Domino Data Lab recently announced $100 million in new venture capital funding led by Great Hill Partners and NVIDIA. Domino and NVIDIA will also expand their partnership, further integrate products, and join sales efforts to support machine learning in the enterprise. The Series F round, which also includes participation from existing investors, brings the company’s total funding to $228 million since its founding.
Domino Data Lab is an enterprise data science platform that allows data scientists to build and run predictive models. The product helps organizations with the development and delivery of these models via infrastructure automation and collaboration. Domino provides users access to a Data Science Workbench that provides open source and commercial tools for batch experiments, as well as Model Delivery so they can publish APIs and web apps or schedule reports.
The news comes on the heels of Domino’s April announcement of NVIDIA-powered data science and MLOps tools. The new platform automatically creates and manages multi-node clusters and releases them when training is done. Domino currently supports ephemeral clusters using Apache Spark and Ray, and will be adding support for Dask in a product release later in the year. Administrators can also divide a single NVIDIA DGX A100 GPU into multiple instances or partitions to support a variety of users with Domino’s support.
In a media statement on the news, Domino Data Lab co-founder and CEO Nick Elprin said: “Our mission is to help our customers unleash the power of data science. We’re thrilled to have the support of Great Hill Partners and NVIDIA to accelerate our growth and innovation, which in turn will help our customers address the world’s most important challenges.”
Read Investing to Make Every Company Model-Driven in the Domino Data Lab to learn more.
- The 23 Best Business Intelligence Software for Retail in 2022 - January 25, 2022
- The 19 Best Business Intelligence Software for Healthcare in 2022 - January 25, 2022
- The 19 Best Visual Analytics Tools and Software for 2022 - January 25, 2022