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Academic peer review software for authors & groups

Collaborative, automated academic peer review software designed specifically for research groups.

Built by NIH-funded cancer researchers

Affiliations

Built by researchers funded by leading cancer-prevention institutions

  • University of Utah
  • Huntsman Cancer Institute
  • National Cancer Institute
  • American Cancer Society

Current platform

A review workflow built around the decisions only the author can make

PerfectPaper now carries context from setup through research, revision, and export—without turning the paper into a generic writing prompt.

Prepare

Tell the review what the paper cannot

Author interview

PerfectPaper asks targeted questions about design decisions and fixed constraints before review, then carries your answers into the critique.

Journal-aware setup

Search the journal catalogue, choose up to three targets, and compare compatible open-access journals before the review starts.

Your own review panel

Brief up to three custom reviewers, declare ground truths, attach instructions, and choose standard or deep-research depth with specific tools.

Investigate

Read the evidence as a connected whole

Methods, claims, citations, and visuals

Specialist reviewers inspect the full paper in context, including figures and tables—not isolated paragraphs.

Cited research

Deep-research reviewers can search the web and scholarly literature, inspect sources, and attach vetted citations to research-backed findings.

Visible review progress

The reading room shows which review areas are working, which findings have arrived, and when a research step could not complete.

Revise

Turn critique into a submission-ready draft

Anchored reading room

Move between each comment and its passage, read your paper as you wrote it in Word, filter feedback, and discuss any finding.

Apply, track, and undo

Preview suggested revisions, apply accepted changes, keep an edit history, and reverse a change without losing the review trail.

Submission exports

Export the revised paper and saved feedback as DOCX, annotated PDF, or print view, and prepare an anonymous copy for blinded review.

Academic peer review software for authors & groups

Most journal-management platforms serve editors and publishers, not authors. PerfectPaper is a specialized peer review software designed specifically for research labs, PIs, and publishing scholars who want automated, referee-grade pre-screening before submitting manuscripts.

PerfectPaper provides the comprehensive peer review tools you need to establish a high baseline of scientific quality across your group.

Scalable lab workflows & automated critique

  • Trainee Self-Correction: Let students work through standard reviewer criticisms independently before handing drafts to their PI.
  • Collaborative Threads: Discuss comments and revisions in-line with co-authors using our intuitive chat pane.
  • High-Impact Outcomes: Shorter turnaround times and fewer revision rounds at journals.

Review my manuscript

Frequently asked questions

What is an AI peer review tool?

An AI peer review tool is specialized software that evaluates the substantive quality of an academic manuscript before journal submission. Unlike basic grammar checkers, these tools analyze your research methods, logical arguments, claim-evidence alignment, and citation completeness.

How does AI peer review software improve submission success?

Peer review software helps authors identify and self-correct logical gaps, missing controls, and underpowered claims before journal editors evaluate them. This significantly reduces the probability of a desk rejection and streamlines the official peer review process.

Are AI reviewer tools safe for unpublished research?

PerfectPaper keeps your unpublished research completely private and secure. All manuscripts and feedback comments are encrypted, stored in your private history, and never shared or used to train public LLM models.

Last updated August 9, 2026

A careful read when you need a second opinion.

Upload your paper and receive structured, sourced feedback before you submit.