Use Cases

Computer Vision & Classification

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    Detection & Tracking

    • Product Identification

    • Damage and Defect Detection

    • Sports Analytics

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    Prediction & Planning

    • Autonomous Vehicles and ADAS

    • Autonomous Checkout

    • Physical Security

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    • Search and Ad Relevance

    • Topic Modeling

    • Policy Enforcement

How it works

Easy to Start, Optimize and Scale

Annotate all the vehicles, pedestrians and traffic lights in the video.

2 callback_url: '',
3 instruction: 'Annotate all the vehicles, pedestrians and traffic lights in the video.',
4 attachment_type: 'video',
5 attachment: '',
6 objects_to_annotate: ['person'],
7 },
8 (err, task) => {
9 // do something with task
10 }
Run Extraction
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    ML-Powered Data Labeling

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    Automated Quality Pipeline

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    Data Input Flexibility

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    Multi-Modal Annotation Support

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    Comprehensive Label Support

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    Infinitely Long Tasks

Quality Assurance

Best-In-Class Quality

Super Human Quality

Video tasks submitted to the platform are first pre-labeled by our proprietary ML models, then manually annotated and reviewed by highly trained workers depending on the ML model confidence scores. All tasks receive additional layers of both ML-based checks and human review.

The resulting accuracy is consistently higher than what a human or synthetic labeling approach can achieve independently.

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Get Started Today