Show HN: AI Peer Reviewer – Multiagent System for Scientific Manuscript Analysis

After waiting 8 months for a journal response or two months for co-author feedback that consisted of "looks good" and a single comma change, we built an AI-powered peer review system that helps researchers improve their manuscripts rapidly before submission.

The system uses multiple specialized agents to analyze different aspects of scientific papers, from methodology to writing quality.

Key features: 24 specialized agents analyzing sections, scientific rigor, and writing quality // Detailed feedback with actionable recommendations. // PDF report generation. // Support for custom review criteria and target journals.

Two ways to use it:

1. Cloud version (free during testing): https://www.rigorous.company - Upload your manuscript - Get a comprehensive PDF report within 1–2 working days - No setup required

2. Self-hosted version (GitHub): https://github.com/robertjakob/rigorous - Use your own OpenAI API keys - Full control over the review process - Customize agents and criteria - MIT licensed

The system is particularly useful for researchers preparing manuscripts before submission to co-authors or target journals.

Would love to get feedback from the HN community, especially from PhDs and researchers across all academic fields. The project is open source and we welcome contributions!

GitHub: https://github.com/robertjakob/rigorous Cloud version: https://www.rigorous.company

Comments URL: https://news.ycombinator.com/item?id=44144280

Points: 42

# Comments: 26

https://github.com/robertjakob/rigorous