Pipeline Drift Monitor

Pipeline Drift Monitor is a ml monitor that detects when data or predictions no longer match the training baseline for automated data and model workflow. It uses statistical tests, time windows, and alert thresholds so teams can respond before quality drops while keeping evidence, reliability, and public-safe operational boundaries clear.

“The machine learning team used Pipeline Drift Monitor when the pipeline missed a validation step, so the team could respond before quality drops before the model moved into evaluation.”