DataRobot Acquires MLOps Provider Algorithmia, Nets $300M Series G

DataRobot Acquires MLOps Provider Algorithmia, Nets $300M Series G

Source: DataRobot

DataRobot recently announced its acquisition of MLOps platform provider Algorithmia and a $300 million-dollar Series G funding round via two press releases. Both items were made public on July 27. The merger will enable DataRobot to give customers access to a reliable and operational backbone for running any machine learning model, including deep learning workloads for NLP and image processing in complex inference pipelines with CPUs and GPUs. Algorithmia’s approach brings together best practices from AI/MLOps and DevOps.

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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 service. 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.

DataRobot’s newest funding will mainly be used to strengthen its augmented intelligence platform. However, DataRobot says it will also use the round to further build out its go-to-market team and operations around the globe. The funding round featured participation from new and exist

In a media statement on the news, DataRobot CEO Dan Wright said: “We are thrilled to welcome the Algorithmia team and advance our leading MLOps offering with world-class, enterprise-grade MLOps infrastructure to organizations across the globe. He added: “This new investment further validates our vision for combining the best that humans and machines have to offer in order to power predictive insights, enhanced data-driven decisions, and unprecedented business value for our customers.”

Read DataRobot is Acquiring Algorithmia, Enhancing Leading MLOps Infrastructure to Get Models to Production Fast, with Optimized GPU Workloads at Scale and Bringing Augmented Intelligence to All in the company’s blog to learn more.

Timothy King
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