FiftyOne Verified Auto Labeling
Annotation doesn’t have to slow you down — or blow your budget. Get AI into production more quickly with Verified Auto Labeling.
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×.
Automated Labeling
Reduce annotation costs with Verified Auto Labeling
Avoid the hidden costs associated with other auto-labeling tools.
Get auto-labeling with built-in QA
Verified Auto Labeling uses foundation models to automatically generate labels — and adds confidence scoring to prioritize the ones that require human review.
It streamlines your annotation workflow, cutting QA, and annotation costs while maintaining near-human accuracy.
Annotation Calculator
Estimate your savings with our auto-labeling calculator
Data curation for annotation
Label smarter
Optimize your annotation budget by ensuring each labeled data point maximizes model performance.
Label the right data, not just more data
Use FiftyOne to identify and prioritize the most valuable data points for annotation.
Identify annotation mistakes
Surface annotation errors by highlighting samples with high false positives, unexpected predictions, detection errors, or inconsistencies in labels.
