Where is your AI exposed to confident-wrong?
Six quick questions about your product. There is no score to game. You get an honest map of which confident-wrong failure modes your product is most exposed to, and the one test that catches each. Answer from what you know today - "not sure" is a real answer, and it counts as exposure.
a RavnLab tool · pairs with the Confident-Wrong Checklist and the Plausible-Wrong Benchmark
how it works
Answer six, get your exposure map
Each question maps to one of the six ways AI ships an answer that reads right and is wrong. Answer honestly. Your map appears at the bottom and updates as you go - it names the failure modes you are exposed to and links each to the test that finds it.
the six questions
Answer from what you know today
your map ↓
Your exposure map
Answer the six questions above - your map appears here and updates as you go.
what to do with this
The map is not the eval - it points to it
- Every exposure above is a real failure mode with a 30-minute test in the checklist. Run those tests against your own product first.
- The one that matters most is the last: if your system cannot say "I am not sure" and route to a human, every other failure ships silently.
- When you want the real thing - adversarial, sourced cases scored the way our public benchmark is - that is the work we do.