373 results about "Enterprise management" patented technology

The invention discloses an intelligent enterprise financial data analysis system and method based on artificial intelligence, and belongs to the technical field of enterprise informatization management and intelligent finance. The objective of the invention is to solve the technical problems of low processing efficiency, insufficient data insight, lagging risk identification, weak intelligent decision-making assistance capability and the like in the existing enterprise financial data analysis process. The system generally integrates a data automatic acquisition and integration module, a financial data deep analysis and modeling engine based on artificial intelligence, a key financial index and operation performance intelligent calculation module, a multi-dimensional financial risk intelligent identification and dynamic early warning module and an interactive visual analysis report and decision support module. The core of the method is that internal and external multi-source heterogeneous financial and operation data of an enterprise are automatically collected and fused, deep processing and intelligent analysis are performed on the data by applying artificial intelligence technologies such as machine learning and natural language processing, and accurate portrait of the financial condition of the enterprise, dynamic evaluation of operation performance and real-time monitoring and prediction of financial risks are realized. And analysis reports and optimization suggestions with insight are generated, so that enterprise managers can make efficient and scientific operation decisions. According to the method, the automation and intelligence level of enterprise financial data analysis can be remarkably improved, the financial information quality and decision support efficiency are improved, the risk prevention capability of enterprises is enhanced, and the enterprises are assisted to realize refined operation and value creation.

The invention relates to the technical field of enterprise management, in particular to an intelligent decision support system and method based on cognitive logic and scenarized semanteme, and the method comprises the steps: obtaining enterprise decision data through multi-source data monitoring, carrying out the preprocessing, and generating cross-modal enterprise scene cognitive information; analyzing cross-modal association among the data, fusing a cognitive logical reasoning rule and a semantic understanding model, and constructing scenarized semantic decision fusion features; training an enterprise decision-making quality evaluation model based on historical cases, performing quality perception on a current decision-making scene, and outputting decision-making quality information; and an execution effect is judged in combination with an expected target, an optimization mechanism is started if the target is deviated, candidate schemes are generated by using a historical knowledge base and a multi-target optimization algorithm, an optimal solution is screened, and intelligent adjustment of a decision scheme is realized. According to the method, multi-source heterogeneous data and cognitive logic are fused, semantic understanding, dynamic evaluation and adaptive optimization capabilities of a decision system are enhanced, and scientificity and real-time performance of enterprise decision are improved.

The invention discloses an intelligent interaction system based on a large language model and a knowledge graph, and relates to the technical field of artificial intelligence and intelligent interaction. According to the system, data processed by a data acquisition and preprocessing module is stored in a local knowledge warehouse in a three-layer nested structure; the multi-modal semantic understanding module constructs a knowledge system in which a triple knowledge graph and a vector database are complementary by optimizing a BERT model and performing dual-channel analysis; the intelligent interaction module realizes natural language interaction and business task automatic triggering based on an RAG technology and a dialogue memory mechanism; the information change identification and analysis module generates a personnel change risk report and performs early warning; and the summary report automatic generation module outputs a structured report. According to the method, the problems of data splitting, complex interaction and slow response in traditional enterprise management are solved, the functions of system intelligent question answering, personnel change risk analysis, structured report automatic generation and the like are realized, and the management efficiency and the information consistency are improved.

The invention relates to the technical field of enterprise management optimization, in particular to an enterprise management optimization method and system based on big data matching, and the method comprises the following steps: S1, collecting enterprise operation data, industry reference data and supply chain dynamic data, and outputting standardized enterprise data; s2, matching the standardized enterprise data with a preset industry feature library to generate a multi-dimensional service label set; s3, constructing a dynamic priority evaluation model, and generating a priority ranking matrix; s4, establishing a resource characteristic spectrum database, and generating a strategy matching degree matrix; s5, generating a resource configuration scheme according to the strategy matching degree matrix; and S6, when the monitoring threshold changes, triggering a weight calibration mechanism. According to the invention, through big data matching and dynamic priority evaluation, enterprise resource configuration decisions are optimized, operation efficiency and market adaptability are improved, and risks and cost are reduced at the same time.

The invention provides a low-code enterprise-level intelligent assistant development platform, and relates to the field of intelligent assistant development. The low-code enterprise-level intelligent assistant development platform comprises an application layer, a platform layer, a capability layer and an underlying service. According to the low-code enterprise-level intelligent assistant development platform, a low-code enterprise-level intelligent assistant development platform is realized, and by means of the platform, a user can develop enterprise-level intelligent assistants suitable for various industries, thereby helping enterprises to realize cost reduction and benefit increase; a user can complete the creation of a knowledge base, a workflow and an intelligent agent only through simple configuration or arrangement, a low use threshold is achieved, enterprise internal services or third-party MCP services can be accessed by means of a plug-in tool and a platform, uploading and publishing of user-defined tools are supported at the same time, high expandability is achieved, and the method can be widely applied to the field of enterprise management. The platform supports high-order functions such as multi-person collaborative development, multi-modal knowledge base construction, multi-modal data interpretation and processing and construction of multiple types of agents, and can meet complex enterprise-level application scenes.

The invention discloses a decision scheme generation method and device based on complex multi-modal management data, equipment and a medium, and relates to the technical field of data processing, and the method comprises the steps: receiving enterprise management data of texts, numerical values and images, extracting a unified feature vector, carrying out the clustering analysis through the dynamic updating of torque clustering and spectral clustering, and obtaining a clustering result; and a causal knowledge graph is constructed according to the result, and a decision scheme is generated by using a fourth-order inference engine, so that efficient processing and real-time response of an enterprise to dynamic multi-modal management data are realized, the cross-modal data analysis capability is enhanced, and the decision accuracy is improved.

Aspects of the disclosure relate to providing a secure large language model data platform. The secure large language model uses a machine-learning large language model and gateway to prevent attacks and unauthorized access to enterprise-managed information and resources. The secure large language model may utilize pre-enrollment at a secure gateway providing a unique identification to each client. A private / public key pair may be generated and stored in the secure gateway database and large language model respectively. In some embodiments, a unique anonymization rule set may be generated and used for each client. Threat actors cannot query the large language model directly based on the pre-enrollment process. Unauthorized requests cannot be decrypted by the large language model due to missing paired keys.

The invention relates to the technical field of enterprise management and information processing, in particular to an intelligent contract-driven enterprise tax risk management system, which adopts a rule management layer and contract execution layer separation architecture: the rule management layer is responsible for configuring and testing a tax rule and generating a rule version identifier; and the contract execution layer is composed of intelligent contracts deployed in the block chain, and comprises a rule state contract for anchoring a rule version and a business risk contract for executing business logic. And coupling the off-chain rule with the on-chain contract through the rule version identifier. And the business risk contract monitors an on-chain evidence storage event, obtains a current effective rule version, delegates under-chain service calculation, verifies a returned result by signature, version, time and the like, and executes corresponding treatment after the verification is passed. For high-risk disposal, the system provides an on-chain arbitration mechanism by governing a contract. According to the method, dynamic and safe updating of the tax risk management rule is realized on the premise of ensuring that the process is automatic, credible and non-tampering.

An information technology system generally includes a cloud-based management platform with a micro-services architecture deploying a set of adaptive intelligence facilities that can be configured to automate a set of capabilities of the platform related to at least one of the value chain network entities and the features of the platform and a set of data storage facilities that can be configured to store data collected and handled by the platform. The data can be related to at least one of the value chain network entities and the features of the platform. A set of monitoring facilities can be configured to monitor the value chain network entities. The platform can be configured to host a set of applications for directing an enterprise to manage the value chain network entities from a point of origin of a product of the enterprise to a point of customer use.

Techniques for wildcard based private application access are disclosed. In some embodiments, a system, a process, and / or a computer program product for wildcard based private application access includes receiving a request for access to an application over a secure access service edge (SASE) network for a user associated with an enterprise; determining if the request for access to the application matches a wildcard (e.g., the wildcard can be configured by an administrator of the enterprise for matching a fully qualified domain name (FQDN) for the application); and automatically configuring access information (e.g., IP address, protocol, and destination port) for the application that matches the wildcard.

The invention relates to the technical field of enterprise management, and discloses a project performance evaluation method and system based on business and financial fusion and a storage medium, and the method comprises the following steps: collecting business data and financial data, and carrying out the standardization processing of the business data and financial data, and obtaining a standardized data set; analyzing the dynamic relevance between the business indexes and the financial indexes according to the standardized data set, and constructing a department strategy game model; calculating the information entropy of the business index and the financial index based on the standardized data set, and generating a game correction coefficient in combination with a department strategy game model. According to the method, business and financial data are collected in real time and subjected to standardization processing, the time-varying relevance of business and financial indexes is captured by using a sliding window technology, a department strategy interaction model is constructed in combination with the game theory, the index distinction degree is quantified through information entropy to generate a basic weight, and then a game correction coefficient is introduced to dynamically adjust the weight.

The invention discloses an enterprise management consultation data analysis method based on machine learning, and relates to the technical field of data analysis, and the method comprises the steps: collecting structured data and unstructured data, carrying out the preprocessing, and generating a unified data set; structural features and non-structural features are extracted from the high-quality repair data set, weight adaptive fusion is carried out in a deep neural network, and a multi-modal feature vector is generated; training a deep neural network based on the multi-modal feature vector and a target business index, and generating a consultation business prediction model in combination with cross validation, hyper-parameter tuning and loss function dynamic adjustment; and performing real-time prediction on the multi-modal feature vector by using a consultation service prediction model, generating a service index prediction result, and forming a preliminary execution strategy in combination with a target service index. According to the invention, the accuracy of business index prediction and the adaptability of the consultation business prediction model to a complex business scene are improved.

The invention provides a performance management scheme intelligent generation method and system, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence and enterprise management, and the method comprises the steps: obtaining the performance management data of a target employee; performing pre-verification of a preset rule on the performance target draft to obtain an initial verification result; generating a current prompt word according to the initial verification result, the performance management data and a preset knowledge base; reasoning the current cue word by using a preset language model to obtain a current performance management scheme; performing preset rule complex verification on the current performance management scheme to obtain a current verification result; and determining a target performance management scheme according to the current verification result. In this way, through close cooperation of rule verification and language model generation, it can be ensured that the generated content conforms to the predefined rule, the intelligent generation capacity of the language model can be utilized to meet diversified and personalized requirements, and therefore the generation efficiency, compliance and language quality of performance goals and comments are improved.

The invention discloses a sports market demand prediction method and device based on deep learning and a medium, and relates to the technical field of market demand prediction, and the method comprises the steps: collecting sports demand data, and carrying out the preprocessing; performing relation mining and graph structure learning on the preprocessed sports demand data through a graph attention space-time network to generate a macroscopic demand potential energy graph; performing potential area identification on the macroscopic demand potential energy diagram by adopting a pre-trained sports market simulation model, and outputting local demand prediction data; performing weighted fusion and error correction on the macroscopic demand potential energy map and the local demand prediction data, and outputting a sports demand prediction score; and making a sports market demand strategy according to the sports demand prediction score and the multi-granularity demand prediction report, and transmitting the sports market demand strategy to an enterprise manager through an enterprise decision support interface. According to the method, multi-level accurate prediction and decision support of sports market demands are realized through dual-mechanism cooperation of the graph attention space-time network and the space-time convolution.

The invention relates to the technical field of enterprise service digitalization and intelligent management, in particular to an enterprise management method and management platform based on dynamic portraits. The method comprises the following steps: S1, accessing and standardizing multi-source heterogeneous data, calculating a source-level quality score and generating an evidence chain; s2, constructing a portrait map and a time axis taking an enterprise as a main node; s3, the rule engine and the LLM-RAG output numbers in parallel; s4, consistent arbitration and belief propagation; s5, event-driven dependency subgraph increment recalculation is carried out; s6, carrying out portrait-strategy matching and task linkage; s7, carrying out closed-loop write-back and auditable playback; and S8, multi-tenant fine-grained permission. According to the scheme, the problems of data fragmentation and insufficient timeliness and traceability are solved, and the linkage of portrait credibility, interpretability and real-time decision is realized.

The invention relates to the technical field of enterprise management, in particular to an enterprise process custom configuration method and system based on a code-free technology, and the method comprises the steps: constructing a multi-layer directed hypergraph containing data, control and condition dependence, calculating an edge weight, and converting the dependence into a first-order logic constraint set; performing incremental satisfiability detection, and outputting a conflict core set containing conflict types and severity in combination with minimum unsatisfiability subset mining and strong connected component analysis; mapping the conflicts into modifiable elements, and generating parameterized candidate repair schemes based on a repair operation library and historical cases; converting the candidate scheme into a weighted constraint optimization problem, and solving an optimal scheme by adopting a branch and bound algorithm; influence propagation verification is completed in the copy, a differential patch and a rollback identifier are generated, transactional submission is carried out after passing, and the weight and the case library are updated. According to the method, automatic diagnosis and low-risk repair of implicit dependency conflicts are realized.

The invention relates to the field of artificial intelligence, and particularly discloses a cooperative office intelligent agent using method and device and a medium, the method comprises the following steps: receiving an input instruction from a user, and analyzing the input instruction to obtain an analysis result; generating a tool calling request based on the analysis result; based on the tool calling request, calling the target MCP Server to generate a tool execution result of the input instruction; and converting the tool execution result into a return result, and sending the return result to the user. And for an enterprise administrator, the intelligent scene access of the service can be completed only by additionally configuring the information of the MCP Server when the light application is originally added. Not only can the scene requirements of enterprise process automation, intelligent work order processing, cross-system data integration and the like be effectively met for enterprises, but also the MCP Server can be automatically expanded for enterprise users, and all the requirements of user office are met.

The invention relates to the technical field of enterprise management, in particular to a dynamic performance management system based on artificial intelligence and an implementation method. The system comprises a data acquisition and processing module used for acquiring structured and unstructured data from a plurality of data sources; the knowledge graph construction module is used for constructing a knowledge graph representing an organization semantic model by utilizing the structured and unstructured data; the performance indicator construction and adjustment module is used for constructing and adjusting performance indicators of the organization by utilizing a reinforcement learning agent based on the knowledge graph; and the visualization module is used for providing a user interface to display the performance indicators and the analysis results. According to the method, KPI strategic correlation is ensured by constructing the organization knowledge graph, closed-loop adaptive optimization of performance indicators is realized by introducing reinforcement learning, and the organization work gravity center can be guided to automatically align with the strategic direction of dynamic change, so that the strategic executive force and agility of the organization are remarkably improved.

The present invention discloses an enterprise human resources comprehensive management platform, which relates to the field of data management technology and includes: a resource management system determination module for determining a resource management system; a management logic chain determination module for determining a management logic chain; a task management strategy determination module for determining a task management strategy; a sensitive management mode setting module for setting a sensitive management mode for sensitive data classes; a sensitive management strategy determination module for determining a sensitive management strategy; and a pre-management task control module for executing and controlling pre-management tasks. The platform solves the technical problems of the existing enterprise human resources management, such as the difficulty in coping with complex and changing enterprise management needs, the lack of integration of multiple enterprise application systems, and the risks of sensitive data management, which lead to the inaccuracy and security of enterprise human resources management. The platform intelligently realizes the comprehensive integration and efficient use of human resources information, achieving the technical effect of improving the accuracy and security of enterprise management.

The invention discloses a templated business process management method, and relates to the technical field of enterprise management.The method comprises the steps that repeatable task units in a business process are represented and packaged into function components capable of being configured in a draggable mode, combined arrangement is conducted in a visual working area template, and process construction is conducted from the development coding level to the development coding level; according to the technical scheme, the method sinks to a configuration level which can be understood by business personnel, in the step of creating the visual workflow template, when the working area templates bearing specific tasks are bound with process nodes, separation and standardized packaging of business logic and execution logic are achieved, and various working area templates are predefined through a graphical interface; the node function assembly can be quickly completed only by quoting the templates in the flow chart, the defect that each node needs to be independently developed or written in a traditional mode is overcome, and the core defects that in the prior art, flow construction is complex, the reuse rate is low, and the method excessively depends on technicians are overcome.

The invention provides an enterprise management system intelligent optimization method and system based on digital twinning, and the method comprises the following steps: constructing an organization structure diagram with a path weight by taking a post as a node, taking a superior-subordinate relationship as a directed edge, and taking a KPI (Key Performance Indicator) target vector as a node attribute; constructing an instruction conduction path model through breadth-first traversal based on the organization structure chart to generate an effective conduction path set, and calculating a target propagation vector of each path; a post is regarded as a reinforcement learning agent, an optimal post behavior strategy is recovered through inverse reinforcement learning, and a target vector matrix of each post adjusted according to the strategy is obtained; constructing an anti-fact management strategy optimization instruction conduction path, and generating an optimized target matrix and path set; and comparing the optimized target matrix with actual execution data, and calculating a target deviation as an execution effect evaluation value. According to the method, the defects of an existing system in the aspects of multi-level management collaboration, behavior deviation modeling and strategic execution consistency guarantee are overcome.

The invention discloses a logistics transportation management and real-time data sharing method and system, and relates to the technical field of logistics transportation, and the method comprises the steps: S1, collecting logistics transportation data on a logistics transportation vehicle in real time; s2, preprocessing the collected real-time data by using an edge computing technology, encrypting the data through a wireless network, and transmitting the data to a cloud computing platform; s3, integrating and storing the real-time data by the cloud computing platform, and performing intelligent analysis by using a machine learning algorithm; s4, giving an optimization suggestion according to an analysis result, generating a report and updating the report in real time; and S5, providing a self-service platform to inquire the cargo state. According to the invention, the transparency of logistics transportation information can be enhanced, all parties can know the logistics transportation condition in time, the user experience is improved, the user credibility is enhanced, the enterprise cost of a carrier is reduced, and the benefit of enterprise management is improved.

The invention discloses an enterprise management information tamper-proof sharing method and system based on the Internet, and relates to the technical field of information security, and the method comprises the steps: obtaining the network state information of an external partner access region; according to the network state information, whether network infrastructure faults exist in the external partner access area is judged, and a network infrastructure fault judgment result is obtained; if the network infrastructure fault judgment result is that the network infrastructure fault exists, obtaining user operation behavior data of an external partner access area; adjusting the weight of a risk assessment factor corresponding to the network state information to obtain a target weight; performing risk assessment on the user operation behavior data according to the target weight to obtain a risk assessment result; and performing authority control on the user operation according to a risk assessment result. According to the invention, tamper-proof sharing of enterprise management information is realized, and the risk assessment accuracy and the system security are improved.

The invention discloses an enterprise digital management system based on multi-source data fusion, and the system comprises a data collection module which is used for constructing a multi-source data view from internal and external data sources of an enterprise; the embedding mapping module is used for generating a feature domain embedding vector set; the improved extremely deep factorization machine model module is used for feature extraction and explicit high-order interactive modeling and outputting a basic matching score; the triple generation module is used for constructing a positive and negative sample triple and calculating a business importance coefficient and an exposure probability; the Bayesian personalized sorting module is used for constructing weighted sorting loss and updating model parameters; and the online recommendation module is used for calculating matching scores of the candidate schemes and sorting and outputting a recommendation management list. According to the method, accurate and intelligent recommendation and sorting decision of candidate schemes in an enterprise management scene are realized by improving an extremely deep factorization machine model and Bayesian personalized sorting.

The invention relates to the technical field of cross-border e-commerce, and discloses a cross-border commodity compliance inspection and supervision system which comprises an enterprise management module, a cross-border commodity compliance evaluation module, an inspection and supervision module, a risk analysis module, a cross-department data sharing module, a credit management module and a system management module. The enterprise management module carries out enterprise registration and qualification auditing; the cross-border commodity compliance evaluation module constructs a dynamic standard knowledge base and generates a compliance evaluation report; the inspection supervision module generates four levels of inspection levels; the risk analysis module calculates cross-border commodity risk scores and performs early warning; the cross-department data sharing module is in butt joint with an external system to initiate joint inspection; the credit management module generates an enterprise credit rating; and the system management module controls and distributes function permissions based on role permissions. According to the invention, through multi-module collaborative linkage and data intercommunication and function collaboration among the modules, the supervision efficiency and the trade convenience level are improved, and an intelligent and collaborative supervision mode is provided for the quality safety of cross-border commodities.

The invention belongs to the technical field of block chain ERP (Enterprise Resource Planning), and discloses an enterprise ERP management system based on a block chain, which realizes credible sharing through an alliance chain architecture of a block chain base layer, ensures sensitive information privacy through a zero-knowledge proof technology, and can establish cooperative trust without endorsement of a third-party mechanism; the intelligent contract of the supply chain cooperation unit automatically executes cooperation rules such as purchase and acceptance, and trust disputes caused by manual intervention are avoided; the intelligent contract engine drives the unit processes of supply chain, production, finance and the like to be automated, so that end-to-end linkage of purchase-production-finance is realized, and manual operation links are reduced; the dynamic contract updating function enables the enterprise to quickly adapt to the business rule change, and the online period of a new business scene is shortened; the digital twinborn technology of the production management unit is fused with the AI model of the data analysis center, so that the decision accuracy of production scheduling and inventory management is improved, the resource configuration is optimized, and the problems of solidified process and slow response of the traditional ERP (Enterprise Resource Planning) are solved.

The invention discloses an enterprise management process service system based on big data, and relates to the technical field of enterprise incubation and intelligent management, and the system comprises a settlement management module, a resource demand module, a resource scheduling module and a project tracking module. The entering management module analyzes enterprise basic information and market environment data through information acquisition and value evaluation, and realizes regional grading and risk grade judgment; the resource demand module calculates a resource comprehensive value and matches an optimal allocation strategy through thermodynamic diagram analysis, shop classification and commuting evaluation; the resource scheduling module outputs, dynamically adjusts and automatically issues funds based on resource demand; and the project tracking module carries out full-cycle data monitoring and risk assessment on the project after investment. Through big data driving and an automatic process, the problems of information isolated island and much manual intervention of a traditional incubator are solved, the full-life-cycle intelligent service of an enterprise from entering to post-investment management is realized, and the resource allocation efficiency and the risk management level are improved.

The invention discloses an enterprise management consultation data privacy protection method and platform based on federal learning, and relates to the field of management consultation and data privacy protection. According to the method, data localization isolation calculation is realized through a distributed calculation framework and a federated learning algorithm, the multi-party cooperation efficiency is improved on the premise of ensuring privacy security, and the data sharing breadth and depth are promoted; a contribution value is recorded by means of a block chain, and a dynamic income distribution rule is combined, so that fair and transparent income distribution is ensured, trust construction is enhanced through a distributed query interface, and enterprise participation motivation is stimulated; based on trust feedback, an incentive parameter is dynamically adjusted, an incentive mechanism is optimized to adapt to enterprise demand changes, an encryption protocol is continuously enhanced, two-way improvement of safety and efficiency is achieved, and technical support is provided for digital transformation in the field of enterprise management consultation.

The invention discloses a user-defined form job license generation method and device and a storage medium, and the method comprises the steps: generating a user-defined job license form in response to an operation instruction of dragging form elements in a form design interface; determining a target field according to the field attribute of each form field in the custom job license form; obtaining field content based on the target field associated data source to fill the target field, and generating a job license; generating an approval task according to the job type of the job license and preset enterprise management regulations, creating an approval task workflow according to the approval task, and determining an approval result; and when the approval is passed, generating an official job license based on the job license. According to the method, the configurable form elements are dynamically constructed through visual dragging, the dynamic / static data fields are combined, and the approval nodes of the roles / organizations are associated to execute the tasks, so that the job license form and the approval process flexibly adapt to different job type requirements, and the management efficiency is remarkably improved.

The invention discloses a data processing method of a full-stack AI enterprise management system. The method comprises the following steps: constructing a time difference sequence of financial links; a delay fluctuation value is calculated through multi-scale wavelet transform and time sequence analysis, and an abnormal service link is identified by using an isolated forest algorithm; generating a consistency deviation index fusing a financial field matching rate and a domain rule weight based on a sequence-to-sequence model of an attention mechanism; inputting the deviation index and the time difference sequence into a space-time diagram convolutional network, and tracing a root business link; a timestamp synchronization strategy is adjusted according to the tracing path, and a financial rule engine is triggered to generate a correction entry; an LSTM model and a reinforcement learning agent are introduced, so that optimization verification and parameter adaptive adjustment are realized; and finally generating an abnormal positioning report and a risk assessment result. By means of the technical scheme, automatic detection, source tracing, correction and continuous optimization are carried out on abnormities in the enterprise management process, and the reliability, compliance and system autonomy ability of financial data circulation are improved.