Sentinel AI monitors every prompt and model response in real time, aggregates weak signals into a unified risk score, and gives you a plain-English explanation for every flag — without black-box complexity.
Lightweight by default. No dashboards you don't need, no agents you can't audit.
Analyze both sides of every LLM exchange. Sentinel catches risky user prompts before they hit your model and unsafe responses before they reach your users.
Multiple weak signals — embedding drift, heuristic flags, policy checks — aggregate into one 0–1 risk score per exchange. No more stitching together separate tools.
Every flagged exchange gets a plain-English reason. Your team knows exactly why something was flagged, not just that it was. No black-box verdicts.
Track prompt embedding similarity over time. Detect when your user population starts asking questions that deviate from your training baseline.
Get notified instantly when risk scores cross configurable thresholds. Slack, webhook, or email — wired to your existing on-call workflow.
One pip install and two lines of code. Works alongside any LLM provider — OpenAI, Anthropic, open-source models. No architectural changes required.
pip install sentinelai-sdk. Available on PyPI. One import, one client initialization.
Pass your prompt and response to client.analyze(). That's it. No middleware, no proxies, no architectural changes to your existing stack.
Receive a risk score and explanation on every call. Route flagged exchanges to a human review queue, block responses, or fire an alert — your call.
No credit card required for free tier. Upgrade or cancel any time.
For individual developers validating the integration.
For engineering teams that have shipped LLMs to production.
Self-hosted or cloud, SLA, priority support, and compliance features.
Start monitoring in under 10 minutes. No model changes, no infrastructure work.