AI and Machine Learning solutions provider, H2O.aiannounced that it has been selected by Credit Suisse as a member of the 2019 Disruptive Technology Recognition (DTR) Program. The program aims to recognise the companies with technologies enough to disrupt traditional IT with new, visionary, and innovative approaches.
“At Credit Suisse, technology innovation is key to providing the best user experience and for our customers and partners. The DTR program was created to recognize the companies that are disrupting the status quo in IT with great products and a clear vision in their respective spaces. H2O.ai is a clear leader in the AI and machine learning space, and continues to push the boundaries on what is possible with these technologies, and helps us deliver high-quality services to our clients,” said David Patten, CIO of Credit Suisse’s IBCM Division at Credit Suisse AG.
The DTR program is a joint initiative between the bank’s Investment Banking and Capital Markets division and Group Chief Technology Officer function and offers participants the opportunity to work collaboratively to promote innovation at the bank and at the Partner firms.
“H2O.ai is honoured to be selected into the coveted Credit Suisse’s DTR program this year. Our partnership with Credit Suisse started years ago with their adoption of H2O Open Source in core finance and banking with Dean Soteropoulos. In 2019, Dean and Anurag Sehgal at Credit Suisse chose H2O Driverless AI to accelerate AI adoption in front-office and back-office investment banking use cases in global markets, fixed income and capital markets. As part of the DTR program, we are thrilled to further partner across every group within Credit Suisse, co-invent AI and transform the space,” said Sri Ambati, CEO and Founder at H2O.ai.
Established in 2012, H2O.ai offers enterprise customers with platforms for AI and machine learning, including open-source platform H2O, automatic machine learning platform H2O Driverless AI, and the recently announced H2O Q, an AI platform for business users