AI

MindsDB Named in 2022 Gartner® Cool Vendor™ in Data-Centric AI report

MindsDB is the leading and fastest growing open source applied machine learning (ML) platform in the world. The company today announced it has been named a 2022 Gartner Cool Vendor in the report titled “Cool Vendors in Data-Centric AI” by Analyst(s): Svetlana Sicular,  Arun Chandrasekaran, Sumit Agarwal, Oleksandr Matvitskyy, Anthony Mullen. 

The Gartner Cool vendor report focuses on lesser-known emerging vendors or service providers that offer unique solutions. According to the report, “Business stakeholders can think of predictions as transactional data, available in (almost) real-time without additional, usually complex, effort of requirements gathering and application development.”

“Using MindsDB Cloud to bring machine learning to Rize has been a game-changer. When I started exploring ML, it seemed like I’d need six months of experimentation, model training and building out pipelines to productionize.” said Macgill Davis, CTO Rize. “By using MindsDB Cloud to train and auto-deploy models directly from my database, I saved months of work and many thousands of dollars.”

To get started with MindsDB please visit http://www.mindsdb.com

Gartner (2022, December 14) Cool Vendors in Data-Centric AI, Svetlana Sicular, Arun Chandrasekaran, et al.., https://www.gartner.com/en/documents/4022242

GARTNER and COOL VENDORS are a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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