43 results about "Enterprise it" patented technology

An AI-driven centralized orchestration system (100) with MCP protocol for real-time compliance and risk data management, including: a. a centralized integration and orchestration platform configured to connect heterogeneous enterprise IT systems through standardized API connections and execute automated workflows; b. a variety of domain-specific artificial intelligence (AI) agents that interface with IT service management (ITSM), vulnerability management, and endpoint and asset management platforms for data collection, analysis, and assessment; c. a Multi-Agent Communication Protocol (MCP) layer that enables structured communication, negotiation and coordination between AI agents in real time; d. a data consolidation module configured to aggregate, standardise and align heterogeneous data into a unified repository using machine learning models; e. a compliance reporting module for dynamically generating and distributing audit-ready compliance reports based on AI-analyzed data and triggered workflows; f. an alerting module configured to deliver context-dependent predictive notifications of compliance violations or risk anomalies through various communication channels; g. a predictive dashboard module capable of displaying compliance status, risk metrics, and proactive insights in real time via AI-driven visualization tools; i.e., where the orchestration platform, AI agents, and MCP layer together enable automated, scalable, and proactive compliance and risk actions.

The invention provides a service fault recovery method and system based on disaster recovery strategy optimization, and the method comprises the steps: obtaining a network topological graph and an enterprise digital twin model based on an enterprise IT architecture; obtaining an initial disaster recovery strategy based on the network topological graph; inputting the initial disaster recovery strategy to the enterprise digital twin model, optimizing the initial disaster recovery strategy until a preset convergence requirement is met, obtaining a target disaster recovery strategy, and storing the target disaster recovery strategy to a preset cloud strategy library; and when a service fault occurs, automatically switching a target disaster recovery strategy based on the preset cloud strategy library so as to recover the service fault. According to the invention, the problem of poor service fault recovery reliability caused by the fact that the disaster recovery scheme cannot be adaptively adjusted according to different service fault scenes in the prior art is solved. According to the invention, self-adaptive adjustment of the disaster recovery strategy is realized, and service fault recovery reliability is improved.

This invention discloses a method and system for assessing technical consulting risks based on the internet, relating to the field of data protection technology. It involves defining an enterprise data pool and establishing connections between the enterprise data pool and both the enterprise itself and the technical consulting platform. The enterprise sends consulting data to the technical consulting platform, which then provides suggested data based on the data. The consulting data and corresponding suggested data are stored in the enterprise data pool. A tracking set is set for the enterprise data pool to statistically analyze access information, including the processing results of accessed data (removal / destruction and normal access), resulting in a risk assessment index for the technical consulting. This invention ensures the security of enterprise-related data storage and also helps identify the cybersecurity risks faced by the enterprise during technical consulting.

The application provides a method, device and equipment for big data fusion remote supervision of small and medium-sized enterprises and a storage medium. It is related to the technical field of environmental supervision. The method first acquires positive text data, extracts keywords and processes the positive index data through TF-IDF. Then, the reverse text data is acquired, and the reverse index data is obtained through text vectorization and clustering. Based on the enterprise ID association, an enterprise-index-behavior matrix is formed, key driving indicators are screened, a dynamic weight distribution model is constructed to determine the index weight, and the index is normalized to calculate the comprehensive score to determine the enterprise level, thereby assisting efficient and accurate remote enterprise supervision and providing a new technical solution for enterprise supervision.

Disclosed herein are system, apparatus, article of manufacture, method and / or computer program product aspects, and / or combinations and sub-combinations thereof, for generating a workflow plan for completing a process. An example embodiment operates by receiving a user request from a user device in which the user request includes a natural language description of the workflow plan. The embodiment then retrieves, from a knowledge database, workflow information associated with a step of the workflow plan. The embodiment then generates a plurality of steps associated with the workflow plan. The embodiment then retrieves plan information from a storage database in which the plan information includes a sample workflow plan generated from a sample user request and the workflow information in which the workflow information is further associated with a step of the sample workflow plan. The embodiment then generates the workflow plan using a large language model (LLM) and a prompt.

The invention discloses an enterprise-level AI system and method based on a software and hardware deep fusion seven-layer integrated framework, and belongs to the technical field of artificial intelligence. The system comprises a hardware layer, a computing power layer, a reasoning layer, a middle layer, a platform layer, an application layer and a security layer from bottom to top; in combination with unified computing power scheduling, local private large model reasoning, a self-developed multi-modal document analysis engine, deep integration of an enterprise IT system and full-stack security management and control, an enterprise-level AI infrastructure integrating data, computing power, algorithm, application and security is constructed; the method has the advantages that the AI resource utilization rate is remarkably increased by 40% or above, the unstructured document analysis accuracy rate is remarkably increased by 90% or above, the AI application deployment period is shortened by 60% or above, and the requirements for privatization, safety, controllability and efficient landing of high-supervision industries such as finance, government affairs and medical treatment are met.

Various examples are provided related to identification of protected information elements associated with unique entities in data files present in data file collections associated with enterprise IT networks. The unique entities can be associated with one or more entity identifications in one or more data files. Computer-generated identification of entity identifications and protected information elements can be conducted, in part, by at least some human review. Information generated accordingly to the disclosed methodology can be used to generate plans for a time and number of human reviewers needed to review data files. Information generated from the processes herein can be configured as user notifications, reports, dashboards, machine learning for subsequent data file analyses, and notifications of unique entities having protected information elements present in one or more data files.

The invention belongs to the field of data monitoring systems or methods, and relates to a platform enterprise entrepreneurship opportunity real-time monitoring method and system based on a digital technology, and the method comprises the steps: firstly, preliminarily obtaining an entrepreneurship opportunity; a new entrepreneurship opportunity is derived through iterative exploration; then data generated in the startup opportunity iterative exploration process serves as new data to be input into the digital intelligence base, the digital intelligence base repeatedly executes the first two steps based on the input data, and startup opportunities are continuously emerged; reasoning the relevance between the continuously emerging startup opportunities to generate a correlative startup opportunity set; and finally, according to the obtained entrepreneurship opportunity set, timely mining and finding entrepreneurship opportunities capable of being applied to the market, and dynamically designing a feasible space of the opportunities based on time lapse and ecological evolution to construct an opportunity map. By adopting the method, it can be ensured that platform enterprises are in industry prospect and leading all the time, the enterprises are helped to stand out in fierce market competition, and sustainable development is achieved.

Disclosed herein are system, apparatus, article of manufacture, method and / or computer program product aspects, and / or combinations and sub-combinations thereof, for multi-agent network and security operations. An example embodiment operates by determining a complexity level of the task is high based on identifying a requirement of a collaboration between a plurality of decentralized agents when executing the task. The embodiment then determines a distributable level of the task is low based on identifying a requirement of a central agent for task allocation when executing the task. The embodiment then, in response to determining the complexity level of the task being high and the distributable level of the task being low, selects a hybrid architecture as the optimal architecture associated with the task. The embodiment then assigns the task to an agent associated with the hybrid architecture. The embodiment then executes the task using the hybrid architecture.

The present subject matter relates to a system (100) and a method (300) for providing automated resolution to one or more anomalous events in an enterprise information technology (IT) environment. The system (100) integrates a processor (201) and a memory (202) that stores instructions to execute various tasks. The system (100) monitors activities within the enterprise IT environment, identifies one or more anomalous events, and correlates the identified anomalous events with one or more predefined resolution workflows. Each workflow includes specific operating instructions tailored to address the identified anomalies. Upon detecting an anomaly, the system (100) extracts the relevant operating instructions from the corresponding workflow and executes them to resolve the issue. Thus, the system (100) significantly reduces the mean time to resolve by automating the detection and resolution of anomalies, thereby improving operational efficiency and minimizing downtime in the enterprise IT environment.

The application discloses a blockchain-based double-trust on-chain and off-chain carbon emission right transaction method and system, acquires carbon emission data of an enterprise, combines the carbon emission data and carbon dioxide mass concentration as real-time carbon emission data, stores the real-time carbon emission data in a BigchainDB storage network, calculates minute, hour, day, month and year carbon emission of the enterprise according to the real-time carbon emission data and stores the carbon emission, then applies for a trusted carbon emission digital certificate, uploads the enterprise ID, enterprise name, enterprise carbon emission, enterprise trusted carbon emission digital certificate and enterprise credit value to a Fabric alliance chain transaction network, and the enterprise performs carbon emission right transaction on the alliance chain transaction network. The application uses the alliance chain technology to ensure data transparency and non-tamperability in the transaction process, and solves the technical problem that the current carbon emission right transaction system cannot guarantee the authenticity and credibility of carbon emission data.

1. The name of the design product: server power control module. 2. The use of the design product: the design product is used in the power supply frame of data center, cloud computing center and large enterprise IT infrastructure. The design product is matched with power supply unit to provide remote monitoring and management of power supply unit status, real-time power usage data and alarm function. 3. The design points of the design product: the overall shape. 4. The picture or photo that best indicates the design points: perspective view 1. 5. Other circumstances that need to be explained: A part enlarged view is an enlarged view of the A part area in the top view. B part enlarged view is an enlarged view of the B part area in the bottom view. C part enlarged view is a partial enlarged view of the C part area in perspective view 1. D part enlarged view is a partial enlarged view of the D part area in perspective view 2.

The invention provides an enterprise investment relation graph construction method, system and device and a medium, and belongs to the technical field of computers. The method comprises the following steps: firstly, inputting information of enterprises, shareholders and capital enterprises into a database to form a main table and a sub-table which both contain unique IDs of the enterprises; then, according to the to-be-queried enterprise ID and the timestamp, two query algorithms are used for respectively obtaining enterprise information, shareholder information and capital enterprise information; a tree structure TreeNode is defined, wherein the tree structure TreeNode comprises enterprise display, associated parameters and a child node list. Through recursive query, an information tree of enterprise shareholders and capital enterprises is constructed. And then combining the two trees into an investment relation tree. And finally, constructing a data model based on the tree, converting the data model into graphic elements, and generating a visual enterprise investment relation graph. In the process, enterprise investment information is efficiently integrated, and visual analysis is facilitated. According to the invention, automatic generation of the enterprise investment relation graph is realized, and the visualization effect and the analysis efficiency of the enterprise investment relation are effectively improved.

The invention provides an enterprise risk assessment method and device, equipment, a storage medium and a program product, and relates to the technical field of risk assessment. The method comprises the following steps: determining two to-be-assessed enterprises associated with a to-be-assessed risk; based on the enterprise relation graph, respectively determining a first node embedding vector of the first to-be-evaluated enterprise and a second node embedding vector of the second to-be-evaluated enterprise; and determining a risk association assessment result of the first to-be-assessed enterprise and the second to-be-assessed enterprise based on a similarity calculation result of the first node embedding vector and the second node embedding vector. The first node embedding vector and the second node embedding vector are determined not only based on own node feature vectors, but also based on feature vectors of neighbor nodes, so that not only are own features of the to-be-evaluated enterprise considered, but also features of the enterprise associated with the to-be-evaluated enterprise are considered, and the evaluation accuracy of the to-be-evaluated enterprise is improved. Therefore, the accuracy of enterprise risk association assessment is improved, and finally the accuracy of enterprise risk assessment is improved.

Systems and methods for buying, selling, and financing enterprise IT infrastructure capacity on a decentralized and distributed marketplace platform are disclosed. In one embodiment, the decentralized and distributed IT marketplace platform is based on the blockchain technology. In one embodiment, a blockchain-based IT marketplace platform provides a decentralized supply chain for IT assets and financial services and establishes a self-regulating and trustless marketplace of connected consumers, producers, and financiers. In one embodiment, the blockchain-based IT marketplace platform enables developing, executing, financing and monetizing modern, cloud native, enterprise compute infrastructure and software applications.

The application discloses a heterogeneous report integration method, device and medium, and the method comprises the following steps: determining an opened report standard interface, wherein the report standard interface comprises a table sample interface, a formula interface and a data interface; receiving heterogeneous report data sent by each report platform through the report standard interface, and analyzing the heterogeneous report data, so as to complete a reconciliation relationship verification; and managing the heterogeneous report data, so as to realize data classification of the heterogeneous report data based on a data warehouse concept, and obtaining enterprise internal report data sources. By combining the report technology and the data modeling, the report standard interface is formulated, the table sample format, the analysis formula and the report data are accessed, the report data of different versions and different storage structures are fused, and the control ability of the enterprise itself is improved.

The invention provides an implementation method for constructing integrated monitoring, electronic equipment and a storage medium, and relates to the technical field of integrated monitoring, and the method comprises the steps: constructing a centralized monitoring platform, and integrating multi-source monitoring data; establishing an end-to-end business resource model, and mapping the model to a document database; the method comprises the following steps: constructing an alarm preprocessing assembly line, receiving multi-source alarm data through Kafka, performing data standardization by using JSON Schema, and dynamically adjusting an alarm level according to service influence; constructing a visual monitoring interface; the visual monitoring interface supports topological graph dynamic display and alarm drilling functions, queries an association relation chain based on a graph database, and aggregates real-time index data through a time sequence database; gNN is applied to train a fault propagation model, a root cause candidate list is generated, and real-time reasoning is carried out in combination with a causal graph to locate a fault root; according to the method, the requirements of IT operation and maintenance of modern enterprises on real-time performance, accuracy and expandability can be met.

The invention discloses a virtual machine migration method and device, electronic equipment and a storage medium, and relates to the technical field of virtualization, and the method comprises the following steps: in response to a received virtual machine migration request, migrating a target virtual machine; in response to completion of migration of the target virtual machine, acquiring a driver installation file, and injecting the driver installation file into the target virtual machine based on a first file injection mechanism; in response to injection failure, injecting the driver installation file into the target virtual machine based on a second file injection mechanism; and installing the target drive based on the drive installation file and the drive installation script. According to the application, through a set dual file injection mechanism, the driving programs required by various platform virtual machines can be automatically installed for the virtual machine after the migration of the virtual machine is completed, so that the virtual machine can stably run, the fault risk caused by hardware configuration difference is reduced, the continuity and the stability of services are guaranteed, and the user experience is improved. And the enterprise IT resource management flexibility and efficiency are improved.

The invention provides a project process backtracking method and system based on a timeline and a graph database, and aims to solve the problems of difficult data backtracking, complex integration and lack of full-process visualization caused by tool chain splitting of an enterprise IT team. The method comprises the following steps: accessing heterogeneous DevOps tool data through a plug-in mechanism; modeling the accessed original data, defining a relationship among a data field, a filtering rule and a data object, and constructing a graph database; data visualization is achieved based on a graph database and a timeline, data can be inquired through an object and relation mode, and the data relation evolution process is traced back through a timeline. According to the method, an existing tool chain does not need to be transformed, full-process data association and visualization are achieved through fusion of the graph database and the timeline, the project problem backtracking efficiency and the data credibility are improved, and the method is suitable for process tracing and influence analysis of the full life cycle of software development.

The invention discloses an IT resource management method and device, a storage medium and a processor. In the scheme, collected multi-dimensional attribute information of enterprise IT resources is converted into a JSON character string, and a hash value corresponding to each resource attribute is calculated; comparing each hash value with a historical hash value to obtain a comparison result; if the comparison result indicates that the data corresponding to the resource attribute is changed, associating the changed data of the resource attribute with an alarm event to obtain alarm association information; calculating a PageRank value of a node related to the alarm associated information through an improved PageRank algorithm by using the resource attribute causal graph model, and determining an alarm root cause matched with the alarm event according to the PageRank value; and generating a corresponding alarm strategy according to the alarm root cause. According to the method, the operation and maintenance closed loop of the IT resources from abnormal perception to root cause repair is realized in an automatic manner, and the operation and maintenance management efficiency of the IT resources is remarkably improved.

AI-Driven Project Governance Computer Device for Enterprise IT Delivery

The invention belongs to the technical field of enterprise IT resource operation and maintenance analysis, and discloses an IT resource maintenance influence range intelligent analysis method and system, and the method comprises the steps: retrieving a constructed IT resource RAG knowledge base according to maintenance plan information, and obtaining IT resource information related to the maintenance plan information; calling a large language model for analysis according to the IT resource information associated with the maintenance plan information to obtain an IT resource maintenance influence range; wherein the construction of the IT resource RAG knowledge base comprises the following steps: modeling IT resources to obtain an IT resource association relationship model; collecting IT resource data according to the IT resource association relationship model to obtain IT resource ledger data and IT resource association relationship data; and carrying out vectorization processing on the IT resource machine account data and the IT resource association relationship data, and constructing an IT resource RAG knowledge base. According to the invention, accurate analysis of the influence range of the IT resource maintenance plan is realized.

The invention discloses an enterprise service bus optimization method and device, electronic equipment and a program product, and relates to the technical field of service bus management. The method comprises the following steps: dividing log data of an enterprise service bus into a plurality of sub-time regions according to equal-time fine granularity of time regions; collecting operation log data and abnormal log data of each sub-time region, and calculating an operation efficiency index and an abnormal processing optimization index based on the operation log data and the abnormal log data, so as to obtain a comprehensive optimization index; and determining a control strategy by comparing the comprehensive optimization index with an optimization threshold value and an early warning threshold value. According to the technical scheme, real-time monitoring of the operation state of the enterprise service bus is achieved, the operation stability and the service adaptation capacity of the enterprise service bus are remarkably improved, the fault risk is reduced, and support is provided for efficient collaboration and service continuity of an enterprise IT architecture.

The invention discloses a business mail automatic processing method and system based on robot process automation. The method comprises the following steps: automatically analyzing a theme, a text and an attachment of a received mail through a natural language processing technology, extracting key information such as an enterprise ID (Identity), a chemical identifier and a mail type, and converting the key information into structured data; identifying task types according to the data and selecting corresponding automatic processes; a headless browser is used for simulating and logging in a third-party system, and automatic processing including attachment downloading, analysis, screenshot and multi-language translation is executed; the execution state is monitored in real time, the success rate and the average time are counted to optimize the performance, and meanwhile, various abnormities are captured and reports are generated to trigger the processing flow; and cleaning the resources after execution is finished, and generating a notification mail based on a result to send and archive. According to the scheme, full-process automation of mail processing is realized, and efficiency and accuracy are remarkably improved.

The invention relates to a method for limiting potentially unauthorized access to data from multiple IT infrastructures, particularly enterprise IT infrastructures, wherein IT systems of the IT infrastructures are examined, technical information of the examined IT systems is recorded, a signature of an IT system is generated using the recorded information, and the signature of the IT system is compared with signatures of IT systems in the other IT infrastructures. The invention further relates to a data processing system for carrying out the method according to the invention.

Disclosed herein are system, apparatus, article of manufacture, method and / or computer program product aspects, and / or combinations and sub-combinations thereof, for generating a dashboard using a natural language command from a user device. An example embodiment operates by retrieving, from a knowledge database, dashboard information associated with an outcome in which the dashboard information includes a previous dashboard associated with the outcome. The embodiment then obtains, from a user context database, user information associated with the user device in which the user information includes a previous user preference of generating the previous dashboard. The embodiment then determines one or more available tools for generating a set of widgets associated with the dashboard. The embodiment then generates the set of widgets associated with the dashboard using the one or more available tools, a large language model (LLM), and a prompt. The embodiment then generates the dashboard using the set of widgets.

Various examples are provided related to identification of protected information elements associated with unique entities in data files present in data file collections associated with enterprise IT networks. The unique entities can be associated with one or more entity identifications in one or more data files. Computer-generated identification of entity identifications and protected information elements can be conducted, in part, by at least some human review. Information generated accordingly to the disclosed methodology can be used to generate plans for a time and number of human reviewers needed to review data files. Information generated from the processes herein can be configured as user notifications, reports, dashboards, machine learning for subsequent data file analyses, and notifications of unique entities having protected information elements present in one or more data files.

The invention relates to a production and teaching fusion visual platform page configuration method and system, and the method comprises the steps: creating an exclusive enterprise page for an enterprise side through the enterprise side, placing all components in a platform side component library in the enterprise page in a dragging manner, and achieving the custom page configuration of the enterprise side; and an enterprise page is generated and can be published at a platform end. A first jump component associated with an enterprise page address is created in a platform home page or a platform sub-page through a platform end, and the enterprise page is set as a jump page of the platform home page or the platform sub-page, so that a subsequent job seeker only needs to log in the platform home page of the platform end and browse the platform home page or the platform sub-page; therefore, the user can jump to the enterprise page of the interested enterprise, and can inquire the related information of the enterprise by himself / herself. According to the production and education fusion visualization platform page configuration method and system, a deep learning model does not need to be trained, matching algorithm codes do not need to be written, the process operation is simple, the cost is low, and the usability and reusability are high.

Disclosed herein are system, apparatus, article of manufacture, method and / or computer program product aspects, and / or combinations and sub-combinations thereof, for generating a response to a user question. An example embodiment operates by querying a large language model (LLM) using a prompt associated with the user question and one or more available tools in a tool service. The embodiment then retrieves an endpoint from the tool service in which the endpoint is a digital location associated with a tool selected by the LLM. The embodiment then requests a database associated with the user question based on the endpoint meeting an endpoint requirement. The embodiment then executes a query at the database, thereby obtains data including the response to the user question. The embodiment then identifies an output format associated with the response. The embodiment then generates the response to the user question based on formatting the data using the output format.

The invention belongs to the technical field of network security analysis, and particularly discloses and provides a network security analysis management system based on big data, which comprises the following steps: by constructing conventional behavior models of different label groups of enterprise branches, mastering the network security situation of an enterprise on the whole; omission of some special but normal behavior modes due to adoption of a single general standard is avoided, so that abnormal response behaviors deviating from the normal mode can be positioned more accurately; the dynamic rationality of the abnormal response behavior is judged by comparing the abnormal response behavior with the enterprise audit content, so that the network security analysis system can track the change condition of the enterprise in real time, and the network security misrecognition condition caused by the change of the enterprise is effectively avoided; by positioning the equipment working behaviors of the personnel dispatched by the enterprise, the security influence of the external network on the network of the enterprise is detected in real time, so that the network security defense capability and the emergency response capability of the enterprise are comprehensively improved.