Instantly check whether text was written by AI — ChatGPT, Claude, Gemini, GPT-5 and more — scored sentence by sentence. Free. No signup to start.
3 free checks a day · no signup · your text is never stored
Your text is processed to return a result and is never stored or used to train models.
We publish how the score is produced and its limits. Read the methodology →
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TextSight is a multi-model AI content detector. It learns the patterns each model family leaves behind, so it works across the current frontier of AI writing — not just one vendor.
Because the underlying signals are model-agnostic — predictability, sentence rhythm, lexical variety and structure — newer and unreleased models still produce a useful estimate. The detector is updated as the landscape changes.
No setup, no card. Paste your text into the AI detector and read the sentence-level breakdown in seconds.
Paste a paragraph or a full document up to 5,000 characters into the detector above. As an AI text detector, TextSight handles short snippets and full essays alike.
Multiple language signals — perplexity, burstiness, and stylometry — combine into one probability. Our AI content detection methodology runs five classifiers on every sentence, not just statistical guessing.
Get an AI probability score plus the human-likelihood complement, and judge the result for yourself. This AI detection tool covers all major language models and is updated as new models ship.
Not just a number — the signals and detail behind every verdict. Our AI content detector reads perplexity, burstiness, and stylometry, and shows why text is flagged, sentence by sentence.
See which passages drive the score instead of guessing from a single overall percentage.
One AI probability number from the AI content checker, with the human-likelihood complement, so the result is easy to read.
Text is processed to return your result, then discarded. Never stored, never used for training.
Recognizes patterns from ChatGPT, GPT-5, Claude, Gemini, DeepSeek, Grok and Llama — updated as new models ship.
We document how the score is produced and where it can fall short. Read it →
Tuned to keep human writing from being wrongly flagged — and we tell you when confidence is low.
AI writing is now everywhere — and for a lot of work, knowing whether a person actually wrote something still matters.
Generative AI can produce a fluent essay, article or report in seconds. That is genuinely useful, but it also means a polished piece of text no longer guarantees a human sat down and thought it through. For anyone who relies on the authorship of a document — a teacher grading an assignment, an editor approving a guest post, a recruiter reading a cover letter, a brand paying for original copy — that uncertainty has a real cost.
An AI content detector closes part of that gap. It does not replace judgment, and it cannot prove who wrote a sentence. What it does is give you a fast, evidence-backed second opinion: an AI-probability score, the specific sentences that look machine-written, and the signals behind the call. That is enough to know where to look more closely, start a fair conversation, or ask for a draft history — instead of guessing.
Used this way, detection protects the things people actually care about: academic fairness, editorial trust, original work that gets paid for, and writing that genuinely reflects the person who signed it. The goal is never to punish AI use — plenty of good writing is AI-assisted — but to keep authorship honest where it counts.
It is also a quick habit. A check takes seconds, runs free on this page, and gives you something concrete to point to — which is far better than a vague feeling that a piece "reads like AI." Whether you are reviewing one assignment or a queue of freelance submissions, a fast, repeatable check keeps your standards consistent and your review fair to everyone.
One number, many signals. Here is what the AI checker actually measures before it returns a result.
Human writing carries a particular unevenness. The pace shifts, sentence lengths vary, and word choices occasionally surprise. Large language models are trained to predict the most probable next word, which makes their output smoother and more statistically "average" than what people usually write. The detector measures that difference across several dimensions at once.
It reads perplexity — how predictable each word is given the words around it; burstiness — how much sentence length and rhythm vary across a passage; lexical variety — the range of vocabulary and how often certain favored AI phrasings appear; and structure — whether sentences cluster around the same few templates. Crucially, it does this sentence by sentence, not just once for the whole document, so a single AI paragraph buried in human writing still shows up.
Because no model family writes the same way, the detector is multi-model: it weighs patterns characteristic of ChatGPT, Claude, Gemini and the rest, then combines them into one probability rather than betting on a single classifier. The signals are model-agnostic, so a model released after today still produces a useful estimate. The full breakdown — every sentence, the likely source family and a downloadable report — is available in the app. See the published methodology →
Writing is rarely all-or-nothing. The detector places your text on a spectrum and tells you which of four states best fits — with the sentence-level evidence behind it.
High AI probability across most sentences — the text closely matches patterns produced by large language models.
Mostly AI with human touch-ups. Some sentences read as reworked, but the underlying draft looks machine-written.
Mostly human, with passages that look AI-assisted — common when a writer uses AI for part of a draft.
Low AI probability with the natural irregularity of human writing — varied rhythm and word choice throughout.
They answer different questions, and most teams use both — one checks originality, the other checks authorship.
Looks at how the text was written. It estimates whether a machine generated the wording, even when every sentence is original and appears nowhere else online.
Looks at where the text came from. It compares your writing against billions of published sources to find copied or closely matched passages.
A document can be 0% plagiarized yet fully AI-generated — original wording, no human author. That gap is exactly why an AI content detector matters alongside a plagiarism checker.
An honest look at where TextSight fits. We show the evidence behind every score and stay genuinely usable for free.
| Feature | TextSight | Typical free detector | Enterprise detector |
|---|---|---|---|
| Free, no signup to start | Yes | Often | No |
| Sentence-level highlighting | Yes | Paragraph only | Yes |
| Signals shown behind the score | Yes | Rarely | Sometimes |
| Multi-model coverage | Yes | Varies | Yes |
| Published methodology | Yes | No | Yes |
| Honest "not proof" framing | Yes | Rarely | Varies |
| Usable free word limit | Generous | Tight | Paywalled |
No detector is a lie detector. The right one shows its work — that is the bar TextSight holds itself to. See the 2026 AI detector comparison →
AI detection is probabilistic, not proof. On our internal benchmarks the detector performs strongly with a low false-positive rate, and it is most reliable on longer passages of unedited text written in English. We deliberately do not publish a single headline accuracy number, because the honest answer depends on the text in front of you.
Detection is hardest on three kinds of writing: very short passages, where there is not enough signal to score reliably; heavily edited or paraphrased text, where human revision blurs the patterns; and formal or non-native English writing, which can legitimately resemble AI. A widely cited 2023 Stanford study found that several popular detectors wrongly flagged more than half of essays written by non-native English speakers as AI-generated — a reminder that a score is a starting point, not a verdict.
That is why every TextSight result comes with a sentence-level breakdown and the signals behind it, and why we say plainly: use the detector to support a human decision, never as the sole basis for one. For grading, hiring or publishing, pair the score with drafts, version history and a conversation with the writer. Read our full methodology →
TextSight is a verification tool. It exists to help people check authorship and protect trust — not to defeat anyone's review.
We are deliberate about what this product is for. The AI content detector is built to support honest review: to give educators, editors, recruiters and content teams clear, explainable evidence they can act on, alongside their own judgment. Every result is framed as a probability with the reasoning attached, never as a guilty verdict, precisely so it is used fairly.
We do not position detection as a weapon, and we are equally clear that no detector should be the sole basis for a high-stakes decision about a person. When a score is borderline, the right next step is a human one — review the drafts, look at the version history, and talk to the writer. That is how authorship questions get resolved fairly, and it is the workflow this tool is designed to support.
A fast second opinion before you publish, grade or approve — with the sentence-level evidence to back up a fair, human-led call. Wherever authorship matters, an AI content check is a quick, low-effort safeguard.
Get sentence-level evidence from the AI checker to support a fair, human-led academic-integrity review.
Add an AI-content check to your editorial QA before content goes live. The AI content checker shows which sentences read as AI-generated, not just an overall score.
Check your own drafts with the AI detector before you publish, so you can confidently say your work is your own.
Verify supplier or freelance copy meets your originality standards before you pay. Whether you're auditing one essay or running bulk scans, our AI detection tool scales with you.
Free to try. No card. No signup for your first scans.