Announcing our Series C with $110M in total funding. Read more →.

Deploy reliable AI models
faster with high-quality data

Encord is the data layer for AI teams. Transform large, multimodal datasets into high-quality, labeled data for training frontier AI models and improving model performance.

Trusted by pioneering AI Teams

Dyna Robotics
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Dyna Robotics
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Captions logo
Mirage logo
Synthesia logo
zipline
Woven by TOYOTA logo
Iterative Health Logo
Stanford Medicine logo
Flock safety logo
Voxel Logo
AXA logo
Philips logo
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Dyna Robotics
Logo1
Captions logo
Mirage logo
Synthesia logo
zipline
Woven by TOYOTA logo
Iterative Health Logo
Stanford Medicine logo
Flock safety logo
Voxel Logo
AXA logo
Philips logo
Logo13
Dyna Robotics
Logo1
Captions logo
Mirage logo
Synthesia logo
zipline
Woven by TOYOTA logo
Iterative Health Logo
Stanford Medicine logo
Flock safety logo
Voxel Logo
AXA logo
Philips logo
Logo13
Explore the product
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60% faster model deployment for Hudl

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30% more accurate annotations for Pickle Robot

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Why Encord?
"Our AI engineers spend more time on improving model performance and less on data management... with easy data curation, rich data segmentation and annotation, we can trust the Encord platform."
Ariana Eisenstein
Ariana Eisenstein
CTO, Pickle Robot
Interactive Product Tour

Manage, curate and annotate AI data

Faster Annotation Pipeline

Faster Annotation Pipeline

Build custom workflows to accurately label and review images, videos, audio, text, 3D scenes and DICOM data more quickly and accurately at scale.

Intelligent Data Curation

Intelligent Data Curation

Search, visualize and review multimodal data in one platform, with both local and cloud data sources. Filter and slice large datasets with metrics and custom metadata.

Deploy production AI faster

Build frontier AI applications with best-in-class data curation, labeling, and model evaluation tools.

Any questions?

Transform petabytes of unstructured multimodal data into high-quality data for training, fine-tuning, and aligning AI models at scale.