Auquan's platform, we enable finance companies to find machine learning solutions to their investment problems, without needing an in-house data science team.

How is this done?

1. We translate these into math problems internally
2. Our data transformer tool masks client’s data, circumventing licensing/data rights issues (ie Bloomberg) and protects proprietary information.
3. Solutions are crowdsourced from a global community of 12,000+ data scientists from Google, Microsoft, MIT, Oxford etc.

Chandini, the CEO, is an ex-derivatives trader at Optiver, Chicago, where she traded volatility arbitrage strategies. At Optiver, she was involved first hand in making the shift from discretionary to automated trading.

Our CTO, Shub has worked on Azure Stack at Microsoft in Seattle and accounting integrations at Gusto, a Y-Combinator unicorn backed by investors like Google Capital and General Catalyst in San Francisco.