AI Detector — was this written by AI?
Drop the text in. Four rival AIs assess it independently and show you the actual evidence — where they agree, where they disagree, and how confident you should really be. No fake certainty scores.
A verdict (likely AI / likely human / mixed / genuinely inconclusive) with the specific tells, where the models disagree, and how much weight the assessment can honestly bear.
Signed off by an independent Final QA audit — with a “verify before you rely on this” list, never a black box.
Why this team
Authorship calls go wrong in two directions — the false accusation and the free pass — so the council is built to argue against itself. The Editor-in-Chief and the Copywriter read for voice the way professionals who handle thousands of drafts do: rhythm, register, the tics a human can’t help and a model can’t fake. The Data Skeptic interrogates the substance — citations that don’t resolve, examples with no lived texture. And the Devil’s Advocate exists to defend the text against the accusation, because fluent non-native writers and heavily edited prose are exactly who single-detector tools wrongly flag. Where they disagree, you see it — that disagreement is the honest confidence level.
Each seat runs on a different frontier model — GPT, Claude, Gemini, Grok — so it’s a genuine cross-model review, not one AI in costumes. How a run works →
What the debate sounds like
An illustrative excerpt — A lecturer suspects a submitted essay was AI-written; the student says English is their second language and they used a grammar tool — the difference matters for an academic-misconduct panel.
The giveaway is not any single sentence — it is the evenness. Every paragraph lands at the same length, every argument gets a tidy both-sides hedge, every transition is "moreover" or "furthermore". Real student prose has a heartbeat: it rushes where they care and limps where they don’t. This text has no pulse.
Everything you just described is also what a careful second-language writer produces after three passes through a grammar checker — the tool flattens the pulse for them. If we call this AI on rhythm alone, we indict every diligent ESL student in the cohort. Show me a tell that editing cannot explain, or the verdict must stay open.
Here is one: footnote four cites a 2019 paper by authors who have never co-published, in a journal whose volume numbering does not reach that issue. A grammar tool does not invent citations — generation does. That single fabricated source moves me more than every stylistic argument combined.
Questions
Why not just give a percentage score like other AI detectors?
Because the percentage is theatre. Detection is probabilistic, and single-detector scores routinely flag fluent non-native writers and heavily edited text as AI. Decidi gives you what a score hides: the actual evidence, quoted from the text, where four independent models agree and disagree, and an honest "inconclusive" when that is the truth. For a decision with consequences — a grade, a hire, a client dispute — the evidence is usable; a bare 87% is not.
Can this prove someone used AI?
No — and any tool that claims proof is overselling. The council can find strong evidence (fabricated citations are the classic), weigh it honestly, and tell you what would settle the question properly: earlier drafts, revision history, or a supervised writing sample. It is built to inform a fair decision, not to convict.
What should I paste in for the best assessment?
The full text, plus anything known about the author’s usual writing — an earlier essay, an email, a report. A known-genuine sample transforms the assessment: voice comparison is far more reliable than style analysis in isolation.
Your material is used only to run your review — never to train public models. Encrypted in transit and at rest. Security & privacy →
Want full control — pick your own minds, set the depth? Open the full council →