagram showing an example of chatbot data stored in the server 100. [Figure 6] 1 is a flowchart showing an example of a method for supporting a system operation task by AI according to a first embodiment of the present invention. [Figure 7] 11 is a flowchart showing another example of the method for supporting system operation work by AI according to the first embodiment of the present invention. [Figure 8]2 is an example of an application screen provided by the server terminal 100 according to the first embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Note that the embodiment described below does not unduly limit the contents of the present invention described in the claims. Furthermore, not all of the components shown in the embodiment are necessarily essential components of the present invention.

[0011] <Configuration> FIG. 1 is a block diagram showing a system for supporting system operation work by AI according to a first embodiment of the present invention. The system 1 includes a server terminal 100, a user terminal 200 managed by the user, an operator terminal 300 of a person in charge of system operation, and the LLM 400, which receive requests from users (e.g., employees of a specific company) using an application that implements an in-house workflow from a user terminal or from another terminal via an API (Application Programming Interface) regarding inquiries about how to use the application, how to use the workflow, and usage problems, analyze the request content, generate a response to the request using a large-scale language model (LLM, for example, GPT) 400, and execute a process of outputting the response via a chatbot or the like. In addition, an application server 500 of an application that implements a workflow and is used by the user may be connected to each terminal constituting the system 1 via an API (Application Programming Interface). For convenience of explanation, each terminal is described as a single terminal, but the number of each is not limited.

[0012] The server terminal 100, the user terminal 200, the operator terminal 300, and the LLM 400 are each connected via a network NW1. The network NW is configured by the Internet, an intranet, a wireless LAN (Local Area Network), a WAN (Wide Area Network), or the like.

[0013] The server terminal 100, LLM 400 and application server 500 may be, for example, a general-purpose computer such as a workstation or a personal computer, or may be configured using cloud computing, a cluster or multicomputer consisting of multiple computers, a virtual machine constructed virtually using software, or a quantum computer.

[0014] The user terminal 200 and the operator terminal 300 are, for example, information processing devices such as personal computers and tablet terminals, but may also be configured as smartphones, mobile phones, PDAs, and the like.

[0015] In this embodiment, the system 1 is described as comprising a server terminal 100, a user terminal 200, an operator terminal 300, an LLM 400 and an application server 500, and a configuration in which users of each terminal use their respective terminals to perform operations on the server terminal 100; however, the server terminal 100 may be configured as a stand-alone system, and the server terminal itself may be provided with a function for each user to perform operations directly.

[0016] Fig. 2 is a functional block configuration diagram of the server terminal 100 of Fig. 1. The server terminal 100 includes a communication unit 110, a storage unit 120, and a control unit .

[0017] The communication unit 110 is a communication interface for communicating with the user terminal 200, the operator terminal 300, the LLM 400, and the application server 500 via the network NW1, and communication is performed according to a communication protocol such as TCP / IP (Transmission Control Protocol / Internet Protocol).

[0018] The storage unit 120 stores programs for executing various control processes and functions in the control unit 130, input data, etc., and is composed of a RAM (Random Access Memory), a ROM (Read Only Memory), etc. The storage unit 120 also has a user data storage unit 121 that stores various data related to users, and a chatbot data storage unit 122 that stores information necessary for operating the chatbot. Note that a database (not shown) that stores various data may be constructed outside the storage unit 120 or the server terminal 100.

[0019] The control unit 130 controls the overall operation of the server terminal 100 by executing a program stored in the storage unit 120, and is composed of a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), etc. Functions of the control unit 130 include an information receiving unit 131 that receives information from each user terminal, and an information processing unit 132 that processes the information. The information receiving unit 131 and the information processing unit 132 are started by a program stored in the storage unit 120 and executed by the server terminal 100, which is a computer (electronic calculator).

[0020] The information receiving unit 131 receives information from the user terminal 200 via the communication unit 110. For example, request information including an inquiry (question, conversation, etc.) regarding how to use an application is received from the user terminal 200 via a chat interface displayed on the user terminal 200.

[0021] The information processing unit 132 performs predetermined information processing such as analyzing the request information received from the user terminal 200 and generating a response to the request information. Note that the server terminal 100 can also perform predetermined processing in cooperation with an external API server (LLM 300) connected via an API.

[0022] The control unit 130 may also have a screen generation unit (not shown), which generates screen information to be displayed via the user interface of the user terminal 200 upon request. For example, using image and text data (not shown) stored in the storage unit 120 as material, the control unit 130 generates a user interface by arranging various images and text in predetermined areas of the user interface based on predetermined layout rules. Processing related to the image generation unit may also be executed by a GPU (Graphics Processing Unit).

[0023] Fig. 3 is a functional block diagram showing the user terminal 200 of Fig. 1. The user terminal 200 includes a communication unit 210, a display operation unit 220, a storage unit 230, and a control unit 240.

[0024] The communication unit 210 is a communication interface for communicating with the server terminal 100 via the network NW, and communication is performed according to a communication protocol such as TCP / IP.

[0025] The display operation unit 220 is a user interface used for inputting instructions by the user, analyzing the input data according to the input data such as text, voice, and image from the control unit 240, and displaying the text, voice, and image as output, and is composed of a display, keyboard, and mouse when the user terminal 200 is configured as a personal computer, and is composed of a touch panel, etc. when the user terminal 200 is configured as a smartphone or tablet terminal. This display operation unit 220 is started up by a control program stored in the storage unit 230 and executed by the user terminal 200, which is a computer (electronic calculator).

[0026] The storage unit 230 stores programs for executing various control processes and functions in the control unit 240, input data, etc., and is composed of a RAM, a ROM, etc. The storage unit 230 also temporarily stores the contents of communication with the server terminal 100.

[0027] The control unit 240 controls the overall operation of the user terminal 200 by executing the programs stored in the storage unit 230, and is configured with a CPU, a GPU, etc. Note that the operator terminal 300 can also have a similar configuration to the user terminal 200, so a description thereof will be omitted.

[0028] FIG. 4 is a diagram showing an example of user data stored in the server 100. As shown in FIG.

[0029] The user data 1000 shown in Fig. 4 stores various data related to a user. For convenience of explanation, Fig. 4 shows an example of one user (e.g., a user unit) (a user identified by a user ID "10001"), but information on multiple users can be stored. The various data related to a user can include, but is not limited to, basic information about the user (e.g., company ID, employee ID, name, company (corporation) name, department, job title, date of birth (age), address, contact information (email address, phone number), name of application used, authentication information for using the application (login ID, password), etc.), and conversation information (e.g., conversation history via a chat interface, etc.).

[0030] FIG. 5 is a diagram showing an example of chatbot data stored in the server 100. As shown in FIG.

[0031] The chatbot data 2000 stores various data related to the operation of the chatbot. The various data related to the operation of the chatbot can include, but are not limited to, prompt data (conditional statements for controlling answer sentences generated by a language model), request information (question sentences, conversation sentences, etc.) and answer sentences, conversation history data (natural language and / or data and data sets obtained by vectorizing natural language), knowledge data (knowledge related to system operation (methods of using applications, methods of using workflows, information for troubleshooting, etc.), and information related to operation flows for performing system operation. The present embodiment is characterized in that knowledge data for generating appropriate answer sentences to question sentences is recorded for each user (business entity) and / or for each data set, and prompts for controlling answer sentences generated by a language model are also recorded. Here, the knowledge data can be generated and updated based on usage manual data such as FAQs for the application, and conversation history with users.

[0032] <Processing flow> The flow of processing of the method for generating a reply sentence by a chatbot in response to request information including an inquiry (question sentence, conversation sentence) by a user, executed by the system 1 of this embodiment, will be described with reference to the figures from Fig. 6 onwards. Fig. 6 is a flowchart showing a basic flow as an example of a method for supporting system operation work by AI according to the first embodiment of the present invention.

[0033] First, in the process of step S101, a user who uses an application in the company inputs request information (question, conversation, etc.) regarding how to use the system via a chat interface implemented in a web browser or application of the user terminal 200, and the information receiving unit 131 of the control unit 130 of the server terminal 100 receives the request information input by the user (for example, "Please assign a paid account to Zoom (registered trademark) (specific application)") from the user terminal 200 via the communication unit 110. The information processing unit 132 of the control unit 130 stores the received request information in the user data storage unit 121 and / or chatbot data storage unit 122 of the memory unit 120 as user data 1000 and / or chatbot data 2000.

[0034] Next, in the process of step S102, the information processing unit 132 refers to the knowledge data stored in the chatbot data storage unit 122 (or an external database) of the memory unit 120 based on the vector data obtained by vectorizing the above request information via the LLM 400, and searches for similar vector data. For example, knowledge data for the above request example may include knowledge such as "Zoom (registered trademark) (a specific application) cannot be assigned to temporary workers. Please check with your supervisor before applying."

[0035] Next, in step S103, the information processing unit 132 acquires the answer sentence generated by the LLM 400 based on the data corresponding to the approximate value extracted as the knowledge search result.

[0036] Next, in the process of step S104, the information processing unit 132, while referring to the operation flow information, transmits the generated reply sentence in a predetermined procedure to the application server 500 used by the user, and transmits it to the user terminal 200 via the application. The information processing unit 132 stores the generated reply sentence as user data 1000 and / or chatbot data 2000 in the user data storage unit 121 and / or chatbot data storage unit 122 of the memory unit 120.

[0037] FIG. 7 is a diagram illustrating another example of a method for supporting system operation work using AI.

[0038] First, in the process of step S201, a user who uses an application in the company inputs request information (question, conversation, etc.) regarding how to use the system via a chat interface implemented in a web browser or application of the user terminal 200, and the information receiving unit 131 of the control unit 130 of the server terminal 100 receives the request information input by the user (for example, "Please assign a paid account to Zoom (registered trademark) (specific application)") from the user terminal 200 via the communication unit 110. The information processing unit 132 of the control unit 130 stores the received request information in the user data storage unit 121 and / or chatbot data storage unit 122 of the memory unit 120 as user data 1000 and / or chatbot data 2000.

[0039] Next, in the process of step S202, the information processing unit 132 refers to the knowledge data stored in the chatbot data storage unit 122 (or an external database) of the memory unit 120 based on the vector data obtained by vectorizing the above request information via the LLM 400, and searches for similar vector data. For example, knowledge data for the above request example may include knowledge such as "Zoom (registered trademark) (a specific application) cannot be assigned to temporary workers. Please apply after checking with your supervisor."

[0040] If knowledge data is detected as the search result of step S202, in step S204, the information processing unit 132 acquires a response text generated by the LLM 400 based on data corresponding to the approximate value extracted as the knowledge search result. On the other hand, if knowledge data is not detected as the search result of step S202 (or if the match rate of the detected approximate value is equal to or lower than a certain threshold), in step S205, the information processing unit 132 issues a ticket to the operator terminal 300 of the person in charge of system operation, transmits request information, and notifies the person in charge of system operation to respond to the request information. At this time, the information processing unit 132 can also transmit a procedure manual based on an operation flow to the operator terminal 200. An example of the procedure manual is information describing a procedure such as "1. Log in to Zoom (registered trademark) with an administrator account. 2. Add the requester's address from https: / / zoom.us / account / user# / . 3. Specify a license user." At this time, if the server terminal 100 and the application server 500 cooperate with each other via an API, the requester's address is registered in the target application (Zoom (registered trademark) in this example) by approving the registration of the requester on the application provided by the server terminal 100, and a series of flows is completed, as shown in Fig. 8. When a response to the user's request information is sent via a chatbot, or via the operator or the application, the user is notified that the response has been completed, and a series of flows is completed.

[0041] As described above, with this embodiment, it is possible to improve business efficiency by introducing AI into request information from users, which was previously handled manually by system operation staff, and by referring to knowledge data and operational flows regarding how to use applications and workflows, it is possible to not only improve efficiency but also achieve more accurate responses.

[0042] Although the embodiments of the present invention have been described above, they can be embodied in various other forms and can be implemented with various omissions, substitutions, and modifications. These embodiments and modifications, as well as omissions, substitutions, and modifications, are included in the technical scope of the claims and their equivalents. [Explanation of symbols]

[0043] 1 System 100 Server terminal, 110 Communication unit, 120 Storage unit, 130 Control unit, 200 User terminal, 300 Operator terminal, 400 LLM, 500 Application server, NW1 Network

Claims

1. A method for supporting a system operation using AI, the method being provided to a system that supports system operation, the system operation including a user terminal of a user who uses an application, a server terminal of a system operation company that operates the application, and an operator terminal of a person in charge of the operation, the user terminal, the server terminal, and the operator terminal being connected via a network, The server terminal includes: receiving request information from the user terminal; referring to a natural language analysis model connected to the server terminal based on the request information, and searching for knowledge data including an operational flow of the application; receiving answer information generated by the natural language analysis model based on the search results; Transmitting the generated answer information to the user terminal; If no knowledge data is detected as a result of the search, a notification is sent to the operator terminal to generate answer information; transmit, together with the notification, a procedure manual for the person in charge of the operation based on the operation flow, which is to be used as a reference when generating the response information, to the operator terminal; a screen of the application for executing an operation flow related to the request information based on the procedure manual is displayed on the operator terminal via an application server of the application.

2. The method of claim 1 , further comprising transmitting the answer information to the user terminal via the application.

3. The method according to claim 1 , further comprising the step of transmitting the response information received from the operator terminal to the user terminal via the application.

4. The method according to claim 1 , wherein the server terminal stores the knowledge data in a storage unit.