Debug your data.
Visualize and compare ground truth labels and model predictions.
Investigate where your model is working well and where it is failing.
Find failure and edge cases through confidence scores and embeddings.
leverage your models
Turn predictions into ground truth.
Get more training data faster by leveraging your model predictions. Use ML-powered tools to verify and correct your predictions.
Implement active learning pipelines.
Prioritize which data to label, manually or programmatically. Upload confidence scores and embeddings. Start with a small labeled dataset, and iteratively grow it to production level sizes.
Label images in no time.
Label objects and regions with a few clicks, assisted by our ML-powered technology. From robotics to microscopic data and from detection to segmentation labels, we've got you covered. Or fully outsource your labeling to us.
Integrate into existing workflows.
You are not building your perception pipeline from scratch.
Our API and Python
SDK enable a deep and seamless integration of our labeling technology into your existing ML pipelines
Powerful management tools
Collaborate with your team or onboard an external workforce. Our management tools make it easy to build and review large datasets together.