Rewrite AI drafts so they read like a person wrote them. Detectors also flag plenty of human writing as machine-made. We fix that, too.
Paste an AI draft, see what a detector would flag, rewrite it in one click, and export a record of your own writing if anyone questions it.
Drop in an AI draft, or your own writing if a detector has already flagged it. A check reads 65 words or more.
You get a score from 0 to 100 and a plain verdict, so you know where the draft stands before anyone else runs a check on it.
One click rewrites every sentence, or take the suggestions one at a time and keep control of the wording.
Export a signed record of your drafting history. Your school can verify it without an account and without contacting us.
A real admissions paragraph, rewritten. Seven tells before, none after, and it still says the same thing.
Detectors score how predictable your writing is, not who wrote it. Four groups get flagged far more often than anyone else.
Second-language writers learn the textbook constructions detectors score as machine-made. Correct grammar reads as low perplexity.
For second-language writers →Formal register and precise, structured phrasing are common autistic writing styles. To a classifier they look like a language model.
Dictation, word prediction and grammar tools smooth text into even patterns. That evenness is exactly what a detector scores as machine-made.
Writers rebuilding language after TBI or stroke tend toward shorter, evenly paced sentences. Low burstiness, high false-positive risk.
These are the patterns detectors key on. Every one is named, found in your text and fixed by the rewrite.
A detector reads your draft one word at a time and scores how predictable each word was. Two numbers do most of the work, and neither one looks at who wrote the text.
In today’s rapidly evolving landscape, organisations must leverage innovative solutions.
The board met twice — March and June — and lost the minutes.
Same word count, same subject. The flat row is the one that scores as machine-made.
The measurement gives a number. Where the line falls between pass and flag is a threshold someone picked, which is why one paragraph clears one tool and fails the next.
Both numbers are averages taken across your sentences. Three sentences give almost nothing to average, so the reading moves a lot on very little evidence. Paste at least 65 words before you trust a score.
Nothing in the score checks whether your argument holds, whether your citations are real, or whether the grammar is correct. A wrong essay and a right one score the same if they are written the same way.
A detector sees the text in front of it and nothing else. It has no record of who typed it or how long it took, so an identical paragraph scores identically every time.
The two charts above illustrate what the measurements mean. They are drawn for the explanation, not read off your text.
Most advice about beating detectors is folklore passed around in group chats. Here is what moves the number, what leaves it exactly where it was, and what makes your situation worse.
Worth your time. Each of these changes the pattern a detector reads.
Put a five-word sentence next to a thirty-word one, then run the check again. Of everything on this list, this is where the number usually moves first.
A generated draft almost always restates the question before it answers anything. Delete that sentence and start on your actual claim.
Words like "Consequently" and "Importantly" at the head of a paragraph often connect nothing. Cut the word, read the paragraph again, and it makes the same point without it.
Generated drafts run three or four paragraphs of near identical length. Merge two, split one, and let a single sentence stand alone as its own paragraph.
Most drafts carry one sentence that restates the point made just before it. Deleting it lowers the score and shortens the draft at the same time.
A date, a course code, the real title of the book, what your supervisor said in week three. No model can predict a detail it was never given.
Widely repeated, and it leaves the score where it was.
Changing "utilize" to "use" fixes one word and leaves the rhythm, the structure and the paragraph shape exactly as they were. The number barely moves.
Spelling is not the pattern being scored, so the draft reads the same to a detector. The errors still cost you marks with the person grading it.
A round trip through another language swaps vocabulary and leaves sentence structure where it was. The grammar usually comes back worse than it went in.
Costs you something real, and still does not work.
"Honestly" and "at the end of the day" dropped into academic prose read as costume. The structure underneath is unchanged and the draft now sounds like two different writers.
Zero-width characters and white text do not survive submission, because portals strip formatting on paste. A grader who finds one stops reading your argument and starts questioning your honesty.
Change one thing at a time. Run a check, make a single edit, run it again, and see whether the number actually moved before you touch anything else.
Each row is a situation, the fastest thing to do in it, and what that costs. Find the one that matches the file you have open.
Check the whole draft first, so you know which sentences are flagged before you touch them. Rewrite those sections, then read the result before you submit it. If a sentence no longer says what you meant, put your own wording back.
Run the check yourself before the conversation starts, so you walk in knowing the score and the flagged sentences. If the flags land on sentence rhythm and stock phrasing rather than content, rewriting fixes them without changing what you said.
Generic usually means the sentences are interchangeable, not that the story is weak. Rewrite only the paragraphs that read as machine-made. Leave the lines carrying your own names, dates and details exactly as they are.
Paste the whole letter in one go, since a single paragraph often falls under the 65-word minimum for a check. After the rewrite, run the AI vocabulary checker for the words every other applicant is also using.
Sections written months apart often read like different writers. Check each one separately and compare the scores. Rewrite the section that sits furthest from the others instead of the whole chapter.
Rewrite the paragraphs that come back flagged, then put a real number or a named example where each hedge was. Check the reading level after the rewrite rather than before, since rewriting changes it.
A detector percentage is a reading of style, not evidence about who wrote the text. Paste a sample of the same student's older work, from before this course, and see what it scores. If the two scores look alike, the number is describing how that student writes.
Eight words that decide these arguments and almost never get explained to the person being accused. What each one means, and what it costs you when the text being scored is yours.
How surprised a language model is by the next word in a passage. Predictable wording scores low, unexpected wording scores high.
Textbook grammar, a memorized essay structure and careful second-language phrasing all read as predictable. A scorer reads predictable as machine-written.
The variation in sentence length and structure across a passage. Human drafts swing between short lines and long ones. Generated text holds a steadier rhythm.
Editing until every sentence runs about the same length lowers burstiness. Polishing your own work can raise your score.
Human writing that a detector reports as AI. The reverse error, generated text passing as human, is a false negative.
The two errors land on different people. A false negative costs the tool some accuracy. A false positive costs you a grade and leaves you proving you wrote your own paper.
How much AI writing is actually in the stack being checked, before any tool runs. An accuracy claim means little without it.
If most of a class writes its own work, most flags land on students who did too, even at a low error rate. Ask how many papers the tool expects to be AI, not how accurate it says it is.
The cutoff score where a tool stops saying human and starts saying AI. Whoever runs the tool picks where it sits.
The same paragraph passes under one threshold and fails under another. A score a point over the line is a setting someone chose, not a finding about your writing.
A number from 0 to 100 estimating how machine-like a writing pattern looks. The checker on this page returns that number with one of three verdicts: reads as AI-generated, borderline, or reads as human-written.
It describes the text and nothing else. No score can see who typed the words, so a high one is a reason to look closer, not a finding of fact.
The share of your text matching sources already in a plagiarism index. Similarity points to a document you can open and compare. An AI score points to a pattern with no document behind it.
A paper can return zero similarity and a high AI score at the same time. Neither number tells you anything about the other.
Evidence of where a document came from and how it was written. One form is a record of your drafting session, signed with ECDSA P-256, that a third party can verify on their own.
Every other term here produces an opinion about finished text. Provenance produces a record of how the text got made, which is what an accusation actually asks for.
An AI humanizer rewrites AI-generated text so it reads like a person wrote it. It changes the things AI detectors score: repetitive sentence rhythm, stock openers like "In today's rapidly evolving landscape", stacked hedges, and words such as delve, leverage and foster. Paste your text above and the rewrite happens in one click, free.
Yes. The AI checker, the AI detector score, the tell explanations, the free tools and the signed evidence export are free with no account. The one-click rewrite is free too, with a daily allowance.
Yes, that is what it is built for. On the sample above, the risk score drops from 80 out of 100 to 11 and all seven tells disappear. Nobody can promise a specific number on a specific detector, because detectors are retrained without notice and disagree with each other on the same paragraph. That is also why human writing gets flagged. Check your text before you submit it rather than after.
They measure how predictable your writing is to a language model. Generated text is unusually predictable: even sentence lengths, common word choices, low variation. Detectors score that pattern, not authorship. Run the checker above and you get the same kind of reading before anyone else runs one on you.
Because detectors score style, not authorship. Writing that is clear, formal and evenly paced looks machine-made to a classifier. Second-language writers, autistic writers and anyone using dictation or grammar tools get flagged most. A Stanford study found 61% of TOEFL essays by non-native speakers were falsely flagged across seven detectors.
It depends on the rules you are working under. Rewriting a draft you were allowed to generate is ordinary editing. Where AI is not permitted in submitted work, that rule covers the draft however it is edited. Read your institution's policy. If you wrote the text yourself and were flagged anyway, export a signed record of your drafting history.
No. Scoring and the tell explanations run in your browser and are never sent to GPTZero, Turnitin or any other detection service. Pressing Humanize or running the full AI check sends that text to our own servers to process it, and it is not stored or used for training.
Counted per network, so a phone and a laptop on the same wifi share the same 10. The count resets the next day.
Needs at least 65 words. You get a score from 0 to 100 and one of three readings: reads as AI-generated, borderline, or reads as human-written.
Needs at least 25 words. Ten credits covers about 500 words of rewriting.
Split anything longer and run it one section at a time.
Free and unlimited. They run in your browser.
The rewrite changes wording and sentence rhythm, so the sentences will not be the ones you typed. Facts, names, numbers and citations carry through, but read the output against your source before you submit. If a figure or a quote shifted, fix that line by hand.
Yes. Both tabs work in a phone browser, with no app to install and no login. Paste from your notes app and run the check there.
Below 65 words there is not enough text to read a pattern from, so any score would be noise. Paste the paragraphs around it and check the passage as a whole. The same goes for the rewrite below 25 words.
Yes. Grammar assistants even out sentence length and swap your phrasing for the most common version of it, which is the pattern detectors score. Run the check on the corrected draft rather than assuming a clean grammar pass reads as human.
Nothing here reports to a school, an instructor or a detection service. There is no account, no login, no card and no email, so there is nothing on file under your name. If you are working on a school laptop, that machine still keeps its own browser history.
Borderline sits between the two clear readings. Look at which tells are marked, then fix those yourself: vary sentence length, cut the stock opener, put your own example back in. Re-run and compare the two numbers.
As many times as your credits allow, at 1 credit per 50 words each pass. Each pass rewrites the output of the last one, so repeated runs drift further from what you meant. One pass plus your own edit usually reads better than three passes.
That depends on the policy you are writing under, and policies differ by course, not only by school. Check the syllabus or the assignment brief for a disclosure line, and ask your instructor in writing if there is not one. A written answer is worth having later.
Run the checker on the draft you already have, which needs 65 words. Read the tells it marks, fix the two or three worst ones yourself, then re-run. Export the signed drafting record last, so you have something to show if the submission is questioned.
Free AI checker and AI humanizer. No account, no card, no sign-up.