Machine learning based processing of network operations using sequence alignment is described to meet performance criteria. A system can identify, from a plurality of function sequences, a sequence to perform an action and identify, for the action, a constraint on an order of functions within the sequence. The system can identify a machine learning (ML) model trained on performance data related to execution of actions using sequences of functions and according to a plurality of constraints for the plurality of actions. The system can determine, using the ML model, a likelihood that the sequence of functions performs the action within a performance tolerance and according to the constraint. The system can provide, responsive to the likelihood satisfying a threshold, an instruction to the transaction processing system to cause the transaction processing system to perform the action using the sequence of functions.
A computer-implemented method, system, and computer program product for configuring a pay statement. An input area is presented for a user to enter settings defining how the pay statement is to be configured. The settings are received from the user. A preview of the pay statement is displayed in a preview area based on the settings. The preview provides a visual representation of how the pay statement will appear for the settings. The user may modify the settings until the preview appears as desired by the user.
A system and method for dynamic script generation for automated filing services is provided. In embodiments, a method includes: initiating a clickstream recording of an electronic document filing interface of a remote platform based on a triggering event; generating a clickstream recording of the electronic document filing interface, wherein the clickstream recording comprising a recording of a navigation of the electronic document filing interface through multiple steps of a document filing process, wherein the clickstream recording is in the form of scripts associated with each of the multiple steps of the document filing process; and generating automated filing instructions for the electronic document filing interface using the clickstream recording, the automated filing instructions enabling computer automated submission of one or more documents to the remote platform via the electronic document filing interface.
Vector-based hybrid search for chatbots is provided. A system receives, via a chatbot, a user query. The system generates, using an artificial intelligence model, a vector representation based on a combination of the user query, historical queries, and corresponding responses and identify a cached response corresponding to the user query in a semantic cache using the vector representation. The system executes, based on the cached response, a hybrid search operation including retrieval of first and second results having a first and second accuracy value by execution of a first and second search process on a first and second data source. The system selects one of the first or the second results based on modeling the first and the second accuracy value and displays, responsive to the user query, an output corresponding to the selected results.
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
8.
Display screen or a portion thereof with a graphical user interface
A method receives an electronic image and uses the image as an input to a neural network. Based on a determination that the image represents a document, the method uses the image as an input to another neural network to identify a portion of the document containing an identifier. The method extracts the identifier by performing character recognition on the identified portion and determines whether the identifier is valid by using a validation API to determine whether the identifier is associated with a valid account at an institution. Based on a determination that the identifier is associated with a valid account, the method authorizes a transaction associated with the identifier. Based on a determination that the identifier is not associated with a valid account, the method denies the transaction. The first neural network classifies the electronic image into one of multiple valid document types and an invalid document type.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06V 30/146 - Alignement ou centrage du capteur d’image ou du champ d’image
G06V 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux
G06V 30/416 - Extraction de la structure logique, p. ex. chapitres, sections ou numéros de pageIdentification des éléments de document, p. ex. des auteurs
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Providing temporary use of non-downloadable computer software for employee and personnel related services, namely, payroll processing, preparation, and administration, tax regulation compliance, employee benefits administration, human resources management services, employee recruiting, and pre-employment background screening
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Payroll processing, preparation, administration, and recordkeeping; Providing human capital management (HCM) services for others; Human resources (HR) management and administration Providing temporary use of non-downloadable computer software for employee and personnel related services, namely, payroll processing, preparation, and administration, tax regulation compliance, employee benefits administration, human resources management services, employee recruiting, and pre-employment background screening
14.
Display screen or a portion thereof with a graphical user interface
Data digitization via custom integrated machine learning ensembles is provided. For example, a system integrates multiple trained machine learning ensembles to identify, extract, and map data. The system receives a data set from sources. The system identifies ensembles can include machine learning models that can determine an outcome. The system filters a subset of data from the data set. The system identifies a layout for the data set based on a vendor type, data type, and the data set. The system executes a block detection module to identify blocks of the layout. The system executes a header detection module. The system executes a policy detection module to identify the headers as policies. The system transforms, based on the headers, the layout, the blocks, and the policies, the data set into a second file type, and presents the transformed data set for integration into a capital management system.
A method, apparatus, system, and computer program code for onboarding client information for provisioning multiple software services. On a first page of the graphical user interface, client location data is received in a consolidated manner for the multiple services. Within the first page of the graphical user interface, each of the multiple software services is configured using a plurality of guided question. The client location data is organized according to Federal Employer Identification Number. Groups of client location data, organized per FEIN, are displayed on a second page of the graphical user interface, providing an easier onboarding process that reduces no-starts and enables a client to onboard services more quickly and accurately.
A system for processing employment documents includes one or more processors, coupled with memory. The one or more processors are configured to receive an input document, determine that the input document is associated with a first field and a second field, extract a first extracted text string corresponding to the first field and a second extracted text string corresponding to the second field, generate a first generated text string associated with the first field based on the first extracted text string, and generate a second generated text string associated with the second field based on the second extracted text string.
G06F 40/166 - Édition, p. ex. insertion ou suppression
G06V 30/416 - Extraction de la structure logique, p. ex. chapitres, sections ou numéros de pageIdentification des éléments de document, p. ex. des auteurs
19.
Display screen or a portion thereof with a graphical user interface
Systems and methods are provided to integrate an email validation application with a web application. A custom email composer of the web application may include a context identifier in a draft email, where the context identifier identifies an issue activity log. The email validation application may validate the draft email in response to a validation request received from the custom email composer, where the validation request includes the context identifier. A custom backend component of the web application may write a validation status to the issue activity log in response to receipt of the validation status from the email validation application. The custom backend component may send the draft email in response to the validation status indicating the draft email is validated.
A method, apparatus, system, and computer program code for automatic data retrieval and validation. A computer system generates an audit file including a set of data objects. The computer system validates the data objects with a compliance policy by deploying a set of software bots to interact at a user level with a set of application programs. In response to validating the data objects, the computer system reflects validation results into a user interface.
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
Aspects extract, from payroll data of employees of an organization, data historically associated to previous instances of certified tax credit eligibility; normalize the extracted data with respect to data type and data value; generate from the normalized extracted data via a neural network classifier multi-class outputs for each employee that indicate strengths of likelihood that each employee is currently eligible for each of a plurality of different tax credits; filter the normalized extracted data by removing portions associated to employees indicated within the multi-class outputs as having no currently eligible likelihood for the different tax credits, thereby generating a remainder set of normalized extracted data associated to remainder eligible ones of the employees; and prioritize application for the tax credits for the remainder eligible employees as a function of respective values and likelihoods of eligibility within the remainder set of normalized extracted data.
A system can receive, from a client device, a request to execute an automatic repeating network operation using a profile data structure. The system can query a database to retrieve multiple source identifiers and corresponding computing infrastructure identifiers. The system can cause the client device to present a user interface comprising an interface object for each of the source identifiers. The interface object can be configured to display configurations for the automatic repeating network operation associated with a respective source identifier. The system can receive interactions corresponding to partial switches for the automatic repeating network operation for at least two of the multiple source identifiers. The system can generate one or more executable commands to cause a payroll processing system to update the profile data structure based on the interactions. The system can execute the automatic repeating network operation in accordance with the updated profile data structure.
Payroll processing, preparation, administration, and recordkeeping; Providing human capital management (HCM) services for others; Human resources (HR) management and administration
Dynamic session headers for a computing session via a remote dictionary are provided. A system establishes a session responsive to receiving a first request from a browser, the session authenticated using a cookie configured to access a first electronic record. The system stores data corresponding to the session in a remote dictionary server. The system identifies a second request to modify the session to access a second electronic record and accesses, using the cookie, the data corresponding to the session from the remote dictionary server. The system receives, using a reverse proxy technique, data to update the session. The system modifies the session by storing the second identifier in the remote dictionary server and provides the browser with access to the second electronic record via the session.
A system can include one or more processors coupled with memory. The one or more processors can determine that a first collection of resources is coupled with the first entity, detect that a second collection of resources has been decoupled from a second entity, cause a user interface to display a first element configured to receive an input to cause an aggregation of the second collection of resources into the first collection of resources based on the first collection of resources being coupled with the first entity, retrieve an electronic form associated with the aggregation of the second collection of resources into the first collection of resources, cause the user interface to display a second element configured to receive information for one or more fields included in the electronic form, and transmit one or more signals to provide the electronic form to a third entity.
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Educational services, namely, providing online continuing education courses, training programs, and instructional materials in the fields of behavioral health, substance use disorder treatment, mental health care, and clinical practice, for healthcare professionals and clinicians, and providing patient education services in the form of online educational information and materials in the fields of behavioral health, substance use disorder recovery, mental health, and wellness, and issuing certificates of completion and continuing education unit (CEU) credits to healthcare professionals and clinicians in connection with the foregoing courses and training programs. Providing online non-downloadable software for use by behavioral health professionals, healthcare practitioners, healthcare practice administrators, and patients, namely, software for electronic health records management, clinical documentation, patient scheduling, appointment management, telehealth and telemedicine services, outcomes measurement and measurement-based care, hosting and delivery of third-party educational content, continuing education credit tracking and management, and healthcare practice management, expressly excluding employment agency services, staffing services, recruiting services, and personnel placement services.
30.
SYSTEMS AND METHODS FOR OPTICAL CHARACTER RECOGNITION
A system can include one or more processors to receive a compressed file, split the compressed first file into a first document and a second document, detect a first page, detect a second page, determine, based on a comparison of the first page with a plurality of stored formats, that the first page matches a first stored format of the plurality of stored formats, detect, using optical character recognition, a first field of the first page, determine, based on a comparison of the first field with a plurality of stored fields, that the first field matches a first stored field of the plurality of stored fields, extract, using optical character recognition, a first field value of the first field, and store, an association of the first field value to the first field, the first page, and the first document.
G06V 30/418 - Appariement de documents, p. ex. d’images de documents
G06V 30/19 - Reconnaissance utilisant des moyens électroniques
G06V 30/412 - Analyse de mise en page de documents structurés avec des lignes imprimées ou des zones de saisie, p. ex. de formulaires ou de tableaux d’entreprise
Intelligent data ingestion is provided. A determined column header name of a selected column in an imported data file is mapped to a predicted corresponding column header name of a particular column in a database corresponding to a human capital management application using a plurality of machine learning models. It is determined whether the predicted corresponding column header name output by each respective machine learning model of the plurality of machine learning models matches. In response to determining that the predicted corresponding column header name output by each respective machine learning model of the plurality of machine learning models does match, the predicted corresponding column header name of the particular column in the database is utilized as a target column name for the determined column header name of the selected column in the imported data file.
The present disclosure relates to a system and method of providing analysis of chatbot conversation paths, and more particularly, to a system and method which provides visual and data observation of conversation paths and related information to provide a more efficient means of analysis. The method includes: receiving, by a computer system, a plurality of conversational transcripts, converting, by the computer system, the plurality of conversational transcripts into a visualization which includes a plurality of branches representing different conversation paths for the plurality of conversational transcripts; and displaying, by the computer system, the visualization with the plurality of branches.
A method for fact retrieval includes receiving an input from a user, said input including a string of text that represents a user intent. The method includes performing natural language processing on the input to generate an embedding that corresponds to a semantic representation of the string of text, and based on the generated embedding, identifying an action that is associated with the user intent. The method includes executing the identified action, such that the executed action returns a result associated with the user intent, and providing the result to the user.
A system can include one or more memory devices that can store instructions thereon that, when executed by one or more processors, cause the one or more processors to receive a selection to indicate a request for a form for display via a user interface. The retrieved form can have a first format. The system can detect that the form is associated with several fields. Further, the system can transmit an Application Programming Interface (API) call to retrieve metadata to identify the fields to be included in the form. Based on the existing fields, and those identified from the retrieved metadata, the system can modify the form to have a second format, and display the form having the second format.
Technical solutions are directed to an intersystem configuration adjustment for periodic operation processing. A processor can receive, from an entity system, a value for a parameter of a client account. The system can determine, based on a configuration for an entity associated with the client account, to perform parameter adjustment according to a protocol of the configuration and identify a rule for parameter adjustment. The system can split, using the rule and based on an accumulated parameter value, the value for the parameter into component values. The system can assign, according to ranking of modifiers, a modifier to each of the components values and generate an adjusted parameter value. The system can command the processing system to execute a process for the client account and the time interval based on the adjusted parameter value.
Technical solutions are directed to automating processing using machine learning and graph structure based rules. A processor can identify a graph data structure that connects, using semantic edges, a plurality of components in accordance with a taxonomy. The processor can detect, using the graph data structure, a change to a protocol used to perform an operation comprising one or more electronic transactions between electronic accounts related to the plurality of components. The processor can generate, using the graph data structure, responsive to detection of the change, one or more rules to perform the operation in accordance with the change to the protocol. The processor can construct a prompt with the one or more rules and at least a portion of an electronic document. The processor can execute, using a model trained with a generative machine learning technique, the operation based on the prompt.
Systems and methods are provided for building personal protection equipment (PPE) rules. A live image may be received from a camera, where the live image is of a human body or a portion of the human body. A machine learning model may identify any body parts in the image for which PPE is usable. An augmented reality image may include the live image and an identifier object superimposed on any identified body parts, enabling a selection of a user-selected body part in the augmented reality image. PPE items usable for the user-selected body part may be added to the set of PPE required for a team. Systems and methods of safety compliance are provided that determine, by a machine learning model, a compliance score from the image, the compliance score indicating a degree to which the person is in compliance with PPE rules.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
G06Q 10/0875 - Énumération ou classification des pièces, des fournitures ou des services, p. ex. nomenclatures
G06Q 50/26 - Services gouvernementaux ou services publics
G06T 19/00 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie
G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique
G06V 20/52 - Activités de surveillance ou de suivi, p. ex. pour la reconnaissance d’objets suspects
G06V 40/10 - Corps d’êtres humains ou d’animaux, p. ex. occupants de véhicules automobiles ou piétonsParties du corps, p. ex. mains
Technical solutions are directed to an intersystem configuration adjustment for periodic operation processing. A processor can receive, from an entity system, a value for a parameter of a client account. The system can determine, based on a configuration for an entity associated with the client account, to perform parameter adjustment according to a protocol of the configuration and identify a rule for parameter adjustment. The system can split, using the rule and based on an accumulated parameter value, the value for the parameter into component values. The system can assign, according to ranking of modifiers, a modifier to each of the components values and generate an adjusted parameter value. The system can command the processing system to execute a process for the client account and the time interval based on the adjusted parameter value.
Technical solutions are directed to automating processing using machine learning and graph structure based rules. A processor can identify a graph data structure that connects, using semantic edges, a plurality of components in accordance with a taxonomy. The processor can detect, using the graph data structure, a change to a protocol used to perform an operation comprising one or more electronic transactions between electronic accounts related to the plurality of components. The processor can generate, using the graph data structure, responsive to detection of the change, one or more rules to perform the operation in accordance with the change to the protocol. The processor can construct a prompt with the one or more rules and at least a portion of an electronic document. The processor can execute, using a model trained with a generative machine learning technique, the operation based on the prompt.
System and methods of this technology can provide a framework using machine learning based message generator. The framework can retrieve elapsed times according to computing devices executing an application. Once the elapsed times are retrieved, the framework can generate a total elapsed time that can indicate an average amount of time captured by the at least one computing devices. The framework can make a determination based on the total elapsed time and a threshold elapsed time. The threshold elapsed time can be generated from data associated with previous months, years, days, among other time periods. Upon determining that the total elapsed time is higher than the threshold elapsed time, the framework can generate instructions to display the metrics associated with the total elapsed time, on another computing device.
The technical solutions provide ML-based generation of queries and responses for operational frameworks of entities. A processor can identify queries of a processing frameworks for an entity and construct embeddings for the queries. Each embedding can correspond to a vector of a query of the plurality of queries that form a plurality of clusters in a vector space. The processor can generate, for each cluster, using API calls to ML models, a cluster query and a cluster response for the cluster query and store, in a storage, a mapping of each cluster query to each cluster response. The processor can receive, from a client, a request and select, using the mapping, the cluster response based on a relation between the cluster query and the request. The processor can provide, to the client, the selected cluster response responsive to the request.
System and methods of this technology can provide a framework using machine learning based message generator. The framework can retrieve elapsed times according to computing devices executing an application. Once the elapsed times are retrieved, the framework can generate a total elapsed time that can indicate an average amount of time captured by the at least one computing devices. The framework can make a determination based on the total elapsed time and a threshold elapsed time. The threshold elapsed time can be generated from data associated with previous months, years, days, among other time periods. Upon determining that the total elapsed time is higher than the threshold elapsed time, the framework can generate instructions to display the metrics associated with the total elapsed time, on another computing device.
Anomaly detection in cross-system operation is provided. A system can generate, using machine learning, predicted values related to a network operation for an object identifier at a first time interval. The system can identify, from one or more systems of records, a plurality of actual values output responsive to execution of the network operation at the first time interval. The system can determine a variance in at least one value of the plurality of actual values based on a comparison of the plurality of actual values and the plurality of predicted values. The system can detect, using the one or more models, an anomaly in the variance. The system can execute, responsive to detection of the anomaly, an action to update the one or more models based on the anomaly.
H04L 41/147 - Analyse ou conception de réseau pour prédire le comportement du réseau
G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p. ex. des interruptions ou des opérations d'entrée–sortie
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04L 41/142 - Analyse ou conception de réseau en utilisant des méthodes statistiques ou mathématiques
Anomaly detection in cross-system operation is provided. A system can generate, using machine learning, predicted values related to a network operation for an object identifier at a first time interval. The system can identify, from one or more systems of records, a plurality of actual values output responsive to execution of the network operation at the first time interval. The system can determine a variance in at least one value of the plurality of actual values based on a comparison of the plurality of actual values and the plurality of predicted values. The system can detect, using the one or more models, an anomaly in the variance. The system can execute, responsive to detection of the anomaly, an action to update the one or more models based on the anomaly.
H04L 41/0604 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant du filtrage, p. ex. la réduction de l’information en utilisant la priorité, les types d’éléments, la position ou le temps
H04L 41/0859 - Récupération de la configuration du réseauSuivi de l’historique de configuration du réseau en conservant l'historique des différentes générations de configuration ou en revenant aux versions de configuration précédentes
H04L 47/125 - Prévention de la congestionRécupération de la congestion en équilibrant la charge, p. ex. par ingénierie de trafic
Systems and methods are provided for building personal protection equipment (PPE) rules. A live image may be received from a camera, where the live image is of a human body or a portion of the human body. A machine learning model may identify any body parts in the image for which PPE is usable. An augmented reality image may include the live image and an identifier object superimposed on any identified body parts, enabling a selection of a user-selected body part in the augmented reality image. PPE items usable for the user-selected body part may be added to the set of PPE required for a team. Systems and methods of safety compliance are provided that determine, by a machine learning model, a compliance score from the image, the compliance score indicating a degree to which the person is in compliance with PPE rules.
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/94 - Architectures logicielles ou matérielles spécialement adaptées à la compréhension d’images ou de vidéos
G06V 40/10 - Corps d’êtres humains ou d’animaux, p. ex. occupants de véhicules automobiles ou piétonsParties du corps, p. ex. mains
A method for accessing information. A computer system receives a request for a piece of the information stored in a location between client computer systems and sources of the information. The information has formats for the information in the location. The formats for the information are controlled by the sources of the information. Each of the sources is assigned to control a group of portions of the information in the location. The computer system identifies the piece of the information corresponding to the request. The computer system returns a response to the request for the piece of the information, enabling simplifying access to the information in different formats.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable mobile application software for use in human capital management (HCM), human resources (HR) management and administration, employee benefits and retirement plan administration, and payroll processing, preparation, and administration Payroll processing, preparation and administration; Providing human capital management (HCM) services for others; Human resources (HR) management and administration; Administration of employee benefit plans concerning medical, dental, vision, and prescription drug plans, flexible spending plans, health reimbursement arrangements, and health saving accounts; Business services for others, namely, providing payroll, employee benefits, human resources (HR) Providing temporary use of online non-downloadable computer software for use in human capital management (HCM), human resources (HR) management and administration, employee benefits and retirement plan administration, and payroll processing, preparation, and administration
50.
SECURE COMPUTING INFRASTRUCTURE FOR ELECTRONIC MESSAGES
Secure computing infrastructure for electronic messages is described herein. A system can intercept an electronic message for transmission to a recipient device. The system can determine, prior to transmission of the electronic message for receipt by the recipient device, a category of the recipient device based on a domain name associated with an internet protocol address of the recipient device. The system can generate a plurality of content segments based on overlapping sequences of words in the electronic message. The system can identify, using machine learning models and based on the category of the recipient device, a security parameter to apply to the electronic message. The system can detect, using machine learning models, an incompatibility between a content segment and the security parameter. The system can block, responsive to the detection of the incompatibility, the transmission of the electronic message for receipt by the recipient device.
A system for automated query resolution using a multi-agent processing framework is described. The system includes one or more processors coupled with memory to generate, using one or more machine learning models and based on a query associated with an account, an embedding corresponding to a vector representation of the query. The system can perform, using the embedding, a vector semantic search in a vector space of a plurality of queries to identify documentation associated with the query and a matching question response pair. The system can identify, from a knowledge graph using the documentation and metadata, one or more entities related to the question response pair and one or more relationships between the entities. The system can select, from a plurality of agents, an agent to provide an interaction with the user to address the entities and relationships, and provide, via the processing framework, a response of the query response pair responsive to the interaction.
Systems and methods for generation of a REST API are provided. A graphical user interface for an end user application may be generated, where the graphical user interface includes a displayed property that corresponds to a stored property retrieved from a database. A property selection mode of the graphical user interface may be entered in response to a first user input. The displayed property may be added to a collection of properties for the REST API in response to a selection of the displayed property while in the property selection mode. The REST API may be generated in response to a second user input, wherein API properties of the REST API include all properties added to the collection of properties.
A system for automated query resolution using a multi-agent processing framework is described. The system includes one or more processors coupled with memory to generate, using one or more machine learning models and based on a query associated with an account, an embedding corresponding to a vector representation of the query. The system can perform, using the embedding, a vector semantic search in a vector space of a plurality of queries to identify documentation associated with the query and a matching question response pair. The system can identify, from a knowledge graph using the documentation and metadata, one or more entities related to the question response pair and one or more relationships between the entities. The system can select, from a plurality of agents, an agent to provide an interaction with the user to address the entities and relationships, and provide, via the processing framework, a response of the query response pair responsive to the interaction.
Systems and methods for generation of a REST API are provided. A graphical user interface for an end user application may be generated, where the graphical user interface includes a displayed property that corresponds to a stored property retrieved from a database. A property selection mode of the graphical user interface may be entered in response to a first user input. The displayed property may be added to a collection of properties for the REST API in response to a selection of the displayed property while in the property selection mode. The REST API may be generated in response to a second user input, wherein API properties of the REST API include all properties added to the collection of properties.
A system includes one or more processors to receive, from a first client system, a first message associated with a transfer of a data file, the first message in accordance with a predetermined protocol, execute a sequence of operations that authenticate the first client system to an application programming interface (API) gateway that controls access to a data storage, upload the data file from the first client system to the data storage, send, to a second client system, a notification in accordance with the predetermined protocol to cause the second client system to transmit a second message, receive the second message in accordance with the predetermined protocol, authenticate the second client system to the API gateway based on execution of the sequence of operations, and provide, to the second client system via the predetermined protocol, the data file to cause the second client system to download the data file.
H04L 67/06 - Protocoles spécialement adaptés au transfert de fichiers, p. ex. protocole de transfert de fichier [FTP]
H04L 67/1074 - Réseaux de pairs [P2P] pour la prise en charge des mécanismes de transmission de blocs de données
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p. ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
H04L 67/133 - Protocoles pour les appels de procédure à distance [RPC]
An application database schema and rules for a software application may be created from a Universal Ontology Model (UOM). A UOM graph is created from the UOM, where the UOM graph is a graph data structure comprising nodes and edges. A System-specific Ontology Model (SOM) graph is created based on the UOM graph and country-specific metadata. A Domain-specific Ontology Model (DOM) graph is created based on the SOM and client specific data. The application database schema is created from the DOM graph. The rules are extracted from the DOM graph and stored in a rule registry.
Managing and applying human resources data comprising aggregating employee transaction data for an organization. A number of human resources-related attributes are evaluated across heterogeneous transaction data. The employee transaction data is classified via statistical machine learning into a number of normalized codes according to the human resources-related attributes, a user interface is presented to adjust a number of organizational operating procedures according to the normalized codes.
An application database schema and rules for a software application may be created from a Universal Ontology Model (UOM). A UOM graph is created from the UOM, where the UOM graph is a graph data structure comprising nodes and edges. A System-specific Ontology Model (SOM) graph is created based on the UOM graph and country-specific metadata. A Domain-specific Ontology Model (DOM) graph is created based on the SOM and client specific data. The application database schema is created from the DOM graph. The rules are extracted from the DOM graph and stored in a rule registry.
A payload including data may be received that is to be written to any of the entities included in an application database schema, where the application database schema governs storage of application data in a fluid database for a software application. A context for the payload is identified, where the context identifies an entity that is to be updated with the data in the payload. The context may include an attribute identifying a country and/or a client. Rules stored in a rule registry are searched and a set of rules is retrieved that matches the context for the payload. The rules are segregated according to context levels and are associated with the entities. The rules stored in the rule registry include logic executable to enforce the rules. The retrieved set of rules are enforced, in the payload received, by execution of the logic included in the set of rules retrieved.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable mobile application software in the field of employer services for preparing and processing employee payroll Payroll processing, preparation, administration, and recordkeeping Providing temporary use of online non-downloadable computer software in the field of employer services for preparing and processing employee payroll
63.
Display screen or a portion thereof with a graphical user interface
Large language model architecture for delivering digital content is provided. A system can receive a query indicating a request for document objects, and criteria for selection of the document objects. The system obtains first data objects each having a first structure in a first format identifying portions of the one or more document objects. The first data objects can be searchable according to the one or more criteria via the first structure. The system provides input to a large language model (LLM) including the query, the first data objects, and second data objects. The second data objects can have a second structure in a second format that is compatible with the LLM. The system generates a reply to the query identifying a set of the one or more document objects that satisfies the one or more criteria for selection.
This technology can provide a platform using one or more protocols to migrate and correct erroneous data. The platform can receive a data structure that includes a plurality of placeholders in accordance with payroll of an entity. The platform can obtain, identify, retrieve, or otherwise receive a template that includes references codes to classify each placeholder within the data structure. Upon classifying each placeholder, the platform can execute a protocol to perform a reverse search and fill the placeholders of the original data structure. For example, the platform can predict values for the placeholders and fill the predicted values for the placeholders’ using results of the reverse search associated with the predicted values. The platform can fill the placeholders with actual values to correct the erroneous data structure and transmit the data structure to a migration system.
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
66.
LARGE LANGUAGE MODEL ARCHITECTURE FOR DELIVERING DIGITAL CONTENT
Large language model architecture for delivering digital content is provided. A system can receive a query indicating a request for document objects, and criteria for selection of the document objects. The system obtains first data objects each having a first structure in a first format identifying portions of the one or more document objects. The first data objects can be searchable according to the one or more criteria via the first structure. The system provides input to a large language model (LLM) including the query, the first data objects, and second data objects. The second data objects can have a second structure in a second format that is compatible with the LLM. The system generates a reply to the query identifying a set of the one or more document objects that satisfies the one or more criteria for selection.
Secure computing infrastructure for electronic messages is described herein. A system can intercept an electronic message for transmission to a recipient device. The system can determine, prior to transmission of the electronic message for receipt by the recipient device, a category of the recipient device based on a domain name associated with an internet protocol address of the recipient device. The system can generate a plurality of content segments based on overlapping sequences of words in the electronic message. The system can identify, using machine learning models and based on the category of the recipient device, a security parameter to apply to the electronic message. The system can detect, using machine learning models, an incompatibility between a content segment and the security parameter. The system can block, responsive to the detection of the incompatibility, the transmission of the electronic message for receipt by the recipient device.
A system can receive one or more documents. The system can determine, for a document, using a machine learning model, a classification of a type of the document and a confidence score associated with the classification, where the confidence score indicates a level of performance with which the machine learning model outputs the classification of the type of the document. For the document, the system can select a data extraction engine based on the confidence score, where the data extraction engine extracts data points from the document. The system can prioritize the extracted data points based on the confidence score associated with the document. The system can update a profile data structure in response to aggregating the prioritized extracted data points. The system can input the profile data structure into a payroll processing system to execute an operation in accordance with the updated profile data structure.
The technology described herein can provide a platform using one or more protocols to migrate and correct erroneous data. The platform can receive a data structure that includes a plurality of placeholders in accordance with payroll of an entity. The platform can obtain, identify, retrieve, or otherwise receive a template that includes references codes to classify each placeholder within the data structure. Upon classifying each placeholder, the platform can execute a protocol to perform a reverse search and fill the placeholders of the original data structure. For example, the platform can predict values for the placeholders and fill the predicted values for the placeholders’ using results of the reverse search associated with the predicted values. The platform can fill the placeholders with actual values to correct the erroneous data structure and transmit the data structure to a migration system.
A status and monitoring platform for resource bandwidth is provided. A system can retrieve, responsive to a request for bandwidth of a resource, a data set that can include at least one constraint related to the resource and historic utilization of the resource. The system can construct, based on the data set, a data structure to replace the request. Based on the data structure, the system can generate a prompt indicating the constraint and the historic utilization. The system can identify, based on the prompt, a model trained with generative artificial intelligence to determine resource bandwidth. The system can input the prompt into the model to generate an output that indicates the bandwidth of the resource and validate the output based on a comparison with a threshold. The system can transmit for display, via an interface, responsive to the validation, an indication of resource bandwidth output by the model.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04L 43/045 - Traitement des données de surveillance capturées, p. ex. pour la génération de fichiers journaux pour la visualisation graphique des données de surveillance
71.
FRAMEWORK-AGNOSTIC PLUGGABLE WEB-APPLICATION ARCHITECTURE FOR LOW-CODE DEVELOPMENT
Systems and methods for an integrated development environment (IDE) are provided. The system may include a common core and a model-view-adapter (MVA) plugin. The common core is executable to transfer data objects to and/or from a metadata database over a network, where the common core is executable within an IDE configured to customize a customizable application, and where application logic of the customizable application is configured to customize aspects of the customizable application based on the data objects. The MVA plugin is executable to generate a visualization of and/or edit a data object of a data object type. The MVA plugin includes a MDO controller, a MDO view, and a MDO adapter. The MDO controller is executable to control the data object in response to IDE events received from the MDO adapter. The MDO view is executable generate the visualization of the data object via the MDO adapter.
An anomaly detection and transaction integrity platform is provided. A system receives data for profiles linked with accounts of an entity. The data indicates first historical data of first interactions of accounts with a first computing system, and second historical data indicative of second interactions of accounts with a second computing system. The system generates, using one or more models trained with machine learning, a metric indicative of a pattern of transactions. The system determines, based on a comparison of a value of the metric with a threshold, to invoke an automated process via the payroll processing system to modify at least one of the metric or the threshold. The system selects, using the one or more models, an action to execute via the automated process that modifies the metric or the threshold. The system commands, via the automated process, the payroll processing system to execute the action.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
73.
SYSTEM AND METHOD FOR QUERY AUTHORIZATION AND RESPONSE GENERATION USING MACHINE LEARNING
Systems, methods, and computer-readable storage media for responding to a query using a neural network and natural language processing. If necessary, the system can request disambiguation, then parse the query using a trained machine-learning classifier, resulting in at least one of an identified subject or an identified domain of the text query. The system can determine if the user is authorized to retrieve answers to the query and, if so, retrieve factual data associated with the query. The system can then retrieve a response template, and fill in the template with the retrieved facts. The system can then determine, by executing a machine comprehension model on the filled response template, a probable readability token, portion of text, of at least a portion of the filled response template and, upon identifying that the probable readability is above a threshold, reply to the text query with the at least a portion of the filled response template.
The present disclosure relates generally to tools to determine a user's intent and, more particularly, to a system, method and computer program product to generate a report template based on user's intent. The method includes: extracting, by a computer system, text and user selected features from one or more reports built in a reporting application; classifying, by the computer system, keywords in the text and the select features; identifying, by the computer system, common keywords and associated selected features within the one or more reports; determining, by the computer system, an intent of the user based on the common keywords and associated selected features; and generating, by the computer system, a report template with prepopulated features of the selected features based on the intent of the user.
G06V 30/262 - Techniques de post-traitement, p. ex. correction des résultats de la reconnaissance utilisant l’analyse contextuelle, p. ex. le contexte lexical, syntaxique ou sémantique
G06V 30/19 - Reconnaissance utilisant des moyens électroniques
G06V 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux
G06V 30/414 - Extraction de la structure géométrique, p. ex. arborescenceDécoupage en blocs, p. ex. boîtes englobantes pour les éléments graphiques ou textuels
75.
Display screen or a portion thereof with a graphical user interface
Disclosed are various embodiments for automated translations for autonomous chat agents. A build service can send a translation request to a machine translation service, the translation request comprising training data in a first language and the translation request specifying a second language. The build service can then receive translated training data from the machine translation service, the translated training data having been translated from the training data into the second language. Next, the build service can create a translated workflow that comprises a translated machine learning model and a translated intent. Subsequently, the build service can add the translated training data to the translated workflow and train the translated machine learning model using the translated training data.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
G06F 40/35 - Représentation du discours ou du dialogue
A status and monitoring platform for resource bandwidth is provided. A system can retrieve, responsive to a request for bandwidth of a resource, a data set that can include at least one constraint related to the resource and historic utilization of the resource. The system can construct, based on the data set, a data structure to replace the request. Based on the data structure, the system can generate a prompt indicating the constraint and the historic utilization. The system can identify, based on the prompt, a model trained with generative artificial intelligence to determine resource bandwidth. The system can input the prompt into the model to generate an output that indicates the bandwidth of the resource and validate the output based on a comparison with a threshold. The system can transmit for display, via an interface, responsive to the validation, an indication of resource bandwidth output by the model.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04L 41/22 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets comprenant des interfaces utilisateur graphiques spécialement adaptées [GUI]
H04L 43/0876 - Utilisation du réseau, p. ex. volume de charge ou niveau de congestion
78.
Display screen or a portion thereof with a graphical user interface
A system includes one or more processors to identify an application configured to access a plurality of products using a plurality of application programming interfaces (APIs) that are agnostic to the plurality of products. A first product of the plurality of products is accessed using one or more APIs of the plurality of APIs. The one or more processors access, responsive to a request to execute at least one product of the plurality of products, data identified by the plurality of APIs, select at least a portion of the data identified by the plurality of APIs, transmit the at least the portion of the data to the at least one product to cause the at least one product to perform an operation using the at least the portion of the data, and provide an indication associated with the performance of the operation by the at least one product.
Systems and methods are described for dynamic and predictive pricing for ecommerce systems and brick-and-mortar retail businesses for a selected geographic location or territory. In one example, a system comprises a computing device that is configured to receive a request to display a network page of an item on a client device. The computing device is further configured to determine a geographic location of the client device and determine a price for the item using a machine learning model based at least in part on the geographic location. The network page is displayed on the client device to include the price of the item.
A system can include one or more processors, coupled with memory, to automatically execute a data replication tool on at least one data instance to generate at least one replicated data instance, push a status of a data instance of the at least one data instance to a data stream associated with the data replication tool, detect a difference between a first structure of a replicated data instance of the at least one replicated data instance and a second structure of a target database, identify a model configured to update the first structure of the replicated data instance to correspond to the second structure of the target database, provide the replicated data instance to the target database, and store, in a data storage, configuration information regarding a status, owner, or action associated with the target database.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
This application is directed to constructing a knowledge graph using generative artificial intelligence. A system can include one or more processors coupled with memory to identify a plurality of items of unstructured data. The system can provide, for one or more generative artificial intelligence models, a first prompt to cause the models to output a plurality of first level categories of a hierarchical data structure for the items. The system can receive the first level categories, each corresponding to a subset of the items grouped by semantic similarity, and evaluate each category according to taxonomy criteria. The system can provide a second prompt to generate second level categories for each first level category, receive the second level categories, and construct a knowledge graph data structure linking the categories and their respective subsets to relate each item of unstructured data with corresponding categories according to the hierarchical data structure.
A method, apparatus, system, and computer program product for processing an on-demand payroll request. In one illustrative example, an on-demand payroll microservice receives a request for an unscheduled payroll for an employee. The on-demand payroll microservice retrieves payroll information for the employee from a first set of microservices. The on-demand payroll microservice submits the payroll information to a second set of microservices for payroll calculations. In response to the second set of microservices completing the payroll calculations, the on-demand payroll microservice retrieves the payroll calculations through the first set of microservices. The on-demand payroll microservice displays the payroll calculations. In response to receiving approval of the unscheduled payroll, the on-demand payroll microservice submits the payroll calculations to the second set of microservices for payroll processing. In response to the second set of microservices completing the payroll processing, the on-demand payroll microservice displays a confirmation of the payroll processing.
G06Q 10/067 - Modélisation d’entreprise ou d’organisation
G06Q 10/1057 - Avantages sociaux ou bien-être des employés, p. ex. assurances, vacances ou régimes de retraite
G06Q 10/1091 - Enregistrement du temps à des fins administratives ou de gestion
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 20/42 - Confirmation, p. ex. contrôle ou autorisation de paiement par le débiteur légal
A method for automated web resource deployment is provided. The method comprises creating web resource publication requests, wherein each web resource publication request comprises a number of configuration changes necessary to publish a web resource, on a network, at a particular uniform resource location. A standard format, validation workflow, and an approval workflow are provided for automation of the web resource publication requests. Once validated and approved, web resource publication requests are automatically converted to API calls which are executed on backend servers to implement the configuration changes required in the environment without further human intervention.
H04L 41/22 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets comprenant des interfaces utilisateur graphiques spécialement adaptées [GUI]
A system includes one or more processors to transmit, to a client device, data to cause the client device to display a first interface including a plurality of software products, receive, via the first interface, a selection of a software product of the plurality of software products, wherein the software product includes software code stored in a plurality of data repositories, transmit, to the client device, data to cause the client device to display a second interface including the plurality of data repositories, scan at least one data repository of the plurality of data repositories selected via the second interface to detect one or more security vulnerabilities in a development branch corresponding to the at least one data repository, and generate, for display via the second interface, a security notification related to the one or more security vulnerabilities detected in the development branch.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 8/10 - Analyse des exigencesTechniques de spécification
The present disclosure relates generally to computer systems and, more particularly, to a cache refresh system and related processes and methods of use. The method of refreshing data in cache memory includes: setting, by a computer system, a refresh indicator to “true”; refreshing data in the cache memory, by the computer system, upon a determination that the refresh indicator is set to “true”; and setting, by the computer system, the refresh indicator to “false” after the refreshing of the cache memory.
A system includes one or more processors to identify a first plurality of attributes associated with a first opening and an entity structure, identify a second plurality of attributes associated with a plurality of positions and one or more entity structures, identify a target item missing from a metadata representation of a candidate for a second opening within the entity structure, execute an automated interview process for the candidate, generate an updated metadata representation of the candidate based on a value for the target item, and provide data of the candidate for display via an interface of a device of the entity structure.
Systems and methods are provided in which topic segments are generated from a product feedback data with a topic segmentation model, where the topic segments include segments of text from the product feedback data in which topics are discussed, and where the topic segments correspond to technical issues with a product. Sentiments expressed in the topic segments about the technical issues may be generated, the sentiments providing an indication of negative or positive emotion expressed in the topic segments about the technical issues. A diagram of the topics may be generated from the sentiments. A technical issue having a high degree of negative emotion expressed about the technical issue may be identified from the diagram based on an image classification model. A resource allocation may be generated to resolve the technical issue identified by the image classification model.
A system can include one or more processors, coupled with memory, to select a plurality of intents associated with an input and having confidence scores between a first threshold level and a second threshold level. The one or more processors to determine that a first intent of the plurality of intents is missing from an intent mapping table. The one or more processors to update the intent mapping table to include a label generated for the first intent. The one or more processors to generate a plurality of elements for display via a chatbot interface including the label generated for the first intent and labels for a subset of the plurality of intents. The one or more processors to transmit data to cause a client device to update the chatbot interface to include the plurality of elements in response to the input.
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
90.
SYSTEM AND METHOD FOR RECOMMENDING COMPUTATIONAL COMMANDS BASED ON A WEIGHTED, RANKED HIERARCHICAL GRAPH
Systems, methods, and computer-readable storage media for recommending computational commands based on a weighted, ranked hierarchical graph. The system converts a map of intended user actions to canonical actions (commands) into a graph representation. Then, via a chatbot algorithm, the system receives an initial intent as a request by a user of the chatbot algorithm. Based on the popularity of alternative canonical actions, the system makes recommendations of alternative actions which are similar to the initial intent provided by the user.
Disclosed are various embodiments for delegating tasks in an enterprise service. A user can associate an action or task within the enterprise service with a delegate. The user can also specify temporal restrictions with the delegation of the task. The temporal restrictions specified time limitations on the authority of the delegate.
AI gateways are provided. An AI service request for an AI model may be received by an AI gateway from a client. The AI service request may be routed to an AI model deployment, where routing the AI service request includes selecting the AI model deployment from AI model deployments based on a quality of service.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04L 47/215 - Commande de fluxCommande de la congestion en utilisant le schéma du seau à jetons
95.
AI Gateway - Normalization of LLM KPIs and Metadata for Observability
AI gateways are provided. An AI service request for an AI model may be received by an AI gateway from a client. The AI service request may be routed to an AI model deployment, where routing the AI service request includes selecting the AI model deployment from AI model deployments based on a quality of service. Performance data may be captured from the processing of the AI service request by the AI model deployment.
Synthetic testing systems are provided for testing AI model deployments. A test execution module may be executable by the processor to perform a synthetic test on at least one of a set of AI model deployments. The synthetic test may include a transmission of a request for an AI model to at least one of the AI model deployments, where the request includes an input prompt comprising predefined test data.
AI gateways are provided. An AI service request for an AI model may be received by an AI gateway from a client. The AI service request may be routed to an AI model deployment, where routing the AI service request includes selecting the AI model deployment from AI model deployments based on a quality of service.
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande
98.
CONVERSATIONAL AGNOSTIC MATCHMAKING MODEL ARCHITECTURE
A system for matchmaking using a conversational agnostic matchmaking model is described. The system can receive a first query indicating a request for document objects and including criteria for selection of the document objects. The system can identify named entities from portions of the first query. The system can generate a second query to obtain the document objects, in response to the named entities being indicative of a context for the first query. The system can obtain the document objects according to the second query. The system can generate a reply to the first query including a description object and the documents, the description object based on the first query. The system can cause a user interface to present the reply to the first query and the description object.
Technical solutions are directed to a computing architecture for determining user characteristics from interactions with user interface and customizing application-generated content according to the user characteristics. A system can detect interactions with elements of content in a user interface and identify, based on interactions input into a model, a characteristic associated with the account. The system can receive a first content for a human capital management service to be displayed using a graphical user interface, the first content generated by an application. The system can generate, based at least on the first content, an arrangement of elements according to the characteristic and display, on the graphical user interface, the arrangement of elements.
A method, apparatus, system, and computer program product are provided for managing the usage of verified credentials. An issuer of credentials receives a request from a person for a credential. The issuer identifies the credential from information that is controlled by the issuer. The issuer identifies a decentralized identifier (DID) record for an audit engine from a blockchain network. The DID record for the audit engine includes a public key of that is associated with the audit engine. The issuer identifies a DID record for the person from the blockchain network. The DID record for the person includes a public key that is associated with the person. The issuer generates an encrypted credential by encrypting the credential and the DID record for the person based on the public key associated with the audit engine. The issuer sends the encrypted credential to the person.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
