Our Series A Round Was Led By Andreessen Horowitz
Today is a big day at SigOpt. Since the seed round we secured last year, we’ve continued to build toward our mission to ‘optimize everything,’ and are now helping dozens of companies amplify their research and development and drive business results with our cloud Bayesian optimization platform.
Following the surge of investment in cloud, big data, and analytics, enterprises have begun leveraging their data through machine learning, artificial intelligence, and predictive analytics. SigOpt amplifies model development and process research, efficiently tuning them to maximize the business value of these investments.
In recognition of this traction, we’ve received one of our strongest validations to date, securing a $6.6 million Series A financing round. The round was led by Andreessen Horowitz, who also led our seed round. You can read a post by Martin Casado of Andreessen Horowitz about the need for SigOpt, and how many business endeavors can be framed as an optimization problem here. We also received additional follow-on participation from Data Collective and welcomed new investors: SV Angel, Stanford University, and Blumberg Capital. We’ll use the money to scale our team, continue to execute for our customers, and expand the capabilities of our platform.
The idea for SigOpt came while I was a PhD student at Cornell. I proved it out at Yelp, optimizing the machine learning models that powered their advertising system. SigOpt was founded on the belief that researchers across a variety of industries face the same challenges I did when they need to tune their systems.
Since starting SigOpt, we’ve gained traction within the financial services and consumer products industries – notably companies that can drive an immediate impact on their bottom line through improvements in their modeling and processes. Today, we count Prudential, MillerCoors, Johnson & Johnson, and some of the world’s leading hedge funds as customers, among others.
“SigOpt helps us optimize the financial models in our funds management platform,” said SigOpt customer Max Logunov, Ph.D., a developer at Optimus Socially Responsible Investments LTD. “The API is convenient and easy to set up. SigOpt gets us better results, optimizing 15 times faster than before. Now, we’re happy to focus on other matters, because SigOpt saves us so much time.”
Make Your Modelers The Hero
The SigOpt optimization platform helps experts across industries amplify their modeling and process optimization initiatives. Our customers include algorithmic traders at hedge funds, advanced risk modelers at large banks and research scientists working to brew tastier beers. By replacing costly trial and error and traditional Design of Experiments (DoE), SigOpt empowers experts to get the most out of their models and processes.
By using SigOpt to improve model performance and reduce the time and resources spent fine tuning, a data scientist or researcher can become a hero on their team, driving significant business results.
Continuing To Invest In Technology Leadership
Our platform was built for seamless adoption. It easily bolts on top of existing machine learning, AI, and predictive analytics pipelines. In developing our technology we’ve sought to anticipate what our customers need and to reinforce our leading position in the market. Since our last funding, we’ve extended our platform to become more:
- Flexible: Integrations with Google’s TensorFlow, SAP HANA, R, Java, Python, and scikit-learn enable SigOpt customers to quickly integrate into any machine learning stack and conduct efficient feature parameter and hyperparameter optimization.
- Intuitive: We expanded SigOpt dashboard to include multi-dimensional visualization, collaboration, and improved experiment management. We’ve also launched a number of improvements to its core API, including a complete REST API overhaul.
- Powerful: We’ve invested to ensure that SigOpt’s core optimization engine continues to be the most powerful in the world. The SigOpt research engineering team has extended support for parallel optimization across a cluster of machines and continues to produce world-class, peer-reviewed research in Bayesian optimization and optimal learning.
“We are thrilled to partner with Scott and the SigOpt team,” said Matt Bornstein, principal at Blumberg Capital. “Machine learning holds massive potential, but it’s complicated – once described as ‘a black box with 500 million knobs.’ SigOpt turns the knobs for you. We think that’s a pretty powerful concept and the company’s customers think so, too.”
The attention we received from investors during this round was humbling and encouraging, and we’re thrilled with our growing team that believes in our vision. We’re also proud of the customer traction and product leadership that we’ve been able to achieve, but we won’t stop here. This round is going to help us execute for our existing customers and grow our business, build our team, and drive product innovation to bring us closer to our vision of optimizing everything. As we say at SigOpt: Stay tuned!