Nainital, India

Mayank Sati

This inventor holds 1 USPTO granted patent. Top assignee: Observe.ai, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Mayank Sati. Retrieved from https://idiyas.com/inventor/mayank-sati

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


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Mayank Sati: Innovator in Machine Learning

Introduction

Mayank Sati is a notable inventor based in Nainital, India. He has made significant contributions to the field of machine learning, particularly in the evaluation of recorded interactions. His innovative approach has the potential to enhance user experience and feedback mechanisms in various applications.

Latest Patents

Mayank holds a patent titled "Machine learning-based evaluation of recorded interactions." This patent involves a comprehensive process that includes obtaining an evaluation plan corresponding to a new question, retrieving a representative interaction based on the new question, and utilizing a reasoning and answer language model to evaluate the interaction. The process culminates in outputting the new question and a preview evaluation result, while also incorporating user feedback to refine the model. He has 1 patent to his name.

Career Highlights

Mayank is currently employed at Observe.ai, Inc., where he applies his expertise in machine learning to develop innovative solutions. His work focuses on improving the evaluation of interactions, which is crucial for enhancing communication and understanding in various domains.

Collaborations

Some of his notable coworkers include Aashraya Sachdeva and Digvijay Anil Ingle. Their collaborative efforts contribute to the advancement of technology in the field of artificial intelligence and machine learning.

Conclusion

Mayank Sati is a pioneering inventor whose work in machine learning is shaping the future of interaction evaluation. His contributions are valuable to the ongoing development of intelligent systems that respond effectively to user needs.

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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