Frequently Asked Questions

AI Pre Review is for authors, editors, and reviewers in the peer-reviewed literature. AI Pre Review validates articles for eligibility for publication against the targeted journal's requirements and published standards and provides clear, actionable suggestions to speed the review process. The goal is to avoid wasting time on avoidable errors and reduce time to publication.

No, AI Pre Review does not write or revise manuscripts. It provides a detailed review of the manuscript and offers suggestions to correct any deficiencies found.

AI Pre Review evaluates compliance with the target Journal's requirements (word count, format, etc.), conformance to published guidelines, checks references, evaluates statistical methodology, reviews figures and tables, provides suggestions to improve syntax and grammar, checks spelling, and performs several other validations. This can be very helpful to authors when preparing submissions, to editors when deciding whether manuscripts comply with the Journal's requirements, and to reviewers so they can focus on content and apply their domain expertise, rather than spend time on issues of format and style.

No. Acceptance decisions rest with each journal's editors and reviewers, who weigh many factors beyond formal requirements, including novelty, scientific merit, fit with the journal's scope, and peer review feedback.

What AI Pre Review does is help ensure your manuscript meets the journal's published requirements and minimum standards before you submit, so it is not delayed or rejected for avoidable reasons.

AI Pre Review reads your manuscript best when it follows standard structure; conveniently for you, this structure matches the typical requirements for journal submissions. For the most accurate analysis:

• Upload a .PDF file with selectable text — not a scanned image (if you can't highlight the text with your cursor, it's harder for the computer to read).
• Give each section a standard heading on its own line: Abstract, Introduction, Methods, Results, Discussion, Conclusion, References.
• Start each figure and table caption with its label and number: Figure 1., Table 2.
• List references as a numbered list (1., 2., 3. …), ideally in a single column.

Analysis still runs on any document — standard structure simply makes the measured statistics (abstract and main-text word counts, figure and table counts, and reference count) exact. See our recommended manuscript structure for full details and troubleshooting.

You can pay per manuscript or subscribe. All prices are in USD.

At this time, only individual subscriptions are available.

No, multilanguage support is not provided at this time. AI Pre Review currently supports manuscripts written in English.

AI Pre Review is a US-based company, located in Arizona.

Only you. Your submitted manuscripts, revisions, and AI Pre Review reports are visible to your account alone. They are never shared with publishers, journals, AI companies, or anyone else.

The one exception is our closed beta and demo program: while you are using a beta or demo account, the AI Pre Review team may view those submissions to debug and improve the service. They are never shared outside the company.

AI Pre Review runs its analysis only on models hosted by Amazon Web Services (AWS Bedrock), inside our own AWS account. Your manuscript and reports are processed there and nowhere else.

The companies that build the models, such as OpenAI, Anthropic, Google, and xAI, never receive your submissions or your reports and have no access to them.

No. Nothing you upload is used to train or fine-tune any AI model, by us or by anyone else. AWS Bedrock does not use the content it processes to train models or pass it to the model developers, and AI Pre Review does not build training data from submissions.

The models do not learn from your submission or remember it afterward.

No, by design. Leading mathematicians, including 25 Fields Medal winners, have recently raised concerns about how frontier AI labs approach research: racing to announce AI-generated results, unclear credit for the people whose work contributed, and too little human review. For any researcher, that raises a fair question about what happens to unpublished ideas shared with an AI company.

AI Pre Review is built so your work cannot feed into anyone else's results. Your manuscript is processed inside our own AWS account, the companies that build the models never receive it, nothing you upload is used for training, and no one outside AI Pre Review can see it. Your ideas, and the credit for them, stay yours.

There is no limit on manuscript revisions.

Ownership of the manuscript and copyright are held by the account holder. Using AI Pre Review does not affect copyright ownership in any way.

Yes, you can permanently delete your manuscript from our servers at any time, directly from your dashboard.

You have full rights to the reports. AI Pre Review maintains a secure, confidential copy of the system-generated reports for quality control purposes. They are never shared outside the company.

Please contact feedback@aiprereview.com with any concerns, ideas, and suggestions. We are eager to improve AI Pre Review and appreciate any ideas and suggestions to do so!