83 results about "Enterprise computing" patented technology

Various aspects of the disclosure relate to enforcing dynamically updated network security policies in real-time (or upon an identified update) from multiple organizations and anonymously analyze computing system configuration information uploaded from third-party computing systems. An analysis engine monitors compliance information and compare the compliance information against the security rules and / or requirements for one or more enterprise networks. A visualization providing a network map with a visual representation of each product system service system may include communication links between internal applications and / or computing systems and drill-down capability to identify issues as they are occurring or are predicted to occur. The security escrow system may include a mechanism to automatically enable / disable access between third party networks and one or more enterprise computing systems in real-time based on identified compliance information.

The invention relates to the technical field of computing power resource sharing in a data center application environment, and discloses an enterprise computing power layout and intelligent decision mobile application system and an implementation method thereof. And real-time monitoring and dynamic scheduling of internal or cloud computing resources of an enterprise are realized. Historical data and real-time load are processed by using machine learning and an optimization algorithm, an optimal scheduling scheme is generated, and an alarm is automatically triggered when abnormality is detected, so that efficient utilization of enterprise resources is ensured. The method has the advantages of being high in real-time performance, intelligent, flexible in expansion, safe, reliable and the like, and the operation and maintenance efficiency and decision response speed of enterprises can be remarkably improved.

Systems and methods for an enterprise computing platform may include a server that may include a desktop-as-a-service module, a user behavior analytics module, a remote monitoring and management module, an analytics-as-a-service module, an insider threat prevention and monitoring module, and a project tracker module. The server or modules may provide remote desktop sessions in an efficient and convenient manner, may analyze user behavior and automatically execute corrective actions in response to rules violations, and may monitor and manage multiple computer systems and computing sessions as to their statuses, versions, authentication, or compliance.

An agent deployment system for adaptively managing artificial intelligence agents within an enterprise computing environment. The system can include an agent subsystem having a control agent configured to receive source data from one or more data sources of the enterprise, continuously monitor the source data for an occurrence of a trigger event indicative of a condition requiring an AI based intervention, detect the trigger event, evaluate the trigger event to identify a relevant operational context, and then based on the trigger event and the operational context, select and deploy the plurality of AI agents from a total set of AI agents to address the trigger event by performing an AI-based intervention.

A computer-implemented system and method for evaluating an AI agent associated with an enterprise computing environment by aggregating a plurality of AI agents associated with the enterprise computing environment, and evaluating, with an agent evaluation unit, a selected AI agent of the plurality of AI agents using evaluation data, wherein the evaluation data includes operational behavior data and trustworthiness data. The agent evaluation unit can be configured to determine a total agent evaluation score for the selected AI agent from a plurality of category specific evaluation scores. The agent specific categories can have associated therewith a category evaluation score and the agent specific categories can include categories associated with the operational behavior and the trustworthiness of the selected AI agent. An AI-based intervention can be applied in response to the total agent evaluation score.

The invention discloses an industrial chain generation method and system based on big data, and the method comprises the steps: designing a main structure of an industrial chain and a keyword table of each node, and determining the classification of the upstream, the middle and the downstream of the industrial chain, including a main node, a child node, a branch node, a name of each node and a keyword contained in the node; multi-dimensional industrial data such as industry and commerce data, bidding and tendering, public opinions, patents and software aboriginal information of enterprises are collected and acquired, and an enterprise basic database is established; primary screening of the uplink enterprises: screening the enterprises from the enterprise basic database according to the industrial chain node keywords, and incorporating the enterprises into an alternative uplink enterprise database; the enterprise upper chain evaluation index system is used for evaluating the matching degree between dimension information such as the business scope, the technical achievement, the public opinion information and the bidding and tendering of the enterprise and the industrial chain node; selecting each node benchmark enterprise on an industrial chain according to industrial research, and calculating each uplink index of each benchmark enterprise; calculating a vector distance between the primarily screened selected enterprise and the benchmarking enterprise; ranking the similarity calculation results in a descending order; according to the Pareto's law, the first 20% of enterprises are taken to be linked, and a complete industrial chain is constructed. The method comprises the following steps: collecting enterprise multi-dimensional data, constructing an industrial chain main body structure and each node keyword, screening to-be-linked enterprises according to keywords, establishing an uplink evaluation index system, calculating vector distances between the to-be-linked enterprises and benchmarking enterprises, and determining an uplink enterprise mode according to vector distance ranking to generate an industrial chain. The method is beneficial for improving the accuracy and efficiency of industrial chain generation, so that reference basis is provided for scientifically evaluating the industrial development level, making investment decisions of industrial development, making effective industrial policies and the like.

A system associated with an enterprise computing environment infrastructure may include a chaos testing tool data store that contains a plurality of electronic records, each record including a chaos engineering fault parameter. A computer processor of a chaos testing tool may receive, from a chaos testing user, injection information associated with an element of the enterprise computing environment infrastructure. The chaos testing tool may then access the chaos engineering fault parameter from the chaos testing tool data store and automatically arrange to inject a chaos engineering fault into operation of the element of the enterprise computing environment infrastructure in accordance with the injection information and the chaos fault parameter. A response of the element of the enterprise computing environment infrastructure may then be measured subsequent to said injection, and the system may output an indication of the measured response to the chaos testing user.

The invention provides an ocean and related industry classification and identification method and system. The method comprises the following steps: S1, establishing an enterprise credit information database; s2, acquiring a standard file, and performing text preprocessing on the standard file and the manual identification sample; s3, establishing a sea-related enterprise identification model according to an artificial identification sample and the standard file; s4, identifying the to-be-identified enterprise by using the sea-related enterprise identification model to obtain a model identification sample, and calculating the identification accuracy and the extra identification ratio of each marine industry by comparing the model identification sample with the artificial identification sample; s5, adjusting the sea-related enterprise identification model, and identifying the to-be-identified enterprise by using the adjusted sea-related enterprise identification model to obtain an enterprise classification result; and S6, calculating an evaluation score of each identified marine industry for the enterprises in the enterprise classification result. The method can improve the accuracy of the recognition result, has interpretability, and can display the classification basis.

Various aspects of the disclosure relate to enforcing dynamically updated network security policies in real-time (or upon an identified update) from multiple organizations and anonymously analyze computing system configuration information uploaded from third-party computing systems. An analysis engine monitors compliance information and compare the compliance information against the security rules and / or requirements for one or more enterprise networks. A visualization providing a network map with a visual representation of each product system service system may include communication links between internal applications and / or computing systems and drill-down capability to identify issues as they are occurring or are predicted to occur. The security escrow system may include a mechanism to automatically enable / disable access between third party networks and one or more enterprise computing systems in real-time based on identified compliance information.

A system and method for the dynamic authentication revocation using privilege assurance of enterprise computer network environments using lateral movement detection and prevention. The system uses local session monitors to monitor logon sessions within a network, generating and verifying event logs and authentication records to ensure the legitimacy of authenticated user sessions and to revoke credentials when an illicit session is detected and further removing potentially compromised network components from the network, halting lateral movement in real-time.

An enterprise engineering and configuration system includes a common configuration database and support services stored in and executed in a compute fabric of an enterprise. The configuration database and support services use and implement a common configuration data schema to support the configuration of hardware and software in the compute fabric and at multiple different sites or physical locations of the enterprise even when different control and automation systems are used at these different sites or physical locations. The configuration system enables implementing hardware or software configuration changes to various different sites or locations of an enterprise either centrally from a configuration device connected directly to the compute fabric of the enterprise or locally from any physical location or site of the enterprise, while maintaining a single integrated enterprise configuration database that stores configuration data for each of the multiple sites of the enterprise. This configuration system is flexible as it enables engineering and configuration changes to be made by users anywhere in the enterprise for any of the sites of the enterprise and across different sites of the enterprise.

A. method of application modernization engine executed by processors. The application modernization engine provides improved application development through simulated intelligence and expanded tooling. The method includes determining, by the application modernization engine, a collection of resources to support a first functionality within an existing enterprise computer system and provide a set of outcomes. The method includes developing, by the application modernization engine, an application including the collection of resources with no-code and full-code operations. The method includes augmenting, by the application modernization engine, the application with a second functionality not present in the existing enterprise computer system. The method includes deploying, by the application modernization engine, the application into the existing enterprise computer system.

Systems and methods are provided for agentless attestation. Agentless attestation can measure the integrity of customer servers without requiring an agent software program to be downloaded to each of the enterprise computer devices. In particular, the system can integrate several standalone components to measure the integrity of monitored devices. This also allows the data center to authenticate, verify, audit, and update any hardware change, including a Platform Certificate.

Various embodiments relate generally to data science and data analysis, computer software and systems, and computing architectures and data models configured to facilitate management and performance of enterprise functions, and, more specifically, to an enterprise computing and data processing platform configured to implement applications and computerized tools configured to facilitate implementation of an enterprise data model to generate and manage component data objects representing enterprise tasks and processes, as well as portions thereof, any of which may be used to create and modify an enterprise data flow or a process flow, for example, using an enterprise computerized tool. In some examples, a method includes activating one or more applications as computerized tools to access subsets of one or more permissions, identifying an enterprise function data object to generate a third subset of permissions.

A method of application modernization engine executed by processors. The application modernization engine provides an improved contextual document processing and specific information extraction. The method includes receiving, by document intelligence sub-system of the application modernization engine, data of an enterprise computer system generated by artificial intelligence agents. The method includes processing, by the document intelligence sub-system, the data by extracting and ingesting specific contextual information to achieve document classification and feature extraction. The method includes providing, by the document intelligence sub-system, the specific contextual information, the document classification, and the feature extraction to the artificial intelligence agents to implement processes on top of the existing enterprise computer system to achieve objectives.

Embodiments of systems and methods disclosed herein provide an application development platform in an enterprise computing environment. More specifically, in certain embodiments, systems and methods are disclosed that enable an application development platform to reuse, extend, and / or customize entity-based applications in an enterprise computing environment. The application development platform can extend an entity to include user configured settings including zero or at least one of a property, a permission, an action, a behavior, or a resource to the entity to generate user customized versions of the entity. The applications may be customized by an end user, while allowing the underlying application to be updated without losing any user customizations.

A document capture server receives a document image from a document capture client and processes the image into an electronic document containing textual content. During capture, the document capture server determines a graphical layout of the document, extracts keywords from the document, classifies the document accordingly, and calls an artificial intelligence (AI) platform to gain insights on the textual content. The AI platform analyzes the textual content and returns additional, insightful data such as a sentiment of the textual content. The document capture server can validate the additional data, integrate the additional data in a process or workflow, and / or provide the textual content and the additional data to a content repository or a computing facility operating in an enterprise computing environment. The document capture server can provide validated data to the AI platform to improve future analyses by the AI platform.

A system and method for monitoring and optimizing work assistant search engines implemented within secured enterprise computing systems include one or more processing devices to receive diagnostic data of a work assistant search engine from a secured enterprise computing system. The one or more processing devices may further determine, by analyzing the diagnostic data, a search quality metric value associated with the feature values and the scores. Responsive to determining that the search quality metric value differs from a target search quality metric value by a predetermined threshold value, the one or more processing devices may further determine an updated score model, and provide the updated score model to the secured enterprise computing system to update the work assistant search engine.

A method and system for synchronizing secrets in an enterprise computing network include a secret and a representation of a directed acyclic graph (DAG) generated at a secret client vault device. The representation of the DAG having a plurality of nodes and a plurality of edges, the plurality of nodes including a record node associated with the record, a leaf node associated with a second secret vault client device, and one or more intermediate nodes and the plurality of edges specify a traversal path from the record node to the leaf node. Transmitting a data stream to the second secret vault client device that comprises multiply encrypted data generated in accordance with a traversal of the representation of DAG and representations of the encryption keys associated with the record node and the one or more intermediate nodes of the DAG traversed to generate the multiply encrypted data.

Computer-implemented systems and methods provision a virtual machine sandbox for evaluating software. Firewall means are provisioned for a cloud network to permit access to an internet site from which source code is downloadable. A client computer device, via virtualization, controls a virtual machine. The client computer device is on an on-premises network that is different from, and in communication with, the cloud network. The virtual machine is controlled to: (a) download to the virtual machine, via the firewall means, the source code from the internet site; and (b) execute the source code for evaluation of the source code. The virtual machine is deleted after a predetermined time period. The source code is prohibited, after provisioning the virtual machine and through deletion of it, from being downloaded from the virtual machine to computer devices on the on-premises network.

A system associated with an enterprise computing environment infrastructure may include a chaos testing tool data store that contains a plurality of electronic records, each record including a chaos engineering fault parameter. A computer processor of a chaos testing tool may receive, from a chaos testing user, injection information associated with an element of the enterprise computing environment infrastructure. The chaos testing tool may then access the chaos engineering fault parameter from the chaos testing tool data store and automatically arrange to inject a chaos engineering fault into operation of the element of the enterprise computing environment infrastructure in accordance with the injection information and the chaos fault parameter. A response of the element of the enterprise computing environment infrastructure may then be measured subsequent to said injection, and the system may output an indication of the measured response to the chaos testing user.

The present invention discloses a method and system for allocating and scheduling enterprise computing power resources, and specifically relates to the technical field of resource allocation and scheduling. Test tasks are generated by simulating real scenarios, and scheduling success rate fluctuation characteristics and conflict resolution efficiency characteristics are extracted. The scheduling accuracy is evaluated by a machine learning model, and the results are classified into accuracy scheduling, incomplete accuracy scheduling, and inaccuracy scheduling. For accuracy scheduling, the existing strategy is maintained and continuously monitored. For inaccuracy scheduling, the algorithm is reconstructed. For incomplete accuracy scheduling, the resource pool ratio is dynamically adjusted by predicting the degree of abnormality, and low-priority tasks are switched to a spare resource pool when the degree of abnormality is high, which significantly improves the rationality of resource allocation and scheduling accuracy, ensures the real-time performance and resource utilization efficiency of key tasks, and reduces the system scheduling failure rate and the economic losses caused by resource conflicts.

The invention relates to the crossing field of artificial intelligence and enterprise computing, in particular to an information alignment system based on an AI proxy network and a dynamic consensus mechanism, which comprises an AI proxy network module, a consensus verification system and an arbitration module, the AI proxy network module comprises one or more sites; information is transmitted between the sites through a structured communication protocol; the AI proxy network module and the consensus verification system transmit response information through a data link; the consensus verification system and the arbitration module transmit a consistency check result through a preset communication channel; the arbitration module is connected with the AI proxy network module and communicates with an external entity through a man-machine interaction interface. According to the invention, a distributed AI proxy network and a dynamic consensus mechanism are adopted, so that decentralized reliable operation is realized, and a single-point fault is avoided; conflicts are accurately detected through semantic alignment, deduction alignment and echo technologies, and the AI error rate is reduced; site roles are flexibly adjusted through modular design, multi-scene tasks are adapted, cost is reduced, efficiency is improved, and decision-making precision is improved.

Various embodiments relate generally to data science and data analysis, computer software and systems, and computing architectures and data models configured to facilitate management and performance of enterprise functions, and, more specifically, to an enterprise computing and data processing platform configured to implement applications and computerized tools configured to facilitate implementation of an enterprise data model to generate and manage component data objects representing enterprise tasks and processes, as well as portions thereof, any of which may be used to create and modify an enterprise data flow or a process flow, for example, using an enterprise computerized tool. In some examples, a method includes activating one or more applications as computerized tools to access user account and enterprise function data, identifying permissions, and filtering access to logical components as a function of, for example, persona application data generated using a persona builder application.

Embodiments of systems and methods for the centralized configuration of distributed heterogeneous services are disclosed herein. Embodiments of such systems and methods may be utilized to configure one or more service instances executing in an enterprise computing environment where each of the set of service instance is one of a set of service types that may be different. These services may, for example, be off-cloud services associated with a cloud based computing platform.

A system and method for monitoring and optimizing work assistant search engines implemented within secured enterprise computing systems include one or more processing devices to receive diagnostic data of a work assistant search engine from a secured enterprise computing system. The one or more processing devices may further determine, by analyzing the diagnostic data, a search quality metric value associated with the feature values and the scores. Responsive to determining that the search quality metric value differs from a target search quality metric value by a predetermined threshold value, the one or more processing devices may further determine an updated score model, and provide the updated score model to the secured enterprise computing system to update the work assistant search engine.

The invention relates to a business relation chain reaching method and system based on a relation graph. The method comprises the following steps: receiving identification information of a target enterprise; based on the identification information, collecting multi-dimensional relation data of the target enterprise; according to the multi-dimensional relation data, constructing a graph data structure with enterprises as nodes and relations between the enterprises as edges; by taking the target enterprise as a starting point, carrying out multi-level relation expansion in a graph data structure, and discovering a reachable enterprise; for a reachable enterprise, calculating a relation path from the target enterprise to the reachable enterprise; based on the calculation result of the relation path, generating an analysis result containing a relation link list, a path analysis report and a reachable enterprise relation graph; and outputting a visual result of the analysis result. The method has the effects of comprehensive integration of multi-dimensional relations, intelligent discovery of multi-level accessible resources, efficient relation path analysis, visual and interactive graph visualization and real-time dynamic updating of data.

The arrangement and composition of elements herein describe an enterprise-level cloud computing capability having a small and portable form factor. This highly capable and portable system is made possible through the combination of high-density computing elements, storage elements, networking elements, cooling elements, and power distribution elements in a single unit that result in a system able to be carried by one person. This portable system therefore affords the functionality and capability of an enterprise cloud server stack where space and / or physical infrastructure limitations prevent the utilization of traditional on-prem cloud server racks typically housed in a remote server rack farm or data center. In addition to the privacy and security benefits of an on-premises enterprise cloud capability, this also provides processing, storage, and networking mobility, as the unit can more easily and quickly be moved from location to location and without the need for server rack equipment.

Techniques are disclosed relating to a method that includes receiving, by a particular computer system included in an enterprise computer system, deployment instructions, from a user, for a particular version of a machine-learning model. One or more versions of the machine-learning model may be stored in a database. The particular computer system may select, based on the deployment instructions, a destination within the enterprise computer system for deploying the particular version. The selected destination may provide access to a particular data set. The particular computer system may schedule a deployment of the particular version from the database to the selected destination. The deployed version of the machine-learning model may operate on the particular data set. Performance data associated with operation of the deployed version of the machine-learning model is collected.

Systems and methods for securely and privately monitoring risky web activities in an enterprise computing system. A service is provided that communicates with a first client- application deployed on a user device and a second client-application deployed on an administrator device. A secure enclave is deployed by the service that ensures zero-knowledge to store sensitive user data (e.g., activity logs of risky web activity logged by the first client- application). Team-Service Logged-Out keys and Team-Enclave Logged-Out keys are deployed to the user device. When an end user associated with the user device is not logged into the service, the Team-Service Logged-Out keys and Team-Enclave Logged-Out keys are used to authenticate the logged-out end user so that an activity log can be sent to the secure enclave and stored. The activity log can be accessed by the second client-application upon authentication of the administrator using a Device-Enclave key pair associated with the administrator.