DriftGuard

DriftGuard is a web app (with optional lightweight agent) that monitors supervised learning models in production and flags data drift, concept drift, and silent performance decay. It connects to common prediction logs and feature stores, then runs statistical drift tests and backtesting on delayed labels when available. The app focuses on practical alerts: which features shifted, which segments are affected, and what to do next (retrain, recalibrate thresholds, or roll back). It also generates simple, audit-friendly reports for stakeholders who don’t read dashboards. This is an AI app + traditional app combination: it uses supervised-learning evaluation and automated analysis, but the value is operational reliability and clear decisioning. Realistically, it won’t replace full MLOps suites; it wins by being smaller, faster to deploy, and priced for teams that can’t justify heavyweight platforms.