Encord

Encord provides an end-to-end data infrastructure platform for physical AI, enabling teams to manage, curate, annotate, and align multimodal data from sensors, video, text, and more. It supports production-grade annotation, data collection, and model alignment workflows, with customers including UiPath and others. The platform emphasizes in-field data collection, RLHF, and deployment-ready data pipelines.

Encord offers a unified platform that handles multimodal data across video, image, text, audio, LiDAR, and sensor data. It provides native annotation tools (video, LiDAR, audio, text, sensor fusion) with label lineage and quality controls, data curation with embedding-based search and model-in-the-loop curation, and data alignment features for RLHF, rubric-based evaluation, and pairwise comparisons. It supports data collection from facilities or fleets, enables model training-ready data from physical AI operations, and includes annotation services by vetted domain experts. The system is API/SDK-first, keeps data in the user’s cloud, and covers the full pipeline from collection to deployment feedback, including data services for production-grade AI.

Who it’s for: Enterprise AI teams working on physical AI applications ( robotics, autonomous vehicles, drones, industrial manufacturing, healthcare, defense, sports AI, etc.).

Customers: UiPath

Mention of 300+ AI teams using Encord; customer spotlights and enterprise adoption