Encord announced a $60 million Series C led by Wellington Management, bringing the company’s total funding to $110 million. Existing investors Y Combinator, CRV, N47, Crane Venture Partners and Harpoon Ventures participated in the round alongside new investors Bright Pixel Capital and Isomer Capital.
The company said the investment will help scale its AI-native data infrastructure platform, which enables AI teams to manage, curate, annotate, and align multimodal data used by physical AI systems, including audio, video, images, sensor data and 3D point clouds. Encord works with more than 300 AI teams globally, including Woven by Toyota, Skydio, and AXA, and reported significant growth in revenue and data volume over the past twelve months amid increased adoption of physical AI.
The company said data hosted on its platform has grown from 1 petabyte to more than 5 petabytes in 12 months, which it noted is three times the amount used to train GPT-4. Revenue from physical AI customers increased 10x over the same period.
Encord said its Series C comes as physical AI, which powers robots, autonomous vehicles, and drones operating in real-world environments, moves from pilot programs into production deployments. Analysts project that more than 400 million AI-powered robots will come online over the next four years and that the physical AI industry will surpass $30 billion during that time. Unlike large language models trained on internet-scale text, physical AI systems rely on proprietary multimodal data captured from sensors, video feeds and robotic telemetry, requiring purpose-built infrastructure to ensure data quality and alignment throughout the model lifecycle.
The funding will support continued product development and expansion into new markets as Encord positions itself as the universal data layer for AI, helping teams manage data across pre-training, annotation, evaluation and model alignment.
The announcement was issued as a corrected release, noting revisions to the list of representative customers in the third paragraph and boilerplate.
KEY QUOTES:
“Everyone is focused on building bigger models. 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.”
Ulrik Stig Hansen, Co-Founder And Co-CEO Of Encord
“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.”
Eric Landau, Co-Founder And Co-CEO Of Encord
“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.”
Bill Tinney, Senior Director Of AI Product Management And Partnerships At Vantor
