Cord B2B Case Studies & Customer Successes

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Cord's algorithmic data labeling & training data platform is designed to automate manual annotation for computer vision. The company's suite of powerful tools allows for seamless collaboration across roles and teams, from domain-expert annotators to project managers and machine learning engineers, enabling data scientists and researchers to algorithmically solve the problem of annotating training data for machine learning applications.

Case Studies

Showing 10 Cord Customer Success Stories

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Automotus achieves 20% higher mAP and 35% smaller datasets with Cord

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Hudl achieves 10x faster annotation and 40% faster review with Cord

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King's College London achieves 6.4x faster video annotation with Encord

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OnSiteIQ achieves 5x faster data throughput with Encord

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Tractable achieves scalable annotation quality control with Encord

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UiPath boosts dataset growth 10x and reaches near-99% model accuracy with Encord

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UVeye boosts annotation speed and streamlines vehicle inspection AI with Cord

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Viz.ai accelerates medical diagnosis and team collaboration with Encord

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Voxel scales annotation workflows and model development with Encord

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Yutori achieves 2-3x faster web task completion with lower inference costs with Cord

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