London-based Encord raises €50 million to support next phase of physical AI deployment

Encord, the data infrastructure company for physical AI, today announced a €50 million ($60 million) Series C in order to accelerate product development, expand into new markets, and scale its AI-native data infrastructure platform as physical AI systems move from pilot programmes into full production.

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

“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.”

Encord’s €50 million Series C comes amid sustained capital flows into Europe’s AI infrastructure and autonomy stack in 2025–26.

In France, Mistral AI secured €1.7 billion in Series C funding to advance model development and expand cloud infrastructure for enterprise deployment. In the UK, Nscale raised €958 million in Series B financing to grow its AI cloud and data centre footprint, while London-based Stanhope AI attracted €6.7 million in Seed funding to develop adaptive AI systems for robotics and defence applications. Meanwhile, Berlin’s Helsing closed a €600 million Series D to expand its AI-enabled defence software platform.

Combined, these rounds represent over €3 billion in disclosed funding, underlining the scale of investment directed towards AI models, compute infrastructure and physical-world applications.

Against this backdrop, Encord’s raise reflects continued investor focus on the data layer underpinning physical AI systems, complementing larger financing rounds targeting model development and compute capacity.

Bill Tinney, Senior Director of AI Product Management and Partnerships at Vantor, an Encord customer, adds, “At Vantor, we build AI for critical infrastructure and national security – we needed a data platform that could match our ambitions. Encord gives us a unified data layer that scales with the complexity of our geospatial workflows, from curation to annotation to evaluation, without tool fragmentation. For production AI teams, how you operationalize your data is a core competitive advantage.”

Founded in 2021, Encord is a universal data layer for AI. The platform helps AI teams train and run their models with the right data – managing, curating, annotating, and aligning data across the full AI lifecycle.

Encord works with over 300 AI teams, including Woven by Toyota, Zipline, AXA, and Skydio.

Today’s investment will help Encord scale its AI-native data infrastructure platform, which helps AI teams manage, curate, annotate, and align the multimodal data that physical AI systems depend on, including audio, video, images, sensor data, 3D point clouds and other formats that legacy data platforms have difficulty handling.

The company says that their Series C comes as physical AI – which powers robots, autonomous vehicles, drones, and other systems that operate in the real world – enters an new growth stage. After years of lab demos and pilot programmes, these systems are moving into production.

Analysts project that over 400 million AI robots will come online in just the next 4 years, and that the size of the physical AI industry will eclipse €25 billion ($30 billion) over the same time period.

Unlike LLMs, which were trained on the open internet, physical AI models must learn from proprietary data, including sensor feeds, video, robotic telemetry, edge cases captured in the field and other sources. Storing and processing this data requires more computational power than storing and processing text.

Encord has seen demand surge as physical AI moves from experimentation to deployment:

• Data on the company’s platform has grown from 1 petabyte to over 5 petabytes in twelve months – 3x more than the data used to train GPT-4
• Revenue from physical AI customers has grown 10x over the same period

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.”

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