Encord lands fresh funding to scale physical AI data
Encord, a data infrastructure company positioning itself as a rival to Scale AI, has raised $60 million in a Series C round at a $550 million valuation. The company said the new capital will be used to expand its “physical AI” data infrastructure—tools and workflows designed to help teams build and manage training data for real-world systems such as robotics and drones.
Why physical AI is driving demand
Unlike many software-only AI applications, physical AI systems must interpret complex sensor inputs—often combining video, images, lidar, and other telemetry—then make decisions in dynamic environments. That shift is pushing companies to invest in high-throughput pipelines for data ingestion, labeling, quality control, and governance.
Encord said it has achieved 10x revenue growth, attributing momentum to a surge in enterprise adoption and the rapid expansion of training datasets. The company also noted that customer data volumes are climbing quickly, reaching roughly 5PB (petabytes) as organizations collect and store more real-world sensor data to improve model performance and safety.
Competitive landscape
The funding highlights intensifying competition among AI data tooling providers as model developers prioritize data quality and workflow efficiency. While Scale AI has long been a prominent player in data labeling and infrastructure, newer entrants like Encord are focusing on end-to-end platforms aimed at computer vision-heavy workloads and physical-world applications.
With the Series C, Encord plans to accelerate product development and expand its infrastructure to support larger datasets and more complex annotation needs, particularly for customers building AI systems that must operate reliably outside the lab.
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