A.I. APPS // FREE TOOLS BY IMPART
Detect A.I. generated writing in seconds
Detect A.I. generated writing in seconds
Paste text to analyse sentence structure, predictability, repetition patterns, and linguistic markers commonly associated with A.I. generated writing.
CHARACTERS // 100 TO 5,000 PER RUN // PROBABILISTIC, NOT DEFINITIVE
TRY ONE //
Works best with prose paragraphs from 100 to 5,000 characters.
0 / 1000 words
Depth
Sensitivity
Content type
HOW IT WORKS
How it works
01
Paste your text
Drop in an essay, email, paragraph, or report. Anywhere from 100 to 5,000 characters per run.
02
Choose depth, sensitivity, and content type
Fast for a quick read, deep for a careful one. Conservative widens the band toward human, aggressive toward A.I. The content-type hint adjusts the rubric to suit academic, business, marketing, or general writing.
03
We score the text on six axes
Sentence predictability, repetition, burstiness, vocabulary variation, structural uniformity, and phrasing consistency. The model returns the breakdown and a short rationale.
04
Read the result with the disclaimer in mind
A.I. detection is probabilistic, not definitive. The result is a signal, not a verdict. Use it as one input among many.
EXAMPLES
Real text from real contexts.
ABOUT
Quick context.
How A.I. detection works
An A.I. detector reads a block of text and estimates the probability that the text was generated by a large language model. The estimate is grounded in measurable surface patterns: sentence-length variation, lexical repetition, structural rhythm. None of these patterns are unique to A.I. generated writing; they are statistically more common in it.
Sentence rhythm and burstiness
Human writing tends to vary sentence length: short punchy lines next to longer, more complex ones. A.I. generated writing tends to flatten that variation, producing a more uniform rhythm. The detector measures burstiness, which is the statistical name for that variation, as one of the six sub-scores.
Vocabulary variation and structural consistency
Two more signals: how often the writer reaches for unusual words, and how often the structure of one sentence resembles the next. A.I. generated writing tends to favour common words and parallel structures. These patterns are not proof, but they are signal.
What this analysis measures
Statistical surface patterns: sentence predictability, lexical repetition, length variation, vocabulary range, structural uniformity, and phrasing consistency. The model combines these into a probability score and a short rationale.
What this analysis cannot guarantee
A.I. detection is probabilistic, not definitive. The result is a signal, not a verdict. Careful human writing can score high; lightly edited A.I. writing can score low. Never use this score as the sole basis for a disciplinary or hiring decision. Pair it with manual review.
USE CASES
Where this earns its keep.
Editorial review
Run incoming submissions through the detector before a senior editor invests time in the piece.
Student work review
Triage essays for further conversation with the student, never as a sole judgement of authorship.
Hiring screening
Spot-check long-form responses on take-home tasks where the brief asked for original writing.
Content authenticity audit
Sample published copy across a site or campaign to estimate the share that reads as templated.
Internal documentation review
Sanity-check internal docs before publishing so the company voice does not drift toward generic templated prose.
Research integrity check
Pair the detector with manual review and source tracing on submissions where authorship matters.
FAQ
Frequently asked questions
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