273 results about "Enterprise system" patented technology

A system and method are provided for providing advisory notifications to mobile applications. The method includes interfacing the server device with at least one endpoint within an enterprise system and storing a model trained by a machine learning engine to automatically determine advisory notifications relevant to client data sets stored by the endpoint(s) and / or the at least one endpoint. The method also includes determining a current state of a client account, using the model to determine an advisory notification for the client account based on the current state, referring to a set of rules to determine when to provide the advisory notification in the mobile application, and in what portion of the mobile application to display the notification; and sending the advisory notification via the communications module to a client device to display the advisory notification in the mobile application.

A system and method are provided for providing advisory notifications to mobile applications. The method includes interfacing the server device with at least one endpoint within an enterprise system and storing a model trained by a machine learning engine to automatically determine advisory notifications relevant to client data sets stored by the endpoint(s) and / or the at least one endpoint. The method also includes determining a current state of a client account, using the model to determine an advisory notification for the client account based on the current state, referring to a set of rules to determine when to provide the advisory notification in the mobile application, and in what portion of the mobile application to display the notification; and sending the advisory notification via the communications module to a client device to display the advisory notification in the mobile application.

Systems and methods are disclosed for optimization, management, and merging of processes. This system integrates a multifaceted technological framework, including generative artificial intelligence, quantum computing simulations, and blockchain technology. It features a user interface for inputting diverse workflow requirements, a generative AI module for processing these inputs, and a quantum computing module for simulating and optimizing workflows. The system utilizes blockchain for secure workflow deployment and a suite of specialized engines for prompt management, data extraction, analysis, optimization, deployment orchestration, and continuous monitoring. These components ensure the system's adaptability to user-specific needs, scalability across various industries, and capability for integration with existing enterprise systems. This invention revolutionizes BPM by streamlining processes, enhancing efficiency, and maintaining high security and customization standards.

The invention discloses a training resource recommendation method and system based on a knowledge graph and electronic equipment, and relates to the field of enterprise data processing, and the method comprises the steps: constructing a target talent knowledge graph of an enterprise; obtaining an existing talent knowledge graph of the enterprise; matching the target talent knowledge graph with the existing talent knowledge graph by using a graph matching algorithm, and calculating a matching degree; according to a matching result of the graph matching algorithm, training resource recommendation is carried out on enterprise employees so as to improve the matching degree of the existing talent knowledge graph and the target talent knowledge graph; and iteration is repeated until the matching degree is higher than a preset threshold value. According to the invention, enterprises can be helped to systematically evaluate and improve the ability of employees, and market demands and enterprise development objectives can be better adapted.

The invention discloses a commerce and trade circulation supply chain optimization method based on multi-modal data fusion, and the method comprises the following steps: 1, multi-modal data collection: collecting the multi-modal data of the whole supply chain in real time through an Internet of Things device, an enterprise ERP system, a logistics tracking system and a third-party platform, the multi-modal data comprises text data, image data, voice data, time sequence data and spatial data. When the scheme is implemented, multi-source heterogeneous data of the Internet of Things, ERP and the like are integrated, so that the problem of an information island in a traditional supply chain is effectively solved; position coding and a cross-modal attention mechanism are introduced into the multi-modal fusion model, so that the data alignment precision is remarkably improved, for example, when'emergency order adding 'in a voice communication record is associated with a corresponding order image, the weight distribution accuracy is improved; the application of the block chain technology ensures the transparency and traceability of the supply chain decision.

The invention discloses a cross-platform authority unified management method and system based on a multi-WEB system, and the key point of the technical scheme is that the method comprises the steps: obtaining organization structure data of an enterprise system, analyzing the organization structure data, constructing a multi-level tree topology network, forming organization entity topology parameters, analyzing the organization entity topology parameters, and storing the analyzed organization entity topology parameters into a database; according to the scheme, post authority baseline parameters are generated, dynamic optimization of channel selection is achieved by constructing a dual-channel transmission decision maker and combining real-time network state data and an inter-system interaction characteristic score table, and compared with a traditional static configuration mode, the mechanism can achieve dynamic optimization of channel selection according to parameters such as department communication strength, system transmission performance and safety scores. According to the method, the optimal transmission path is automatically selected, network congestion or high-delay nodes are avoided, cross-system adaptation rules are generated through mapping calculation of an authority interface strategy and post authority baseline parameters, the problem of authority granularity difference between different systems is solved, and the accuracy and consistency of authority distribution are ensured.

Techniques for operating a chatbot system for enterprise-level conversational agents are disclosed. These techniques are performed by an application or cloud service executing on one or more computing devices. An enterprise system can deploy conversational agents onto user devices to run as chat interfaces for logging analytics question-answering. One example application or cloud service may be a multi-model chat mechanism configured to support these chat interfaces with backend functionality. In response to an incoming question, the chat mechanism first consolidates the question with any conversation history and then, classifies the user's question as either a question regarding unstructured document data, a question regarding structured log data, or a hybrid question. Based on the classification, the chat mechanism can generate a proper large language model (LLM) response.

The invention relates to the field of enterprise safety assessment, in particular to an enterprise data safety capability assessment method and system. The method comprises the following steps of: obtaining an enterprise historical security log based on an enterprise information system, performing real-time data flow analysis and dynamic positioning of a storage position on the enterprise historical security log, and constructing an enterprise data flow mapping model; performing abnormal intrusion attack simulation on the enterprise data flow mapping model, performing enterprise security risk assessment, and marking potential risk nodes; performing historical normalized behavior analysis on the dynamic enterprise data flow model, and performing access behavior deviation detection on potential risk nodes to obtain abnormal intrusion behavior data of the enterprise system; and performing multi-time-window intrusion trajectory backstepping on abnormal intrusion behavior data of the enterprise system, and performing deep mining of abnormal attack features to obtain intrusion attack features. According to the invention, efficient and accurate enterprise data security assessment is realized, so that the enterprise is helped to make a targeted security protection decision.

The disclosure relates to the system and methods for generating a guidance path for automated navigation of large agricultural equipment. Vehicle path data from leading vehicles can be recorded, stored or inputted into the system for generation of guidance paths offset from the swaths traversed by the leading vehicle. Combines, planters sprayers and other vehicles utilizing guidance system can be used to record leading vehicle data for use by the following vehicle in real time or in subsequent cycles. Enterprise systems can manage multiple grain carts and / or combines or other vehicles to maximize efficiency.

The invention relates to the technical field of enterprise system construction, in particular to an enterprise standard system construction system based on dynamic classification and strategic adaptation, which comprises a dynamic classification module, a strategic adaptation verification module and a feedback optimization channel module, wherein strategic document semantic analysis and industry benchmark data are fused in real time through a dynamic classification module to generate a strategic weight coefficient, an environment sensitivity coefficient is calculated by combining compliance dynamics and a market risk model, and the fusion weight ratio of the strategic document semantic analysis and the industry benchmark data is dynamically adjusted based on threshold judgment, so that standard label weight distribution and hierarchical division are realized; the strategic adaptation verification module tracks the dynamic contribution degree of a standard node by using a node influence attenuation model of the association map, and detects strategic deviation by executing the deviation between an index and an expected value in real time; and after the feedback optimization channel module analyzes the deviation signal, the fusion weight is adjusted according to the deviation direction and amplitude, and standard level elastic lifting is triggered through sliding window monitoring, so that strategic suitability real-time verification and quantitative response to external environment change are realized.

The present disclosure relates to cybersecurity architectures and systems for assessing and quantifying security threats and risks associated with machine-readable codes, such as quick response codes, barcodes, data matrix codes, and other types of codes. A security application comprises a multi-context threat assessment system configured to analyze a broad spectrum of risk assessment attributes across multiple contexts. These contexts relate to the machine-readable code itself, target network resources identified by the code, entities affiliated with the code, end-users interacting with the code, and enterprise systems policies. The system can evaluate various risk assessment attributes for each of these contexts to more accurately quantify potential security risks associated with the machine-readable codes. The security application further includes an API for extending its threat assessment capabilities to various digital ecosystems and an AI-powered learning network comprising language models and computer vision systems to enhance threat detection and risk quantification capabilities.

Systems, computer program products, and methods are described herein for optimizing workflow management and response systems in a distributed network. The present disclosure is configured to integrate various enterprise systems, analyze workflow data for efficiency improvements, automate access management, and enhance task prioritization using advanced machine learning algorithms. Specifically, the system leverages real-time analytics and historical data to fine-tune workflows, predict delegation needs, and provide end-users with an actionable dashboard, thus streamlining operations and decision-making processes within an organization.

Techniques that enable users to generate an artificial intelligence (AI) integration configured to perform a task utilizing one or more machine learning models are described herein. An AI studio provides a user with options for creating a configuration object associated with an AI integration via a user interface. The AI studio may receive a request, from a user, to generate a prompt, the prompt defining an instruction to one or more machine learning model(s) (e.g., a large language model) to perform a task or generate an output based in part on input received from a user. A user may be presented with an option to select a type of transformer and deployment configuration to associate with the AI integration, the deployment configuration indicating an enterprise system and a deployment location within the enterprise system.

A system (100) for dynamic data pipeline configuration based on real-time enterprise integration context, comprising: (a) a context monitoring and event detection module configured to detect changes in enterprise systems in real time, including changes in data sources, schemas, system availability and regulatory conditions; b) an integration context analyzer configured to map and analyze the enterprise integration landscape, including data dependencies, formats, API endpoints, and metadata relationships; c) a pipeline orchestration and configuration engine configured to dynamically create, update, and deploy data pipelines in response to contextual triggers using the outputs of the integration context analyzer; (d) a rule-based decision and policy management module configured to apply user-defined and system-generated rules for data transformation, routing logic, security enforcement, and compliance controls during pipeline configuration; e) an AI and ML-driven optimization module configured to analyze historical data flow performance, predict bottlenecks, recommend schema transformations, and optimize pipeline efficiency based on learned patterns; f) a real-time data flow and transformation engine configured to perform adaptive ETL operations, handle schema evolution, support conditional transformations, and manage error recovery in live data streams; g) and an audit, logging and compliance module configured to maintain detailed records of pipeline actions, configuration changes and integration results for regulatory compliance, troubleshooting and traceability.

In order to actively monitor functioning of security infrastructure such as local security agents on endpoints in an enterprise system, a security update is created for the endpoints that includes a detection rule for use by the local security agents, along with a separate computing object including a trigger for the detection rule. The security update can be stored, e.g., at a threat management facility or similar, for retrieval by endpoints during a security update. When the security update is retrieved by an endpoint, it can be unpacked to add the detection rule to the local security agent, and then to add the trigger to the endpoint protected by the local security agent. A successful detection of the trigger by the (updated) local security agent on an endpoint can be transmitted to the threat management facility as a verification that the endpoint security measures are properly functioning and receiving updates.

Systems and methods for automated temporary device connectivity include receiving data requesting that a first device be associated with a second device and generating a request for an identifier of the second device to be associated with the first device. This request may be sent to an enterprise system and the second identifier may be received from the enterprise system. Data authorizing the first identifier to be associated with the second identifier for pairing purposes may be generated and stored. An indication may be received that the first device has moved within a threshold range of the second device and commands may be sent to cause the first device and the second device to enter a pairing mode.

A computer-implemented method includes: receiving, by a computer device, a request for a new online account for accessing data stored in an enterprise system; determining, by the computer device, an identity associated with the request; determining, by the computer device, a risk score for the request; determining, by the computer device, validation steps based on the risk score; and executing, by the computer device, the validation steps.

An enterprise system may include one or more devices with sensors that measure operational parameters of the devices. The enterprise system may also include a sustainability platform system that obtains a sustainability model representative of a state of operations of the enterprise based on the measured operational parameters and receives sustainability target data that includes one or more threshold limits, one or more ranges, or both for one or more sustainability parameters. The sustainability platform system may also obtain one or more action plans for adjusting respective operations of the devices based on the sustainability model and the sustainability target data, simulate a performance of the action plans over a period of time relative to the sustainability parameters, and determine whether the simulated performance of the action plans is effective.

The invention discloses an intelligent agent platform and information system integration compatible method and equipment, belongs to the technical field of digital transformation, and aims to overcome the defects of high cost, long development period, difficulty in maintenance and the like of an existing intelligent agent platform and information system integration scheme. And dynamic upgrading of an enterprise system and access of a new system are difficult to adapt. The method comprises the following steps: constructing dynamic protocol conversion middleware supporting multiple protocols, and converting heterogeneous protocol data through the dynamic protocol conversion middleware to obtain standardized data; performing format conversion on the standardized data through a hierarchical data converter to obtain readable data; respectively transmitting the high-frequency calling data and the low-frequency calling data to an intelligent agent platform through a hybrid communication bus; wherein enterprise sensitive data in the readable data is transmitted to the intelligent agent platform in a token form after being subjected to desensitization operation and / or encryption operation.

Techniques for a service provider network to manage a meeting between individuals located in a conference room with one or more other individuals remote from the conference room are discussed herein. An Enterprise system can implement one or more machine learned models to generate tiles that represent different individuals associated with a meeting. A same or different machine learned model can automatically arrange a series of tiles for display that, when presented collectively, promotes inclusiveness and attention for both in-room and remote participants of the meeting. The meeting management techniques can include determining which content to include on a display device based on evaluating changes in behavior of the meeting participants over time.

The invention relates to the technical field of information security, in particular to a cluster self-discovery method suitable for a cloud server cipher machine, which comprises the following steps: when physical equipment of the cloud server cipher machine leaves a factory, a certificate management module generates an equipment certificate and a root CA certificate in combination with an enterprise CA system, and stores the equipment certificate and the root CA certificate; after the virtual cipher machine is created and started, the key management service module combines with the certificate management module to generate a virtual machine certificate, and stores the virtual machine certificate, the storage device certificate and the root CA certificate together; the cluster management service module enables the master node of the virtual cipher machine to discover the slave node of the virtual cipher machine in the same network domain through UDP broadcast, and executes three-level verification on the slave node of the virtual cipher machine from three aspects of an equipment certificate, a virtual machine certificate and an authentication signature; and the virtual cipher machine master node synchronizes the cluster master key to the virtual cipher machine slave node passing verification. According to the invention, hierarchical identity isolation and verification of the cloud server cipher machine host and the virtual cipher machine can be realized, and the security of cluster self-discovery and authentication stages is ensured.

A system and method for generating a guidance path for automated navigation of large agricultural equipment. Vehicle path data from leading vehicles can be recorded, stored or inputted into the system for generation of guidance paths offset from the swaths traversed by the leading vehicle. Combines, planters sprayers and other vehicles utilizing guidance system can be used to record leading vehicle data for use by the following vehicle in real time or in subsequent cycles. Enterprise systems can manage multiple grain carts and / or combines or other vehicles to maximize efficiency.

A hybrid architecture that combines the efficiency of small language models with the accuracy of large language models for enhanced selection of requested functionality and identification of data visualizations using an enterprise system is described. For instance, a widget selection method employs a hybrid architecture using both small and large language model to efficiently search through possible widgets by using an LLM to vectorize the titles widgets and information associated with those widgets and a small language model to use a natural language model to search the vectorized widgets.

At least one non-transitory computer readable media storing instructions that, when executed by one or more hardware processors, causes performance of operations. The operations include receiving a natural language query defining a policy for a workflow. The operations also include retrieving supplementary information relevant to at least one of the workflow and the natural language query, wherein the supplementary information includes at least one code fragment. The operations further include building an input prompt for a large language model. The input prompt includes the natural language query and the supplementary information, and the input prompt directs the large language model to generate, based at least in part on the at least one code fragment, code that is executable to implement the policy for the workflow.

The invention relates to the technical field of ERP financial risk assessment, and discloses an ERP financial data risk assessment method based on machine learning. The method comprises the steps of obtaining multi-dimensional historical financial data in a target enterprise ERP system, and performing preprocessing to generate a standardized financial data set associated with a timestamp and a financial index type label; constructing a dynamic feature extraction network, and extracting time sequence correlation features and cross-dimension coupling features from the dynamic feature extraction network according to tags; initializing a risk assessment model containing a parallel anomaly detection branch and a trend prediction branch, wherein the two branches respectively receive corresponding features; iteratively optimizing the model by adopting a hierarchical adversarial training strategy until two branch outputs meet an error convergence condition; and inputting real-time ERP financial data, and generating an evaluation report containing a risk level mark and a confidence score. The method adapts to ERP financial data characteristics through cooperation of multi-dimensional feature extraction and a double-branch model, and can be effectively used for enterprise financial risk management and control.

The invention discloses an intelligent accounting and analysis system for enterprise operation cost and expense, and relates to the technical field of intelligent accounting and analysis of enterprise operation, comprising a data preprocessing module used for obtaining original cost data from an enterprise ERP system, a financial system and a production management system, performing cleaning, field mapping and time sequence alignment operations on the original cost data, and outputting a structured unified data set; the deviation decomposition module is used for dividing a total cost deviation into four types of components, namely a usage difference, a price difference, an efficiency deviation and a structure migration deviation, based on a budget value and an actual value in the structured unified data set, performing attribution analysis according to a department, a product line or a project dimension, and outputting deviation detail data; and the weight calculation module is used for generating a dynamic weight vector according to the historical fluctuation characteristics of each cost item in the deviation detail data and the business association strength of the cost item in the enterprise operation in combination with an external market change signal.

The invention relates to the technical field of artificial intelligence, in particular to a hierarchical tree and auto-reflection-based retrieval enhancement generation method, device and medium, the method comprises: constructing a multi-layer tree structure knowledge base, the knowledge base comprising a plurality of tree index structures constructed based on text similarity, enterprise organization architecture and level architecture; receiving user query and user identity information; generating a plurality of sub-queries corresponding to different retrieval intentions based on the user query and the user identity information; performing multi-path retrieval on each sub-query in the corresponding tree index structure to obtain a related knowledge fragment set; and based on an auto-reflection mechanism, a final answer is generated, and knowledge traceability is realized at the same time. According to the method, the problems of low knowledge base quality, poor retrieval result correlation and single retrieval path in the traditional RAG technology are solved, and the accuracy, correlation and interpretability of enterprise system questions and answers are remarkably improved.

In an example embodiment, machine learning is utilized to create a virtual world where a user can view and interact with data in a graphical environment. This virtual world may be termed a “Story Verse” environment, which can create multiple different virtual world universes capable of segmenting the traditional complexities of Enterprise system data into an easily usable and holistic set. In a further example embodiment, the virtual world is presented in a way that data is represented as real world objects, such as amusement park rides, clouds, etc.

The invention relates to the technical field of system compliance management, and discloses a system compliance early warning method and system, electronic equipment and a storage medium, and the method comprises the steps: collecting system file data, and carrying out the standardization processing and structural analysis; data preparation is carried out based on the system metadatabase and the supervision fine tuning corpus set, an initial model is constructed and trained, a trained system large model is formed, and version management is carried out; determining early warning types, establishing a system revision early warning model for different early warning types, and triggering early warning reminding according to an output result of the early warning model; performing difference comparative analysis on the same-theme systems based on the system large model, and generating a compliance inspection report; receiving a natural language question, generating an answer and providing system traceability information; a system outline is generated according to system revision requirements, a chapter summary and clause content are generated based on the system outline, and real-time compliance check and clause recommendation are supported. According to the invention, the intelligent demand of enterprise system full-life-cycle management can be met.