- Surface and interactively explore IOU, PR curves, confusion matrices
- Identify image clusters contributing to model errors
- Quantify model accuracy improvements by class over training cycles
- Correlate accuracy improvements with labeling spend

Reduce hours of work to minutes. Cut time spent on data selection and curation.
Avoid wastages in labelling spends. Get more for the $s you spend.
Accelerate your path to model accuracy. Reduce the iterations and guess work.