Boston-based DataRobot, a startup developing an end-to-end enterprise AI platform, today raised $270 million in equity funding led by Altimeter Capital. The company says that the pre-IPO round — which was joined by new and existing investors including T. Rowe Price, Blackrock, Silverlake, NEA, and Tiger — values the company at over $2.7 billion.
The benefits of AI and machine learning can feel intangible, yet surveys show this hasn’t deterred enterprises from adopting the technology in droves. Business use of AI grew a whopping 270% over the past four years, according to Gartner, while Deloitte says 62% of respondents to its corporate October 2018 report deployed some form of AI, up from 53% a year ago. But adoption doesn’t always meet with success, as the roughly 25% of companies who’ve seen half of their AI projects fail will tell you.
DataRobot was founded in 2012 and claims to have had triple-digit recurring revenue growth dating back to 2015, as well as two billion models built on the platform to date. DataRobot CEO Jeremy Achin was previously property casualty insurer Travelers’ director of research and modeling and Tom de Godoy, DataRobot cofounder and CTO, was a senior director of research and modeling at the carrier.
DataRobot’s suite is a portable architecture that runs on cloud platforms, on-premise datacenters, or as a fully managed service. It lets customers prepare data and create and validate machine learning models including classification, advanced regression, time series, and deep learning algorithms. Once deployed, these customers can monitor models from a single dashboard as well as test, run, and maintain them to optimize the outcomes that inform decision-making.
In a nutshell, depending on a customer’s wants and needs, DataRobot automatically runs a competition within itself by testing hundreds or even thousands of solutions to a problem and delivering the models expected to provide the most accurate predictions. The platform’s automatic feature engineering, apps, and machine learning model selection features are domain-agnostic. DataRobot’s customers span more than a third of the Fortune 50 including Kroger, Nationwide, Lenovo, PNC, and others across banking, health care, insurance, finance, manufacturing, retail, government, sports, and gaming verticals.
Using DataRobot, data scientists can explore, combine, and shape datasets into assets ready for AI models courtesy of self-service tools. The platform supports a range of data types and content from traditional tabular data in rows and columns to free-form text, images, and geospatial data.
DataRobot recently launched AI Catalog, which leverages tech from Cursor, a company DataRobot acquired in February 2019. It’s designed to help users find data in large organizations and understand how to make it searchable and sharable to bolster collaboration. AI Catalog compliments MLOps, a DataRobot service introduced late last year takes existing solutions for modeling and combines them with tools from AI operations company ParallelM, which was acquired by DataRobot in June 2019. MLOps operates atop Apache Spark and Kubernetes and comes with tools designed to help organizations deploy models in production, such as a dashboard for automatically identifying systems that need to be retrained to improve performance.
DataRobot’s other acquisition targets include Nutonian, which developed a platform — Eureqa — focused on classification, numeric, multi-series, and time series capabilities. More recently, DataRobot nabbed Nexosis and Paxata, companies working to simplify the way developers build AI apps and prep data.
The infusion of capital brings DataRobot’s total raised to $700.6 million following a $206 million series E in September 2019, making the company among the top-funded AI startups in the world. Competitors like Determined AI, Explorium, Ople, Domino Data Lab, and Kaskada trail hundreds of millions of dollars behind.