Encord, a San Francisco, CA-based provider of an AI data development platform for advanced vision and multimodal teams, has raised $60 million in a Series C funding round led by Wellington Management.
The round also saw participation from Y Combinator, CRV, N47, Crane Venture Partners, Harpoon Ventures, Bright Pixel Capital, and Isomer Capital.
The funding round increased the total to $110M.
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The company plans to use the funds to grow its AI data platform, which helps AI teams manage, organize, label, and align diverse data types, such as audio, video, images, sensor data, and 3D point clouds, that older systems cannot easily handle.
Encord works with more than 300 AI teams worldwide, including Woven by Toyota, Skydio, AXA Financial, and other leading AI labs. Over the past year, the company has grown quickly in both revenue and the amount of data on its platform, driven by rising demand for physical AI.
Encord’s Series C comes as physical AI—used in robots, self-driving cars, drones, and other real-world systems—enters a period of rapid growth. After years of testing and pilot programs, these systems are now moving into full production. Analysts expect more than 400 million AI robots to be deployed over the next four years, with the physical AI market projected to surpass $30B during that time.
Unlike large language models that are trained on public internet data, physical AI models rely on proprietary data such as sensor feeds, video, robot telemetry, and real-world edge cases. Managing this type of data requires much more computing power than handling text alone.
That data doesn’t organize itself. Making sure the right data goes into models—and the wrong data stays out—at scale requires AI-native data infrastructure built specifically for this purpose.
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 12 months—3x the amount used to train GPT-4.
Revenue from physical AI customers has grown 10x over the same period.
Encord’s physical AI platform helps AI teams collect, organize, and reuse data throughout the entire model lifecycle. From supporting data creation during pre-training to aligning models with human feedback, the platform is built to manage the data processing and automation tasks that physical AI companies face.
“Everyone is focused on building bigger models,” said Ulrik Stig Hansen, Co-Founder and Co-CEO of Encord. “But in physical AI, the real challenge isn’t model size—it’s having the right data. Even the most advanced model will fail if the data is incomplete, inconsistent, or doesn’t match real-world conditions. That’s the problem we solve.”
Bill Tinney, Senior Director of AI Product Management and Partnerships at Vantor, an Encord customer, said, “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.”
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
Founded by Ulrik Stig Hansen, Encord is a universal data platform for AI. It helps AI teams manage, organize, annotate, and align data throughout the AI lifecycle, enabling them to train and run models with the right data. Encord works with more than 300 AI teams, including Woven by Toyota, AXA, and Skydio.
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