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Upload your manuscript
PDF, DOCX, and image-with-text supported. Upload main file, tables, and figures separately — the AI treats them as authoritative.
About us
Reviewer-facing feedback before journal submission
Review My Manuscript is an AI-assisted pre-submission review platform developed by Prof. Dr. Alp Özgün Börcek, a neurosurgery professor and active academic author. Free preview: see the most important issue with a suggested fix; every issue is in the full report.
Review my manuscript
From the founder
Prof. Dr. Alp Özgün Börcek
Professor of neurosurgery · active academic author
I have spent years writing papers and watching peer-review and editorial workflows up close. Clear, structured pre-submission feedback is still slow, expensive, or inaccessible for many researchers — yet much desk-reject and major-revision risk shows up early as methodology and reporting gaps.
That is why I built Review My Manuscript: not to replace a human reviewer or supervisor, but to give a literature- and checklist-grounded, actionable pre-review in minutes. The goal is not a publication guarantee — it is helping you see weak points before you submit.
By the numbers
540+
Journals indexed for fit suggestions
5–15 min
Average report turnaround
14 days
Refund window (digital-service exception applies)
Default
No general-purpose model training
Our mission
Most peer-review platforms either rewrite your manuscript or send you to a generic chat model. We do neither. Our pipeline runs a multi-agent reviewer-style analysis grounded in academic literature, statistical reporting checklists (CONSORT, STROBE, PRISMA), and a curated journal catalog — and returns a structured report you can act on before submitting.
We built it because pre-submission feedback is uneven, slow, and expensive in academia. A focused, transparent AI tool can flag obvious risks (methodology gaps, statistical reporting issues, journal-fit mismatch) in minutes — without replacing the human peer reviewer or your supervisor.
How it works
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Multi-agent AI pipeline
A core reviewer model plus specialist agents (editorial, statistical, visual, language) run against your manuscript with RAG-grounded literature and journal context.
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Reviewer-style report
You get a structured report: methodology risks, statistical issues, literature context, journal-fit suggestions, and an action plan — exportable as DOCX.
Transparency & data
Default principle: no general-purpose model training
Uploaded manuscripts are used only to generate your report. Where available, we enable "no training" options with third-party AI providers; any model-training use requires explicit consent.
Regulated payment partner
Our payment partner acts as Merchant of Record and handles billing, taxes, and refunds in accordance with applicable consumer law. A 14-day right of withdrawal applies where the law allows; see refund details in our terms.
Encrypted upload & storage
TLS-encrypted upload to Firebase Storage; signed URLs for AI processing; your manuscript stays confidential, is never shared with third parties, and is kept while your account is active.
Failed pipeline → automatic refund
If our pipeline fails to deliver a report, your order is automatically moved to 'refund pending' and we initiate the refund without a separate request.
Ready to see what a reviewer would say?
Free preview: see the most important issue with a suggested fix; every issue is in the full report.