DataRobot Pledges Funds to Expand Global Footprint

DataRobot Pledges Funds to Expand Global Footprint

The new capital will be deployed to double the size of DataRobot’s world-class data science and engineering organizations which will teach DataRobot to be faster

Data scientists Jeremy Achin and Thomas DeGodoy founded DataRobot, in 2012, with the vision to open up the world of data science to non-data scientists and increase productivity for data scientists through automated machine learning (ML). The result was 110 million plus predictive models developed by DataRobot’s customers, using the SaaS version of the DataRobot automated machine learning platform, by 2016.

DataRobot recently raised $54M in the first close of a Series C round led by global venture capital firm New Enterprise Associates (NEA), with a significant portion expected in the second round. Just over a year back it secured  $33M in funding from a group of top investors.  This is NEA’s  third investment in DataRobot that brings the total funding to $111.42M.

The company pledged the funds to bring automated machine learning to mainstream business users. DataRobot also plans to expand its global footprint, and increase support for existing partners, which include Cloudera and Alteryx.

“With this new capital we will double the size of our world-class data science and engineering organizations which will accelerate our ability to teach DataRobot to be faster and better at solving a wider variety of AI and ML problems,” said Jeremy Achin, CEO, and Co-Founder of DataRobot.

The software platform features hundreds of open-source machine learning algorithms and harnesses best practices and knowledge from the world’s leading scientists, enabling users of all skill levels to build predictive models for their companies. What users do is just upload their data, select their target variables, and DataRobot automates, trains, and evaluates multiple predictive models for them.  Its software filters millions of different configurations until finding the best way of carrying out the task at hand.

Highlighting the need for ML, Achin  explained that the number of AI and machine learning (ML) solutions being generated by all the data scientists in the world is not even making a dent in the massive demand for these solutions, and this deficit is growing rapidly as executives across the globe–in all verticals–realize that an AI-driven organization is now a necessity.

He further notified, “The only way to meet this demand is to automate the development of AI and ML solutions by teaching machines to do most of the work. While DataRobot [software] can already solve many of the world’s AI and ML problems on its own, there are still many things it needs to be taught.

Bringing Predictive Insights to Enterprises

Industries such as insurance, banking, healthcare, and financial tech, among others, are finding that the DataRobot platform democratizes predictive insights across their enterprise. “Until now, AI was no more than a vague promise for business applications. Automated machine learning, in particular, has put these opportunities in reach of all enterprises, including those with no previous AI experience,” said Tom Davenport, President’s Distinguished Professor of IT and Management, Babson College.

Tony Florence, NEA General Partner, and DataRobot Board Member said “Our confidence is buoyed by their data science-like approach to their own development. They are not only the best product for the market but have also defined the category. Their high-caliber and the extremely dedicated workforce is productizing AI technologies that deliver significant competitive advantages to their users.”

AI Impacts Businesses that have Little or No Data Science Experience

Recruit -the largest HR and Media Company in Japan and among the largest in the world has been benefiting from DeepRobot’s ML software.  “DataRobot empowers our business executives and analysts, allowing us to better serve our customers. Executive training from DataRobot University has helped our business leaders identify opportunities where AI can impact the business, while the automation platform enables analysts with little or no data science experience to successfully execute on those opportunities. This represents the true democratization of AI and machine learning,” said Joe Saijo, Managing Director, Recruit Strategic Partners Inc.

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