Labelbox, a San Francisco, CA-based data labeling platform for enterprises to train expert machine learning applications, raised $3.9m in seed financing.
The round was led by Kleiner Perkins with participation from First Round Capital and Google’s new AI fund, Gradient Ventures.
The company intends to use the funds to accelerate the development of its technology platform for building and maintaining in-house machine learning infrastructure, and to further expand its go-to-market strategy.
Co-founded by Manu Sharma, Ysiad Ferreiras, Daniel Rasmuson, and Brian Rieger, Labelbox provides a platform that gives users the ability to import new datasets, create and manage labeling tasks, and administer the way they are assigned to labelers. The product also includes quality control functionality and performance analytics. Its performance analytics dashboard allows customers to identify high and low performing labelers, and compare sources of labor against one another to choose the optimal provider.
Today, Labelbox is serving startups and enterprises including Conde Nast, Lytx and Genius Sports.