A Team with a Passion for Innovation & Customer Success

DataChat is built in the Midwest, but based everywhere. Headquartered in Madison, Wisconsin, DataChat’s stellar team brings together deep academic roots, rich entrepreneurial success, and industry know-how to make analytics and data science available to everyone.

Join Our Team

Our Vision

Today the vision of DataChat is to build on the research of our co-founders to make data and analytics more accessible by allowing teams to use our Guided English Language instead of traditional data science tools to gain insights from their data.

Our History

DataChat was founded by Jignesh Patel and Rogers Jeffrey Leo John based on research they began at the University of Wisconsin-Madison. Their work focused on using natural language to create data science pipelines.

Our Funding

The UW founders funded early development with investment from America’s Seed Fund in the form of Small Business Innovation Research (SBIR) grants from the National Science Foundation.

The Wisconsin Alumni Research Foundation (WARF) was also an early investor in the Company. In 2020, DataChat raised an early stage investment round that was led by Silicon Valley venture capital firms Celesta Capital (formerly WRVI Capital) and Nepenthe Capital as well as individuals from Google and Palo Alto Networks.

DataChat’s Series A round in late 2021 was led by Redline Capital and Anthos Capital with participation from the existing institutional investors.

Leadership

  • Jignesh Patel

    CEO & Co-founder

  • Rogers Jeffrey Leo John

    Innovation Lead & Co-founder

  • Robert Claus

    Chief Technology Officer

  • Amos Kendall

    Director of Product

  • Kamal Sekhon

    Senior Director, Business Development

  • Laura Strong

    VP Strategy & Healthcare

  • Manish Kalra

    Head of Marketing

Our Team

  • Ashutosh Bakre

  • Austin Jiang

  • Bethany Schmeling

  • Cheng Li

  • Connor Hanson

  • David Khachatryan

  • Deepan Das

  • Donald Conway

  • Dustin Gallo

  • Elias Wilz

  • Ethan Gabrielse

  • Indrani Datta

  • Jack Strosahl

  • James Killian

  • Jiatong LI

  • Junda Chen

  • Kenny Mui

  • Kou Wang

  • Madeline Bushbeck

  • Matt Karrman

  • Munazza Mehroze

  • Nate Goethel

  • Nick Bell

  • Owen Hunt

  • Patrick Gallant

  • Prithvi Daniel Undavalli

  • Rui Huang

  • Sai Chandra

  • Spandana Muttavarapu

  • Stephen Shi

  • Sulong Zhou

  • Takashi Matsuzawa

  • Tyler Boddy Spargo

  • U.D. Gupta

  • Ushmal Ramesh

  • Varun Sreenivasan

  • Xiaoyu Liu

  • Yukiko Suzuki

  • Zach Mathe

Advisors

Chris Ré

Advisor / Professor @ Stanford / MacArthur Fellow

Chris is an associate professor in Computer Science at Stanford University. Research from his group has been incorporated into humanitarian efforts, such as the fight against human trafficking.

He has also co-founded four companies: SambaNova and Snorkel, along with two companies that are now part of Apple, Lattice in 2017 and Inductiv in 2020. He has won several awards including the MacArthur Foundation Fellowship in 2015, and best paper awards in both database and machine learning conferences.

David DeWitt

Advisor / Professor @ MIT / NAE Member

David has pioneered many of the parallel database technologies that power today’s parallel, distributed and cloud database platforms, while he was a professor at Wisconsin, where he also held the John P. Morgridge Chair. He was also a Technical Fellow at Microsoft, and is currently at MIT.

He is a member of the National Academy of Engineering and Fellow of the ACM, and has won several awards including the ACM SIGMOD Edgar F. Codd Innovations Award, the AM ACM Software System Award, and the IEEE Emanuel R. Piore Award, all for his seminal contributions to the field of database systems.

Samuel Madden

Advisor / Professor @ MIT / Sloan Fellow

Sam is a professor at MIT where he co-directs the Data Systems for AI Lab (DSAIL), an industry-backed initiative to unite researchers at MIT and leaders from industry to investigate the issues related to systems and algorithms for data that is high rate, massive, or very complex.

He is the recipient of numerous awards including a Sloan Foundation Fellowship, best paper and test-of-time awards in premier database conferences including VLDB and SIGMOD.

Sharon Yixuan Li

Advisor / Professor @ UW-Madison

Sharon is an Assistant Professor at the University of Wisconsin where her research interests include deep learning and machine learning.

She completed her Ph.D. at Cornell and a post-doc at Stanford. She is the recipient of the Facebook Research Award, JPMorgan early-career faculty award, and was named to Forbes' 30 Under 30 in Science.

Investors