24 results about "Client organization" patented technology

A computing services environment may include a database system storing database records for client organizations accessing computing services including a conversational chat interface, an application server providing access to the conversational chat interface, a metadata repository storing metadata entries describing and defining interaction data for interacting with agents, and an orchestration service configured to execute an orchestration process based on a natural language request message received via the conversational chat interface. An input prompt including the natural language request message and agent descriptions selected from the plurality of metadata entries may be determined and transmitted to a generative language model. A prompt completion including a selection of the designated agent based on the plurality of agent description may be received from the generative language model. Novel text responsive to the natural language request message may be generated by transmitting a request to the designated agent.

A computing services environment may include a database system storing a plurality of database records for a plurality of client organizations accessing computing services including a conversational chat assistant. The computing services environment may also include an application server may receive user input for the conversational chat assistant, a generative language model interface, an orchestration and planning service configured to identify one or more actions based on the user input, to execute the one or more actions to determine a natural language response message, and to determine a recommended action for selection via a conversational chat interface. The computing services environment may also include a communication interface configured to transmit the natural language response message and a user interface generation instruction executable by the client machine to provide a selection affordance for selecting the recommended action.

A computing services environment may include a database system may store database records for client organizations accessing computing services including a conversational chat assistant. The computing services environment may also include an application server receiving natural language user input for the conversational chat assistant and a generative language model interface providing access to one or more generative language models. The computing services environment may also include an orchestration and planning service configured to analyze the natural language user input via a generative language model of the one or more generative language models to identify a plurality of actions to execute via the computing services environment to fulfill an intent expressed in the natural language user input. The computing services environment may be configured to execute the plurality of actions to determine a natural language response message.

A computing services environment may include a database system storing database records for client organizations accessing computing services including a conversational chat interface, an application server providing access to the conversational chat interface, a metadata repository storing metadata entries characterizing a actions capable of being performed via the computing services environment, and an orchestration service configured to execute an orchestration process based on a natural language request message received via the conversational chat interface. An input prompt including the natural language request message and descriptions of actions selected from the metadata entries may be determined and transmitted to a generative language model. A prompt completion including a plan that includes a subset of the actions and a natural language description of the plan may be received from the generative language model and sent to a client machine via the conversational chat interface.

A computing services environment may include a database system storing database records for client organizations accessing computing services including a conversational chat interface, an application server providing access to the conversational chat interface, and an orchestration service configured to execute an orchestration process based on a natural language request message received via the conversational chat interface. An information enrichment and disambiguation process may be executed to determine candidate values corresponding to a text portion of the natural language request message. Novel clarification text requesting clarification of the candidate information may be determined and transmitted via the conversational chat interface. Updated information may be determined based on the candidate information and clarification input received via the conversational chat interface. Novel response text responsive to the natural language request message may be determined based on the updated information.

A computing services environment may include a database system storing a plurality of database records for a plurality of client organizations accessing computing services including a conversational chat assistant, an application server receiving user input for the conversational chat assistant, a generative language model interface providing access to one or more generative language models, an orchestration and planning service configured to identify a plurality of actions based on the user input and to execute the plurality of actions to determine a natural language response message, and / or a metadata framework. The metadata framework may specify information related to the conversational chat assistant. The metadata framework may include a definition associated with an action of the plurality of actions. The definition may include one or more inputs, one or more outputs, and one or more operations performed via the computing services environment.

A computing services environment may include a database system storing database records for client organizations accessing computing services including a conversational chat assistant. The computing services environment may also include an application server receiving natural language user input for the conversational chat assistant and a generative language model interface providing access to one or more generative language models. The computing services environment may also include an orchestration and planning service configured to analyze the natural language user input via a generative language model of the one or more generative language models to identify a plurality of actions to execute via the computing services environment to fulfill an intent expressed in the natural language user input. The computing services environment may be configured to execute the plurality of actions to determine a natural language response message.

A computing services environment may include a database system storing a plurality of database records for client organizations accessing computing services including a conversational chat assistant accessible via various communication channels. The computing services environment may also include a communication interface configured to receive an input message from a client machine via a communication channel, a generative language model interface providing access to one or more generative language models, and an orchestration and planning service. The orchestration and planning service may be configured to analyze the input message to determine a novel text passage via a generative language model, to determine novel text formatting information based on designated text formatting configuration information specifying one or more parameters for formatting text generated for transmission via the communication channel, and to transmit the novel text passage and the novel text formatting information to the client machine via the communication interface.

Disclosed are some techniques for implementing a data discovery agent in a network associated with a customer organization of a data privacy management system. Some implementations relate to one or more connections with one or more data sources storing private data of the customer organization. The one or more data sources can be scanned to obtain scanned data from the private data. The scanned data can be processed, including anonymizing the scanned data, to obtain preprocessed data for use by one or more classification operations. The preprocessed data can be shared with the data privacy management system. One or more classification promotion operations can be performed on classified data elements.

A computing services environment may include a database system storing database records for client organizations accessing computing services including a conversational chat interface, an application server providing access to the conversational chat interface, and an orchestration service configured to execute an orchestration process based on a natural language request message received via the conversational chat interface. An information enrichment and disambiguation process may be executed to determine candidate values corresponding to a text portion of the natural language request message. Novel clarification text requesting clarification of the candidate information may be determined and transmitted via the conversational chat interface. Updated information may be determined based on the candidate information and clarification input received via the conversational chat interface. Novel response text responsive to the natural language request message may be determined based on the updated information.

Methods, systems, devices, and computer-readable media for generating authentication policy recommendations and insights using generative AI are described. An authentication policy recommendation system associated with an identity management system may receive a request from a client organization for an authentication policy configuration recommendation for an application associated with the client organization. One or more recommended authentication policy rules may be generated for the application using a machine learning model (such as a large-learning model). The model may output the authentication policy rules in a machine-readable format. Based on an analysis of applying information about the client organization to the model-generated recommended authentication policy rule to generate a context-specific recommended authentication policy rule, an impact of implementing the context-specific recommended authentication policy rule may be determined and output. The impact of implementing the context-specific recommended authentication policy rule may be determined in advance of implementing the recommended authentication policy rule.

The present application relates to a computer-implemented identity and access management system comprising at least two domains respectively assigned to a user organization, where a first domain is an OEM domain associated with a user of the OEM organization and a second domain is an end-customer domain associated with a user of the end-customer organization, where the first domain is an OEM domain associated with a user of the OEM organization and the second domain is an end-customer domain associated with a user of the end-customer organization. Each domain comprises a function storage module and a data storage module for data corresponding to the function, and wherein the function storage module and the data storage module of the OEM domain are configured such that they only authorize user access by the OEM organization.

Presented herein are a system and secure device onboarding techniques. A Connectivity Management Platform (CMP) receives a request for an access token that includes a user identifier, a customer organization identifier, and an authorization code from a Device Management Platform (DMP), verifies the authorization code, queries an enterprise server using the user identifier and the customer organization identifier to confirm the user belongs to the customer organization, generates the access token, stores the access token in an authentication datastore, and transmits the access token to DMP. The CMP receives a provisioning request including an eSIM identifier of a device and an access token from the DMP, verifies the access token, obtains a customer organization identifier based thereon, queries an enterprise server using the eSIM identifier and the customer organization identifier to confirm the device belongs to the customer organization, and facilitates secure provisioning of the device with an eSIM profile.

A cross-account data management (CAM) service of a provider network may assign, to a primary account of an organization of a client, permission to manage resource management plans for other accounts of the organization. The CAM service may specify, using the primary account (e.g., by an administrator using the primary account), a resource management plan (e.g., data backup plan) The CAM service may indicate, using the primary account, multiple accounts of the organization that the resource management plan is to be implemented for. The CAM service may cause, based on the permission assigned to the primary account, the resource management plan to be implemented for the different accounts of the organization (e.g., by causing execution of jobs to implement a backup plan).

Methods, systems, and computer-readable media for managing a pool of virtual desktop instances are disclosed. A plurality of virtual desktop instances are provided in a pool for a client organization. A number of virtual desktop instances does not exceed a number of virtual desktop slots for the client organization. Access to a particular virtual desktop instance is provided to a first client device associated with a first user based on (at least in part) a determination that a current number of connected virtual desktop instances is less than the number of virtual desktop slots. Access to the plurality of virtual desktop instances is denied to a second client device associated with a second user based on (at least in part) a determination that the current number of connected virtual desktop instances is consistent with the number of virtual desktop slots.

The invention relates to the technical field of customer relationship management, and discloses a customer contact relationship evaluation method and system based on multi-feature quantization, and the method comprises the following steps: recognizing a plurality of key persons in a customer organization; and carrying out quantitative evaluation on seven types of features of each key person, wherein the seven types of features comprise relationship closeness, scheme recognition degree, price acceptability, one-ticket overbiter, one-ticket approver, report relationship and influence relationship. According to the customer contact relationship evaluation method and system based on multi-feature quantification, a'seven-feature 'quantification model (relationship closeness, scheme recognition degree, price acceptability, one-ticket overtaker, one-ticket approver, report relationship and influence relationship) is created, so that an originally fuzzy and subjective customer relationship judgment standard is converted into a unified and objective numerical index; and subjective judgment which varies from person to person is eliminated, so that the customer relationship state becomes measurable, comparable and traceable, and a data foundation is laid for fine management.

Presented herein are a system and secure device onboarding techniques. A Connectivity Management Platform (CMP) receives a request for an access token that includes a user identifier, a customer organization identifier, and an authorization code from a Device Management Platform (DMP), verifies the authorization code, queries an enterprise server using the user identifier and the customer organization identifier to confirm the user belongs to the customer organization, generates the access token, stores the access token in an authentication datastore, and transmits the access token to DMP. The CMP receives a provisioning request including an eSIM identifier of a device and an access token from the DMP, verifies the access token, obtains a customer organization identifier based thereon, queries an enterprise server using the eSIM identifier and the customer organization identifier to confirm the device belongs to the customer organization, and facilitates secure provisioning of the device with an eSIM profile.

Computer-implemented methods and systems for sharing data between customer institutions are disclosed. The invention relates to a method and system for sharing data between customer institutions participating in a digital health platform. The method comprises: providing at least one data compartment adapted to store data of an application of a source mechanism; selecting, by a user of the source institution, a data compartment to generate a data compartment sharing request for sharing the selected data compartment with the specified target institution; notifying a user of the target institution of a data compartment sharing request of a user of the source institution; approving or denying, by a user of the target institution, a data compartment sharing request of a user of the source institution; notifying a user of the source institution of approval or denial of the data compartment sharing request by a user of the target institution; and providing access to the data stored in the selected shared data compartment of the source institution to the target institution if the data compartment sharing request is approved by the user of the target institution.

A machine learning model is trained using information pertaining to accesses of data items at a software-as-a-service (SaaS) management platform. A first training input is generated. The first training input includes access data identifying multiple data items accessed at the SaaS management platform using a subset of user accounts of multiple user accounts associated with a client organization. A first target output is generated. The first target output identifies for each user account, information identifying a respective job title associated with the client organization. The training data is provided to train the machine learning model on (i) a set of training inputs including the first training input, and (ii) a set of target outputs including the first target output.

A computer-implemented identity and access management system that includes at least two domains that are each assigned to a user organization, wherein a first domain is an original equipment manufacturer (OEM) domain assigned to users of an OEM organization, and a second domain is an end customer domain assigned to users of an end customer organization, where each domain includes a function memory module and a memory module for data corresponding to the functions, and where the function memory module and the data memory module of the OEM domain are configured such that they grant access only to a user of the OEM organization.

An indication of an incoming voice call from a first telephone number associated with an end user device and to a second telephone number associated with a client organization of the software as a service (SaaS) platform is received at a SaaS platform. Responsive to receiving the indication of the incoming voice call, end user data associated with the first telephone number is identified. A first communication service, among a plurality of communication services, is identified based on an evaluation of the end user data in view of one or more first conditions defined by the client organization. The incoming voice call is routed to the first communication service.

Architectures and techniques are described that can personalize, customize, or otherwise tailor a presentation of product version update information in accordance with certain embodiments of this disclosure. Such can be accomplished by comparing software product version data (e.g., release notes, data from a code repository, data from a documentation repository, . . . ) to customer data (e.g., customer equipment, topology, configuration, settings, . . . ). The tailored output can be tailored to a specific customer, a specific role within the customer organization (e.g., security officer, database administrator, . . . ), or a specific user within the customer organization. The tailored output can be targeted to appeal to a specific audience, increasing the likelihood of prompt acceptance of the new version of the software product.

A cross-account data management (CAM) service of a provider network may assign, to a primary account of an organization of a client, permission to manage resource management plans for other accounts of the organization. The CAM service may specify, using the primary account (e.g., by an administrator using the primary account), a resource management plan (e.g., data backup plan) The CAM service may indicate, using the primary account, multiple accounts of the organization that the resource management plan is to be implemented for. The CAM service may cause, based on the permission assigned to the primary account, the resource management plan to be implemented for the different accounts of the organization (e.g., by causing execution of jobs to implement a backup plan).