US 2024/0256534 A1 · Automated Data Ingestion and Processing

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.

Claims20

Dependent claims

A method for automatically ingesting newly released documents and storing data extracted from the newly released documents in an established non-relational database for conversion into a different format, the method comprising:

identifying, via one or more backend application programming interfaces (APIs), one or more newly released documents that include data for one or more users;
automatically ingesting, via an ingestion call executed via the one or more backend APIs in response to the identifying, the one or more newly released documents;
extracting, using a computer vision model trained on a plurality of different types of documents, a set of data from the one or more newly released documents, wherein the extracting includes identifying one or more locations within respective ones of the one or more documents from which to extract information;
storing the extracted set of data in the established non-relational database storing data extracted from previously ingested documents for a plurality of users in a text-based object format;
and
converting, 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.

3 more elements

A non-transitory computer-readable medium having instructions stored thereon that are capable of causing a system to implement operations comprising:

identifying, via one or more backend application programming interfaces (APIs), one or more newly released documents that include data for one or more users;
automatically ingesting, via an ingestion call executed via the one or more backend APIs in response to the identifying, the one or more newly released documents;
extracting, using a computer vision model trained on a plurality of different types of documents, a set of data from the one or more newly released documents, wherein the extracting includes identifying one or more locations within the document from which to extract information;
storing the extracted set of data in a database storing data extracted from previously ingested documents for a plurality of users in a text-based object format;
and
converting, based on a plurality of metatags, data corresponding to a given user from the text-based object format to a queryable file format.

3 more elements

A system, comprising:

at least one processor;
and
a memory having instructions stored thereon that are executable by the at least one processor to cause the system to perform an automatic document ingestion process, including:
identifying, via one or more backend application programming interfaces (APIs), one or more newly released documents that include data for one or more users;
automatically ingesting, via an ingestion call executed via the one or more backend APIs in response to the identifying, the one or more newly released documents;
extracting, using a computer vision model trained to identify user data within documents, a set of user data from the one or more newly released documents, wherein the extracting includes identifying one or more locations within the document from which to extract information;
storing the extracted set of user data in an existing non-relational database storing data extracted from previously ingested documents for a plurality of users in a text-based object format;
and
converting, 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.

6 more elements

Dependencies are inferred from the claim text.

Automated Data Ingestion and Processing

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Automated Data Ingestion and Processing

Life of this patent

Abstract

Claims20