Encord

Encord is a multimodal data layer platform designed for physical AI systems. It provides tools for data annotation, curation, model alignment, and managed data services, supporting modalities like video, LiDAR, image, audio, text, and geospatial data. Encord helps teams build high-quality datasets through embedding-based curation, label QA, and lineage tracking, and it integrates into CI/CD pipelines via API and SDK. The platform serves industries such as autonomous vehicles, robotics, drones, and smart spaces, enabling end-to-end data workflows from collection to deployment.

Key Features

• Native multimodal annotation for video, LiDAR, audio, text, and sensor fusion.
• Embedding-based curation to find edge cases and reduce dataset size.
• Model alignment tools including RLHF, rubric-based evaluation, and pairwise comparison.
• API/SDK-first integration for automation and pipeline versioning.
• Managed data services for expert annotation and collection at scale.
• Enterprise-grade security with SOC 2, HIPAA, and GDPR compliance.

Use Cases

• Training world models and vision-language-action models for physical AI.
• Developing perception systems for autonomous vehicles and ADAS.
• Labeling multi-sensor data for robotics and humanoid manipulation.
• Building AI systems for drones, aerial inspections, and smart spaces.

Who It’s For

Encord is built for AI teams, machine learning engineers, data scientists, and domain specialists working on physical AI systems that require high-quality multimodal data pipelines.

Key Benefits

• Native multimodal support for video, LiDAR, audio, text, and more
• Embedding-based curation and label QA to ensure data quality
• API and SDK for pipeline automation and integration
• Integrated data services for managed collection and annotation