Business rules management system for process enterprises using NLP

ChangeBridge: Patent Grants - Business Methods (G06Q)

Published April 7th, 2026

Detected April 7th, 2026

Summary

USPTO granted Patent US12596983B2 to Infosys Limited on April 7, 2026. The patent covers a method and system for managing business rules in process enterprises using Natural Language Processing (NLP). The system parses user inputs to extract business keywords, maps them to technical keywords using NLP, and identifies and updates relevant business rules. The patent contains 18 claims and relates to business method automation technology.

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What changed

USPTO granted Patent US12596983B2 to Infosys Limited for a method and system of managing business rules in process enterprises. The patented technology uses Natural Language Processing (NLP) to parse user inputs, extract business keywords, map them to technical keywords, and update business rules accordingly. The patent provides Infosys with exclusive rights to this automated business rules management technology.\n\nFor technology companies and enterprises using business process management systems, this patent establishes IP protection that may restrict competitors from offering similar NLP-based business rules management solutions. Organizations developing competing technologies in this space should review the patent claims to assess potential licensing requirements or design-around considerations.

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Source document (simplified)

← USPTO Patent Grants

Method and a system for managing business rules in a process enterprise

Grant US12596983B2 Kind: B2 Apr 07, 2026

Assignee

Infosys Limited

Inventors

Arun Ganesan

Abstract

The present disclosure relates to method and system for managing business rules in a process enterprise. Firstly, an input from a user is received for managing one or more business rules from a plurality of business rules associated with the process enterprise. The input is parses for extracting one or more business keywords. Further, one or more technical keywords corresponding to the one or more business keywords are identified based on a pre-stored mapping information, using a Natural Language Processing (NLP) model. Then, at least one business rule is identified from the plurality of business rules based on the one or more technical keywords. Further, one or more actions to be performed on the at least one business rule is identified based on the input. Finally, the at least one business rule is updated, based on the one or more actions.