FiftyOne Annotation
FiftyOne is the multimodal data annotation platform that automates the annotation process with intelligent QA and active learning to deliver high quality labels.
Automated QA & Review
Maximize label quality with automated annotation QA
Intelligent Review uses embeddings, model predictions, and auto-label comparison to surface annotation errors at scale. Spot systematic labeling mistakes across entire batches, review the highest-risk labels first, and resolve quality issues in bulk.
Agentic Auto-Labeling
Speed up the annotation process with Agentic Labeling
Agentic Labeling, powered by VLMs, speeds up data labeling by 80% without sacrificing quality.
Describe what you need in natural language, review agent outputs and zero-shot labels, and refine your prompts until the labels align with your annotation guidelines. Labels can then be propagated across similar objects in the dataset. Then save that configuration and reuse it across projects. No code required.
Agents handle the repetitive volume while your team focuses on review and edge cases.
Smart Data Selection
Make every annotation dollar count with active learning
Not all data is equally valuable. According to the State of Physical AI report, one in three teams (36%) say that most of their annotated data never makes it into production.
Smart Data Selection helps teams identify the samples most likely to improve model performance, reducing wasted labeling effort and ensuring budgets are spent where they'll have the greatest impact.
Select the right data before you label it
Use model-assisted tagging and pre-filtering to surface the most relevant samples upfront, so annotation teams spend time on data that actually improves models.
Find exactly what needs attention in seconds
Search and filter your dataset using natural language and intuitive filters to quickly isolate specific scenarios, edge cases, or labeling tasks without digging through raw data.
Focus on high-value, high-quality samples
Surface similar samples and outliers, remove blurry or low-quality data, and visualize class distribution to keep datasets balanced and production-ready.
Built for production
Drive high-throughput, high-quality annotation
Annotation project management with configurable review workflows
Design and manage multi-stage annotation pipelines that give you full control over how work moves from labeling to review to approval. Built-in project management review stages, rejection loops, and quality gates help you coordinate teams, enforce standards, and keep production datasets moving without operational friction.
Track and optimize annotator productivity with real-time performance metrics
Gain real-time visibility into your labeling velocity, throughput, and quality within FiftyOne Annotation's project management tools. Performance tracking breaks down metrics by sample, label, and individual annotator so you can pinpoint bottlenecks and deliver projects on time.
FiftyOne Annotation
Supported modalities in FiftyOne Annotation
FiftyOne supports multimodal data annotation with synchronized 2D and 3D annotation. Customize workflows to bridge annotation, data curation, and model evaluation in one unified platform.
Data labeling platform
Simplify procurement with enterprise-grade data annotation
Deploy anywhere
Get an end-to-end data flywheel that accelerates model performance
Smart data labeling
Manage annotation schema
Identify annotation errors
Manually correct labels
ML Research
Auto-labeling rivals human performance
The latest paper from our ML researchers, Auto-Labeling Data for Object Detection, benchmarks auto-labeling against human annotation. We reveal how foundation models can deliver labels at near-human accuracy, while reducing annotation costs by up to 100,000×.
Questions?
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