Systems and methods for determining entity attribute representations

ChangeBridge: Patent Grants - AI & Computing (G06N)

Published March 31st, 2026

Detected March 31st, 2026

Summary

USPTO granted Patent US12591598B2 to Xero Limited on March 31, 2026. The patent covers a computer-implemented method for determining entity attributes using machine learning, including entity identifier determination, entity server address verification, transmitting information requests, and generating numerical entity representations via trained ML models.

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What changed

US Patent No. 12,591,598B2 was granted to Xero Limited (Application No. 18912545) on March 31, 2026. The patent describes a method for determining entity attributes by determining entity identifiers, verifying entity server addresses, transmitting information requests to entity servers, and using machine learning models to generate numerical representations of entities based on received entity information. The filing date was October 10, 2024, and the patent contains 17 claims covering various aspects of the entity attribute determination system.

This is a routine patent grant notice and does not impose any compliance obligations, deadlines, or penalties. No action is required by any party. The patent may be relevant to entities developing or using similar AI/ML systems for entity attribute determination or entity resolution, who may wish to review for potential licensing considerations or patent infringement concerns.

Source document (simplified)

← USPTO Patent Grants

Systems and methods for determining entity attribute representations

Grant US12591598B2 Kind: B2 Mar 31, 2026

Assignee

Xero Limited

Inventors

Maksymilian Clark Polaczuk, Christopher Darius Herrmann, Timothy Matthew Leathart, Divya Jitesh Patel

Abstract

A computer implemented method for determining entity attributes. The method comprises determining one or more entity identifiers, determining an entity server address of the entity based on the one or more entity identifiers, wherein the entity server address points to an entity server; verifying the entity server address transmitting a message for request for information to the entity server address, receiving entity information from the entity server; and providing, to a machine learning model, the received entity information. The machine learning model is trained to generate a numerical representations of entities based on the entity information.