London-Based Encord Raises €50 Million To Support Next Phase Of Physical AI Deployment

The round was led by Wellington Management, bringing Encord’s total funding to €93 million ($110 million). Existing investors Y Combinator, CRV, N47, Crane Venture Partners and Harpoon Ventures joined the round, alongside new backers Bright Pixel Capital and Isomer Capital.

Founded in 2021, Encord provides a universal data layer for AI, enabling teams to manage, curate, annotate, and align data across the entire AI lifecycle. The platform supports more than 300 AI teams, including Woven by Toyota, Zipline, AXA, and Skydio.

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The new funding will help Encord scale its AI-native data infrastructure, designed to handle the multimodal datasets physical AI systems rely on such as audio, video, images, sensor data, and 3D point clouds formats that traditional platforms often struggle to process.

The Series C comes as physical AI powering robots, autonomous vehicles, and drones shifts from pilot programmes to real-world production.

Analysts estimate more than 400 million AI-powered robots could come online within four years, with the physical AI market surpassing €25 billion ($30 billion) over the same period.

Unlike large language models trained on open internet data physical AI systems depend on proprietary datasets, including sensor feeds, field-captured edge cases and robotic telemetry. Processing this complex data requires significantly greater computational resources than text-based AI models.

“Everyone is focused on building bigger models ” says Ulrik Stig Hansen, co-founder and co-CEO of Encord. “But for physical AI, the bottleneck isn’t model size. It’s data readiness. You can have the most sophisticated model in the world, and it will still fail if the data feeding it is incomplete, inconsistent or misaligned with real-world conditions. That’s the problem we solve.”

Eric Landau, co-founder and co-CEO of Encord, said the funding will accelerate product development and expansion into new markets. “The companies winning in physical AI understand something that others are just beginning to realize: the model is only as good as the data behind it. We’re building the infrastructure that makes that data usable – not just once, but continuously, as these systems learn and improve in the real world.”

About Encord

Encord provides an AI-native, universal data layer that enables over 300 teams to train and run models using the right data. Its platform indexes, curates, annotates, and evaluates datasets across the full AI lifecycle, from development to production, and is trusted by leading enterprises worldwide.