San Francisco, CA, United States of America

Abhi Sharma

USPTO Granted Patents = 4 

Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2024-2025

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4 patents (USPTO):Explore Patents

Title: Abhi Sharma: Innovator in Machine Learning and Digital Communication

Introduction

Abhi Sharma is a prominent inventor based in San Francisco, CA, known for his contributions to the field of machine learning and digital communication. With a total of four patents to his name, Sharma has made significant strides in enhancing automated interactive digital text threads.

Latest Patents

Sharma's latest patents focus on utilizing machine learning models to improve client interactions through personalized digital text reply options. One of his patents describes a system that employs machine learning to determine predicted client intent classifications, generating tailored digital text reply options within an automated interactive digital text thread. This innovation aims to bypass the inefficiencies of traditional menu options, providing a more streamlined experience for clients. Another patent highlights the use of machine learning to create personalized agent escalation digital text reply options, further enhancing the client experience by predicting when a client may need to escalate their interaction to a human agent.

Career Highlights

Abhi Sharma is currently employed at Chime Financial, Inc., where he applies his expertise in machine learning to develop innovative solutions for digital communication. His work has been instrumental in advancing the capabilities of automated systems, making them more responsive and user-friendly.

Collaborations

Sharma collaborates with talented individuals such as Jigar Mehta and Abbey Chaver, contributing to a dynamic work environment that fosters innovation and creativity.

Conclusion

Abhi Sharma's work in machine learning and digital communication exemplifies the potential of technology to enhance client interactions. His patents reflect a commitment to improving automated systems, making them more efficient and personalized.

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