# GPTRevealer

> AI text detector built for Czech and Slovak. Paste a text or upload a file to see the score, the sentences that read as generated and a colour map of the whole text — then rewrite it in one step.

We run the same service on these other domains: Čeština (https://detekcegpt.cz/), Slovenčina (https://detekciagpt.sk/), Deutsch (https://gpterkennung.de/), Deutsch (Österreich) (https://gpterkennung.at/).
The full text of every article is at https://gptrevealer.com/llms-full.txt.

## What is worth knowing

- The tool is built for Czech and Slovak and works out which of the two a text is on its own. For other languages some of the detectors have nothing to compare against, so the result is indicative only.
- The interface runs in Czech, Slovak, English and German, but the analysed text is still judged as Czech or Slovak.
- A text goes through seven detectors at once and each score is shown separately; they are never merged into a single number.
- The seven detectors measure different things: the deviation from the user's earlier texts, how closely the text follows the template of the chosen document type, phrases typical of AI, machine-like sentence rhythm, hidden characters, plus two separate models, OpenAI and ZeroGPT.
- The result is not just one number — it also includes a colour map of the text and a list of the specific sentences that look suspicious.
- Alongside the general score there is a deviation from the user's earlier texts; the baseline is built from up to the last fifty checks and starts working from six.
- Detection needs at least one hundred characters and a single text can hold at most two hundred thousand characters, which covers a whole thesis at once.
- Before detection you pick a document type — essay, academic paper, reflection, narrative, blog, post, review, e-mail, cover letter or report. Some of the detectors judge the text differently depending on it.
- Humanisation rewrites the whole submitted text so that the facts, the numbers and the tone stay unchanged.
- Texts are stored only in the account's history, they are not used to train a shared model, and the user can delete the entire history in one step.
- No AI text detector is one hundred per cent accurate — the result is evidence for a decision, not a verdict.
- Detection and humanisation both require signing in and the limits are counted per account, on requests and on characters: five checks, five humanisations and two hundred thousand characters per 30 days on the free plan, two hundred checks a day and four million characters per 30 days on Pro. Whichever runs out first applies.
- The service is operated by Ollcee s.r.o., Příčná 1892/4, 110 00 Prague 1, Czech Republic, company number 230 80 817, contact info@detekcegpt.cz.
- The terms of business and the privacy policy are on the site as plain text and can be downloaded as .txt; the translation is informative and the Czech wording prevails.

## Pages

- [Home page](https://gptrevealer.com/): What the tool does, how it differs from foreign detectors, pricing and frequently asked questions.
- [Help](https://gptrevealer.com/hint): Answers to the most common questions — the first check, reading the score, plans, privacy and data.
- [Detectors compared](https://gptrevealer.com/compare): An honest comparison of GPTZero, ZeroGPT, Copyleaks, Originality.ai and Turnitin — what each does, where it is better and where it stops.
- [Blog](https://gptrevealer.com/blog): Articles on detecting AI text in Czech and Slovak, on working with the results and on the rules at school and in editorial work.
- [Reviews](https://gptrevealer.com/review): Experiences of teachers, editors, copywriters and students.

## Articles

- [Why two detectors give a different number for the same text](https://gptrevealer.com/blog/why-two-detectors-give-different-numbers) (2026-09-14): Why scores differ between tools, what the disagreement says about the text and why averaging the numbers makes no sense.
- [Half yours, half AI: what a detector shows on mixed text](https://gptrevealer.com/blog/mixed-human-and-ai-text) (2026-09-07): How the score behaves on a text written together with a model, why it disappears in a long document and what to read instead of the overall number.
- [How to set an assignment a model cannot do for the student](https://gptrevealer.com/blog/ai-resistant-assignments) (2026-08-31): What makes an assignment resistant to a model — own data, concrete context, staged deliverables and a short defence.
- [Accused of writing with AI: what you can actually show](https://gptrevealer.com/blog/accused-of-using-ai-what-to-do) (2026-08-24): Which evidence holds up when an honestly written text comes out as machine-made, and how to talk about it with a school or an employer.
- [What an AI watermark is and why you cannot rely on it in a text](https://gptrevealer.com/blog/ai-watermark-in-text) (2026-08-17): What a model's hidden mark in a text looks like, which models add one today and why you cannot lean on it when judging a text.
- [How to choose an AI text detector: seven things worth comparing](https://gptrevealer.com/blog/how-to-choose-an-ai-text-detector) (2026-08-10): What to compare AI text detectors on — Czech and Slovak, sentences instead of a single number, handling false positives, history and how your data is treated.
- [Why AI text detectors do worse in Czech and Slovak than in English](https://gptrevealer.com/blog/ai-detection-in-czech-and-slovak) (2026-08-03): Czech and Slovak have free word order, rich inflection and smaller training corpora. What that does to detection and how to read the results.
- [What the percentage from a detector means and what to do with it](https://gptrevealer.com/blog/what-a-detector-score-means) (2026-07-27): A score of 0 to 100 is not the probability of cheating. How to read it, where the thresholds are and what to do with a result in the middle.
- [When your own text comes out as AI: what false positives are](https://gptrevealer.com/blog/false-positives-in-ai-detection) (2026-07-20): Why an honestly written text sometimes ends up with a high score, and how to resolve that situation without accusations.
- [Perplexity, burstiness and stylometry: three different routes to detection](https://gptrevealer.com/blog/perplexity-burstiness-stylometry) (2026-07-13): The three approaches AI text detectors are built on, how they differ and why they give different results on the same text.
- [Detection against your own hand: what a personal style baseline is](https://gptrevealer.com/blog/detection-against-your-own-hand) (2026-07-06): How comparing a text against your own older texts works and why it gives a different answer than a general detector.
- [Can a detector result be proof?](https://gptrevealer.com/blog/can-a-detector-result-be-proof) (2026-06-29): What a detector result can carry and what it cannot, how to handle it at school and in a newsroom, and what to do instead of accusing.
- [How to get through thirty term papers in a morning](https://gptrevealer.com/blog/checking-thirty-term-papers) (2026-06-22): A procedure for working through a whole batch of student papers without spending half an hour on each one.
- [Humanising a text vs. rewriting by hand: when each is worth it](https://gptrevealer.com/blog/humanisation-vs-rewriting-by-hand) (2026-06-15): The difference between rewriting a sentence automatically and rewriting it yourself, and how to use humanisation so the text does not end up worse.
- [Checking a master's thesis chapter by chapter](https://gptrevealer.com/blog/checking-a-masters-thesis-by-chapter) (2026-06-08): Why not to check a whole thesis at once, where false alarms pile up and when to schedule the check.
- [How to fit detection into an editorial process with freelancers](https://gptrevealer.com/blog/ai-detection-in-the-newsroom) (2026-06-01): Where an AI check belongs in an editorial workflow, how to communicate it to authors and what to do with the result.
- [AI content and SEO: what search engines actually object to](https://gptrevealer.com/blog/ai-content-and-seo) (2026-05-25): Search engines do not punish AI text as such. What really drags results down, and where detection is useful for content teams.
- [Cover letters written by AI: what to do about it in hiring](https://gptrevealer.com/blog/ai-written-cover-letters-in-hiring) (2026-05-18): Why cover letters are now almost useless as a filter, and how to adjust hiring instead of hunting for culprits.
- [How to spot AI text by eye: nine signs to watch for](https://gptrevealer.com/blog/spotting-ai-text-by-eye) (2026-05-11): The specific patterns that give generated text away even without a tool — and why none of them is enough on its own.
- [How much text a detector needs to make sense](https://gptrevealer.com/blog/how-much-text-a-detector-needs) (2026-05-04): Why short texts cannot be judged reliably, where a reasonable minimum lies and how to split a long text.
- [What happens to the text you put into a detector](https://gptrevealer.com/blog/privacy-and-ai-detectors) (2026-04-27): What to ask about any tool, where the text is stored in DetekceGPT and why this matters with other people's work.
- [Verification questions instead of accusations](https://gptrevealer.com/blog/verification-questions-instead-of-accusations) (2026-04-20): Why a conversation about the text works better than confronting someone with a number, and how to prepare the questions.
- [Why keep a history of checks and what you can read from it](https://gptrevealer.com/blog/why-keep-a-check-history) (2026-04-13): A one-off check says little. What several checks of the same author over time can tell you.
- [Checking PDF and DOCX without copying the text](https://gptrevealer.com/blog/checking-pdf-and-docx-files) (2026-04-06): Which formats can be uploaded, what to do with a scanned PDF and why checking the file beats checking an excerpt.
- [How to write school rules for using AI](https://gptrevealer.com/blog/school-rules-for-using-ai) (2026-03-30): What a rule needs to contain to work — concrete boundaries instead of a ban, and an agreed procedure when there is a suspicion.
- [Company rules for AI: what has to be written down first](https://gptrevealer.com/blog/company-rules-for-using-ai) (2026-03-23): What a company AI policy has to cover — where it is allowed, what must never be pasted into a chat and who is accountable for the output.
- [When not to run a detector: cases where the result settles nothing](https://gptrevealer.com/blog/when-not-to-use-ai-detection) (2026-03-16): Short texts, fixed wording, foreign languages and cases with no chance to ask the author — when a detector will not help and what to do instead.
- [Why texts by non-native writers score worse with detectors](https://gptrevealer.com/blog/ai-detection-and-non-native-writers) (2026-03-09): Why a simpler vocabulary and careful sentence structure push the score up, who it affects most and how to read such a result.
- [AI in academic writing: what publishers ask of authors](https://gptrevealer.com/blog/ai-in-academic-writing) (2026-03-02): Why a model cannot be a co-author, what belongs in an AI use statement and where the line usually sits for language editing.
- [How to check a text you commissioned from an outside writer](https://gptrevealer.com/blog/checking-text-from-a-freelance-writer) (2026-02-23): What to agree up front, what to read on delivery and how to raise a suspicion without wrecking the working relationship.
- [Why a translated text comes out as machine-made](https://gptrevealer.com/blog/translated-text-and-detectors) (2026-02-16): What translation does to a text — by hand or by machine — and why the score rises afterwards even when a human wrote the original.
- [Why a detector needs to know what kind of text it is reading](https://gptrevealer.com/blog/why-the-text-type-matters) (2026-02-09): What changes when you pick the text type before a check, why an e-mail has different limits than a term paper and what Type template measures.
- [Your first text check, step by step](https://gptrevealer.com/blog/your-first-ai-text-check) (2026-02-02): What to do on a first detection, in what order to read the result and what to avoid right at the start.
- [Is text from AI plagiarism? How it differs from copying](https://gptrevealer.com/blog/is-ai-text-plagiarism) (2026-01-26): Why generated text passes a similarity check, why it is still usually a breach of the rules and what academic codes tend to say about it.
- [Why the same text scores differently the second time](https://gptrevealer.com/blog/why-the-score-changes-between-runs) (2026-01-19): What causes the difference between two checks of the same text and how big a difference is still normal.
- [Is humanising a text cheating? Where the line runs](https://gptrevealer.com/blog/is-humanising-text-cheating) (2026-01-12): When rewriting is ordinary editorial work, when it is dodging the rules, and how to tell the two apart.
- [Can I use AI for my coursework? How to find out and how to do it](https://gptrevealer.com/blog/can-i-use-ai-for-my-coursework) (2026-01-05): Where the rules live, what is usually allowed, how to declare your use and what to avoid in an academic paper.

## Documents

The terms of business and the privacy policy are issued by the operator in Czech; this is an informative translation and in the event of any discrepancy the Czech wording prevails.

- [Terms of Business](https://gptrevealer.com/terms): The terms on which you may use detection, humanisation and the other tools — your account, payments, your content and where our liability ends.
- [Privacy Policy](https://gptrevealer.com/privacy): What personal data we process, why, how long we keep it, who we pass it to and what rights you have under the GDPR.