Salt Lake City, WA, United States of America

Chandra Sekhar Inguva

This inventor holds 2 USPTO granted patents. Top assignee: Microsoft Technology Licensing, LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Chandra Sekhar Inguva. Retrieved from https://idiyas.com/inventor/chandra-sekhar-inguva

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

Calculating rank

% Patents Active = 50.0

Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2026

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2 patents (USPTO):Explore Patents

Title: Chandra Sekhar Inguva and AI-Driven Software Deployment Policies.

Introduction

Chandra Sekhar Inguva is an inventor associated with Microsoft Technology Licensing, LLC. The supplied information lists his location as Salt Lake City, WA (US) and identifies 1 patent.

Latest Patents

Inguva’s listed patent is titled “Deployment Policy for Software Updates Across Cloud Environments Driven by Artificial Intelligence.” It describes a data processing system that receives a request to deploy a software change and determines factors that may affect the best deployment policy. The system queries an AI trained on optimized deployment policies to recommend a policy that includes a ring rollout policy, ring bake time, and deployment time. It then carries out the deployment using the recommended policy and updates the AI’s training based on the factors and deployment results.

Career Highlights

The patent focuses on applying artificial intelligence to software deployment across cloud environments. Its approach uses deployment factors and observed outcomes to inform policy recommendations and refine the AI’s training over time.

Collaborations

The supplied information names Amy Leigh Josefczyk and Michael John Neuburger as Inguva’s coworkers. It does not specify their roles in the patent or describe their contributions.

Conclusion

Chandra Sekhar Inguva’s listed patent presents an AI-based approach to selecting, executing, and improving software deployment policies across cloud environments.

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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