Business Intelligence Buyer's Guide

DataRobot Nets $270 Million in Pre-IPO Funding with $2.7B Valuation

DataRobot Nets $270 Million in Pre-IPO Funding with $2.7B Valuation
DataRobot Nets $270 Million in Pre-IPO Funding with $2.7B Valuation

Source: DataRobot

DataRobot recently announced a pre-IPO funding round worth $270 million, according to a press release on its website. Led by Altimeter Capital with inclusion from new and existing investors, the capital injection brings DataRobot’s total raised to more than $700 million. DataRobot has a current valuation of $2.7 billion, which represents a 100 percent increase from the time of its Series E funding round.

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DataRobot offers an enterprise AI platform that automates the end-to-end process for building, deploying, and maintaining AI. The product is powered by open source algorithms and can be leveraged on-prem, in the cloud or as a fully-managed AI services. DataRobot includes three independent but fully integrated tools (Automated Machine Learning, Automated Time Series, MLOps), and each can be deployed in multiple ways to match business needs and IT requirements.

In a media statement about the news, DataRobot President and COO Dan Wright said: “We’re seeing overwhelming demand for our platform. This latest round of financing further validates this momentum, and we intend to use it to accelerate our rapid growth globally. Modern enterprises are generating and capturing more data than ever before, and this data is also changing more rapidly than ever. Traditional business intelligence and manual machine learning methods are completely inadequate to keep pace. Businesses need AI-driven insights into what will happen, rather than simply what has happened, in order to win in today’s increasingly competitive market.”

This announcement comes on the heels of DataRobot’s April AI platform release, which is highlighted by the integration of DataRobot Paxata data preparation. DataRobot Paxata is integrated with the platform’s AI catalog so users can explore, clean, combine and shape data for training and deploying machine learning models. Any machine learning model can be turned into an AI application. The AI applications feature also includes Applications Gallery, a collection of AI applications available to business users.

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