RecOpsKit

RecOpsKit is a web app (with optional Slack alerts) that helps small-to-mid product teams run recommendation systems like a production service, not a science project. It plugs into your existing recommender (or simple “related items” logic) and continuously monitors key failure modes: sudden distribution shifts, runaway popularity bias, broken candidate generation, latency spikes, and metric regressions after deploys. It provides automated canary testing, segment-level dashboards (new users, long-tail items, regions), and one-click rollback suggestions based on pre-set thresholds. The honest truth: most teams don’t need a fancier model—they need reliability, observability, and a repeatable release process. RecOpsKit focuses on operational discipline: alerting, experiment hygiene, and post-mortems, with lightweight integrations so you can adopt it without rewriting your stack. It’s an AI app + traditional app combination: AI helps detect anomalies and suggest likely root causes, but the core value is operational tooling.