Labelbox

Labelbox is a training data platform for building real-world artificial intelligence and machine learning. The software is built for industrial data science teams for labeling and management of neural network training. Labelbox works to develop high-quality labeled training data in order to reduce machine learning development cycles.

Labelbox was founded in March 2018 in San Francisco by Manu Sharma, Dan Rasmuson, and Brian Rieger.

The platform consists of label editor tools, batch & real-time labeling workflows, collaboration, quality review, analytics, and an optional, fully managed and dedicated labeling workforce.

The training software is primarily designed to combat time and monetary costs associated with engineers and data specialists annotating and labeling data. A 2019 study showed that data preparation and engineering tasks consume over 80% of the time spent on most AI and machine learning projects, and that third-party data labeling is five times more cost-effective than internal efforts.

Labelbox was awarded an Air Force Innovation Hub Network (AFWERX) Phase 1 Small Business Innovation Research (SBIR) Artificial Intelligence Grant by the US Department of Defense on April 9, 2020. The company's customers include American Family Insurance, Lytx, Airbus, Genius Sports, and Keeptruckin.

The startup has received $38.9 million USD in funding from companies including Gradient Ventures, First Round Capital, Kleiner Perkins, and Andreesen Horowitz (a16z).