The source never existed.
A plausible paper title, author, DOI, court case, or policy link can be fabricated while looking perfectly formatted.
Why AnswerCheck exists
The hardest errors are not obvious nonsense. They are polished answers, exact-looking numbers, and citations that seem real—until you check them.
The trust problem
Users describe the same exhausting pattern: the answer looks good enough, then a source does not exist, the model doubles down, and the time saved by AI disappears into checking everything again.
A plausible paper title, author, DOI, court case, or policy link can be fabricated while looking perfectly formatted.
The answer may exaggerate an association into causation, swap populations, or attach a real citation to the wrong conclusion.
Routes close, regulations change, prices move, guidance updates, and products evolve. Fluent answers can silently preserve old reality.
Ten summaries may all copy the same press release. Repetition creates visibility, not independent confirmation.
Our role
We do not ask you to stop using AI, and we do not replace your judgment with another unexplained score. Select the answer that matters; AnswerCheck isolates its claims, retrieves inspectable sources, and shows where the evidence supports, conflicts with, or cannot verify them.
See how that changes a real decision →ChatGPT was publicly launched in January 2020, and the Eiffel Tower is 450 meters tall.
claims conflictwith retrieved evidence
Date mismatchJAN 2020→NOV 30, 2022
Measurement mismatch450 M→≈ 330 M
How judgment stays yours
Broad prose becomes specific dates, numbers, citations, quotations, and causal claims that can actually be checked.
Evidence remains linked so you can inspect the institution, publication date, methodology, and original context yourself.
AnswerCheck explains scope mismatches, stale evidence, source conflicts, and missing context instead of hiding them behind certainty.
When the evidence is insufficient or mixed, the honest result is uncertainty—not a forced true-or-false label.
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