Manu SharmaFebruary 11, 2021

Why we raised our Series C round

Over the past few years, the technology community has seen a drastic change in computing. It has evolved from software development, which uses logical expressions to tell computers what to do, to data-centric programming, which uses data to teach computers. This shift to AI has the potential for tremendous growth. As Peter Levine of Andreessen Horowitz said, “Every company is going to be an AI company.

Building AI, like software development, is most successful when it can iterate quickly. Currently, even the most successful AI teams take as much as four weeks for a single iteration. Speeding up this process will allow models to improve and move to production much faster. At Labelbox, our mission is to deliver workflows that accelerate iteration with the most comprehensive and integrated training data platform available. This new $40M round of funding was raised to continue realizing this mission.

Labelbox is a training data platform built around three pillars: the ability to annotate data, manage people and processes, and iterate on training data.

Labelbox is built around three key pillars: manage, annotate, and iterate.

We’ve designed the platform to be fully configurable, so teams can set up workflows to suit their needs. They can import their own model data as pre-labeled training data, set benchmarks and dynamic queueing, and collaborate across both internal and external labeling teams. Just as Figma and Github have become central to designers and software developers for establishing the workflow that accelerates collaboration and innovation, Labelbox is the platform that ML engineers, labelers, and stakeholders rely on to create training data for AI.

Labelbox enables disparate teams — both internal and external — to collaborate seamlessly.

Labelbox functions as a hub set on top of our customers’ data, so they can access multiple datasets and ontologies for all their AI projects.

Labelbox serves as the central hub for an organization’s training data efforts.

To date, we’ve seen our platform adopted by both Fortune 500 enterprises and leading AI-first companies across industries, including agriculture, insurance, healthcare, media, and more.

With the funding from the series C round, we plan to further build out functionality that makes the process of training data — and building AI — faster and easier than ever before. Labelbox aims to be the standard platform for organizations that want to deliver AI breakthroughs.

Rashmi Gopinath at B Capital led the round with contributions from our existing investors, Andreessen Horowitz, Gradient, and Kleiner Perkins. We also welcomed a few new investors who have inspired and helped us along the way: Cathie Wood (founder of Ark Invest, a $30B technology-first public ETF), Tau Ventures, and Kunal Bahl and Rohit Bansal (founders of Snapdeal).

If your team is looking to iterate faster on your models, read more on how Labelbox might be the solution you’re looking for. Here at Labelbox, we have big plans and big ideas — all we need is to continue growing our talented team to help us realize this ambitious vision. Join us.

Manu Sharma and Brian Rieger

Co-founders at Labelbox