GraphLab, originally developed at Carnegie Mellon University, has raises $6.75m series A round.
Graph computation network startup Graphlab has received $6.75m in series A funding in a round led by Madrona Venture Group and joined by New Enterprise Associates.
Founded five years ago by current GraphLab chief executive Carlos Guestrin at Carnegie Mellon University, the open source project has developed into graph-based distribution computation network that can be used for machine learning, data-mining, and other computing tasks.
The Seattle-based firm is now developing a commercial product for applying advanced machine learning to massive graph data sets.
Carlos Guestrin, who is now also the Amazon Professor of Machine Learning at the University of Washington, said: “Data has the ability to make our lives better – whether applied to public health, economics, or suggesting the perfect song. But as the complexity of data sets grows, the need for entirely new ways of thinking about them has grown as well. The industry’s response to the GraphLab project has been clear, this is the solution that drives millions of transactions daily and we are excited to continue to build on this success with commercial products that make a difference.”
As part of the round, Matt McIlwain from MVG and Greg Papadopoulos from NEA will be joining the GraphLab board.
