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Encord raises $60M in Series C to scale physical AI data. 27 February 2026 Key Takeaways * Encord raised $60 million in a Series C round led by Wellington Management. * Data volume on Encord's platform expanded from 1 to over 5 petabytes in 12 months. * Encord supports more than 300 AI teams globally, including robotics and autonomous vehicle developers. Encord, an AI startup based in San Francisco, has closed a Series C funding round of $60 million led by Wellington Management, and is now looking to expedite the further development and deployment of its AI data platform. Encord is the latest startup to benefit from the venture capital boom in data infrastructure for the physical AI market. This Series C round adds to the $50 million in funding Encord secured in 2020 and brings its total funding to approximately $110 million. Encord is now positioned to further develop and deploy its AI data platform for robotics, autonomous vehicles, drones, and all other forms of AI. The AI startup is primarily focused on developing a data platform designed for the emerging generation of AI. Encord utilizes its platform to assist other companies in managing and processing large and intricate datasets of a variety of formats that have traditionally been very challenging for data systems to process. The datasets required for the training of physical AI models, such as audio, video, 2D and 3D imagery, and other sensor feeds, and data point clouds, are considered multimodal because of their complexity. Encord is also looking to expand its data processing capabilities and infrastructure to new markets as a result of this round of funding. This round also saw the participation of all of Encord's existing investors, including Y Combinator, CRV, N47, and Harpoon Ventures, as well as the new investors Bright Pixel Capital and Isomer Capital. Why the physical AI market matters. After numerous years of development, initial testing, and field studies, physical AI technology, which allows machines to understand and interact with the everyday world, will begin to mature commercially. We are starting to see the commercial rollout of delivery drones, robots, self-driving cars, and systems for automating industry. Analysts believe an AI market of over $30 billion will be created in the next 4 years, with 400 million intelligent robots expected to be operational by then. In contrast to the market for large language models, which rely on the internet for training data, physical AI models use a world of data and often require the development of sophisticated paradigms to help collect, organize, and vet the data, and then create a training data set. This data collection process is challenging, and is the goal of Encord's platform. Growth and adoption. In the past year, Encord has seen significant growth in both the volume of data on its platform and revenue from physical AI customers. According to the company, the amount of data stored has increased from around 1 petabyte to more than 5 petabytes, a volume that exceeds even some of the largest training datasets used in other major AI training workflows. At the same time, revenue from its customer base has reportedly grown more than tenfold. Encord now supports more than 300 AI teams worldwide, including organizations developing autonomous vehicles, delivery drones, robotics systems, and advanced automation tools. Its customers include industry players like Woven by Toyota, Zipline, Skydio, and AXA Financial, among others. Encord's new funding will support their plans to expand the range of products offered and improve the performance of their platform, as well as continue increasing their international presence. Given the growing prevalence of physical AI systems, the company's commitment to data readiness, or ensuring that AI models are trained with high-quality, robust data, will become even more important. I'm a crypto writer with 4+ years of experience passionate about turning big, technical ideas into content anyone can understand. From blockchain to stablecoins to everything in between, I enjoy helping readers stay informed in a space that never stops moving. Disclaimer VentureBurn is a media platform covering the latest in cryptocurrency, artificial intelligence, venture capital, and the startup ecosystem. Opinions expressed on VentureBurn are for informational purposes only and do not constitute investment advice. Before making any high-risk investments in digital assets or emerging technologies, readers should conduct their own due diligence. All transactions and financial decisions are made at your own risk, and any losses incurred are solely your responsibility. VentureBurn does not endorse or recommend the buying or selling of any digital assets and is not a licensed investment advisor. Please note that VentureBurn may participate in affiliate marketing programs.

Encord raises $60 million in Series C to develop native data infrastructure for AI, as physical AI reaches an inflection point. Feb 27, 2026, 10:52 ET The round led by Wellington Management brings Encord's total funding to $110 million, with the company seeing its revenue in the physical AI field multiplied by 10 over the past twelve months. SAN FRANCISCO, February 27, 2026 /PRNewswire/ - Encord, the data infrastructure company for physical AI, announced today 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 also participated in this round, along with new investors Bright Pixel Capital and Isomer Capital. This investment will help Encord develop its native data infrastructure platform for AI, which assists AI teams in managing, storing, annotating, and aligning multimodal data that physical AI systems rely on, including audio, video, images, sensor data, 3D point clouds, and other formats that traditional data platforms are not designed to handle. Encord works with over 300 AI teams worldwide, including Woven by Toyota, Skydio, AXA Financial, and many leading physical AI labs. Over the past twelve months, the company has recorded significant growth in its revenue and data volume on its platform due to the rise of physical AI. The Inflection Point of Physical AI Encord's Series C comes as physical AI, which powers robots, autonomous vehicles, drones, and other systems operating in the real world, enters a new phase of explosive growth. After years of lab demonstrations and pilot programs, these systems are going into production. Analysts predict that over 400 million AI robots will be deployed in just the next four years, and the physical AI industry will represent over $30 billion during the same period. Unlike large language models, which have been trained on the open internet, physical AI models must learn from proprietary data, including sensor feeds, video, robotic telemetry, field-captured scenarios, and other sources. Storing and processing this data requires greater computational power than storing and processing text. This data does not organize itself. Integrating the right data into models and excluding incorrect data, continuously and at scale, requires a native data infrastructure for AI specifically designed for this purpose. "Everyone is focused on building bigger models," said Ulrik Stig Hansen, co-founder and co-CEO of Encord. "But for physical AI, the bottleneck is not model size. It's data availability. You can have the most sophisticated model in the world; it will still fail if the data feeding it is incomplete, inconsistent, or misaligned with real-world conditions. That's the problem we're helping to solve." Encord has seen demand skyrocket as physical AI moves from experimentation to deployment: * Data on the company's platform increased from 1 petabyte to over 5 petabytes in twelve months, three times more than the data used to train GPT-4. * Revenue from clients in the physical AI sector multiplied by 10 during the same period. Encord's physical AI platform enables leading companies and AI teams to capture, organize, and redeploy data throughout the model lifecycle. From supporting data generation in pre-training phases to aligning models based on human feedback, Encord's software is designed to handle all automation and data processing tasks that physical AI companies may face. Bill Tinney, Senior Director of Product Management and AI Partnerships at Vantor, an Encord client, said: "At Vantor, we develop AI for critical infrastructure and national security. We needed a data platform that matched our ambitions. Encord provides us with a unified data layer that adapts to the complexity of our geospatial workflows, from storage to evaluation to annotation, without tool fragmentation. For production AI teams, how you make your data operational is a key competitive advantage." Eric Landau, co-founder and co-CEO of Encord, said the funding will accelerate product development and expansion into new markets. "Companies winning in physical AI understand one thing that others are only beginning to realize: the value of a model is measured by the quality of the data feeding it. We are building the infrastructure that makes this data usable, not just once, but continuously, as these systems learn and improve in the real world." About Encord Encord is the universal data layer for AI. The platform helps AI teams train and run their models with the right data, managing, storing, annotating, and aligning data throughout the AI lifecycle. Encord works with over 300 leading AI teams, including Woven by Toyota, AXA, and Skydio. Press Relations: Chris Clemens Nexios Communications Strategies [email protected]