Small and medium-sized enterprise SaaS management platform construction method and system based on comprehensive agent

Abstract

The invention relates to the technical field of artificial intelligence, in particular to a small and medium-sized enterprise SaaS management platform construction method and system based on a comprehensive agent, and the method comprises the steps: constructing an SaaS management platform based on an enterprise benchmark architecture; a comprehensive agent is arranged in the SaaS management platform, and the comprehensive agent can automatically generate a complete service flow according to an input service name; the comprehensive agent provides decision support and processing capability for different functional modules of the SaaS management platform by calling the large model; the SaaS management platform supports integration with third-party application programs and services; and a multi-level safety guarantee method is adopted in the running process of the SaaS management platform. The technical problems that management tools of small and medium-sized enterprises are complex, difficult to use and incapable of flexible adjustment can be solved, and digital and intelligent transformation of enterprise management is promoted.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and particularly relates to a method and system for constructing a SaaS management platform for small and medium-sized enterprises based on an integrated intelligent agent. Background Art

[0002] With the rapid development of information technology, enterprise management is gradually transforming towards digitalization and intelligentization. In particular, the widespread application of cloud computing and artificial intelligence technologies has provided new opportunities for enterprises in terms of resource integration, process optimization, and efficiency improvement. Among them, the software as a service (SaaS) model, with its characteristics of low cost, on-demand use, and rapid deployment, has become an important development trend in modern enterprise management solutions, providing flexible and efficient management tools for various enterprises.

[0003] Most existing enterprise management SaaS platforms are based on standardized and modular designs, and are developed around fields such as customer relationship management (CRM), enterprise resource planning (ERP), financial management, and human resource management. These platforms usually provide rich function options, support automated processing of processes and in-depth analysis of data, to meet the requirements of large enterprises in cross-departmental collaboration, multi-level management, and customization needs, and promote the development of enterprise management towards refinement.

[0004] However, existing enterprise management SaaS platforms are generally designed for large enterprises, and their complexity and high cost make it difficult for small and medium-sized enterprises to adapt. Small and medium-sized enterprises usually have limited resources and lack professional IT technical teams, making it difficult to bear high subscription fees and implementation costs. At the same time, the general-purpose design of these platforms cannot meet the diverse and actual demand-oriented management scenarios of small and medium-sized enterprises. Therefore, small and medium-sized enterprises urgently need a low-cost, easy-to-use SaaS management platform with functions that fit their business needs to support the efficient operation and sustainable development of their businesses. Summary of the Invention

[0005] The present application provides a method for constructing a SaaS management platform for small and medium-sized enterprises based on an integrated intelligent agent, which can solve the technical problems of complex, difficult-to-use management tools for small and medium-sized enterprises and the lack of flexible adjustment capabilities, and promote the digital and intelligent transformation of enterprise management. The present application provides the following technical solutions:

[0006] In a first aspect, the present application provides a method for constructing a SaaS management platform for small and medium-sized enterprises based on an integrated intelligent agent, the method comprising:

[0007] Constructing a SaaS management platform based on an enterprise benchmark architecture;

[0008] Setting an integrated intelligent agent within the SaaS management platform, the integrated intelligent agent being capable of automatically generating a complete business process according to an input business name;

[0009] The comprehensive intelligent agent provides decision-making support and processing capabilities for different functional modules of the SaaS management platform by invoking a large model;

[0010] The SaaS management platform supports integration with third-party applications and services;

[0011] During the operation of the SaaS management platform, multi-level security protection methods are adopted.

[0012] In a specific feasible implementation, the construction of the SaaS management platform based on the enterprise benchmark architecture includes:

[0013] The SaaS management platform includes pre-set functional modules designed according to the enterprise benchmark architecture;

[0014] The SaaS management platform adopts a microservices architecture, which splits each functional module of the SaaS management platform into independent services, and the functional modules interact through a lightweight communication protocol.

[0015] In a specific feasible implementation, the comprehensive intelligent agent can automatically generate a complete business process according to the input business name, including:

[0016] After the user inputs the business name, the comprehensive intelligent agent accesses the preset template library, selects the template that best matches the business name in the template library and performs automatic matching;

[0017] The comprehensive intelligent agent performs automated operations according to the steps in the template with the highest matching degree to generate a business process that meets the specifications.

[0018] In a specific feasible implementation, the selection of the template that best matches the business name in the template library and the automatic matching include:

[0019] Define the business name as B, and the template library as T = {T 1 , T 2 , T 3 , …, T m}, and evaluate the matching degree of the business name B and the template T j through the character matching counting function CommonChars(B, T j ):

[0020] M(B, T j ) = CommonChars(B, T j )

[0021] Among them, the character matching counting function CommonChars(B, T j) Represents the number of common characters in business name B and template T j The function calculates through the following steps:

[0022] CommonChars(B, T j ) = |C(B) ∩ C(T j )|

[0023] Where C(B) and C(T j ) are the character sets obtained by transforming business name B and template T respectively j According to the matching degree of all templates and business names, select the template with the best matching degree.

[0024] In a specific feasible implementation, the selection of the most suitable template for the business name in the template library and automatic matching include:

[0025] Define the business name as B, and the template library as T = {T 1 , T 2 , T 3 , …, T m}, and use the following formula to evaluate the matching degree of business name B and template T j :

[0026]

[0027] Where C(B) and C(T j ) are the character sets obtained by transforming business name B and template T respectively j , max(|C(B)|, |C(T j )|) is the normalization factor, and sim(B, T j ) represents the cosine similarity between business name B and template T j ;

[0028] Select the template with the best matching degree according to the matching degree of all templates and business names.

[0029] In a specific feasible implementation, the integration of the SaaS management platform with third - party applications and services includes:

[0030] The SaaS management platform realizes docking with external systems by providing standardized API interfaces, allowing third - party developers to access and expand the platform functions.

[0031] In a specific feasible implementation, the multi - level security guarantee method adopted during the operation of the SaaS management platform includes:

[0032] The SaaS management platform encrypts all transmitted and stored data and implements an authentication method at the same time;

[0033] The SaaS management platform hierarchically configures system permissions based on user roles and responsibilities to ensure that users can only access data and functions related to their responsibilities;

[0034] The SaaS management platform regularly performs security vulnerability scans and penetration tests to fix potential security risks.

[0035] In a second aspect, the present application provides a system for building a SaaS management platform for small and medium-sized enterprises based on an integrated intelligent agent, adopting the following technical solutions:

[0036] A system for building a SaaS management platform for small and medium-sized enterprises based on an integrated intelligent agent includes:

[0037] A SaaS management platform building module for building a SaaS management platform based on an enterprise benchmark architecture;

[0038] An integrated intelligent agent setting module for setting an integrated intelligent agent in the SaaS management platform, and the integrated intelligent agent can automatically generate a complete business process according to the input business name;

[0039] A large model calling module for the integrated intelligent agent to provide decision support and processing capabilities for different functional modules of the SaaS management platform by calling a large model;

[0040] An external access module for the SaaS management platform to support integration with third-party applications and services;

[0041] A security guarantee module for adopting a multi-level security guarantee method during the operation of the SaaS management platform.

[0042] In a third aspect, the present application provides an electronic device, and the device includes a processor and a memory; a program is stored in the memory, and the program is loaded and executed by the processor to implement a method for building a SaaS management platform for small and medium-sized enterprises based on an integrated intelligent agent as described in the first aspect.

[0043] In a fourth aspect, the present application provides a computer-readable storage medium, and a program is stored in the storage medium, and when the program is executed by a processor, it is used to implement a method for building a SaaS management platform for small and medium-sized enterprises based on an integrated intelligent agent as described in the first aspect.

[0044] In summary, the beneficial effects of the present application at least include:

[0045] 1) By building a standardized SaaS management platform based on the enterprise benchmark architecture, combined with the microservices architecture and modular design, the platform can be flexibly configured according to different enterprise needs, thus avoiding the high costs and complexities of traditional SaaS platforms when adapting to enterprises of different scales. This design not only enables small and medium-sized enterprises (SMEs) to select functional modules according to actual needs, avoiding unnecessary expenses, but also simplifies the use of the platform, making it easier to deploy and maintain, and reducing operating costs.

[0046] 2) The introduction of the comprehensive intelligent agent and the support of large model technology endow the platform with a high degree of intelligence in business processes and decision-making support. The comprehensive intelligent agent can automatically generate compliant business flows and provide intelligent decision-making support based on large models, thus helping enterprises operate efficiently without a professional IT team. By intelligently analyzing market trends, customer behavior, financial data, etc., enterprises can better respond to the dynamic market environment and management challenges, improving their decision-making efficiency and accuracy. This intelligent support enables SMEs to achieve refined management and efficient business operations despite limited resources.

[0047] By building a SaaS platform based on the enterprise benchmark architecture and adopting a microservices architecture for modular design, the platform is flexible and scalable, and can provide customized support according to the different development stages and business needs of SMEs. The comprehensive intelligent agent automatically generates compliant business flows according to the business name by accessing the preset template library, and provides intelligent decision-making support and automated processing capabilities for each module by invoking large model technology. In addition, the platform also designs an open ecosystem to support the integration with third-party applications and services, and ensures data security and privacy protection of the platform through multi-level security measures. The overall solution solves the technical problems of complex, difficult-to-use management tools for SMEs without flexible adjustment capabilities through standardized, modular, and intelligent designs, and promotes the digital and intelligent transformation of enterprise management.

[0048] The above description is only an overview of the technical solution of this application. In order to understand the technical means of this application more clearly and implement it according to the content of the specification, the following describes in detail with the preferred embodiments of this application and in conjunction with the accompanying drawings. Description of the Drawings

[0049] Figure 1 It is a schematic flowchart of the method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent agent in an embodiment of this application.

[0050] Figure 2 It is a block diagram of the structure of the system for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent agent in an embodiment of this application.

[0051] Figure 3 It is a block diagram of an electronic device constructed based on an integrated agent-based SaaS management platform for small and medium-sized enterprises in an embodiment of the present application. Detailed implementation manners

[0052] The following will further describe in detail the specific implementation manners of the present application in conjunction with the accompanying drawings and embodiments. The following embodiments are used to illustrate the present application, but are not used to limit the scope of the present application.

[0053] Optionally, the present application takes the method for constructing an integrated agent-based SaaS management platform for small and medium-sized enterprises provided in each embodiment as an example for illustration in an electronic device. The electronic device is a terminal or a server. The terminal can be a mobile phone, a computer, a tablet computer, etc. The type of the electronic device is not limited in this embodiment.

[0054] Refer to Figure 1 , which is a schematic flowchart of a method for constructing an integrated agent-based SaaS management platform for small and medium-sized enterprises provided in an embodiment of the present application. The method at least includes the following steps:

[0055] Step S101: Construct a SaaS management platform based on an enterprise benchmark architecture.

[0056] In step S101, the SaaS management platform is constructed based on an enterprise benchmark architecture, providing a standardized SaaS platform aimed at meeting the basic transaction requirements of small and medium-sized enterprises in various industries and development stages. The core of the platform design is to adopt an enterprise benchmark architecture, which integrates industry best practices and key elements of enterprise management, ensuring that the platform can be flexibly configured according to the specific needs of different enterprises. The platform includes a series of pre-set functional modules, such as strategic planning, product development, supply chain management, marketing, customer service, financial management, human resources, etc. These modules are designed according to the enterprise benchmark architecture to ensure that they can comprehensively support the daily operations of small and medium-sized enterprises in various fields.

[0057] In implementation, in order to achieve efficient system operation and scalability, the SaaS platform adopts a microservices architecture. The microservices architecture splits each functional module of the SaaS platform into independent services, and the modules interact through a lightweight communication protocol, ensuring loose coupling between the modules, thus facilitating independent development, testing, deployment, and maintenance. Each module can run independently and can also cooperate with other modules. It is seamlessly connected through API interfaces and data streams to ensure the unity and efficiency of the entire system. In addition, the microservices architecture makes the platform more flexible, capable of adding, deleting, and adjusting modules according to enterprise needs to meet the management needs of enterprises at different development stages.

[0058] In addition, in terms of modular design, each functional module of the SaaS platform not only has the ability to run independently but can also be quickly adjusted when business requirements change. For example, an enterprise can enable, disable, or customize specific functional modules according to actual situations without affecting the operation of other parts of the platform. Through this modular design, the platform can not only provide personalized services to enterprises but also maintain efficient and reliable performance support in complex enterprise management tasks.

[0059] Step S102: Set up a comprehensive intelligent agent in the SaaS management platform. The comprehensive intelligent agent can automatically generate a complete business process based on the input business name.

[0060] In step S102, the SaaS management platform has a built-in comprehensive intelligent agent. Users only need to input the business name, and the comprehensive intelligent agent can automatically generate a complete business process.

[0061] Specifically, after the user inputs the business name, the comprehensive intelligent agent accesses the preset template library, selects the template that best matches the business name in the template library and performs automatic matching, and then the comprehensive intelligent agent performs automated operations according to the steps in the template with the highest matching degree to generate a business process that meets the specifications.

[0062] In implementation, define the business name as B, and the template library as T = {T 1 , T 2 , T 3 , …, T m}. Evaluate the matching degree between the business name B and the template T j through the character matching counting function CommonChars(B, T j ):

[0063] M(B, T j ) = CommonChars(B, T j )

[0064] Among them, the character matching counting function CommonChars(B, T j ) represents the number of common characters between the business name B and the template T j . The function is calculated through the following steps:

[0065] CommonChars(B, T j ) = |C(B) ∩ C(T j )|

[0066] Among them, C(B) and C(T j ) are the character sets obtained by transforming the business name B and the template T j respectively. Finally, select the template with the best matching degree according to the matching degrees of all templates and the business name.

[0067] In another feasible embodiment, the following formula can also be used to evaluate the matching degree between business name B and template T j :

[0068]

[0069] where C(B) and C(T j ) are the character sets obtained by transforming business name B and template T j respectively, max(|C(B)|, |C(T j )|) is the normalization factor, which is obtained by calculating the sizes of the character sets transformed from business name B and template T j respectively, and then taking the larger value of the two as the normalization factor. sim(B, T j ) represents the cosine similarity between business name B and template T j . In the above formula, by measuring the frequency of each character, the cosine similarity takes into account the semantic level on the basis of the character intersection. Even if the character intersection of two business names is small, but their semantic structures or usage frequencies are close, the cosine similarity will regard them as similar, thus avoiding missing potential templates with high matching degrees. In a multiplicative way, the matching degrees of the two parts will affect each other, avoiding the over-dominant effect of a certain factor on the final result. For example, if the character intersection is very low but the cosine similarity is high, then the final matching degree will still not be very high, and vice versa. This design can comprehensively reflect the similarity of characters and semantics.

[0070] Optionally, the formula for evaluating the matching degree Match(B, T j ) between business name B and template T j can also be as follows:

[0071]

[0072] where C(B) and C(T j ) are the character sets obtained by transforming business name B and template T j respectively, sim(B, T j ) represents the cosine similarity between business name B and template T j , and sem(B, T j ) represents the Manhattan distance between business name B and template T j .

[0073] In the above formula, the part of the intersection and union of the character sets evaluates the character similarity between the business name and the template. The overlap degree of the two sets at the character level is measured by calculating the ratio of the character intersection to the union. The larger the ratio, the more similar they are at the character level. Subsequently, the cosine similarity in the vector space of the business name and the template is calculated to measure their semantic similarity. Cosine similarity can take into account the arrangement of words and the grammatical structure, reflecting the deeper similarity between the business name and the template. Finally, the Manhattan distance is used to evaluate the semantic difference between the business name and the template. It helps to identify cases where there are still some semantic differences even though there are semantic similarities by measuring the absolute differences of the two vectors in each dimension. The Manhattan distance is especially suitable for measuring discrete features in a multi-dimensional space, and it can effectively capture context differences or different word meanings. The formula integrates the matching degrees at the character level and the semantic level, as well as the weighting mechanism through cosine similarity and Manhattan distance, enabling not only literal matching to be considered but also deeper semantic similarities to be captured. This helps to overcome the method that only relies on character-level matching and avoid mis-matching.

[0074] Step S103: The comprehensive intelligent agent provides decision support and processing capabilities for different functional modules of the SaaS management platform by calling the large model.

[0075] Specifically, in the SaaS management platform, the comprehensive intelligent agent not only has the function of automatically generating business processes but also can provide intelligent decision support and automated processing capabilities for each functional module by calling large model technology.

[0076] For example, in the strategic planning module, the comprehensive intelligent agent calls the large model to analyze market trends and competitor situations and provides strategic suggestions. In the product development module, the comprehensive intelligent agent calls the large model to predict market demand and optimize the product design and development process. In the supply chain management module, the comprehensive intelligent agent calls the large model to optimize inventory management and logistics scheduling and reduce operating costs. In the marketing module, the comprehensive intelligent agent calls the large model to analyze customer behavior and provides precise marketing strategies. In the customer service module, the comprehensive intelligent agent calls the large model to provide intelligent customer service support and improve customer satisfaction. In the financial management module, the comprehensive intelligent agent calls the large model to conduct financial forecasts and risk assessments and optimize fund management. In the human resources module, the comprehensive intelligent agent calls the large model to conduct talent recruitment and performance management and enhance team efficiency.

[0077] Step S104: The SaaS management platform supports the integration with third-party applications and services.

[0078] In step S104, to enhance the flexibility and scalability of the SaaS management platform, the platform designs an open ecosystem that supports integration with third-party applications and services. By providing standardized API interfaces, the platform can achieve seamless docking with external systems, allowing third-party developers to access and expand the platform's functions. Each functional module adopts a loose-coupling design, enabling third-party applications to be flexibly integrated into specific modules or to expand functions. At the same time, the platform provides a developer community and technical support to promote resource sharing and technical exchanges, helping partners quickly respond to market changes and improve their technical capabilities.

[0079] On this basis, the platform's open ecosystem can support various business scenarios and industry requirements, and third-party services can provide customized solutions for the platform according to specific needs. In addition, the platform ensures the security and privacy protection of data during the integration process through improved data security and compliance guarantee measures. The open ecosystem not only enhances the applicability and expandability of the platform, but also provides more innovation and cooperation opportunities for enterprises, helping enterprises achieve more efficient resource integration and business collaboration.

[0080] Step S105, The SaaS management platform adopts a multi-level security guarantee method during operation.

[0081] In step S105, to ensure the security of the SaaS management platform, the platform adopts a multi-level security guarantee method. First, the platform encrypts all transmitted and stored data, using the AES-256 encryption algorithm and the TLS protocol to ensure the confidentiality and integrity of data during transmission. At the same time, the platform implements strict authentication methods, including multi-factor authentication, by verifying user identities, devices, and behavioral characteristics to prevent unauthorized access.

[0082] Secondly, the platform configures system permissions hierarchically based on user roles and responsibilities through a refined permission management method, ensuring that users can only access data and functions related to their responsibilities. Moreover, the platform implements a comprehensive log auditing function to record and monitor user operation behaviors in real time, facilitating the tracking of abnormal activities and timely response to potential threats.

[0083] In addition, the platform regularly performs security vulnerability scans and penetration tests to ensure the security of the system by fixing potential security risks. Combining security tools such as firewalls, intrusion detection systems (IDS), and anti-virus software, the platform can effectively respond to external attacks and comprehensively protect the privacy of user data and the overall security of the platform.

[0084] In summary, this application aims to solve the problems of the existing SaaS platform being complex, costly, and difficult to meet the diverse needs of small and medium-sized enterprises. By building a SaaS platform based on the enterprise benchmark architecture and adopting a microservices architecture for modular design, the platform is flexible and scalable, and can provide customized support according to the different development stages and business needs of small and medium-sized enterprises. The comprehensive intelligent agent can automatically generate a business process that meets the specifications according to the business name by accessing the preset template library, and provides intelligent decision-making support and automated processing capabilities for each module by calling large model technology. In addition, the platform also designs an open ecosystem to support integration with third-party applications and services, and ensures data security and privacy protection of the platform through multi-level security measures. The overall solution solves the technical problems of complex, difficult-to-use management tools for small and medium-sized enterprises without flexible adjustment capabilities through standardized, modular, and intelligent design, and promotes the digital and intelligent transformation of enterprise management.

[0085] Specifically, by building a standardized SaaS management platform based on the enterprise benchmark architecture and combining a microservices architecture and modular design, the platform can be flexibly configured according to different enterprise needs, thus avoiding the high costs and complexities of traditional SaaS platforms when adapting to enterprises of different scales. This design not only enables small and medium-sized enterprises to select functional modules according to actual needs, avoiding unnecessary expenses, but also simplifies the use of the platform, making it easier to deploy and maintain, and reducing operating costs.

[0086] Secondly, the introduction of the comprehensive intelligent agent and the support of large model technology endow the platform with a high degree of intelligence in business processes and decision-making support. The comprehensive intelligent agent can automatically generate a business process that meets the specifications and provide intelligent decision-making support based on large models, thus helping enterprises operate efficiently without a professional IT team. By intelligently analyzing market trends, customer behavior, financial data, etc., enterprises can better respond to dynamic market environments and management challenges, improving their decision-making efficiency and accuracy. This intelligent support enables small and medium-sized enterprises to achieve refined management and efficient business operations despite limited resources.

[0087] Figure 2 It is the structural block diagram of a system for building a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent agent provided by an embodiment of this application. The system at least includes the following modules:

[0088] The SaaS management platform building module is used to build a SaaS management platform based on the enterprise benchmark architecture;

[0089] The comprehensive intelligent agent setting module is used to set a comprehensive intelligent agent in the SaaS management platform. The comprehensive intelligent agent can automatically generate a complete business process according to the input business name;

[0090] The large model invocation module is used for the comprehensive intelligent agent to provide decision-making support and processing capabilities for different functional modules of the SaaS management platform by invoking the large model;

[0091] The external access module is used for the SaaS management platform to support the integration with third-party applications and services;

[0092] The security guarantee module is used to adopt multi-level security guarantee methods during the operation of the SaaS management platform.

[0093] For relevant details, refer to the above method embodiments.

[0094] Figure 3 It is a block diagram of an electronic device provided by an embodiment of the present application. The device at least includes a processor 401 and a memory 402.

[0095] The processor 401 may include one or more processing cores, such as: a 4-core processor, an 8-core processor, etc. The processor 401 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 401 may also include a main processor and a coprocessor. The main processor is a processor used to process data in the wake state, also known as the CPU (Central Processing Unit); the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 401 may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for the rendering and drawing of the content to be displayed on the display screen. In some embodiments, the processor 401 may also include an AI (Artificial Intelligence) processor, and the AI processor is used to process computational operations related to machine learning.

[0096] The memory 402 may include one or more computer-readable storage media, and the computer-readable storage media may be non-transitory. The memory 402 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 402 is used to store at least one instruction, and the at least one instruction is used to be executed by the processor 401 to implement the method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent agent provided by the method embodiments in the present application.

[0097] In some embodiments, the electronic device may further optionally include: a peripheral device interface and at least one peripheral device. The processor 401, the memory 402, and the peripheral device interface may be connected through a bus or signal lines. Each peripheral device may be connected to the peripheral device interface through a bus, signal lines, or a circuit board. Schematically, the peripheral devices include, but are not limited to: a radio frequency circuit, a touch display screen, an audio circuit, and a power supply, etc.

[0098] Of course, the electronic device may also include fewer or more components, and this embodiment does not limit this.

[0099] Optionally, the present application also provides a computer-readable storage medium, in which a program is stored, and the program is loaded and executed by a processor to implement the method for constructing a SaaS management platform for small and medium-sized enterprises based on an integrated agent in the above method embodiment.

[0100] Optionally, the present application also provides a computer product, which includes a computer-readable storage medium, in which a program is stored, and the program is loaded and executed by a processor to implement the method for constructing a SaaS management platform for small and medium-sized enterprises based on an integrated agent in the above method embodiment.

[0101] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0102] The above embodiments only represent several implementation manners of the present application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several deformations and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent entity, characterized in that: The method comprises: Build a SaaS management platform based on the enterprise benchmark architecture; An integrated intelligent entity is set in the SaaS management platform, and the integrated intelligent entity can automatically generate a complete business flow according to the input business name; The integrated intelligent agent provides decision support and processing capabilities for different functional modules of the SaaS management platform by calling the large model; The SaaS management platform supports integration with third-party applications and services; A multi-level security assurance method is adopted during the operation of the SaaS management platform.

2. The method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent entity according to claim 1, characterized in that: The SaaS management platform constructed based on the enterprise benchmark architecture includes: The SaaS management platform includes pre-set functional modules designed according to the enterprise benchmark architecture; The SaaS management platform adopts a microservice architecture, which splits each functional module of the SaaS management platform into independent services, and the functional modules interact with each other through a lightweight communication protocol.

3. The method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent agent according to claim 1, characterized in that: The comprehensive intelligent agent can automatically generate a complete business flow according to the input business name, including: After the user enters the service name, the integrated agent accesses the preset template library, selects the template that best matches the service name in the template library and automatically matches it; The comprehensive intelligent agent automates the steps in the template with the highest degree of matching to generate a business flow that meets the specifications.

4. The method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent agent according to claim 3 is characterized in that: The step of selecting the template that best matches the service name from the template library according to the service name and automatically matching the template includes: Define the service name as B, and the template library as T = {T1, T2, T3, ..., T m }, through the character matching counting function CommonChars(B, T j )Evaluation business name B and template T j Degree of match: M(B,T j )=CommonChars(B,T j ) Among them, the character matching counting function CommonChars(B, T j ) indicates the service name B and template T j The number of common characters in the function is calculated by the following steps: CommonChars(B,T j )=|C(B)∩C(T j )| Among them, C(B) and C(T j ) are the business name B and template T j The converted character set selects the template with the best matching degree based on the matching degree between all templates and the business name.

5. The method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent agent according to claim 3 is characterized in that: The step of selecting the template that best matches the service name from the template library according to the service name and automatically matching the template includes: Define the service name as B, and the template library as T = {T1, T2, T3, ..., T m }, use the following formula to evaluate business name B and template T j Degree of match: Among them, C(B) and C(T j ) are the business name B and template T j The converted character set, max(|C(B)|,|C(T j )|) is the normalization factor, sim(B, T j ) indicates the service name B and template T j The cosine similarity of The template with the best matching degree is selected based on the matching degree between all templates and the business name.

6. The method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent agent according to claim 1, characterized in that: The SaaS management platform supports integration with third-party applications and services including: The SaaS management platform achieves docking with external systems by providing a standardized API interface, allowing third-party developers to access and expand platform functions.

7. The method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent agent according to claim 1, characterized in that: The multi-level security assurance methods used in the operation of the SaaS management platform include: The SaaS management platform encrypts all transmitted and stored data and implements identity authentication methods; The SaaS management platform configures system permissions in layers based on user roles and responsibilities to ensure that users can only access data and functions related to their responsibilities; The SaaS management platform regularly performs security vulnerability scans and penetration tests to fix potential security risks.

8. A system for building a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent entity, characterized in that: include: SaaS management platform building module, used to build a SaaS management platform based on the enterprise benchmark architecture; An integrated agent setting module, used to set an integrated agent in the SaaS management platform, wherein the integrated agent can automatically generate a complete business flow according to an input business name; A large model calling module, used for the integrated intelligent agent to provide decision support and processing capabilities for different functional modules of the SaaS management platform by calling the large model; An external access module, used for the SaaS management platform to support integration with third-party applications and services; The security assurance module is used to adopt a multi-level security assurance method during the operation of the SaaS management platform.

9. An electronic device, characterized in that: The device includes a processor and a memory; a program is stored in the memory, and the program is loaded and executed by the processor to implement a method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent body as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a program, which, when executed by a processor, is used to implement a method for constructing a SaaS management platform for small and medium-sized enterprises based on a comprehensive intelligent body as described in any one of claims 1 to 7.

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