San Francisco-based AI platform Scale announced Tuesday that it raised $155 million in a Series D round led by Tiger Global. The latest round places the unicorn’s valuation at more than $3.5 billion, according to the company.
As part of the raise the company announced its acquisition of Helia, another SF-based AI company. Helia’s software is used to help companies run AI models on video streams in real time. The company’s three-person team previously worked on the development of Tesla’s autopilot system.
“Scale’s mission — to accelerate the development of AI applications — is an exceptional fit with Helia’s ML infrastructure tech and expertise. I’m so proud of team Helia for what we’ve accomplished in such a short time,” Russell Kaplan, co-founder and CEO of Helia wrote on Twitter.
The additional capital will enable Scale to accelerate hiring and expand to new markets. The company is now hiring for dozens of open roles across multiple departments at its San Francisco headquarters.
Scale’s API solution collects raw data from developers and churns out training data that’s ready for building production-grade AI algorithms. From autonomous driving to consumer technology, the Scale platform is used to build AI algorithms in a variety of industries.
“The potential applications of AI are going to deeply improve the world: scalable medical diagnosis to everyone in the world, massive reduction in driving accidents, goods which are dramatically cheaper to manufacture and transport, and much more,” Scale CEO Alexandr Wang said in a statement.
After dropping out of the Massachusetts Institute of Technology and landing a role at Quora as their engineering lead, Wang eventually left to start Scale in 2016.
“We started by building a platform that solves the necessary, foundational layer that fuels all machine learning models: large annotated data sets,” Wang said.
While many businesses are adopting AI they are oftentimes forced to build their technology stack from scratch, which significantly slows progress, according to Wang. Scale’s platform aims to solve that problem.
Scale’s combo of machine learning and human intelligence is used to annotate tens of millions of data points per week, according to the company. The company’s customers include DoorDash, Pinterest, Airbnb, OpenAI, Toyota and General Motors.
“We’ve continued to see demand for our platform to grow. We are still very early in the journey of AI and we remain optimistic about all the future dreams we will support,” Wang said.
The company currently has its sights set on building additional tools to help manage the full life cycle of AI development across enterprise teams. In August, the company launched a new data visualization tool, Nucleus. The new tool offers development teams a central hub to view and organize their data sets, test and compare models, and share data with their peers.
Scale has additional offices in Austin and Washington, D.C.
