Data science platform provider Domino Data Lab recently announced that it has secured $40 million in new venture capital. Led by previous investor Sequoia Capital, the round brings the company’s total amount raised to $80.6 million since its founding in 2013. The funding will help Domino continue to innovate in the data science platform marketplace, expand its reach, and deepen partnerships like those it has already with SAS and Amazon Web Services.
Domino Data Lab is an enterprise data science platform that allows data scientists to build and run predictive models. Its product helps organizations with the development and delivery of these models via infrastructure automation and collaboration. Domino provides user 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 funding comes at a perfect time for Domino, as it has seen increased demand in during the last year, even tripling its revenue in the last nine months. Domino unveiled a new Model Management framework at its first annual Rev Summit back in May as well. The Model Management framework helps model-driven organizations develop, deliver and manage predictive models. The vendor has also seen its name in several major analyst reports recently, first as a visionary in Gartner’s Magic Quadrant for Data Science and Machine-Learning Platforms, and then in CRN’s Big Data 100 in May.
In a press statement, Domino’s co-founder and CEO Nick Elprin said: “Customers using Domino have happier and more productive data scientists building and delivering models faster. The strong backing from Sequoia and Coatue amplifies our ability to help our customers improve their models, whether that lets them increase crop yields, reduce fraud, invent new medicine, or simply recommend the best meal to order.”
Latest posts by Timothy King (see all)
- 13 Top Machine Learning LinkedIn Groups for Practitioners - January 24, 2020
- The 14 Best Data Science and Machine Learning Platforms for 2020 - January 24, 2020
- Outlier Nabs New Funding to Automate Business Analysis - January 22, 2020