Tamr, a startup using artificial intelligence to speed up data analytics workflows, has raised $18m in fresh funding.
Capital in the funding round came from new investors SBI Investment, INTAGE Open Innovation Fund, Samsung Ventures, Fenox Venture Capital, and Alumni Ventures Group.
The round also featured additional participation from founding investors NEA and GV, as well as other existing investors.
Tamr said it will use the new funds to continue its rapid growth, which is being fueled by new urgency in large enterprises to reinvent how they manage data to accelerate their digital transformation, as well data and privacy, such as GDPR.
“Our mission when we founded the company in 2013 was to enable large enterprises to unify key data to realize maximum strategic and operational benefit,” said Andy Palmer, co-founder and CEO of Tamr. “This new financing underscores the strategic importance of that mission as well as our ability to deliver for our customers. DataOps — our vision for how enterprises can reinvent the way they manage data to accelerate digital transformation — is fast becoming a reality and driving widespread adoption of Tamr’s best-of-breed data unification solutions.”
Based in Cambridge, Massachusetts, Tamr’s solutions are based on the company’s patented enterprise data unification software platform.
By applying machine learning and human expertise to large-scale data curation challenges, Tamr claims its data mastering and classification solutions are able to break through the limitations of traditional rules-based data integration approaches inherent in ETL and MDM products.
Tamr also claims to simplify GDPR compliance with unified data. It provides a free risk assessment which allows the user to understand the relationship between data sources and quantify the amount of fragmentation within their data, meaning they can apply the right compliance strategy.
Yoshitaka Kitao, representative director, president & CEO of SBI Holdings, added: “We have chosen to invest in Tamr because their innovative application of machine learning to the long-standing challenges of large-scale data integration has enormous disruptive potential.
“The company has already demonstrated that it can deliver impressive results for customers in several different industries, and we are excited to partner with them to further accelerate their growth.”
Copyright © 2018 RegTech Analyst
Copyright © 2018 RegTech Analyst
