AI Peer Review for Your Manuscript — Before Submission
Catch methodological issues, statistical gaps, and literature weaknesses before reviewers do. Get structured, severity-classified feedback with actionable revision suggestions in minutes.
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Everything for Better Research
AI-powered review that catches what human reviewers look for, delivered instantly.
Deep Analysis
Deep dive into methodology, statistics, and research design.
Structured Feedback
Issues classified by severity so you know what to prioritize.
Actionable Suggestions
Every issue comes with implementable revision recommendations.
Fast Turnaround
Comprehensive feedback in minutes, not weeks.
Multi-Format Support
Upload PDF, DOCX, or plain text. We handle extraction.
Secure & Confidential
Your research stays private. We never share manuscripts.
Deep Analysis
Deep dive into methodology, statistics, and research design.
Structured Feedback
Issues classified by severity so you know what to prioritize.
Actionable Suggestions
Every issue comes with implementable revision recommendations.
Fast Turnaround
Comprehensive feedback in minutes, not weeks.
Multi-Format Support
Upload PDF, DOCX, or plain text. We handle extraction.
Secure & Confidential
Your research stays private. We never share manuscripts.
See What You'll Get
Here's an example review from a real manuscript (anonymized). Every review includes severity-classified issues with specific, actionable suggestions.
The Impact of Social Media Usage on Academic Performance Among Undergraduate Students
8,432 words
Overall Assessment
This manuscript presents an interesting investigation into social media's effects on academic outcomes. While the research question is timely and relevant, several methodological and analytical issues need to be addressed before the findings can be considered robust.
Issues Identified
The study uses n=50 participants without providing a power analysis or justification for this sample size. For detecting the reported correlation of r=-0.34, a larger sample would be needed to achieve adequate statistical power (typically 0.80).
Add a priori power analysis using G*Power or similar software, or justify the sample size based on similar published studies in your field.
Strengths Identified
This is a sample review
Your review will be tailored to your specific manuscript
5 free reviews • No credit card required
From Manuscript to Actionable Insights
Swipe through to see how ManuscriptMind transforms your research paper into a comprehensive, structured review.
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research_manuscript_v3.pdf
2.4 MB • Ready for review
AI Analysis in Progress
Multi-agent deep review pipeline
Abstract: This study examines the relationship between social media usage and academic performance among undergraduate students.
Using a cross-sectional survey design with n=50 participants, we collected data on daily social media usage patterns...
Results indicate a statistically significant negative correlation (r = -0.34, p < 0.05) between hours spent on social media and GPA...
Analysis Agents
Methodology
Statistics
Literature
Review Complete
Comprehensive analysis with actionable recommendations
Issues Identified
Sample size not justified
The study uses n=50 without power analysis or justification.
Add a priori power analysis or justify sample size based on similar studies.
Missing effect sizes
Statistical tests reported without effect size measures.
Include Cohen's d or η² for all significant findings.
Recent literature gaps
Key 2024 meta-analyses not cited.
Update literature review with recent systematic reviews.
Strengths Identified
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Frequently Asked Questions
Everything you need to know about ManuscriptMind
ManuscriptMind is designed to complement, not replace, human peer review. Our AI identifies the same types of issues that journal reviewers look for—methodological gaps, statistical concerns, literature weaknesses—with high consistency. In our validation studies, 94% of users found actionable issues they hadn't previously identified. Think of it as a rigorous pre-submission check that helps you address common problems before your manuscript reaches reviewers.
ManuscriptMind works across all academic disciplines—from STEM fields like biology, chemistry, and computer science to social sciences, humanities, and interdisciplinary research. The AI adapts its analysis based on the structure and conventions of your manuscript. Whether you're writing a clinical trial report, a theoretical physics paper, or a qualitative sociology study, you'll receive relevant, field-appropriate feedback.
Absolutely. Your manuscripts are encrypted in transit and at rest using industry-standard AES-256 encryption. We never share your research with third parties, and we do not use your manuscripts to train AI models. You retain full ownership of your work. Manuscripts are automatically deleted from our servers 30 days after review, or you can delete them immediately from your dashboard.
You start with 5 free credits—each credit equals one full manuscript review. After using your free credits, you can earn more by rating the quality of your reviews. Each rating takes about 30 seconds and earns you additional credits. This helps us improve our AI while giving you ongoing access. We may introduce paid plans in the future for users who need higher volume.
We accept PDF, DOCX, and plain text files up to 50MB. For best results, upload your manuscript in its submission-ready format with all sections (abstract, methods, results, discussion, references). The AI analyzes the full text, so ensure your file isn't locked or password-protected.
Most reviews complete in 3-5 minutes, depending on manuscript length. A typical 8,000-word paper takes about 3 minutes. Longer manuscripts (20,000+ words) may take up to 10 minutes. You'll receive an email notification when your review is ready, and you can track progress in real-time from your dashboard.
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