How to fact-check AI with another AI — the checker must not be the author
Asking a model to check its own answer barely works: it generated the mistake with the same process it would use to find it, so it usually defends rather than detects. The working method is independence — have a different model, trained by a different lab, review the claim. The checker must never be the author.
Decidi runs that method for you. Your answer goes in front of several independent frontier models — GPT, Claude, Gemini and Grok — that were not its author: they test the claims, argue out the points where they disagree, and a Data Skeptic and a QA Auditor persona press on the least-supported assertions. The verdict marks which claims held, which broke, and which need a primary source — and a Final QA audit checks that verdict itself before you see it. Cross-examination in one place, instead of you refereeing chat tabs.
- The checker is never the author — different models, different blind spots
- Each load-bearing claim tested, not the vibe of the answer
- Fabricated facts and citations exposed where independent models diverge
- A verdict that marks what held, what broke, and what needs a primary source
- A Final QA audit that checks the verdict itself before you act
- One structured cross-check instead of four tabs and a guess
Part of: Why a council beats one AI
A claim-by-claim read on your AI answer: what the models could confirm, where they contradicted it, and the specific points to verify against a real source.
Common questions
Can an AI fact-check itself?
Not reliably. The model produced the error with the same process it would use to detect it, and it has no independent source to compare against — so asked "are you sure?", it typically restates the answer with more confidence. Self-checking catches typos, not confident fabrications.
Why does a different model catch what the first one missed?
Because errors are mostly not shared. Models trained by different labs on different data rarely invent the same false fact, so a fabrication by one usually contradicts what another knows. Where independent models diverge, an error is likely hiding — that divergence is the detection signal.
How does Decidi run the cross-check?
You paste the answer (or the question), and several frontier models plus verification-minded personas — a Data Skeptic, a QA Auditor — test each claim and argue the disagreements out across rounds. The moderator’s verdict marks what held and what to verify, and a Final QA audit reviews that verdict before it reaches you.
Is cross-checking proof the answer is right?
No — it is a much stronger signal, not a guarantee. Agreement across independent models makes an error far less likely, and Decidi still flags what it cannot verify so you know exactly what to check against a primary source. Anything with legal, medical or financial consequence deserves that final human check.
Try it on your own decision
Put your question to a council of GPT, Claude, Gemini and Grok — they debate it, a Final QA audit reviews it, and you get one clear verdict. 1,500 free credits to start — no sign-up, no card required.
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