About
Enterprise data management tools and powerful project analytics to help you manage your way to better datasets.Multi-step QA, interactive feedback mechanisms and consensus ensure quality standards are maintained and empower you to build the best benchmark datasets for automation or external labeling teams.
This product is intended for
- Machine Learning Engineer
- Computer Vision Engineer
- Head of Machine Learning
- Director of Machine Learning
- Manager of Machine Learning
- Data Scientist
- Head of Data Science
- Data Governance Manager
- Product Data Manager
- Business Intelligence Developer
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Data & Project Management
Enterprise data management and powerful project analytics. Automate your way to better datasets.
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Validate and optimize your training datasets
Deliver more accurate annotations, ensure consistency, and boost model performance with quality control tools embedded into the annotation workflow. Multi-step QA, interactive feedback mechanisms and consensus ensure quality standards are maintained and empower you to build the best benchmark datasets for automation or external labeling teams.
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Consensus Scoring
Compare, remove inaccuracies, and consolidate annotation results from multiple labelers into new images or videos using our Python SDK.
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Manual QA
Cross-check the accuracy of your automated and hand-labeled data with built-in review and approval mechanisms and integrated issue threads.
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Make smarter, data-driven decisions
Discover insights faster and closely track project progress, team performance, validation efforts, and other key metrics with actionable analytics and reporting. Object and category analytics help you better understand your labeled data and inform improvements.
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