Auburntown, TX, United States of America

Jason L Keeney

This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignee: State Farm Mutual Automobile Insurance Company. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Jason L Keeney. Retrieved from https://idiyas.com/inventor/jason-l-keeney

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Jason L. Keeney and AI-Based Query and Response Systems

Introduction

Jason L. Keeney is an inventor associated with Auburntown, Texas, and State Farm Mutual Automobile Insurance Company. His patent work addresses the use of artificial intelligence to help representatives respond to incoming messages in real time.

Latest Patents

Keeney is named on 1 patent: “Artificial Intelligence-Based Query and Response Systems and Methods.” The invention describes a computing system that presents a proposed AI-generated response to an incoming query, along with links to relevant documents retrieved from a subject-category database. It also lets a representative provide feedback on the proposed response. The system records that feedback, uses it to create a training dataset, and retrains the AI model to generate a revised response in real time.

Career Highlights

Keeney’s listed patent reflects an application of AI to customer-service workflows. By combining suggested responses, relevant reference materials, and representative feedback, the system is designed to refine its responses over time.

Collaborations

Keeney’s listed coworkers include Catherine Espel-Logan and Chelli D. Whitaker. His patent is associated with State Farm Mutual Automobile Insurance Company.

Conclusion

Jason L. Keeney’s patent focuses on improving real-time message responses through AI-generated suggestions, relevant documents, and feedback-based model training.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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