This inventor holds 2 USPTO granted patents and 1 published patent application. Top assignee: Sap Se. Active years: 2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2026
Title: Sparshad Kasote: Inventor in Natural Language Data Querying and Interactive Machine Learning
Introduction
Sparshad Kasote is an inventor based in Pune, India, whose work includes inventions in natural-language data querying and interactive machine learning. He is associated with SAP SE and is credited with 2 patents.
Latest Patents
Kasote’s listed patents address ways to make data systems more accessible and responsive to users.
“Natural language data query systems and methods” describes techniques for querying a data store with natural-language inputs. A machine-learning model is trained using natural-language inputs, SQL queries, and data-store metadata. In some embodiments, training may also use user-interface code and visualizations. The system processes a user’s input, generates a query, and displays the results in a user interface. It can also present selected natural-language inputs as links that users can choose to generate further queries.
“Interactive machine-learning framework” describes a system that presents a user with an output generated from activity data. The user can review the data and designate a portion as unavailable for generating future outputs. The system then excludes that portion when producing outputs for the user.
Career Highlights
Kasote’s patent work reflects an interest in applying machine learning to practical data interactions. His inventions describe both natural-language interfaces for querying information and user controls over the activity data used to generate machine-learning outputs.
Collaborations
Kasote is associated with SAP SE. His listed coworkers include Krishnan Vijayaraghavan and Gautam Guha.
Conclusion
Sparshad Kasote’s two patents focus on making data querying more intuitive and giving users greater control over machine-learning systems.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
