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A plagiarism checker that shows its working

We compare your text with pages across the web and with every document already in your workspace, then highlight each copied passage next to the source it came from. No black-box score: you see the words.

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Your documents are only ever compared within your own workspace.

How our checker works

Our own matching engine does the work, from fingerprints to highlighted passages. A plain web search only tells it where to look.

  1. Step 1

    Fingerprint

    Your text is broken into overlapping five-word runs. Each run gets a short hash, and a winnowing step keeps a small, evenly spread set of them as the document's fingerprint.

  2. Step 2

    Compare

    We search the web for your most distinctive sentences and look up your fingerprint in your workspace library. Every shared fingerprint is checked word by word and stretched to the full matching passage.

  3. Step 3

    Report

    Matches are highlighted in the color of their source, with a side-by-side view. The similarity score counts each copied word once, so overlapping sources never inflate it.

What it catches

Built for the kinds of copying that actually turn up in essays, articles and client work.

  • Copy and paste

    Passages lifted word for word, even when the quote marks, dashes, capitals or spacing were changed on the way.

  • Light edits

    Copied text with a word swapped here and there, a sentence dropped, or paragraphs moved around. Swaps show up as near-identical passages.

  • Reused submissions

    Work handed in before, by the same writer or a classmate. Every document you check joins your workspace library and is compared with the next.

What it won’t catch: translation, or text so thoroughly rewritten, by a person or an AI tool, that no sentence still follows its source. For machine-written text, run the AI detector on the same document.

A sample report

Produced by our engine from a short essay and three sources: two web pages and one earlier submission. Hover a highlight to see its source, or pick a source to compare the passages side by side.

Why cities run hot

Words checked
263
Matched
133 words, 23 paraphrased
Sources
2 web · 1 library

Matched text

  • Identical
  • Near-identical
  • Paraphrased
Anyone who has walked from a shaded park onto an open parking lot in July knows that a city does not warm evenly. The difference can be felt through the soles of your shoes, and it shapes who stays comfortable during a heat wave and who does not. Asphalt and concrete absorb most of the sunlight that strikes them and release that energy slowly after dark, which is why dense neighborhoods can stay several degrees warmer than the surrounding farmland long after sunset. (identical match with source 1, How pavement turns cities into ovens) Rooftops, idling engines and air conditioners add their own waste heat to the streets below. On calm, clear nights the effect is at its strongest, since there is no wind to stir cooler countryside air into the streets. (paraphrased match with source 1, How pavement turns cities into ovens, 83% similar) Trees are the cheapest defense we have. A mature street tree can reduce the surface temperature of the pavement under it by more than ten degrees, partly through shade and partly by releasing water vapour through its leaves. (near-identical match with source 3, What one street tree is worth in August) Even so, many low-income blocks have only a handful of trees. As the city's own heat plan admits, "the neighborhoods with the least shade are the ones where residents are least able to pay for cooling." Planting is only half the job; young trees need watering for several summers before they can survive a dry spell on their own. Cool roofs are a second option. Painting a dark roof white or pale grey reflects sunlight back into the sky before it can be absorbed, and studies of warehouse districts have found that the effect is noticeable at street level on the hottest afternoons. (identical match with source 2, Cooling the city (submitted last term))

Hover or focus a highlight to see its source. Select it to compare the passages side by side.

Side by side

Source 1 of 3

Compare with source 1: How pavement turns cities into ovens

Webmetroclimate.example

Share of your text
22%
Matched
58 words
Passages
2
  1. Passage 1 of 2Identical · 35 words
    Your text

    … The difference can be felt through the soles of your shoes, and it shapes who stays comfortable during a heat wave and who does not. Asphalt and concrete absorb most of the sunlight that strikes them and release that energy slowly after dark, which is why dense neighborhoods can stay several degrees warmer than the surrounding farmland long after sunset. Rooftops, idling engines and air conditioners add their own waste heat to the streets below. On calm, clear nights the effect is at its …

    Source · metroclimate.example

    … lot at noon and you will feel the heat rising off the ground. That warmth was stored during the morning and it does not disappear when the sun goes down. Asphalt and concrete absorb most of the sunlight that strikes them and release that energy slowly after dark, which is why dense neighborhoods can stay several degrees warmer than the surrounding farmland long after sunset. Scientists call this the urban heat island effect. The effect is strongest on calm, clear nights, when there is no wind to mix cooler air in from the

  2. Passage 2 of 2Paraphrased · 83% similar · 23 words
    Your text

    … the surrounding farmland long after sunset. Rooftops, idling engines and air conditioners add their own waste heat to the streets below. On calm, clear nights the effect is at its strongest, since there is no wind to stir cooler countryside air into the streets. Trees are the cheapest defense we have. A mature street tree can reduce the surface temperature of the pavement under it by more than ten …

    Source · metroclimate.example

    … why dense neighborhoods can stay several degrees warmer than the surrounding farmland long after sunset. Scientists call this the urban heat island effect. The effect is strongest on calm, clear nights, when there is no wind to mix cooler air in from the countryside. The city's heat plan puts the stakes plainly: the neighborhoods with the least shade are the ones where residents are least able to pay for cooling.

Paraphrased sentences make the same point in other words, so they are compared whole rather than word by word.

Private by design

Checking a document shouldn’t mean handing it to a database you can’t see into. Here is exactly what happens to your text.

  • Your library stays yours

    Documents are compared only with other documents in the same workspace. They are never matched against another customer's files, and no one outside your workspace sees your text.

  • Web pages are fetched to compare, nothing more

    We search for a handful of your sentences, download the pages that come back and compare them on our own servers. Your full document is never sent to a search engine.

  • A polite crawler

    Our fetcher identifies itself, follows robots.txt, skips anything that isn't a public web page and keeps a copy for a day so the same page isn't downloaded again and again.

  • Delete it and it's gone

    Deleting a document removes it from your library along with its fingerprints, so it can't turn up as a match in any later check.

Questions about plagiarism checks

Straight answers on how matching works and what happens to your documents.

No. Fingerprinting, matching, scoring and highlighting all run on our own engine. We use an ordinary web search API only to find pages worth comparing, then fetch those pages and compare them ourselves.

A run of at least 8 words that also appears in a source, ignoring capitals, punctuation and quote styles. If a word or two was swapped, added or dropped inside the run, it is shown as near-identical instead of identical. A sentence that says what a source sentence says in other words is shown as paraphrased.

No. Text inside quotation marks and a reference list at the end of the document are left out of matching by default, along with stock boilerplate such as licence notices. The report tells you how many words were left out.

It is the share of your words that match any source. When several sources contain the same passage, those words count once, toward the source that matches the most text, so the per-source figures add up to the total.

Public web pages found by searching for your most distinctive sentences, pages we have fetched for earlier checks, and every document already in your workspace. Paywalled journals and books are not included.

Yes, sentence by sentence. A sentence that makes the same point as a source sentence in other words is flagged as paraphrased and counts toward the score. Translations, and rewrites that change the structure as well as the wording, can still slip through. Use the AI detector on the same document to check for machine-written text.

2 credits per word, charged when the check starts. If a check fails, the credits go straight back to your workspace.

Usually between 10 and 60 seconds, depending on length and how many web pages need fetching. You can leave the page; the report will be waiting in the document's Plagiarism tab.

Check the next draft before it’s handed in

Run AI detection and a plagiarism check on the same document, and keep every report in one place.

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