AI Checks
AI checks let you assert things that are hard to express as a status code or a keyword. You write what "correct" looks like in plain language, and on each run an AI model evaluates your page or API response against that description — passing or failing with a short explanation.
How it works
On each run the checker fetches your target (a rendered page or an API response), then asks an AI model to evaluate your natural-language assertion against the content. It returns a pass/fail verdict plus a rationale so you can see why it decided that.
This shines for checks that resist rigid rules:
- "The pricing page shows three plans and none of them say Coming soon."
- "The homepage headline is in English and mentions our product name."
- "The checkout confirmation includes an order number and a total in USD."
- "The API response returns a list of at least five products, each with a non-empty name and price."
Because a model call is heavier than a fetch, AI checks run on a moderate cadence (configurable). Keep assertions specific and observable so verdicts stay consistent.
What triggers an alert
- The AI evaluates the assertion as false for the current content.
- The target is unreachable or returns an error before evaluation.
- Optionally, low-confidence verdicts can be surfaced as warnings for you to review.
The rationale is attached to the incident so you can confirm the call quickly.
Setting it up
- Add monitor and choose AI Check.
- Enter the target URL (page or API endpoint).
- Write your assertion in plain language — be specific about what must be true.
- Set the check interval.
- Attach notifications.
Phrase assertions around things that are visibly true or false on the page. Vague or subjective prompts ("does it look good?") produce inconsistent verdicts — prefer concrete, checkable statements.
Related
- Health Checks · Uptime · Broken Links
- Notifications
- Marketing: AI checks feature