Copyleaks scans text for AI-generated writing and plagiarism in a single report, with explainable AI Logic, 30+ language AI detection and integrations for Canvas, Moodle, Blackboard and other LMS platforms. Built for educators, publishers and enterprise compliance teams.
Used this tool? Rate it
Used this tool? Rate it
Copyleaks is a content integrity platform that answers two related questions about a piece of writing: was any of it produced by a generative model, and does any of it already exist somewhere else. Copyleaks positions itself as a content integrity and AI detection platform serving everyone from Fortune 500 companies to the world's top universities, and the product is built around the idea that those two questions belong in one workflow rather than two separate tools. Founded in 2015, the company began as a plagiarism detection service and expanded into AI detection and compliance tooling as large language models moved into everyday writing. That history matters when you evaluate it, because the plagiarism side rests on a database and matching techniques refined over roughly a decade, while the AI detection side rests on statistical classifiers that are much newer and, as this page discusses at length, considerably more contested.
The practical shape of the product is a scan and a report. You submit text through the web app, a browser extension, a Google Docs add-on, an API call or a learning management system, and you get back a document view with passages highlighted and a percentage attached. On the plagiarism side the report shows matched sources. On the AI side it shows which passages carry the statistical signature of machine generation. Text detection returns AI analysis and plagiarism matching in a single report, but image detection only judges AI presence and does not check for image plagiarism, so the unified report is a property of text scanning specifically.
Who it is for depends on which half you care about. Universities and schools use it as an academic integrity layer wired into their LMS. Publishers and marketing teams use it to check whether contributed copy is original and whether it reads as machine-written. Enterprises use it for intellectual property compliance, GenAI governance and verifying that AI training data is human-authored. Individuals use the free tier to check their own work before submitting it. The company reports coverage across more than 100 countries, over 500 enterprises and educational institutions, and more than 30 million scans each month, though those are self-reported figures rather than audited ones.
New accounts include a limited number of free credits, which is enough to run real documents through the product and judge the reports before paying. There is no perpetual free tier of meaningful volume for heavy use, so the free allowance is best understood as an evaluation mechanism.
Paid individual plans are subscriptions billed on a credit system. Personal runs $16.99 per month or $13.99 per month billed annually, and Pro runs $99.99 per month or $74.99 per month billed annually, with Pro adding 25 user seats, advanced detection filters, whole-site scanning via sitemap upload, cross-language plagiarism detection and an analytics dashboard. Billing runs on unified credits, where one credit covers up to 250 words or one image — so a 5,000-word paper consumes 20 credits, and a plan's headline credit count translates to roughly 250 times that many words. Enterprise and Education plans are custom-quoted; education pricing is based on the number of full-time students at the institution, and API access and LMS integration are only available through these tiers.
Three commercial terms deserve attention before you subscribe, because they are easy to miss and expensive to discover late. Plans do not stack, so switching overrides the current plan and forfeits remaining credits, and refunds are only considered within the first 10 days of a billing cycle and only if no credits were used. All plans renew automatically until cancelled. If you expect seasonal usage — a semester rather than a year — check whether monthly billing is actually available to you at checkout before committing to an annual term.
This section deserves more weight than the equivalent section for most tools, because AI detection accuracy is a question where the marketing claims and the independent evidence diverge sharply, and because the consequences of a wrong answer fall on individuals.
The accuracy figure is a vendor self-report. Copyleaks advertises over 99% accuracy, but the headline figure carries a footnote stating that the accuracy rating is based on internal testing of English language datasets, which makes it a vendor self-report rather than an independently audited result. That is not an accusation of bad faith — the footnote is on the page — but a 99% figure derived from a company's own English-language test set should not be read as a guarantee about your document in your language.
Non-English performance is materially weaker, by the vendor's own numbers. The vendor's own per-language table shows a gradient, with the AI-side figure falling from 99.20% in English to 95.63% in German and 93.08% in Portuguese. A roughly 7-point gap in Portuguese means substantially more missed detections than the headline number implies. Note also that AI detection covers 30+ languages while plagiarism detection covers 100+ languages, and the two numbers are not interchangeable.
Independent academic research contradicts the category's marketing. A peer-reviewed study by Weber-Wulff and colleagues, published in the International Journal for Educational Integrity, tested 14 detection tools and concluded that the available detection tools are neither accurate nor reliable and carry a bias towards classifying output as human-written. The same work found that content obfuscation techniques significantly degrade tool performance. One clarification is warranted here: Copyleaks appears in that paper only within its survey of prior studies, not among the 14 tools the authors themselves tested, so this is evidence about the category rather than a direct measurement of this product.
Be careful with the "Cornell study" framing. The claim that a Cornell University study named Copyleaks the most accurate detector circulates widely, but arXiv is a preprint platform operated by Cornell Tech, so publication there is not a Cornell University finding or endorsement. Preprints also have not necessarily passed peer review. Treat any detector's cited academic backing by checking who ran the study, on what test set, and whether it was reviewed.
False positives fall hardest on non-native English writers. In reporting by The Markup, seven detectors flagged writing by non-native English speakers as AI-generated 61% of the time, and on roughly 20% of papers that misjudgement was unanimous, while native speakers' writing almost never drew the same error. The mechanism is straightforward: detectors reward linguistic unpredictability, and writers working in a second language often produce the formal, low-variance prose their education rewarded. Any institution deploying detection without accounting for this is building a discriminatory process, whichever vendor it chooses.
User sentiment is poor and clusters on exactly this issue. Trustpilot shows a TrustScore of 2.6 out of 5 across 344 reviews, with 49% of them one-star and the company ranked 80th of 85 in its Software Vendor category. The dominant complaint is human-written work being scored as AI-generated, raised by reviewers who describe themselves as a retired Army veteran and as graduate students. A caveat on reading this: review platforms select for aggrieved users, and someone wrongly flagged has far more reason to post than someone whose scan confirmed what they expected. The score should be read as evidence about the shape of the failure mode, not as a measurement of overall accuracy.
The vendor's own position is more measured than its headline. In public replies the company concedes that highly formulaic human writing can occasionally mimic AI patterns and advises treating the AI score as a strong indicator with human judgement as the final call. That guidance is sound, and it is worth holding the marketing to it.
Known interference and operational constraints. Common writing aids can trigger flags, minimum text lengths mean short passages give unstable results, and scan configuration differences can produce different scores for the same document — reviewers repeatedly describe the same document scoring differently for a student and for their instructor, which the company attributes to differing scan configurations.
Copyleaks advertises over 99% accuracy with a 0.03% false positive rate, but that figure comes from internal testing on English datasets, as the footnote on its own site states. Independent peer-reviewed research on the category concluded that detection tools generally are neither accurate nor reliable. The honest answer is that it performs comparatively well among a class of tools whose fundamental reliability is contested, and that no current detector justifies treating its output as proof.
New accounts receive a limited allowance of free credits, enough to evaluate the product on real documents. Ongoing use requires a paid plan: Personal at $16.99 per month or $13.99 monthly billed annually, and Pro at $99.99 or $74.99 respectively.
For text, yes — both appear in a single report. For images, no: image scanning detects AI presence only and does not perform plagiarism comparison.
AI detection covers more than 30 languages; plagiarism detection covers more than 100. Published per-language accuracy is highest in English and falls measurably in other languages, so treat non-English results with extra caution.
Possibly. Copyleaks states directly that platforms like Grammarly use ChatGPT and other generative models for some functionality and that such output can be flagged as potential AI content. Basic spelling and grammar corrections are not supposed to trigger flags, but generative rewriting features may.
Yes, through native connectors for Canvas, Moodle, D2L Brightspace, Blackboard, Schoology, Edsby and Sakai. LMS integration is only available on Education and Enterprise plans, not individual subscriptions.
You can upgrade your plan or buy additional one-time credits. Be aware that plans do not stack — switching plans overrides the current one and forfeits any remaining credits — so upgrading mid-cycle can cost you unused allowance.
Open the report rather than the score and look at which passages were flagged and why AI Source Match points where it does. Gather evidence of your process — draft history, version control, notes. If you are being assessed on the result, ask which scan configuration was used, since the same document can score differently under different settings. Non-native English writers should know that research has documented a substantial bias against them across detectors generally, which is a legitimate point to raise.
The company states it holds PCI DSS, SOC 2, SOC 3 and GDPR credentials. Enterprise and education buyers can choose on-premises or private cloud hosting with regional storage options, which is the path to take if data residency is a requirement. Individual plans run on the standard hosted service.
Refunds are not guaranteed. The published policy grants them only if requested within the first 10 days of the billing cycle and only if no credits have been used, so evaluate with the free credits before subscribing rather than after.
