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
Start in chat free, with no account. When the answer matters, put it to GPT, Claude, Gemini and Grok — they debate it, a Final QA audit reviews it, and you get one clear verdict with the open questions named.
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