A single AI can confidently state false things. The fix isn't 'trust one model less'—it's run multiple. CouncilMind runs your claim through four frontier models, surfaces every dissent, and gives you a prioritized list of what to verify against primary sources.
The claim is broadly true. Standard sources support it.
True in spirit, but the specific number cited has been revised in the latest data—the order of magnitude is right, the precise figure is not.
Synthesis: claim is qualitatively correct; the specific figure should be sourced from the latest revision.
Different training data, correlated errors broken apart
When the claim survives four independent reads with the same conclusion, the verification cost drops sharply.
The most efficient verification workflow: pull primary sources only on the points where models disagreed.
Run the claim through a skeptic to find the strongest counter-evidence.
Disagreement-first verification
Headline, statistic, quotation, technical claim.
Each independently assesses with citations.
The dissent list is your prioritized verification queue.
Free tier. Premium models included.