System for Providing Software Related Answer Based on Trained Model
Summary
USPTO published patent application US20260099736A1 for a system providing software-related answers using a trained AI model. The invention involves natural language understanding for code base queries, using a custom enhancement model to determine user intent and a trained model (with generic and specific inputs) to generate natural language responses. Inventors: Joel Hart and Douglas Lee of SAFERITE.
What changed
USPTO published patent application US20260099736A1 titled 'System for Providing Software Related Answer Based on a Trained Model.' The application discloses a computer-implemented method for natural language understanding of development processes, involving receipt of natural language queries regarding code bases, processing through a custom enhancement model to determine intent, and processing through a trained model to generate responses.
Technology companies developing AI-powered developer tools, code analysis systems, or natural language interfaces for software development may benefit from reviewing this patent to understand the scope of protected methods in this domain and assess freedom-to-operate considerations for similar offerings.
Archived snapshot
Apr 17, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
System for Providing Software Related Answer Based on a Trained Model
Application US20260099736A1 Kind: A1 Apr 09, 2026
Inventors
Joel Hart, Douglas Lee SAFERITE
Abstract
A system and associated computer-implemented methods for providing natural language understanding. One computer-implemented method provides natural language understanding of a development process. The method is executed by an electronic processor and includes receiving, from a user interface, a natural language query regarding a code base, processing the natural language query through a custom enhancement model to determine an intent of the natural language query and provide an enhanced query, and processing the enhanced query through a trained model to determine a natural language response for the natural language query, the trained model trained with generic inputs and specific inputs. The method also includes providing, through the user-interface, access to the natural language response.
CPC Classifications
G06N 5/04 G06F 40/44 G06F 40/58
Filing Date
2025-12-02
Application No.
19406019
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