Correct answers
Every claim checked against your own policies and documents.
61%
overall quality
0/100
12,400 convos
✓ independently measured, every finding cited to your docs
Every claim checked against your own policies and documents.
61%
Does the reply actually address what the user asked?
78%
Is each claim supported by your real sources? Measured where retrieval is available.
54%
How often it confidently states something your documents contradict.
14%
The bot answering questions your knowledge base does not cover.
9%
Marked resolved, but the answer was wrong and the user quietly gave up.
112 found
85% deflected
61% verified correct
Counted as resolved
Silent failures surfaced
Nothing in the dashboard
Failure clusters, each cited
Every finding is cited to your own policy documents, so nothing reaches you without evidence. This is not about grading your vendor. It is shared ground truth you can both act on.
We score every
conversation for
hallucination.
accuracy.
relevance.
grounding.
hallucination.
drift.
Then you see exactly where your chatbot is losing accuracy, and how much it stands to gain. That is the difference between an assistant people quietly abandon and one they genuinely trust. Let's find out what is possible for your model.
See what's possible for your modelKnow what your AI is actually doing, measured independently and cited to your own documents. We'll show you one named failure pattern and its business impact to start.
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