Abstract: Obtaining a data model associated with one or more tenants of a multi-tenant platform. Ingesting data from one or more data sources, wherein the data includes a plurality of columns. Generating a first natural language summary, by a first large language model, underlying data of each of the columns of the data. Generating a second natural language summary, by a second large language model, the data model, wherein the data model includes a plurality of different fields. Comparing the first natural language summary and the second natural language summary. Automatically classifying, based on the comparison of the first natural language summary and the second natural language summary, a first portion of the data as corresponding to a first field of the data model and a second portion of the data as corresponding to a second field of the data model. Obtaining a query from a user. Resolving the query, based on the automatic classification, to generate an answer for the query. Providing the answer to the user.

Abstract: Instantiating a first microservice-based platform instance in a first geographic region, wherein a first microservice of the first microservice-based platform instance performs index searching, a second microservice of the first microservice-based platform instance performs audit tracking, a third microservice of the first microservice-based platform instance performs object history tracking, and a fourth microservice of the first microservice-based platform instance performs entity matching. Instantiating a second microservice-based platform instance in a second geographic region, wherein the second microservice-based platform instance is a duplicate of the first microservice-based platform instance. Continuously synchronizing the first microservice-based platform instance and the second microservice-based platform instance. Receiving a query. Detecting a failure of the first microservice-based platform instance. Redirecting the query to the second microservice-based platform instance.

Abstract: Instantiating a first microservice-based platform instance in a first geographic region, wherein a first microservice of the first microservice-based platform instance performs index searching, a second microservice of the first microservice-based platform instance performs audit tracking, a third microservice of the first microservice-based platform instance performs object history tracking, and a fourth microservice of the first microservice-based platform instance performs entity matching. Instantiating a second microservice-based platform instance in a second geographic region, wherein the second microservice-based platform instance is a duplicate of the first microservice-based platform instance. Continuously synchronizing the first microservice-based platform instance and the second microservice-based platform instance. Pre-calculating, via the microservices, the index searching, the audit tracking, the object history tracking, and the entity matching.

Abstract: Ingesting data from a plurality of data sources. Converting the data into a plurality of vectors, wherein each vector represents a respective object of the data. Comparing the plurality of vectors with each other. Determining a distance between the plurality of vectors based on the comparison. Receiving a query. Automatically determining a set of candidate matches based on the query and the determined distances between the plurality of vectors based on the comparison. Resolving the query based on matching one or more portions of the query with the set of candidate matches.

Abstract: Obtaining a unified data model, wherein the unified data model provides a logical view of a plurality of data structures of a computing platform, wherein the computing platform is in communication with a plurality of cloud service providers that each provide respective storage services for the computing platform. Providing an abstraction layer, wherein the abstraction layer maps respective attributes of the unified data model to corresponding attributes of each of the plurality of cloud service providers. Selecting, by the abstraction layer, a first storage scheme of a first cloud service provider of the plurality of cloud service providers. Receiving, from a user, a first input.

Abstract: Among other techniques, techniques for parallelized rules-based and machine learning-based grouping are described.

Abstract: Accessing a multi-tenant computing platform, wherein the multi-tenant computing platform comprises a plurality of different underlying data structures, applications, functions, and back-end services. Defining a unified data model for the multi-tenant computing platform, wherein the unified data model normalizes the plurality of different underlying data structures, applications, functions, and back-end services of the multi-tenant computing platform. Receiving a first user input. Presenting, responsive to the first user input and based on the unified data model, a single logical view of the plurality of different underlying data structures, applications, functions, and back-end services across multiple tenants of the multi-tenant computing systems. Modifying at least one of the different underlying data structures, applications, functions, and back-end services. Receiving, subsequent to the modification, a second user input, wherein the second user input is the same as the first user input.

Abstract: Obtaining a unified data model, wherein the unified data model provides a logical view of a plurality of data structures of a computing platform, wherein the computing platform is in communication with a plurality of cloud service providers that each provide respective storage services for the computing platform. Providing an abstraction layer, wherein the abstraction layer maps respective attributes of the unified data model to corresponding attributes of each of the plurality of cloud service providers. Selecting, by the abstraction layer, a first storage scheme of a first cloud service provider of the plurality of cloud service providers. Receiving, from a user, a first input.

Abstract: Among other techniques, techniques for parallelized rules-based and machine learning-based matching are described.