Additionally, refinement is a key focus of ours. Figuring out the best data points to retrain the model upon has twin benefits:

1) It provides automated issue resolution and saves data scientists' effort to debug and fix their models. 2) It allows us to reduce false positives in alerting: we send alerts only when we see a dip in model performance, or retraining can lead to improved model accuracy.