SigOpt, a research optimisation and machine learning startup serving banking, insurance and trading firms, has raised $6.6m in a Series A round led by Silicon Valley heavy weight Andreessen Horowitz.
The San Francisco-based company’s software is designed to boost businesses’ bottom lines by improving their modelling processes. The company optimises these by replacing manual trials with machine learning and predictive analytics.
SigOpt says its customers include algorithmic traders at hedge funds and advanced risk modelers at large banks, as well as researchers in consumer goods.
Data Collective, SV Angel, Stanford University and Blumberg Capital also contributed to the new round, which follows a $2m seed round raised by the firm last year that Andreessen Horowitz and Data Collective jointly led.
SigOpt says the capital will go towards scaling up its team and expanding the platform’s capabilities.
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