Anti-Cliché & Natural Humanizer
Humanize AI Text & Eliminate AI Clichés in Seconds
Transform robotic ChatGPT, Claude, and Gemini drafts into authentic, natural writing. Say goodbye to 'delve', 'tapestry', and unnatural phrasing without changing your original meaning.
- Humanize AI Prose Naturally
- Pattern-aligned for Turnitin, GPTZero, Copyleaks
- 250 Words Free
Your AI Draft
YOUR AI DRAFTHumanized Output
HUMANIZED OUTPUTHumanized Output Lands Here
Restructured sentences stay highlighted so you can review every change. Machine patterns eliminated while preserving all facts, citations, and terminology.
LINGUISTIC HEALTH & DETECTOR AUDIT
Updated automatically after each rewriteAI Cliché Rate⚡
0.1 / 1k words
↓ 98% clichés eliminated
Sentence Rhythm🎵
Dynamic Wave
High variation in sentence lengths
◄►
Lexical Diversity📚
Rich & Nuanced
Natural vocabulary distribution
Pattern CompatibilityAligned
Turnitin AIStructure Aligned
GPTZeroHigh Burstiness
CopyLeaksPatterns Cleared
The difference, in one paragraph
Detectors do not read meaning. They read rhythm.
Drag the divider. On the left is a stock ChatGPT paragraph with the vocabulary every classifier is trained on. On the right is the same argument, restructured.
Raw AI draft
In today's fast-paced world, it is important to delve into the rich tapestry of modern research methods. Furthermore, this pivotal shift underscores a profound transformation across the academic landscape, and it is crucial that institutions leverage these cutting-edge tools.
Cliché Density170.7 per 1,000 words
Burstiness2.50
Lexical Richness0.929
Raw AI Draft · Predictable formulaic phrasing
After Un-AI Text
Research methods have changed fast, and they deserve a closer look. The mix on offer now is wider than it was five years ago. That matters: it is quietly reshaping how academic work gets done, and universities that ignore the new tooling will feel it first.
Cliché Density0.0 per 1,000 words
Burstiness4.78
Lexical Richness0.870
Humanized Prose · Restructured for dynamic cadence
Classifier Coverage
Targeted against common classifier heuristics
Engineered to eliminate the predictable syntactic markers and formulaic phrasing targeted by major AI detectors.
What we measure
Three measures, computed from your own text
We do not run anyone else's classifier and we do not predict what one would say. These are the three things we compute, for the Draft and for the Rewrite, so you can see the movement.
Cliché Density
How many machine-typical phrases appear per thousand words — delve into, rich tapestry, it is important to note that. Reported with the specific phrases found, so you can check the count rather than take it.
Burstiness
How much sentence length varies across the passage. People write a twenty-eight-word sentence and then a four-word one; model output tends toward a uniform middle. This is the standard deviation of sentence length, in words.
Lexical Richness
How varied the vocabulary is, measured as the ratio of distinct words to total words over a fixed window, so a long passage is not penalised for repeating a subject's name.
How it works
Three steps, about forty seconds
Copy from ChatGPT, Claude or Gemini into the left pane. The engine reads what you paste as sentences rather than as markup, so paste the prose you want reworked rather than a whole document — and read the Highlights, which mark every sentence a Run changed.
The same paragraph, rewritten four ways
Generated on this page by the deterministic pre-pass the engine runs before it calls a model. Change the Mode and the output changes with it.
The same Draft
The survey ran across three semesters and covered nearly two thousand undergraduates, and the picture it returned was robust enough that the committee stopped arguing about whether the shift was real and started arguing about what to do. Students who delve into the reading still do it, but the draft they hand in now arrives with its argument already half-formed, and it is not clear when that started. Institutions can leverage this, but nobody has yet written down what a fair policy looks like, or who on campus should own it.
StandardPre-pass output
Splits sentences over 34 words · contractions
The survey ran across three semesters and covered nearly two thousand undergraduates. The picture it returned was strong enough that the committee stopped arguing about whether the shift was real and started arguing about what to do. Students who examine the reading still do it, but the draft they hand in now arrives with its argument already half-formed, and it's not clear when that started. Institutions can use this, but nobody has yet written down what a fair policy looks like, or who on campus should own it.
Pricing
Start free. Upgrade when the word cap gets in your way.
Free
Enough to check whether it actually works on your text.
$0forever
No card required.
- 250 words per run
- Standard mode
- Basic Detector Check
- Ad-supported
Pro Unlimited
For anyone submitting more than one thing a week.
$9.99/ mo
Billed monthly. Cancel any time.
- Up to 5,000 words per run
- All 4 specialized rewriting modes
- Citation & fact preservation pipeline
- No ads
- Fast processing
- DOCX export
Team / Agency
Shared seats and batch jobs for content teams.
$29.99/ mo
Billed monthly per workspace.
- 5 seats
- API access
- Bulk batch processing
- Everything in Pro Unlimited
7-day money-back guarantee Secured by Stripe · 256-bit SSLVISAMASTERCARDAPPLE PAYPAYPAL
FAQ
Questions people actually ask first
Will the Rewrite change what my argument actually says?
No. The engine works at the level of phrasing and sentence boundaries, not claims. Every sentence it touches stays highlighted in the output pane, so you can read the change and reject it if the meaning drifted. On every Mode, a sentence carrying a citation, footnote marker, figure or table reference, or block quote is not sent to the model at all and comes back exactly as you typed it — a property of the engine itself, not something Academic Mode adds. Detection is a set of patterns, though, so an unusual citation style can still be missed; the same highlighting is what lets you catch one that moved.
What does the Word Cap apply to?
It is a per-Run limit, not a daily one. Free accepts 250 words in a single Run and allows 20 Runs a month, so you can rewrite as many short passages as you like. Pro raises the Word Cap to 5,000 words per Run, so a full essay or long section goes through in one pass and keeps its structure across paragraph boundaries, and raises the Run Allowance to 500 a month.
Do you store the text I paste in?
It depends on whether you are signed in. Without an account, a Run is computed, returned and discarded — nothing is written down, which also means there is nothing to come back to later. Signed in, each Run is saved as a Draft in your account so you can find it again, and you can delete it. Either way, your text is not used to train anything and is not shared with any detection vendor. The privacy policy has the detail.
Which Mode should I pick?
Coursework and dissertations: Academic, which holds a formal register and keeps every changed sentence highlighted. Blog posts, newsletters and email: Casual. Anything where you want the strongest restructuring: Deep Rewrite, which varies sentence length hardest. If you are unsure, Standard is the safe default, and you can re-run in another Mode without re-pasting.
Is using this against my university's rules?
That depends entirely on your institution's policy, and reading it is your responsibility. Un-AI Text is built as a drafting and language-editing aid: it improves the phrasing of work you have already thought through. Submitting work you did not write as your own is academic misconduct wherever you study. If you are unsure whether a drafting aid is permitted on your course, ask your supervisor before you use one.