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AI Detector for university students, from the first essay to the final dissertation chapter.

Pre-scan undergrad coursework, master's submissions, and dissertation chapters before Turnitin or your supervisor sees them. Sentence-level highlights show exactly which lines read AI, with perplexity and burstiness signals so you can fix the prose instead of guessing. Calibrated for international and ESL writers across UK, EU, Indian, Australian, and African universities. FERPA + GDPR aware, no training on student work. Free to try. No card.

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Institutional Pro at $13.99/mo FERPA + GDPR aware Dissertation chapter history
Who it is for

Built for university coursework and dissertations.

University writing covers a wider arc than college does. Freshers writing their first 1,500-word essay, master's students submitting term papers under tight deadlines, and PhD candidates drafting full chapters all need the same pre-submission scan, but for different reasons.

The university stack runs from undergraduate seminars to master's coursework to doctoral chapter drafts. Pre-scanning fits every layer because the institutional report at the end is the same Turnitin AI check, regardless of whether you are in year one or the third year of a PhD.

Undergraduate essays and seminar papers

Two to ten pages of structured argument across multiple modules. Free tier covers casual single-essay scans up to 5,000 characters. Pro at $19.99 a month, or $14.99 a month on yearly, unlocks 10,000 character pastes and unlimited scans for the weeks where you are submitting on rotation across three or four modules.

Master's coursework and term papers

Heavier reading load, denser citation requirements, and supervisors who already know what AI-shaped prose looks like. The sentence-level highlights matter here because master's writing rewards specificity and a single AI-rewritten paragraph can be the one your supervisor questions. The 90-day Pro history is the safety net.

PhD candidates and dissertation writers

Chapter drafts that get scanned chapter by chapter as they come together. The 10,000-character cap forces you to scan in sections, which matches how supervisors actually read drafts. PDF export keeps a defensible record of which version of each chapter was scanned and when, useful when an examiner asks about a draft you submitted three weeks ago.

Fits beside Turnitin and your LMS

A pre-Turnitin draft workflow that finishes before the deadline does.

TextSight is not a Turnitin replacement. Turnitin still dominates university integrity workflows worldwide. TextSight is the pre-submission scan that runs while you edit, so you have sentence-level context before your supervisor's report decides anything.

Step 1: draft normally

Write in your usual editor: Word, Docs, Overleaf for LaTeX, or directly in Canvas or Blackboard. Using ChatGPT for an outline, a literature review brainstorm, or to break writer's block is the realistic 2026 default. Write the prose itself in your own voice from your own notes.

Step 2: paste and scan

Open app.textsight.ai, paste the final draft, and scan. Free tier handles 5,000 characters in one paste. Pro handles 10,000. For dissertation chapters past 10,000 characters, split by section and scan each in turn. The scan returns in about thirty seconds with an Authenticity Score and a sentence-by-sentence colour map.

Step 3: read the highlights and edit

Above 75, submit. Between 50 and 75, look at the red sentences and rewrite those specifically. Below 50, the section needs more substantial editing. The point is to fix the prose that is genuinely AI-shaped, not to game the score on prose you wrote yourself.

Step 4: re-scan and submit

One round of editing usually moves a borderline score by 15 to 25 points. Re-scan, confirm you are in the safe band, then submit to your LMS or hand the chapter to your supervisor. A typical undergrad essay round-trips in about six minutes; a master's chapter section in about fifteen.

Plans & pricing

Pricing for undergrads, master's, and PhDs.

Verified institutional emails get the .edu discount on Pro automatically at signup. Pro is $19.99 a month standard, $14.99 a month on yearly, and $13.99 a month with institutional verification. Full details on the pricing page.

Free
$0/forever

 

Sample a single essay or chapter section. No card, no email.
  • 3 scans / day
  • 5,000 chars per scan
  • Sentence-level highlights
  • 2 lifetime AI rewriter uses
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Starter
$7.49/month

Billed $89.88/year — Save $30

For a student writing one essay or section a week.
  • 20 scans / day
  • 20,000 AI rewriter words/mo
  • Chrome extension
  • Email support
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Business
$29.99/month

Billed $359.88/year — Save $120

For PhD cohorts, writing centres, and lab groups.
  • 100,000 AI rewriter words/mo
  • 5 team seats, shared history
  • Audit log, REST API
  • White-label PDFs
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.edu, .ac.uk, .ac.in, .edu.au, .edu.sg, .edu.ph, .edu.vn, and .ac.ke emails get Pro at $13.99/mo. The discount applies automatically at signup. View full pricing →

What you see in a scan

Sentence highlights, perplexity, burstiness, and paragraph-level scores.

A single percentage is not a fix path. The TextSight result panel shows which sentences reacted and why, with paragraph-level rollups for longer chapter sections, so you can edit the specific lines instead of rewriting the whole submission.

Sentence-level highlights

Every sentence is colour-coded by its own AI-likeness score. Red sentences clustered in one paragraph are a stronger signal than scattered yellows. Scattered yellows in otherwise structured prose often just mean you were taught to write formally. You read the pattern, not just the headline number.

Perplexity, read-only on Pro

Perplexity is how predictable your word choices are to a language model. Low perplexity reads AI-like. The score is shown per-sentence on Pro, which is the diagnostic context you need to decide whether a flag is real AI residue or just an unusually well-rehearsed literature review intro.

Burstiness, read-only on Pro

Burstiness is how much your sentence length and structure vary across the section. ChatGPT defaults to uniform medium-length sentences. Real human writing has bursty rhythm: one short sentence, one long, one fragment. Low burstiness across an entire chapter is the classic AI fingerprint and the one supervisors learn to spot first.

Paragraph-level scores for longer drafts

For dissertation chapters and master's papers, paragraph-level rollups identify which sections of a long draft drift AI-shaped and which stay clean. Useful when you have a 9,000-character chapter section and need to know which two paragraphs to revisit rather than rereading the whole thing.

Graduate-level workflows

Dissertation and thesis support, chapter by chapter.

Master's theses and PhD dissertations run far past the 10,000-character per-scan cap. The Pro workflow is to scan by section, archive each result, and treat the 90-day history as your draft audit trail before the examination board sees anything.

Scan chapter sections, not whole chapters

A typical PhD chapter runs 8,000 to 15,000 words. Pro caps each scan at about 1,600 words. Split a chapter into its natural sections, introduction, literature review, methodology, findings, discussion, conclusion, and scan each one in turn. The split matches how supervisors actually read drafts, so the granularity is useful, not punitive.

The 90-day history is your audit trail

Every scan is retrievable for 90 days on Pro. For a writer iterating across a six-month dissertation cycle, that means every clean chapter scan and every revision is on record. PDF export lets you save longer-term archives chapter by chapter. When an examiner asks about a draft from three weeks ago, you have receipts.

Supervisor handoff before viva

Pre-scanning each chapter section before handing a draft to your supervisor catches AI-shaped phrasing before it reaches the person who will sign off your work. The conversation shifts from "did you use AI" to "this paragraph reads AI-shaped, let us discuss the underlying argument", which is the conversation you actually want.

LaTeX and Overleaf workflows

Copy the rendered text into TextSight rather than the LaTeX source. The classifier reads the prose, not the markup, and citation commands or equation environments will throw off scores if pasted directly. The cleanest workflow is to compile, copy the body text from the rendered PDF or output, and scan that.

Fits with your LMS

LMS context: Canvas, Blackboard, Brightspace, and Moodle.

Native plugins are not shipped yet. Here is the honest 2026 picture of what works today and what is on the roadmap, so you can plan around it during your degree.

Today: copy-paste from your LMS

Draft inside Canvas, Blackboard, Brightspace, Moodle, or Google Classroom as you normally would. Before you click submit, copy the final text into TextSight at app.textsight.ai. Edit the flagged sentences in TextSight or back in your LMS, then submit the cleaned version. Round-trip is about six minutes for a typical undergrad essay.

Today: file upload on Pro

Drag a DOCX, PDF, or TXT into TextSight if you wrote in Word, Docs, or exported from Overleaf. Pro accepts files up to 10,000 characters per scan and returns the same sentence-level result the paste-in workflow does. Useful when formatting matters and you do not want to lose it in copy-paste.

Today: Chrome extension

One-click scan from any web page including LMS submission views. Useful when you want to scan an assignment description, a peer review, or a paragraph from your own draft without leaving the tab. Available on Starter and above.

Roadmap: native plugins

Canvas, Blackboard, Brightspace, Moodle, and Google Classroom plugins are on the 2026 roadmap. We are not promising dates while LMS plugin requirements keep changing each term. We would rather ship a working integration once than ship a thin wrapper that breaks every semester.

Calibration with policy, not auto-fail

Academic integrity: scores as conversation starters.

Treating any single number as proof that a student used AI is unfair and unreliable. The 2026 expectation across most universities is that detection is one input among several. The design here is built around that expectation, on both sides of the conversation.

Use the score as a signal, not a sentence

A low Authenticity Score means your submission reads more AI-like to the classifier. It does not by itself mean you used AI, and it does not by itself mean a supervisor will accuse you. False positives are real, particularly for ESL writers and for highly-structured academic prose where phrasing overlaps with AI defaults.

If you wrote it yourself and still got flagged

Run the scan and save the PDF report. The report stores the input text, the Authenticity Score, the sentence-level flags, the timestamp, and the classifier version. That is the format an integrity committee actually wants to see, and it gives you something specific to discuss instead of a vague denial.

If you used AI more than you remember

Be honest with yourself when the score is below 50 on prose you thought was mostly yours. ChatGPT-assisted drafting often creeps further into the final submission than students remember, especially across a long dissertation cycle. The fix is to rewrite those paragraphs in your own voice, not to rewrite them through another tool.

Auto-fail on a single percentage is bad policy

Several US and UK universities have lost lawsuits in 2025 for auto-failing students on a single detector percentage. Most institutions now require sentence-level evidence, a student conversation, and a review of earlier drafts before any sanction. The score is the start of that process, not the end.

Your draft stays yours

Privacy first: FERPA and GDPR aware by default.

Student submissions are protected by FERPA in the US, by GDPR in the EU and the UK, by the DPDP Act in India, and by local equivalents elsewhere. TextSight is designed to honour those rules out of the box, not as a paid setting you have to find.

No training on student work

Essays, chapters, and theses submitted for scanning are never used to train the classifier or any other model. This is a contract clause, not a configuration toggle. It applies on the free tier the same way it applies on Pro and Business.

No account required on free

The free tier needs no email, no account, no identity. For students worried about privacy or institutional disclosure, this matters. You can scan a draft chapter without TextSight ever knowing who you are or which university you attend.

Your university does not see your scans

Scan history is private to your account. We do not share scan data with universities, supervisors, examination boards, Turnitin, or any third party. Your scans are not part of any institutional record, and your supervisor or examiner cannot pull them.

Deletion on request

Any scan can be deleted from your history. On Pro you can delete individual records. Data retention is bound to your settings, and a standard DPA is available on Business and Enterprise tiers for university writing centres and graduate-school cohorts.

FAQ

University students frequently ask.

Does TextSight match what my university's Turnitin report shows?
Within 5 to 10 percentage points in our internal testing against 3,100 university student submissions covering undergraduate essays, master's coursework, and PhD chapter drafts. A TextSight Authenticity Score of 80 typically corresponds to a Turnitin AI percentage under 15. A TextSight score below 50 typically corresponds to Turnitin above 40. Use TextSight as the pre-submission pre-flight and treat your university's Turnitin report as the source of truth for the institutional record.
Can I scan a full dissertation or thesis on TextSight?
Pro caps each scan at 10,000 characters, about 1,600 words. A full dissertation or master's thesis must be scanned chapter by chapter or section by section. The 90-day Pro history keeps every chapter scan retrievable, so you can track which sections are clean and which still need attention before final submission to your supervisor or examination board. PDF export keeps a defensible record of which version of each chapter was scanned and when.
Does my university or supervisor see my TextSight scans?
No. TextSight scans are private to your account. The free tier does not require an email or any identity. Paid tier scan history is visible only to you. We do not share scan data with universities, supervisors, examination boards, Turnitin, or any third party. Your scans are not part of any institutional record and your supervisor cannot pull them.
What is the institutional email discount?
Students who sign up with a verified institutional email such as .edu, .ac.uk, .ac.in, .edu.au, .edu.sg, .edu.ph, .edu.vn, or .ac.ke get Pro at $13.99 a month instead of the standard $19.99. Pro includes unlimited scans, a 10,000 character cap per scan, 90-day scan history, file upload, and the integrated AI rewriter. The discount applies automatically at signup. If your university domain is not auto-recognised, contact support with your student ID for manual verification within 24 hours.
Does TextSight integrate with Canvas, Blackboard, Brightspace, or Moodle?
Native LMS plugins are not shipped yet. The honest workflow today is to draft in Word, Docs, or your university LMS editor, copy the final text into TextSight to scan, edit the flagged sentences, then paste the cleaned version back into your LMS for submission. Canvas, Blackboard, Brightspace, Moodle, and Google Classroom integrations are on the 2026 roadmap. A Chrome extension covers one-click scans from any submission view in the meantime.
What about false positives for international and ESL students?
False positives on non-native English writing are real and well-documented. Detectors over-flag structured English from non-native writers at several times the rate of native US writers. The TextSight classifier was tuned against essays from Indian, Filipino, Nigerian, Chinese, Vietnamese, and Kenyan student populations. False positive rates are roughly 40 percent lower than for US-only competitors. Scattered yellow flags in otherwise structured prose usually reflect formal English instruction, not actual AI use.
Will TextSight train its model on my dissertation chapters?
No. Text submitted for scanning is never used to train the classifier or any other model. This is a contract clause, not a configuration toggle. Data retention is bound to your history settings, deletion on request is supported, and our privacy practices are FERPA-aware in the US, GDPR-aware in the EU and UK, and aligned with local equivalents elsewhere. Dissertation drafts are treated identically to undergraduate essays.
What if my university auto-fails students on a single detector percentage?
Several US and UK universities have lost lawsuits in 2025 for auto-failing students on a single detector percentage. Most institutions now require sentence-level evidence, a student conversation, and a review of earlier drafts before any sanction. Even where formal policy is strict, the TextSight scan plus PDF report is the format an integrity committee actually wants to see. The score is a conversation starter, not a verdict.
Related

More for university students.

Pre-scan a chapter. Submit clean. Defend confidently.

Free to try. No card. Institutional Pro at $13.99/mo for verified .edu, .ac.uk, .ac.in, and .edu.au emails.

Start free, no card See pricing
FERPA + GDPR aware · No training on student work · Sentence-level highlights · Institutional Pro discount