Aquarium Learning

ML models are only as good as the datasets they're trained on, and that means that most improvement to model performance comes from improvement to the quality and diversity of their datasets. Our tooling makes it easy for ML teams to find anomalies + failure patterns in their datasets and fix these problems by editing / adding the right data. So the next time you retrain your model, it just gets better.