AI Peer Review · Pre-Submission Manuscript Review

AI Peer Review for Scientific Manuscripts.

Get comprehensive, structured feedback on your manuscript in minutes — not months. Methodology, statistics, reporting compliance, references, and language quality, all in one review.

Review Your ManuscriptSee how it works →
The case for a second opinion

Pre-submission review that catches what you miss.

Submitting a manuscript without independent review is like performing surgery without imaging. You might get it right, but you're working blind to problems that are obvious to someone else.

PeerReviewAI surfaces those problems before you submit — methodological gaps, statistical issues, incomplete reporting, reference errors, and language weaknesses that trigger desk rejection or painful revisions.

Structured, comprehensive, delivered live as it generates. You watch the analysis unfold on screen, section by section.

Inside the review

What the review covers.

Seven evaluation dimensions, one structured pass — each with findings tied to the section they came from.
Scientific substance
01
Methodology & Study Design
Checks whether your design fits your research question, whether methods are detailed enough to replicate, and whether sources of bias are addressed.
02
Statistical Analysis
Reviews statistical methods, assumptions, and sample-size justification. Flags multiple-comparison issues and inappropriate test selection.
03
Reporting Guideline Compliance
Identifies your study type and checks the manuscript against the appropriate reporting guideline — CONSORT, STROBE, PRISMA, and 16 others.
04
Reference Verification
Cross-checks every citation against published records — flagging errors and discrepancies between what you cited and what was actually published.
Polish & presentation
05
Language & Clarity
Flags writing that may confuse reviewers — tone, precision, and readability issues across the manuscript.
06
Figures & Tables
Assesses whether figures and tables are appropriately referenced, clearly described, and consistent with the results reported in the text.
07
Ethics & Declarations
Checks for required ethics statements, conflict of interest declarations, data availability statements, and other journal-required disclosures.
Pick the depth that fits

Three review modes for different needs.

Pay per manuscript. No subscription. Go deeper when the manuscript matters more.
Essentials
Essentials
$2.99per manuscript

Structured critical appraisal with study detection, literature search, reference verification, and reporting-guideline compliance. Great for quick pre-submission checks and journal club prep. Try it free — one review with every new account.

Peer Review
Peer Review
$29per manuscript

Comprehensive pre-submission review — methodology, statistics, reporting compliance, references, and language. Detailed feedback on every section.

Author Review
Author Review
$79per manuscript

The deepest review, built for competitive journals. Everything in Peer Review plus a journal-specific compliance audit and tracked changes in a Word document — color-coded edits you can accept or reject.

Premium Journal Club · $19.99/mo

Evidence that finds you — not the other way around.

Every account includes a free monthly journal club email — a structured critical appraisal of recent research in your field. Want it weekly? Upgrade to Premium for $19.99/mo (14-day free trial) — seven rotating content types, up to 3 fields of interest, and content that builds on itself.

$19.99/mo
Free with every account · Premium starts with 14-day free trial
Learn More
Add-on · ESL Language Editing · $29

For authors writing in a second language.

Add dedicated language editing to any review. Not generic grammar checking — it targets the patterns that mark ESL academic writing: article usage, preposition selection, hedging, academic register, nominalizations, and collocations. Delivered as tracked changes in Word.

$29
add-on per manuscript
Add ESL editing
Real-time streaming

Watch your review generate live.

No black box · no waiting

No 30-minute wait for an email report. Each section of feedback appears on screen as it generates — methodology first, then statistics, then reporting compliance, and so on.

No black box. You watch it happen, section by section.

Generating · Statistical Analysis
Statistical methods & assumptions
Primary outcome analysis uses a Cox proportional hazards model. Proportional-hazards assumption is not explicitly tested; consider Schoenfeld residuals
Five secondary outcomes reported, but methods state no adjustment for multiple
Next · Reporting Guideline Compliance
29,539
Journals in our database
Tailored to your target journal

The right review for the right journal.

Select your target journal and the review is tailored to its requirements. The database covers ~30,000 journals across every scientific discipline, with author instructions for 141+ major journals cross-referenced during review — not just general best practices.

Don't see your journal's specific requirements reflected? Upload your target journal's author guidelines directly and they become part of your review. The system incorporates them automatically — checking your manuscript against the exact formatting, structure, and submission requirements your journal demands. Guidelines uploaded by one user benefit the entire community. Instead of spending hours reading through pages of author instructions and manually reformatting, upload the guidelines and let PeerReviewAI handle the compliance checking for you.

Protected by Anthropic’s Zero Data Retention

Your intellectual property is processed for the review — and then gone.

Your manuscript is never stored, logged, or used for training. PeerReviewAI is built on Anthropic’s Zero Data Retention — the architectural foundation, not a checkbox on a settings page.

Never stored.
Manuscripts are processed for the review and then discarded — not retained on our servers after the session ends.
Never logged.
Manuscript content does not appear in our application logs. Only operational metadata (word counts, timings) is kept.
Never used for training.
Your work is never used to train, fine-tune, or improve any model — ours or anyone else's.
Ready when you are

Ready to see what reviewers will see?

FAQ

Questions, answered.

Don't see yours? Email us — we read every one.