Vendors retrain models without warning. Accuracy drops. Refusals spike. Costs creep up. This framework catches it automatically — before your users do.
Built for engineers who depend on third-party AI services and can't afford silent failures.
Continuously evaluates your AI APIs on a schedule. No manual checks. No surprises.
Tracks accuracy, refusal rate, latency, cost, and behavioral consistency simultaneously.
Uses Z-score anomaly detection, PELT change-point detection, PSI, and EWMA control charts.
Works with OpenAI, Anthropic, Google, or any LLM API. Compare providers side by side.
Webhooks fire the moment drift is detected. Pipe into Slack, PagerDuty, or any CI/CD system.
Runs entirely on your infrastructure. Your prompts and responses never leave your stack.
Create a structured dataset of test prompts across categories: math, code, safety, legal, and more.
Seed your first evaluation run. This becomes the reference point everything is compared against.
Run evaluations daily or weekly. The engine scores every response against the baseline automatically.
When the model changes, you'll know within hours — with severity, metric, and timestamp.
Open the dashboard and see what's happening right now.
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