Product scheme generation method and device, equipment, medium and product

Abstract

The embodiment of the invention provides a product scheme generation method and device, equipment, a medium and a product, and belongs to the technical field of computer application. The method comprises the following steps: calling a domain-driven design model to generate a business process, corresponding to a business scene, of a target product according to the business scene corresponding to the target product; extracting each system function menu required by the target product from the business process; the authority of the system corresponding to each system function menu is broken through through a single sign-on technology, and the system function menus are combined to obtain an integration process of the target product; performing multiple rounds of conversations based on the integration process through the intelligent assistant to obtain a target product scheme of the target product; wherein the intelligent assistant is obtained by training the intelligent large model based on the product field data corresponding to the target product. The method and the device can be applied to business scenes such as financial science and technology, medical health and the like, and can improve the generation efficiency of the product scheme.

Description

Technical Field

[0001] The present application relates to the field of computer application technology, and in particular to a method, device, equipment, medium and product for generating a product solution. Background Art

[0002] With the continuous development of the insurance market, the number and variety of insurance products currently available are enormous, covering a wide range of categories, including health insurance, life insurance, property and casualty insurance, and accident insurance. While this diversity and complexity provides consumers with abundant choices, it also presents significant challenges for insurance professionals. In practice, certain specific insurance scenarios often require high concentration and timeliness. For example, insurance product demands targeting specific seasonal risks (such as accident insurance during peak travel season) or specific demographics (such as high-end medical insurance for high-income groups) require rapid response to market changes and the launch of products that meet these needs.

[0003] However, current insurance product development often relies on manual offline communication and goes through a complex versioning process (including service configuration, finance, etc.) to obtain new products and then bring them to market. This brings about the problem of low efficiency in the generation of current product solutions. Summary of the Invention

[0004] The main purpose of the embodiments of the present application is to propose a method, device, equipment, medium and product for generating a product solution, aiming to improve the efficiency of generating product solutions.

[0005] To achieve the above objectives, a first aspect of an embodiment of the present application provides a method for generating a product solution, the method comprising: Calling the domain-driven design model to generate the business process of the target product corresponding to the business scenario according to the business scenario of the target product; Extracting various system function menus required by the target product from the business process; The system permissions corresponding to each system function menu are opened up through single sign-on technology, and each system function menu is combined to obtain the integration process of the target product; The intelligent assistant conducts multiple rounds of dialogue based on the integration process to obtain the target product solution of the target product; wherein, the intelligent assistant trains the intelligent big model based on the product domain data corresponding to the target product to obtain In some embodiments, the step of conducting multiple rounds of dialogues based on the integration process by the intelligent assistant to obtain a target product solution for the target product includes: Conduct multiple rounds of dialogues based on the integration process through an intelligent assistant to obtain an initial product plan for the target product; Acquire first content related to the initial product solution; wherein the first content includes one of the following: a text description, a reference image, an audio script, and a video script; Invoking a generative model to determine, based on the first content, second content of the initial product solution; wherein the second content includes at least one of the following: a product manual of the initial product solution determined based on the text description; a poster of the initial product solution determined based on the reference image; an audio of the initial product solution determined based on the audio script; or a video of the initial product solution determined based on the video script; The target product plan is determined based on the second content of the initial product plan and the initial product plan.

[0006] In some embodiments, the intelligent assistant conducts multiple rounds of dialogue based on the integration process to obtain an initial product solution for the target product, including: Conduct multiple rounds of dialogue with internal users based on the preset dialogue process to obtain the target needs of the internal users; Based on the target requirements and the product domain data in the intelligent assistant, an initial product solution for the target product is generated.

[0007] In some embodiments, calling the domain-driven design model to generate a business process of the target product corresponding to the business scenario according to the business scenario of the target product includes: The business scenario corresponding to the target product is input into the domain-driven design model, the characteristic information of the target product is configured based on the business scenario through the domain-driven design model, and the business process of the target product corresponding to the business scenario is generated based on the characteristic information, wherein the characteristic information includes roles, nodes, functions and menus.

[0008] In some embodiments, before calling the domain-driven design model to generate a business process of the target product corresponding to the business scenario based on the business scenario of the target product, the method further includes: Obtain external user feedback on existing products and development trend data of current insurance business in related business scenarios; Generate a current insurance analysis report based on the feedback information and the development trend data; Based on the current insurance analysis report, the insurance needs of the external user are evaluated to obtain business demand information; wherein, the business demand information is used to determine the business scenario to which the target product belongs.

[0009] In some embodiments, the method further comprises: Obtaining a generation log of the target product solution; A notification email is sent to internal users based on the generation log, and a corresponding report is generated based on the generation log at a preset period.

[0010] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a device for generating a product solution, the device comprising: A generation module is used to call the domain-driven design model to generate a business process corresponding to the business scenario of the target product according to the business scenario of the target product; An extraction module, used to extract various system function menus required by the target product from the business process; The first obtaining module is used to open up the system permissions corresponding to the various system function menus through single sign-on technology, combine the various system function menus, and obtain the integration process of the target product; The second obtaining module is used to conduct multiple rounds of dialogues through an intelligent assistant based on the integration process to obtain a target product solution for the target product; wherein, the intelligent assistant obtains the target product by training an intelligent big model based on the product domain data corresponding to the target product.

[0011] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.

[0012] To achieve the above-mentioned purpose, the fourth aspect of the embodiments of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the method described in the first aspect.

[0013] To achieve the above-mentioned purpose, the fifth aspect of the embodiments of the present application proposes a computer program product, which is stored in a storage medium and executed by at least one processor to implement the method described in the first aspect.

[0014] The product solution generation method, device, equipment, medium, and product proposed in this application generate a business process for the target product corresponding to the business scenario by calling a domain-driven design model based on the business scenario corresponding to the target product, and then extract the various system function menus required by the target product from the business process. Secondly, the system permissions corresponding to each system function menu are opened up through single sign-on technology, and the various system function menus are combined to obtain the integrated process of the target product. Finally, the target product solution for the target product is obtained by conducting multiple rounds of dialogues based on the integrated process through an intelligent assistant; wherein the intelligent assistant trains the intelligent large model based on the product domain data corresponding to the target product. In this way, the domain-driven design model is called to design the business process corresponding to the business scenario. When the business scenario changes, only the corresponding configuration needs to be adjusted. For each system function menu in the business process, the permissions are opened up using single sign-on technology, so that the originally scattered system function menus are organically combined, breaking down the barriers between systems. Then, based on the integration process, the target product plan is automatically generated through multiple rounds of dialogue between the intelligent assistant and the user. This not only simplifies the existing process and improves the flexibility of configuration, but also improves the accuracy and generation efficiency of the product plan. Furthermore, the efficient generation of product plans can also improve the operational efficiency of insurance companies. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flow chart of a method for generating a product solution provided in an embodiment of the present application; Figure 2 yes Figure 1 Flowchart of step S104 in FIG. Figure 3 yes Figure 2 Flowchart of step S201 in FIG. Figure 4 yes Figure 1 Flowchart of step S101 in FIG. Figure 5 yes Figure 1 The flowchart before step S101 in FIG. Figure 6 This is another flow chart of the method for generating a product solution provided in an embodiment of the present application; Figure 7 This is another flow chart of the method for generating a product solution provided in an embodiment of the present application; Figure 8 This is a schematic diagram of the structure of a device for generating a product solution provided in an embodiment of the present application; Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0017] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0019] First, let’s analyze some of the terms used in this application: Artificial intelligence (AI) is a new technical discipline that studies and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence. A branch of computer science, AI seeks to understand the essence of intelligence and produce new intelligent machines that can respond in a manner similar to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, and expert systems. AI can simulate the information processes of human consciousness and thinking. It also encompasses the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, to perceive the environment, acquire knowledge, and use that knowledge to achieve optimal results.

[0020] Natural language processing (NLP): NLP uses computers to process, understand, and apply human languages ​​(such as Chinese and English). NLP is a branch of artificial intelligence and an interdisciplinary subject between computer science and linguistics, often referred to as computational linguistics. Natural language processing includes grammatical analysis, semantic analysis, and discourse understanding. Natural language processing is commonly used in technical fields such as machine translation, handwritten and printed character recognition, speech recognition and text-to-speech conversion, information intent recognition, information extraction and filtering, text classification and clustering, public opinion analysis, and opinion mining. It involves data mining related to language processing, machine learning, knowledge acquisition, knowledge engineering, artificial intelligence research, and linguistic research related to language computing.

[0021] Information Extraction: A text processing technology that extracts specified types of entity, relationship, event, and other factual information from natural language text and forms structured data output. Information extraction is a technology that extracts specific information from text data. Text data is composed of some specific units, such as sentences, paragraphs, and chapters. Text information is composed of some small specific units, such as characters, words, phrases, sentences, paragraphs, or a combination of these specific units. Extracting noun phrases, names, place names, etc. from text data is all text information extraction. Of course, the information extracted by text information extraction technology can be of various types.

[0022] Based on this, the embodiments of the present application provide a method, apparatus, device, medium and product for generating a product solution, aiming to improve the efficiency of generating a product solution.

[0023] The method, device, equipment, medium and product for generating the product solution provided in the embodiments of the present application are specifically illustrated through the following embodiments. First, the method for generating the product solution in the embodiments of the present application is described.

[0024] The method for generating a product solution provided in the embodiment of the present application relates to the field of computer application technology. The method for generating a product solution provided in the embodiment of the present application can be applied to electronic devices, and further, can be applied to the software of electronic devices. The electronic device can be a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server can be configured as an independent physical server, or as a server cluster or distributed system composed of multiple physical servers, or as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the method for generating a product solution, etc., but is not limited to the above forms.

[0025] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0026] It should be noted that in each specific embodiment of the present application, when it comes to the need to perform relevant processing based on data related to the user's identity or characteristics, such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0027] The method for generating product solutions in the embodiments of the present application can be applied to business scenarios such as financial technology, medical health, and especially to solution generation for insurance systems. At the same time, the method in the embodiments of the present application is also applicable to other systems with business scenarios, such as banking systems, transaction systems, and order systems.

[0028] Figure 1 This is an optional flowchart of the method for generating a product solution provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S103.

[0029] Step S101: calling the domain-driven design model to generate a business process of the target product corresponding to the business scenario according to the business scenario of the target product; Step S102, extracting various system function menus required by the target product from the business process; Step S103: Using single sign-on technology, the system permissions corresponding to each system function menu are opened up, and each system function menu is combined to obtain the integration process of the target product; Step S104: The intelligent assistant conducts multiple rounds of dialogue based on the integration process to obtain a target product solution for the target product; wherein the intelligent assistant trains the intelligent big model based on the product domain data corresponding to the target product.

[0030] Steps S101 to S103 shown in the embodiment of the present application generate a business process of the target product corresponding to the business scenario by calling the domain-driven design model according to the business scenario corresponding to the target product, and then extract the various system function menus required by the target product from the business process. Secondly, the permissions of the systems corresponding to the various system function menus are opened up through the single sign-on technology, and the various system function menus are combined to obtain the integrated process of the target product. Finally, the target product solution of the target product is obtained by conducting multiple rounds of dialogues based on the integrated process through the intelligent assistant; wherein, the intelligent assistant trains the intelligent big model based on the product domain data corresponding to the target product. In this way, the domain-driven design model is called to design the business process corresponding to the business scenario. When the business scenario changes, only the corresponding configuration needs to be adjusted. For each system function menu in the business process, the permissions are opened up using the single sign-on technology, so that the system function menus originally scattered are organically combined together, breaking the barriers between systems. Then, based on the integration process, the target product plan is automatically generated through multiple rounds of dialogue between the intelligent assistant and the user. This not only simplifies the existing process and improves the flexibility of configuration, but also improves the accuracy and generation efficiency of the product plan. Furthermore, the efficient generation of product plans can also improve the operational efficiency of insurance companies.

[0031] In some embodiments, step S101 identifies and analyzes the business scenario to which the target product belongs. Based on the Domain-Driven Design (DDD) model, flexible and configurable business processes are implemented by configuring business scenario roles (e.g., underwriter, claims adjuster, customer, etc.), nodes (key steps in the business process, such as underwriting review and claims processing), functions (specific operational functions corresponding to each node, such as information entry and approval), and menus (user-friendly interface menus).

[0032] It should be noted that a business scenario can be the application scenario and demand background of the target product in a specific business field, including factors such as product type (such as health insurance, life insurance, etc.), target customer group, and market trends. Business scenarios can also include risk assessment scenarios, claims processing scenarios, customer interaction scenarios, and other business scenarios.

[0033] The DDD model can be used to understand and design software systems with a domain-centric approach, and can help decompose complex business requirements into manageable domain models.

[0034] A business process can be a series of steps and operations designed to achieve specific business goals, including various links from demand analysis, plan formulation to product launch and subsequent management.

[0035] For example, let's take a health insurance product as an example. The target customer group is determined to be middle-aged and elderly people. Based on the DDD model, a business process is designed that includes health assessment, plan recommendation, underwriting, and claims processing.

[0036] In step S102 of some embodiments, the function menu required for each link of the target product is extracted from the business process.

[0037] It should be noted that the system function menu can be a specific function item provided in each business system, such as the customer information entry function in the customer management system, the underwriting rule configuration function in the underwriting system, etc.

[0038] In step S103 of some embodiments, the permissions of various systems are connected through single sign-on (SSO) technology, the function menus are combined into the same process, and the functions originally scattered in various systems are connected in series into the same process.

[0039] It should be noted that a consolidation process can be defined as integrating functional menus scattered across different systems into a unified process, enabling one-stop processing of business operations. Single sign-on technology can be an authentication technology that allows users to log in once using a single set of credentials (such as a username and password), and then access multiple related but independent systems or applications without having to re-enter those credentials.

[0040] In some implementations, single sign-on technology can be used to connect permissions across various systems. A unified user authentication and authorization mechanism can be established to ensure seamless user switching between systems. Function menus can then be integrated into business processes. Finally, according to the logical sequence of the business process, function menus can be sequentially integrated into the corresponding links to form a complete integrated process.

[0041] In other implementation methods, middleware or API gateway technology can be used to realize data interaction and function calls between different systems, and then integrate the function menu into the corresponding links according to the logical order of the business process to form a complete integration process.

[0042] For example, let's take the health insurance product in the insurance business as an example: 1. Select SSO technology, configure the SSO authentication server, and implement unified user login.

[0043] Second, based on the permissions of the business process, identify the function menus required for each step. Extract the "customer information entry" function from the customer management system, the "underwriting rule configuration" and "risk assessment" functions from the underwriting system, and the "performance tracking" function from the performance management system. Filter and organize the function menus to ensure that each function menu meets the business process requirements and permission settings.

[0044] Third, sort and organize the functional menus according to the logical order of the business process: customer information entry → underwriting rule configuration → risk assessment → product configuration → performance tracking. Use a workflow engine to combine these functional menus into a complete business process. Test and optimize the integrated business process to ensure that each step is executed correctly. The resulting integrated business process for health insurance products integrates customer information entry, underwriting, product configuration, and performance tracking, achieving a one-stop business operation.

[0045] In step S104 of some embodiments, the intelligent model is trained using product domain data to generate an intelligent assistant. The intelligent assistant then engages in multiple rounds of dialogue with the user, understanding the user's input, generating appropriate responses, and guiding the user to clearly express their needs. Based on the results of these multiple rounds of dialogue and integrated into the process, a product solution that meets the user's needs is output.

[0046] It should be noted that the intelligent assistant can be a model built based on AI technology and trained using product domain data, and can perform intelligent configuration and recommendations based on integration processes and user needs.

[0047] Multi-round dialogue can be a continuous multi-round interactive dialogue between the product generation system and the user, which is used to collect user needs, provide information and guide operations.

[0048] The target product solution can be the final product solution generated based on user needs and integration processes, including detailed product configuration, functional description, application cases, etc.

[0049] Product domain data can be various data related to insurance products, including historical business data, market trend data, customer behavior data, product feature data, etc.

[0050] In some implementations, natural language generation technology can be introduced for multi-round dialogues to improve the naturalness and fluency of the dialogues.

[0051] In other implementations, knowledge graph technology can be combined with intelligent assistants to enhance their understanding and reasoning capabilities of business knowledge.

[0052] For example, in the health insurance product business process, a multi-round conversation takes place between the user and the intelligent assistant. The user enters "I want to apply for health insurance," and the intelligent assistant asks detailed questions such as "What is the target user's age? Do they have any chronic conditions?" Based on the user's answers, the intelligent assistant generates a target product plan with detailed information such as insurance coverage, premium calculation, and claim conditions.

[0053] See also Figure 2 In some embodiments, step S104 may include but is not limited to steps S201 to S204: Step S201: Conduct multiple rounds of dialogues with the intelligent assistant based on the integration process to obtain an initial product plan for the target product; Step S202: Acquire first content related to the initial product solution; wherein the first content includes at least one of the following: a text description, a reference image, an audio script, and a video script; Step S203: Invoke the generative model to determine the second content of the initial product solution based on the first content; wherein the second content includes at least one of the following: a product manual of the initial product solution determined based on the text description; a poster of the initial product solution determined based on the reference image; an audio of the initial product solution determined based on the audio script; or a video of the initial product solution determined based on the video script. Step S204: Determine the target product solution based on the second content of the initial product solution and the initial product solution.

[0054] In step S201 of some embodiments, based on the integration process, multiple rounds of dialogues are conducted between the intelligent assistant and the user, and an initial product solution is generated based on the results of the multiple rounds of dialogues.

[0055] In step S202 of some embodiments, the first content type to be acquired is determined based on the requirements of the initial product plan. For example, if the initial product plan is a health insurance product, relevant text descriptions (such as product introductions and terms and conditions), reference images (such as reference images of promotional posters), audio scripts (such as product promotional audio scripts), and video scripts (such as product introduction video scripts) may be acquired.

[0056] In some implementations, the corresponding first content may be obtained from an internal database, an external data source, or material provided by a user.

[0057] In other implementations, data mining technology is introduced to automatically obtain relevant material content from the Internet.

[0058] In step S203 of some embodiments, the first content is input into a generative model to generate second content, and the generated second content may be reviewed and optimized.

[0059] In some implementations, AI-generated content (AIGC) can be used to generate posters, header images, audio, video, and product manuals required for the product, thereby enriching product content.

[0060] In other implementations, a manual review process can be introduced to perform final quality control on the generated content.

[0061] In some embodiments, step S204 integrates the initial product proposal with the generated secondary content. The secondary content (e.g., product instructions, posters, audio, video, etc.) is added to the initial product proposal to form a complete product proposal. The integrated product proposal is reviewed and verified, and the final target product proposal is released.

[0062] In some implementations, the initial product solution can be directly combined with the generated second content to obtain a final target product solution.

[0063] In other implementations, the target product solution can be adjusted periodically in combination with a user feedback mechanism to obtain a more complete product solution.

[0064] In the embodiment of the present application, it should be noted that the initial product plan can be a preliminary product plan generated based on internal user needs and business processes, including basic product information and basic functional configuration.

[0065] The first content can be various material contents related to the initial product plan, used to further enrich and improve the product plan. The first content includes at least one of the following: text description, reference image, audio script and video script.

[0066] Generative models are AI-based models that generate new content based on input. Examples include Generative Pre-trained Transformers (GPT) and Bidirectional Encoder Representations from Transformers (BERT).

[0067] The second content can be generated based on the first content and is more specific and complete, related to the initial product proposal. The second content includes at least one of the following: a product manual generated based on the text description, a poster generated based on the reference image, an audio file generated based on the audio script, or a video file generated based on the video script.

[0068] For example, using health insurance as an example, first, a user engages in a multi-turn conversation with an intelligent assistant, entering a requirement: "Apply for a health insurance policy. The users are 60 and 62 years old, with a history of chronic conditions." The intelligent assistant generates an initial product plan based on the conversation, including information such as coverage and premium calculation. Second, based on the initial product plan, the first piece of content required is determined: a text description of the product introduction, a reference image for the promotional poster, an audio transcript of the product promotional speech, and a video transcript of the product introduction video. Third, the second piece of content for the initial product plan is determined: the text description can be input into a GPT model to generate a detailed product manual. The reference image can be input into an image generation model to generate a promotional poster. The audio transcript can be input into a speech synthesis model to generate the product promotional audio. The video transcript can be input into a video generation model to generate the product introduction video. Fourth, the generated product manual, promotional poster, audio, and video content are integrated into the initial product plan. The integrated product plan is reviewed and verified to ensure all content is accurate. Finally, the final target product plan is released for users to review and use. Through the above steps, the final health insurance product plan not only contains basic product information, but also includes detailed product manuals, promotional posters, audio and video content, which can fully meet user needs and market promotion requirements.

[0069] The embodiments of the present application achieve intelligent interaction with users through multiple rounds of dialogue, accurately understand user needs, and improve the customization of product solutions. By obtaining the first content related to the initial product solution, basic materials are provided for the subsequent generation of richer and more complete product solutions. The second content is generated through a generative model, which can improve the efficiency and quality of content generation. At the same time, the second content helps enrich the content of the product solution and improve the market competitiveness of the product.

[0070] See also Figure 3 In some embodiments, step S201 may include but is not limited to steps S301 to S204: Step S301: Conduct multiple rounds of dialogue with internal users based on a preset dialogue process to obtain the internal users' target needs; Step S302: Generate an initial product solution for the target product based on the target requirements and the product domain data in the intelligent assistant.

[0071] In step S301 of some embodiments, based on the integration process, a multi-round dialogue process and questions are designed, and a connection is established with the internal user via the intelligent assistant to initiate a multi-round dialogue. The internal user is guided through the dialogue to express their needs, and the internal user's answers and the dialogue process are recorded for subsequent product solution generation.

[0072] In step S302 of some embodiments, the target requirements acquired through multiple rounds of conversation are input into the intelligent assistant, which then generates a preliminary product solution based on the trained product domain data. The generated preliminary solution undergoes a preliminary review and outputs the initial product solution. The initial product solution can be presented in various formats, such as tables and charts.

[0073] In the embodiment of the present application, it should be noted that the preset dialogue process can be a series of questions and interaction steps designed to guide users to express their needs, and can be customized according to business processes, or according to business processes and user portraits.

[0074] Target requirements can be specific needs and expectations related to the target product expressed by internal users in multiple rounds of conversations.

[0075] Internal users can be staff who directly use the product solution generation method, such as insurance product managers, business analysts, underwriters, etc. Internal users participate in the product solution generation process by engaging in multiple rounds of dialogue with the intelligent assistant.

[0076] For example, let's take the case where an internal insurance user needs to generate a health insurance product reminder plan: Collect product domain data, including historical business data, market trends, and customer behavior data for health insurance products. After preprocessing the data, select an appropriate machine learning algorithm for model training to generate an intelligent assistant. Design a conversational flow to guide internal insurance users in expressing their needs. For example, design questions such as: "What type of health insurance product recommendation plan do you need?", "What is the age range of the target customer group?", and "Do you need specific coverage (such as critical illnesses and hospitalization)?" Use the intelligent assistant to conduct multiple rounds of conversations with the internal insurance user and record their responses. For example, the internal insurance user may respond, "I need to generate a health insurance product recommendation plan for middle-aged and elderly people, including critical illness and hospitalization coverage." Transform the internal insurance user's needs into model inputs and feed them into the intelligent assistant. Based on the trained product domain data, the intelligent assistant generates a preliminary product plan, including basic information such as product name, coverage, premium estimate, and target customer group. Conduct a preliminary review of the generated preliminary product plan to ensure it meets business rules and internal insurance user needs. Output the preliminary product plan and present it to the internal insurance user in the form of a text description and a table.

[0077] This embodiment of the application provides rich data support for the intelligent assistant by acquiring product domain data. Through multiple rounds of dialogue, it can gain a deeper understanding of the specific needs of internal users, improving the accuracy and completeness of demand acquisition. Generating preliminary product solutions based on internal user needs can improve work efficiency, reduce manual intervention, and shorten the product development cycle.

[0078] See also Figure 4 In some embodiments, step S101 may include but is not limited to step S401: Step S401: Input the business scenario corresponding to the target product into the domain-driven design model, configure the characteristic information of the target product based on the business scenario through the domain-driven design model, and generate the business process of the target product corresponding to the business scenario based on the characteristic information, wherein the characteristic information includes roles, nodes, functions and menus.

[0079] In step S401 of some embodiments, the business scenario corresponding to the target product is input into the domain-driven design model, and a flexible and configurable business process is achieved by configuring the roles of the business scenario (such as underwriter, claims adjuster, customer, etc.), nodes (key steps in the business process, such as underwriting review, claims acceptance, etc.), functions (specific operating functions corresponding to each node, such as information entry, approval, etc.) and menus (interface menus that facilitate user operation).

[0080] In the embodiment of the present application, it should be noted that feature information may be key elements describing a business process, including roles, nodes, functions, and menus.

[0081] In the embodiment of the present application, a business process is designed through a domain-driven design model. This design approach allows only the corresponding configuration to be adjusted when the business scenario changes, without the need for large-scale modifications to the system architecture generated by the entire product. This greatly improves the adaptability and maintainability of the system, and can also better guide users in configuration, reducing the difficulty of user operation.

[0082] See also Figure 5 In some embodiments, before step S101, the following steps may be included but not limited to steps S501 to S503: Step S501: Obtaining feedback from external users on existing products and development trend data of current insurance business on related business scenarios; Step S502: Generate a current insurance analysis report based on the feedback information and development trend data; Step S503: Based on the current insurance analysis report, evaluate the insurance needs of external users to obtain business demand information; wherein the business demand information is used to determine the business scenario to which the target product belongs.

[0083] In some embodiments, step S501 collects external user feedback on existing products through various channels, such as online questionnaires, customer interviews, user evaluation systems, and social media monitoring. Current insurance business development trend data, such as annual insurance market analysis reports and industry regulatory policy updates, is obtained from industry reports, market research institutions, and regulatory agencies. The collected feedback and trend data are collated and pre-processed.

[0084] In some implementations, data analysis tools can be used to perform visual analysis on the collected data to intuitively display the characteristics of feedback information and trend data.

[0085] In other implementations, natural language processing technology can be introduced to extract topics from text data fed back by external users, so as to quickly understand the key issues that external users are concerned about.

[0086] In step S502 of some embodiments, the collected feedback information and development trend data are comprehensively analyzed to generate a detailed insurance analysis report, including market status, user demand analysis, business process problem diagnosis, trend forecasts, etc. The report is reviewed and proofread to ensure the accuracy and logic of the content, and a final report document is generated.

[0087] In some implementations, machine learning algorithms can be combined to learn and optimize historical analysis reports to improve the efficiency and quality of report generation.

[0088] In other implementations, an expert system can be introduced to intelligently review and supplement the report content to ensure the professionalism of the report.

[0089] In step S503 of some embodiments, the insurance analysis report is analyzed to identify the external user's insurance needs. Based on the external user's insurance needs, specific business requirement information is extracted, such as product functionality requirements and business process optimization requirements. This business requirement information is matched with the business scenario to determine the business scenario to which the target product belongs. For example, if the external user requires a health insurance product for the elderly, the business scenario is determined to be "elderly health insurance."

[0090] In this embodiment of the present application, it should be noted that external users may be the recipients of internal user services, i.e., customers or potential customers who ultimately use insurance products. External user feedback information may include feedback and suggestions collected from external users regarding insurance products, services, business processes, and other aspects.

[0091] Development trend data can be data that reflects the overall development direction and trend of the current insurance business, including market growth rate, product innovation trends, changes in customer demand, etc.

[0092] An insurance analysis report can be a report generated after a comprehensive analysis of the collected feedback information and trend data, and can include market status analysis, user demand insights, business problem diagnosis, etc.

[0093] The insurance needs of external users may be their needs and expectations in insurance, such as coverage, insured amount, premium budget, service requirements, etc.

[0094] Business demand information can be specific business needs extracted based on the insurance needs of external users, and is used to guide product design optimization.

[0095] For example, take health insurance products for the elderly as an example: 1. Through online questionnaires and customer interviews, collect feedback from the elderly and their children on health insurance products, such as "I hope common chronic diseases can be covered" and "the premiums should not be too expensive".

[0096] Obtain data on the current health insurance market's growth trends, product innovation directions, and other data from industry reports and market research institutions, such as "the annual growth rate of the elderly health insurance market is 15%" and "chronic disease protection has become the focus of product innovation."

[0097] 2. Using data analysis tools to analyze the collected data, we found that the elderly have a high demand for chronic disease protection, but the premiums of existing products are generally high.

[0098] Write an insurance analysis report, propose the idea of ​​“developing a cost-effective chronic disease health insurance product for the elderly”, and analyze market opportunities and potential risks.

[0099] 3. Organize business personnel and product experts to discuss and analyze the report to determine that the insurance needs of external users are mainly concentrated in chronic disease protection, high cost-effectiveness, etc.

[0100] Extract specific business demand information, such as "products must cover common chronic diseases, such as diabetes, hypertension, etc.", "premiums should be controlled within the range that the elderly can afford, such as no more than 300 yuan per month", etc.

[0101] Match the business demand information with the business scenario and determine that the business scenario to which the target product belongs is "Chronic Disease Health Insurance for the Elderly".

[0102] This embodiment of the application collects user feedback and market trend data to provide comprehensive and accurate data support for subsequent insurance analysis reports. By converting the collected data into insightful analytical results, it can help identify business opportunities and potential risks. By translating external users' insurance needs into specific business requirements, it provides clear direction and basis for product design and business process optimization. By determining the business scenarios for the target products, it provides clear positioning and guidance for subsequent product development and business implementation.

[0103] See also Figure 6 In some embodiments, the method for generating a product solution provided in the embodiments of the present application may also include, but is not limited to, steps S601 to S602: Step S601: Obtain the target product solution generation log; Step S602: Send a notification email to internal users based on the generation log, and generate a corresponding report based on the generation log at a preset period.

[0104] In some embodiments, in step S601, a logging function is enabled in the backend of the product solution generation system to ensure that every operation is recorded. This may include defining the content and format of the log record, including the operation time, user ID, operation type (e.g., dialogue input, solution generation request, etc.), and operation results. The log data is stored in a reliable storage medium, such as a database or file system.

[0105] In some implementations, a distributed logging system, such as the ELK log analysis platform (Elasticsearch, Logstash, and Kibana Stack, ELK Stack), can be used to handle high-concurrency logging requirements and improve the scalability and stability of the product solution generation system.

[0106] In other implementations, data encryption technologies (such as symmetric encryption and asymmetric encryption) can be introduced to encrypt and store sensitive log data to ensure data security.

[0107] In some embodiments, in step S602, required information, such as the progress of product solution generation and key issues, is extracted from the generation log and sent to internal users via email. At the same time, a time period is set to extract content from the generation log, generate a report, and present it to internal users.

[0108] In the embodiment of the present application, it should be noted that the generation log can be a detailed operation record and data information generated during the target product solution generation process, including the time, steps, input content, generation results, etc. of the user operation.

[0109] The preset period can be a time interval pre-set according to business needs, such as daily, weekly, monthly, etc.

[0110] By generating logs, the embodiments of this application can provide detailed data support for subsequent process tracking and troubleshooting. Regularly reporting the progress and status of product solution generation to relevant personnel ensures timely and transparent information delivery. Converting log data into intuitive reports helps managers quickly understand the execution and effectiveness of business processes.

[0111] In view of the above embodiment, the embodiment of the present application also provides a feasible solution description for the method of generating a product solution: 1. Business process design phase, that is, calling the domain-driven design model to generate the business process corresponding to the target product and the business scenario according to the business scenario of the target product.

[0112] Sorting out the business scenarios of insurance products. To sort out the business scenarios of insurance products, it is necessary to conduct in-depth analysis of the business needs and operational processes of insurance products in different scenarios. For example, for auto insurance products, scenarios such as vehicle information entry, risk assessment, and premium calculation should be considered in the underwriting process; scenarios such as accident reporting, on-site investigation, damage assessment and claims settlement should be considered in the claims process. Secondly, a set of flexible and configurable business processes are designed through the domain-driven design model. For example, by configuring the roles of the scenarios (such as underwriters, claims adjusters, customers, etc.), nodes (key steps in the business process, such as underwriting review, claims acceptance, etc.), functions (specific operational functions corresponding to each node, such as information entry, approval, etc.) and menus (interface menus that are convenient for user operation), a flexible and configurable business process is achieved.

[0113] 2. System function integration stage, that is, extracting various system function menus required by the target product from the business process, and opening up the system permissions corresponding to each system function menu through single sign-on technology, combining various system function menus to obtain the integrated process of the target product.

[0114] Insurance business usually involves multiple systems, such as core business systems, claims systems, customer relationship management systems, etc. It is necessary to extract functional menus related to insurance products from these systems, such as policy entry and policy query functions in the core business system, and claim application and claim review functions in the claims system. Secondly, through single sign-on technology, the permissions of each system are connected, the functional menus are combined in the same process, and the functions originally scattered in various systems are connected in series in the same process. That is, SSO technology allows users to log in to multiple applications with one set of login credentials (such as user name and password) without having to log in repeatedly. By connecting the permissions of each system through SSO technology, users can seamlessly access and operate the functional menus of different systems when generating product solutions.

[0115] 3. The intelligent assistant construction stage, that is, through the intelligent assistant, multiple rounds of dialogue are conducted based on the integration process to obtain the initial product plan for the target product.

[0116] First, leveraging the powerful learning and comprehension capabilities of large AI models, they are trained on a vast amount of data from the insurance product sector. This data can include historical policy data, claims data, market data, and customer inquiry data. Through training, the model develops a deep understanding and grasp of the relevant knowledge and business logic of insurance products. The trained model is then packaged into an intelligent assistant (A), enabling its widespread application in multiple insurance product scenarios. For example, in underwriter performance tracking, the intelligent assistant can collect and analyze underwriter work data in real time to generate performance reports. In post-mortem analysis scenarios, it can conduct in-depth analysis of completed business processes to identify existing issues and areas for improvement. In pricing systems, it provides product pricing recommendations based on market data and risk assessment results. In Q&A (question and answer) scenarios, it can quickly and accurately answer underwriters' and customers' questions about insurance products. During underwriting operations, it assists underwriters with risk assessment and decision-making. In product proposal development scenarios, it automatically generates personalized product proposals based on customer needs and market conditions. In addition, the intelligent assistant can cover the entire life cycle of products from listing to clearance, interact with users through multiple rounds of dialogue, and automatically generate product plans, reports, etc.

[0117] 4. The content generation stage is to determine the second content of the initial product plan.

[0118] AIGC technology generates various types of content based on input instructions and requirements. During the insurance product creation process, AIGC technology is used to generate required posters, header images, audio, video, and product manuals, enriching product content. For example, based on the product's characteristics and target customer groups, attractive posters and header images can be generated to attract customer attention; audio and video introductions can be produced to explain product advantages and the claims process; and detailed and accurate product manuals can be generated to facilitate customer understanding of product details.

[0119] 5. Process tracking and monitoring stage, that is, obtaining the generation log of the target product solution, sending notification emails to internal users based on the generation log, and generating corresponding reports based on the generation log at a preset period.

[0120] The process tracking and monitoring stage includes online traceability and task tracking, email reminder functions, and timeliness report generation.

[0121] Online traceability and task tracking record every step of the insurance product creation process, recording detailed information such as the operator, time, and content. Furthermore, each task is tracked to clearly identify the person responsible, start time, and expected completion time, allowing for real-time monitoring of task progress. This facilitates subsequent process tracing and analysis, allowing for timely identification and resolution of issues.

[0122] Email reminders notify relevant personnel promptly when there are changes in task progress (such as task completion, task extension, etc.) or when further action is required from relevant personnel (internal staff). This ensures that everyone is kept informed of work progress and avoids delays caused by untimely information.

[0123] Timeliness report generation is to regularly generate timeliness reports to collect statistics and analyze the entire process of insurance product assembly, including key indicators such as the average processing time of each link and the task completion rate on time.

[0124] For example, Figure 7 As shown, a feasible solution for generating product solutions can be briefly described as follows: first, conduct a market demand analysis (obtain business demand information), match the market demand analysis to the insurance product business scenario, and then, through the use of domain-driven design models and single sign-on technology, establish permissions and configure the process in a system. Secondly, through multiple rounds of dialogue, the intelligent assistant automatically generates the product solution (initial product solution). Then, AIGC is used to produce materials and enrich the content to form the final target product solution. Each of the above steps is recorded and logged, and insurance personnel can be notified via email tracking. Finally, after all steps are confirmed to be correct, the product is launched.

[0125] See also Figure 8 The present application also provides a device for generating a product solution, which can implement the above-mentioned method for generating a product solution. The device includes: A generation module 801 is configured to call a domain-driven design model to generate a business process corresponding to a target product and the business scenario according to the target product; Extraction module 802, used to extract various system function menus required by the target product from the business process; The first obtaining module 803 is used to open up the system permissions corresponding to the various system function menus through single sign-on technology, combine the various system function menus, and obtain the integration process of the target product; The second obtaining module 804 is used to conduct multiple rounds of dialogues based on the integration process through an intelligent assistant to obtain a target product solution for the target product; wherein, the intelligent assistant obtains the target product solution by training an intelligent big model based on product domain data corresponding to the target product.

[0126] The specific implementation of the device for generating the product solution is basically the same as the specific implementation of the method for generating the product solution described above, and will not be repeated here.

[0127] The present application also provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-mentioned method for generating a product solution. The electronic device can be any smart terminal, such as a tablet computer or an in-vehicle computer.

[0128] See also Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is shown. The electronic device includes: The processor 901 can be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902, and the processor 901 calls and executes the method for generating the product solution of the embodiments of this application; Input / output interface 903, used to implement information input and output; Communication interface 904, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.); Bus 905 , which transmits information between various components of the device (e.g., processor 901 , memory 902 , input / output interface 903 , and communication interface 904 ); The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0129] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the method for generating the above-mentioned product solution.

[0130] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0131] An embodiment of the present application also provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for generating the above-mentioned product solution.

[0132] The method, device, equipment, medium and product for generating a product solution provided in the embodiments of the present application generate a business process of the target product corresponding to the business scenario by calling the domain-driven design model according to the business scenario corresponding to the target product, and then extract the various system function menus required by the target product from the business process. Secondly, the system permissions corresponding to each system function menu are opened up through the single sign-on technology, and the various system function menus are combined to obtain the integrated process of the target product. Finally, the target product solution of the target product is obtained by conducting multiple rounds of dialogues based on the integrated process through the intelligent assistant; wherein, the intelligent assistant trains the intelligent big model based on the product domain data corresponding to the target product. In this way, the domain-driven design model is called to design the business process corresponding to the business scenario. When the business scenario changes, only the corresponding configuration needs to be adjusted. For each system function menu in the business process, the single sign-on technology is used to open up the permissions, so that the system function menus originally scattered are organically combined together, breaking the barriers between systems. Then, based on the integration process, the target product plan is automatically generated through multiple rounds of dialogue between the intelligent assistant and the user. This not only simplifies the existing process and improves the flexibility of configuration, but also improves the accuracy and generation efficiency of the product plan. Furthermore, the efficient generation of product plans can also improve the operational efficiency of insurance companies.

[0133] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0134] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0135] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0136] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0137] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0138] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0139] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0140] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0141] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0142] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0143] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A method for generating a product solution, characterized in that: The method comprises: Calling the domain-driven design model to generate the business process of the target product corresponding to the business scenario according to the business scenario of the target product; Extracting various system function menus required by the target product from the business process; The system permissions corresponding to each system function menu are opened up through single sign-on technology, and each system function menu is combined to obtain the integration process of the target product; The intelligent assistant conducts multiple rounds of dialogue based on the integration process to obtain a target product solution for the target product; wherein, the intelligent assistant obtains the target product by training the intelligent big model based on the product domain data corresponding to the target product.

2. The method according to claim 1, characterized in that The intelligent assistant conducts multiple rounds of dialogue based on the integration process to obtain a target product solution for the target product, including: Conduct multiple rounds of dialogues based on the integration process through an intelligent assistant to obtain an initial product plan for the target product; Acquire first content related to the initial product solution; wherein the first content includes one of the following: a text description, a reference image, an audio script, and a video script; Invoking a generative model to determine, based on the first content, second content of the initial product solution; wherein the second content includes at least one of the following: a product manual of the initial product solution determined based on the text description; a poster of the initial product solution determined based on the reference image; an audio of the initial product solution determined based on the audio script; or a video of the initial product solution determined based on the video script; The target product plan is determined based on the second content of the initial product plan and the initial product plan.

3. The method according to claim 2, characterized in that The intelligent assistant conducts multiple rounds of dialogue based on the integration process to obtain an initial product solution for the target product, including: Conduct multiple rounds of dialogue with internal users based on the preset dialogue process to obtain the target needs of the internal users; Based on the target requirements and the product domain data in the intelligent assistant, an initial product solution for the target product is generated.

4. The method according to claim 1, wherein The calling of the domain-driven design model to generate a business process of the target product corresponding to the business scenario according to the business scenario of the target product includes: The business scenario corresponding to the target product is input into the domain-driven design model, the characteristic information of the target product is configured based on the business scenario through the domain-driven design model, and the business process of the target product corresponding to the business scenario is generated based on the characteristic information, wherein the characteristic information includes roles, nodes, functions and menus.

5. The method according to claim 1, wherein Before calling the domain-driven design model to generate a business process of the target product corresponding to the business scenario according to the business scenario of the target product, the method further includes: Obtain external user feedback on existing products and development trend data of current insurance business in related business scenarios; Generate a current insurance analysis report based on the feedback information and the development trend data; Based on the current insurance analysis report, the insurance needs of the external user are evaluated to obtain business demand information; wherein, the business demand information is used to determine the business scenario to which the target product belongs.

6. The method according to claim 1, characterized in that The method further comprises: Obtaining a generation log of the target product solution; A notification email is sent to internal users based on the generation log, and a corresponding report is generated based on the generation log at a preset period.

7. A device for generating a product solution, characterized in that: The device comprises: A generation module is used to call the domain-driven design model to generate a business process corresponding to the business scenario of the target product according to the business scenario of the target product; An extraction module, used to extract various system function menus required by the target product from the business process; The first obtaining module is used to open up the system permissions corresponding to the various system function menus through single sign-on technology, combine the various system function menus, and obtain the integration process of the target product; The second obtaining module is used to conduct multiple rounds of dialogues through an intelligent assistant based on the integration process to obtain a target product solution for the target product; wherein, the intelligent assistant obtains the target product by training an intelligent big model based on the product domain data corresponding to the target product.

8. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the method for generating a product solution according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for generating a product solution according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for generating a product solution as described in any one of claims 1 to 6.

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