Encord Raises $60M Series C Funding to Scale Vision and Multimodal AI Data Development Platform
$60M just walked into the room, quiet as a drone at altitude. Not hype. Not noise. Capital with intent. Encord just secured a $60M Series C, pushing total funding to $110M, led by Wellington Management with Y Combinator, CRV, N47, Crane Venture Partners, Harpoon Ventures, Bright Pixel Capital, and Isomer Capital in the mix. That is not a cap table. That is a table where serious people sit down and decide what the next decade of AI infrastructure looks like.
Respect where it is due. Ulrik Stig Hansen and Eric Landau, Co-Founders and Co-CEOs, built this out of London with a San Francisco edge, and turned a sharp thesis into a 10x surge in physical AI revenue in 12 months. Over 300 AI teams now run through Encord’s rails. Woven by Toyota. Zipline. Skydio. AXA Financial. When robots, drones, and autonomous systems need their data clean, aligned, and battle ready, they call the cord that actually encords.
Physical AI is not a chatbot in a hoodie. It is steel, rotors, sensors, and consequence. When a drone misreads a frame, gravity wins. Encord built an AI native data infrastructure that indexes, curates, annotates, and validates multimodal data at scale so machines can see the world without hallucinating it. Images, video, unstructured chaos turned into signal. A unified data layer that does not just store information but sharpens it. The difference between a model that demos well and one that deploys in the wild often lives in the data. Encord lives there.
The lesson for founders paying attention is simple and ruthless. Pick the layer everyone else ignores. While the market obsessed over model releases, Ulrik Stig Hansen and Eric Landau went after the plumbing. They built for the teams in the arena, not the crowd in the comments. Enterprise grade security with SOC2, HIPAA, and GDPR compliance. A platform designed to plug into real workflows, not theory. That is how you earn Wellington Management’s conviction and keep your early believers doubling down.
And for enterprises still patching annotation tools together, consider the math. Physical AI is hitting an inflection point. Hardware is scaling. Models are improving. The bottleneck is data discipline. The teams that win will not just train models. They will engineer feedback loops where every frame makes the next deployment smarter.
Encord is not chasing the spotlight. It is wiring the stage so the spotlight works. Congratulations to Ulrik Stig Hansen, Eric Landau, and the entire Encord team. The infrastructure era of AI is here, and the companies building the backbone rarely make noise, but they tend to make history.
