FiftyOne Agentic Labeling
Turn natural-language prompts into annotated datasets using vision-language models. Preview outputs, refine your prompts, and scale to your full dataset — no code required.
Auto-labeling
Auto-label proprietary data without training a custom model
FiftyOne Agentic Labeling uses state-of-the-art VLMs to generate labels for both common and domain-specific concepts using natural language prompts.
Review results with built-in quality assurance workflows, correct only the predictions that need attention, and build high-quality datasets without the upfront investment of training a custom labeling model.
Author a Labeling Agent
Describe what you want labeled in natural language. Add positive and negative visual examples to sharpen the agent's understanding.
Preview generated labels
The VLM generates outputs on a handful of samples. Refine prompts until labels match your annotation guidelines.
Label the full dataset
Run the reusable agent on connected compute, returning a labeled baseline across your entire dataset.
80% faster labeling without sacrificing quality
VLMs can generalize to new categories with little or no task-specific data.
FiftyOne's VLM-based Agentic Labeling outperforms SigLIP on malaria cell classification with 95% vs. 49% accuracy across 100 samples.
Smart Data Selection
Make every annotation dollar count with FiftyOne Annotation
One in three teams (36%) say that most of their annotated data never makes it into production.
Agentic Labeling is part of FiftyOne Annotation, which helps teams identify high-value samples for labeling, ensuring labeling dollars are spent where they'll have the greatest impact.
Inside FiftyOne Annotation
Drive high-throughput, high-quality annotation
Annotation project management with configurable review workflows
Build multi-stage annotation pipelines that give you full visibility and control over how work moves from labeling to review to approval, with configurable review stages, rejection loops, and quality gates.
Track and optimize annotator productivity with real-time performance metrics
Track labeling velocity, throughput, and quality across projects and annotators. Spot bottlenecks and keep production on track in real time.
Get started with Agentic Labeling
Bring your own data and start labeling in minutes. Author a labeling agent in natural language, preview results, and scale a high-quality baseline across your full dataset, no custom model required.
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