Encord

Encord builds data infrastructure for teams training models on multimodal data — annotation, curation, and search across images, video, audio, 3D point clouds, and sensor streams. It was founded in 2020 by Eric Landau and Ulrik Stig Hansen, who run the company as co-chief executives, is headquartered in London with US operations, and came through Y Combinator.

The company's argument is that preparing training data is one workflow rather than several stitched-together tools, and that doing it well requires the platform to understand data semantically. That shows up in two load-bearing places: embedding-based retrieval, which is what makes petabyte-scale collections searchable by content rather than filename, and model-assisted annotation, where a model produces a first-pass label that a human then corrects. The product splits into Annotate for labelling, Active for curation and quality scoring, and Index for large-scale search, with data agents layered across them.

Encord's clearest strategic position is physical AI — robots, drones, and autonomous vehicles — where synchronised multi-sensor data is genuinely hard to handle and image-only tools do not extend. The company reported that physical-AI customer revenue grew tenfold in the twelve months to February 2026 and that data hosted on its platform rose from one petabyte to more than five over the same period. Named customers include Woven by Toyota, drone maker Skydio, geospatial-intelligence firm Vantor, and AXA Financial, across roughly 300 AI teams.

It raised a $60 million Series C led by Wellington Management in February 2026, bringing total funding to $110 million, with participation from Y Combinator, CRV, N47, Crane Venture Partners, Harpoon Ventures, Bright Pixel Capital, and Isomer Capital. Encord competes with Scale AI, Labelbox, and Roboflow, alongside open-source options such as CVAT and Label Studio.