Machine-learning GraphLab raises $18.5m and rebrands as Dato

A multi-million dollar investment is the cue for a company name change as well as expansion plans for GraphLab and its predictive app development platform.

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Carlos Guestrin: Making benefits of data science accessible. Image: Dato

As well as announcing a change of company name to Dato, machine-learning firm GraphLab says a new $18.5m funding injection will help finance expanded engineering, business-development and customer-support teams.

The $18.5m series B funding round announced today, led by Vulcan Capital with Opus Capital Ventures and previous investors NEA and Madrona Ventures, takes the total raised by GraphLab-Dato to $25.25m.

Behind the Seattle-based company is technology that originated at Carnegie Mellon University in 2009 with the GraphLab open-source project started by the firm's CEO, Carlos Guestrin. The software originally focused on applying large-scale machine learning to graph analysis but now can handle tables, text and images.

The company said the change of name from GraphLab to Dato is designed to underline that shift in the technology.

"We have been about so much more than graph data for so long that it was important to get the word out broadly," the firm said.

"While we began life as a graph-analytics, open-source project, the underlying engine has morphed, adding significant innovations for the handling and analysis of tabular data as well as text and images."

According to Dato, the platform is being used by companies such as Adobe, Cisco, PayPal and Zillow in a range of predictive applications including item recommendation, fraud detection, and sentiment analysis.

"The investments made in Dato will help us empower many more data scientists, software developers and engineers. We are delivering a complete environment that makes data science and its benefits accessible to every business," Guestrin, who is also a professor of data science at The University of Washington, said in a statement.

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On top of the GraphLab C++ engine are a number of toolkits and deployment options that are designed to make it easier for data scientists and app developers to embed predictive functionality into applications.

Last October, GraphLab announced the general availability of its flagship GraphLab Create 1.0 product. As well as support for graphs and tabular data with SGraph and SFrame, the GraphLab Create Python library offers a simple interface, advanced machine-learning toolkits and the ability to deploy predictive services directly to the cloud.

The company says it is built on a strong open-source community that already consists of thousands of members and continues to grow daily. Its annual conference takes place in San Francisco in late July.

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