Research optimization and machine learning startup SigOpt announced today that it has closed a $6.6 million investment round — led by existing investor Andreessen Horowitz — to scale its team and “expand the capabilities of its platform.”
The Y Combinator alumnus’ technology promises to help businesses “optimize everything” by using machine learning, artificial intelligence, and predictive analytics to replace the manual trial and error process.
“Our customers include algorithmic traders at hedge funds, advanced risk modelers at large banks, and research scientists working to brew tastier beers,” said SigOpt founder and CEO Scott Clark.
“[M]any business endeavors can be framed as an optimization problem,” explained A16Z’s Martin Casado in a blog post. “And for complicated problems where there is no simple correlation between the inputs and the outputs (which tends to be all of the interesting ones) SigOpt can produce better results exponentially faster than anyone else.”
Data Collective, SV Angel, Stanford University, and Blumberg Capital also contributed to the series A round that leaves SigOpt with a total of $8 million in funds, including a $2 million seed round last year.