The scalable annotation platform for videos.
Use CasesConfidently deploy highly accurate models to detect and track objects, predict and plan behavior, classify videos and more.
Locate and identify objects of various classes and track them frame by frame.
Product Identification
Damage and Defect Detection
Sports Analytics
Understand relationships between objects and predict behavior and intent.
Autonomous Vehicles and ADAS
Autonomous Checkout
Physical Security
Classify entire videos or events within videos with start and end timestamps.
Search and Ad Relevance
Topic Modeling
Policy Enforcement
How It WorksBuild models you can trust while maximizing operational efficiency and reducing the cost of ML projects.
Bounding Box
Classification
Polygon
Cuboid
"Annotate all the vehicles, pedestrians and traffic lights in the video."
client.createVideoannotationTask(
{
callback_url: 'http://www.example.com/callback',
instruction: 'Annotate all the vehicles, pedestrians and traffic lights in the video.',
attachment_type: 'video',
attachment: 'http://example.com/video.mp4',
objects_to_annotate: ['person'],
},
(err, task) => {
// do something with task
}
);
Receive large volumes of high-quality annotated videos via ML-powered pre-labeling and active tooling such as smart interpolation and superpixel segmentation as well as ML-based quality checks.
Have confidence in the quality of annotated data. Quality assurance systems built into the product rapidly monitor and prevent errors. ML model confidence scores trigger varying levels and types of human review.
Submit videos as a distinct data type or as a sequence of images for annotation. Native video annotation is best suited for user-generated content, sports footage or any video combined with audio.
Jointly represent data to understand relationships between different modalities. Scale Video supports integration with audio, voiceovers, transcripts, and text in a single task to link different types of data inputs.
Specify geometries for different classes (e.g. polygons for furniture, ellipses for plates). Combine geometries in a singular task and label for events (e.g. music playing) to enhance scene understanding.
Annotate hours-long videos to accurately track objects. Our advanced algorithms enable no limits on video length with tracking accuracy even for objects that leave the camera view for long periods of time.
Enterprise ReadyGet started today with on-demand, or chat with us about an enterprise plan.
Enterprise-grade SLAs include task completion times and tasks can be rapidly scaled up and down to meet your requirements.
Each enterprise customer is paired with a dedicated engagement manager who will ensure smooth on-boarding and continued data delivery.
Enterprise engagements provide upfront and volume-based discounts, and is the most cost-effective solution for high-quality labels. Plus with Scale AI, there are no platform fees.
Quality AssuranceIndustry leading quality datasets safe-guarded against ever-changing, messy data.
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.
CustomersScale Video is trusted by leading machine learning teams to develop more accurate models.
