Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for recreating a conversation history to be processed by an artificial intelligent (AI) agent. A prompt is divided into a plurality of segments. For at least one segment, one or more corresponding compressed segments are generated and stored. A user query is received. For at least a first segment of the plurality of segments, a level of relevance to the query is estimated. A compressed segment is selected from a set of segments including the compressed segments, based, at least in part, on the level of relevance to the query. A conversation history is recreated using segments including the selected compressed segment. The query and recreated conversation history are provided to the AI agent.

Abstract: In some embodiments, a first agent receives a request for a transaction where the request is from a second agent. The method authenticates the second agent using an authentication policy to determine an authentication result. The authentication policy is based on an identity of the second agent. Chained transaction metadata is determined based on multiple transactions including the second agent and a third agent. The method validates the transaction using the chained transaction metadata based on a transaction policy to determine a transaction validation result. It is determined whether to validate the transaction based on the authentication result and the transaction validation result.

Abstract: Techniques are disclosed relating to implementing database table schema changes. A computer system stores a source table associated with a current schema that is used to process transactions against a database. The computer system creates a target table associated with a temporary schema, where the target table includes one or more database table schema changes relative to the source table. The computer system provisions synchronization triggers to capture record changes made to the source table and replicate them on the target table. The computer system then performs a copy operation to copy data stored in the source table to the target table while transactions operate on the source table. After completing the copy operation, the computer system performs a schema swap operation to associate the current schema with the target table and not the source table so that the target table is used to process transactions against the database.

Abstract: Disclosed herein are system, method, and device embodiments for providing a mobile interface powered by artificial intelligence. A user remains on a single user-interface page, conducting interactions with a customer relationship management tool using natural language. The technique leverages a large language model as an intermediary middle-layer, allowing a user to engage core functions. The technique builds an appropriate prompt including the natural language and uses the large language model to build an execution plan that references tools and tasks performable in the customer relationship management tool. By chaining prompts, the technique incorporates prior interactions into subsequent prompts. Mobile-specific information such as location, images, and scanned barcodes may be included in a prompts. Running the large language model on the client device allows the user to perform CRM functions while operating in an offline mode, a mode that secures user data and enhances privacy.

Abstract: A computing platform is configurable to cause initiating a communication session with a user, the user having a user account associated with a workflow data object implemented in an on-demand application hosted by the computing platform, the workflow data object being configured to represent a plurality of operations associated with the user and an organization, and further associated with a vaccination status of the user. The computing platform is configurable to cause identifying a verified status indicator used by at least one of the plurality of operations represented in the workflow data object, the verified status indicator comprising a verified credential associated with at least one of the plurality of operations. The computing platform is configurable to cause identifying a transfer operation associated with the verified status indicator and identifying a target entity based on the user account, and implementing the identified transfer operation based on the identified target entity.

Abstract: Techniques are disclosed pertaining to modifying storage properties of application pods in a computing environment. A computer system may receive an update to a set of storage properties associated with a deployment of application pods coupled to storage volumes that satisfy the storage properties. The computer system performs a volume conversion process to replace the application pods with ones coupled to storage volumes that satisfy an updated set of storage properties corresponding to the update. The volume conversion process involves transitioning a particular application pod into a suspended state in which the pod is unavailable for data access and replicating data associated with the particular application pod to at least one other application pod. After replicating the data, the computer system deletes the particular pod to trigger a deployment system to provision a replacement application pod coupled to a storage volume satisfying the updated set of storage properties.

Abstract: Database trigger firing techniques for reducing unnecessary trigger firings are disclosed. In one embodiment a computer system stores trigger information relating to initiating execution of at least one trigger instruction for a database in connection with a database operation statement. The trigger information includes a first set of one or more database field identifiers for a first set of one or more fields in the database and a second set of one or more database field identifiers for a second set of one or more fields in the database. The computer system receives a database operation statement and makes determinations that at least one field within the first set of fields and at least one field within the second set of fields is specified by the database operation statement. Based at least in part on the determinations, the computer system initiates execution of the at least one trigger instruction.

Abstract: A method may include receiving, at a database that may include extension-based functionality, a database query request to perform a machine learning inference operation on data stored in the database, the machine learning inference operation to be performed at the database in accordance with the extension-based functionality. The method may include instantiating, in accordance with the extension-based functionality, a user-defined function (UDF) for performing machine learning inference operations. The method may include calling, with the UDF, the machine learning inference operation to process, at the database, the data retrieved from a table of the database. The method may include transmitting a response to the database query request, the response that may indicate an output of the machine learning inference operation, the output that may include a processed version of the data.

Abstract: The disclosed techniques automatically ingest new documents and store data extracted from the documents in a database for conversion into a different format. The disclosed techniques identify, via a backend API, newly released documents that include data for users and, based on the identifying, automatically ingest, via an ingestion call executed made by the backend API, the newly released documents. The disclosed techniques extract, using a computer vision model trained on different types of documents, a data from the newly released documents, where the extracting includes identifying locations within the documents from which to extract data. The disclosed techniques store the extracted data in the database storing data extracted from previously ingested documents for users in a text-based object format and convert, using a machine learning model trained on a plurality of metatags, data corresponding to a given user from the text-based object format to a queryable file format.

Abstract: A method is provided for reusing custom concepts in visual analytics workflows. The method includes displaying a data visualization for a data source. The method also includes receiving a natural language input directed to the visualization. The method also includes parsing the natural language input to data fields and/or data values. The method also includes executing queries to data sources for retrieving results, based on the data fields and/or the data values. The method also includes generating and storing a named concept from the results, including either (i) saving underlying data as the named concept or (ii) querying the results and saving resulting data as the named concept. Saving the underlying data corresponds to saving data in an attribute. Querying the results is performed when a referenced attribute is not part of the results so a new query is issued that adds data from the referenced attributes.

Abstract: Techniques for modifying a period of time that data, associated with a characteristic, transmitted via a communication platform is retained are described. A data retention rule can include a first period of time for retaining data transmitted via the communication platform, in association with an organization. The first user can additionally establish a specific data retention rule associated with data associated with a particular characteristic. The specific data retention rule can include an instruction to store communications including the particular characteristic for a second time period that is different from the first time period associated with the data retention rule. The communication platform can receive data from a second user computing device associated with the second user of the organization. Based on a determination that the data is associated with the characteristic, the communication platform can store the data according to the data retention rule specified for such data.

Abstract: An application server may receive, from a user and at an interface for accessing a large language model, a request for a response from the large language model. In some cases, the request may include a prompt for the large language model and data access role information associated with the user. The application server may retrieve, from a data source including a set of data objects, one or more data objects for inputting to the large language model based on comparing the data access role information associated with the user with data access policy information associated with the one or more data objects. The application server may then input, via a model interface, the one or more data objects to the large language model, and may receive, via the model interface, an output of the large language model based on the one or more data objects.

Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for processing consent information. A data consolidation system obtains, from each of two or more computing systems, a corresponding set of data objects such that two or more sets of objects are obtained. Each data object is associated with a corresponding individual and includes consent information indicating whether the individual consents to an action in relation to corresponding contact information of the individual. Consent information is extracted, for at least one individual, from the sets of data objects such that two or more sets of consent information are collected, the sets of consent information including a first set of consent information corresponding to a first computing system and a second set of consent information corresponding to a second computing system.

Abstract: Disclosed herein are system, method, and computer program product embodiments for implementing variable a declarative authentication engine. The system generates a schema that includes a field and has a format defined by an authentication protocol associated with a service. The system then validates a connection request based on comparing the field of the generated schema to a field of the connection request for the service, wherein the connection request is formatted according to the schema and received from a client device. The system then provides the client device access to the service according to the connection request based on a result of the validating.

Abstract: Disclosed herein are system, method, and computer program product embodiments for implementing grounding of prompt templates using record snapshot. An embodiment operates by parsing a data record to generate a hierarchical tree graph of context data corresponding to a prompt template selected based on a type of a prompt request, and the data record is identified based on a data-record reference in the prompt request. The embodiment then generates a prompt from the prompt template by grounding the prompt template with a data object comprising the hierarchical tree graph of context data. The embodiment then queries a large language model with the prompt to generate an output specific to the data record.

Abstract: Techniques are disclosed relating to a database recovery routine to start up a database system in response to a database failure. The database system accesses checkpoint information identifying a set of active database transactions that were active at a flush point that occurred before the database failure. As a part of the database recovery routine, the database system replays database transactions that occurred between a recovery point and the flush point. The database transactions include the set of active database transactions but exclude any committed or aborted database transactions that occurred between the recovery point and the flush point such that less than a total number of database transactions occurring between the recovery point and the flush point are replayed. The database system further replays, without excluding committed or aborted database transactions, database transactions occurring between the flush point and a recovery end point at which the database failure occurred.

Abstract: Embodiments described herein provide systems and methods for training neural network based language models using human feedback. An existing (or generated) summary of a document is provided, and that summary may be used to generate a number of other summaries. A human annotator may reject the summary if there is any factuality issue with the summary. Summaries which are agreed to have no factuality problems are used as baseline summaries. Small atomic edits are made to the baseline summaries (e.g., replacing a single word or phrase) to create a group of summaries. Human annotators label each of these summaries as factual or not. The annotated summaries are used to train a summarization model and/or a factual detector model.

Abstract: A method receives audio data from a call. Services are performed to process the audio data to automatically generate a response, wherein the services include converting the audio data to input text, inputting the input text into a model to automatically generate a text response, and converting the text response to an audio response. Supplemental words are selected based on the input text. The method determines a type of service based on services performed to generate the audio response and determines a position in the response to insert the supplemental words based on the type of service. The supplemental words are provided for insertion in the call at the position to supplement the audio response.

Abstract: A method of data processing is described. The method includes converting a plain-text query into a vector-based object by using a text embedding function to process one or more tokens in the plain-text query. The method further includes retrieving a set of passages from a first datastore of the data processing system based on using one or more search indexes stored in a second datastore of the data processing system to compare the vector-based object and the one or more tokens in the plain-text query to vector-based objects and token-based objects associated with the set of passages. The method further includes generating a prompt that includes tokens from the plain-text query, tokens from one or more of the set of passages retrieved from the first datastore, and instructions for creating a response to the plain-text query. The method further includes transmitting the prompt to a large language model (LLM).

Abstract: Techniques for generating a virtual space overview are discussed herein. A communication platform may receive a request from a user profile to view an overview of a virtual space. Based on the request, the communication platform may receive criteria associated with the request. The criteria may indicate a type of content to include in the overview, a recency of the content, filters, etc. The communication platform may identify the content to include in the overview based on the criteria. The communication platform may use the content to generate the overview. That is, the overview may include one or more sections that include summaries and/or relevant data based on the content. The communication platform may cause overview to be displayed via a user interface of a user device of the user profile.