Encord Raises $60M in Series C Funding for AI-Native Data Infrastructure

Insider Brief

  • Encord raised $60 million in a Series C round led by Wellington Management, bringing total funding to $110 million to expand its AI-native data infrastructure platform for production-scale AI systems.
  • The company said the funding will accelerate development of a universal data layer for managing, curating and aligning multimodal data used in robotics, autonomous vehicles and other physical AI deployments.
  • Encord reported managed data volume growing from one to five petabytes over the past year and tenfold revenue growth from physical AI customers, as demand rises for production-grade data infrastructure.

Encord has raised $60 million in a Series C round led by Wellington Management, bringing total funding to $110 million as the company expands its AI-native data infrastructure platform for production-scale artificial intelligence systems.

According to the company, the round included existing investors Y Combinator, CRV, N47 and Crane Venture Partners, along with new backers Bright Pixel and Isomer Capital. The funding will be used to accelerate development of what Encord describes as a universal data layer designed to manage, curate and align multimodal data for AI models operating in real-world environments.

The London- and San Francisco-based company said it is targeting a growing bottleneck in the AI industry: data infrastructure built for cloud applications rather than robotics, autonomous vehicles and other physical AI systems. While earlier generations of AI relied heavily on large text datasets, newer systems depend on vast streams of video, sensor and multimodal inputs that must be continuously organized, annotated and validated.

The company noted its platform focuses on three core functions: data curation to identify relevant training inputs; data management to index and trace datasets across storage systems; and annotation and alignment to ensure models are trained and evaluated against specific performance requirements. Encord indicated that legacy enterprise data tools often struggle when AI projects transition from prototype to commercial deployment.

Encord said demand is rising as AI systems move into industrial and robotics applications. Over the past year, the company reported its managed data volume increased from roughly one petabyte to more than five petabytes, while revenue from physical AI customers grew tenfold.

Customers include companies developing autonomous vehicles, drones and other next-generation AI systems, including Woven by Toyota, Skydio and Synthesia.

Image credit: Encord

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