AI Peer Reviewer System Helps Researchers Improve Manuscripts Before Submission

Researchers frustrated with slow journal responses and minimal co-author feedback have developed an AI-powered peer review system to help improve manuscripts before submission. The tool, called Rigorous, uses a multiagent approach to analyze scientific papers, providing detailed feedback on methodology, writing quality, and more.

Key Features

• 24 specialized agents analyzing various sections of manuscripts
• Detailed feedback with actionable recommendations
• PDF report generation for easy sharing
• Support for custom review criteria and target journals

How It Works

1. Cloud Version (Free During Testing)

   • Upload your manuscript at https://www.rigorous.company/?utm_source=agenthunter.io&utm_medium=news&utm_campaign=newsletter
   • Receive a comprehensive PDF report within 1–2 working days
   • No setup required

2. Self-Hosted Version (GitHub)

   • Available at https://github.com/robertjakob/rigorous?utm_source=agenthunter.io&utm_medium=news&utm_campaign=newsletter
   • Use your own OpenAI API keys
   • Full control over the review process
   • Customize agents and criteria
   • MIT licensed

Target Audience

The system is particularly useful for researchers preparing manuscripts before submission to co-authors or target journals. The developers are seeking feedback from the HN community, especially PhDs and researchers across all academic fields. The project is open source and welcomes contributions.

GitHub: https://github.com/robertjakob/rigorous?utm_source=agenthunter.io&utm_medium=news&utm_campaign=newsletter Cloud version: https://www.rigorous.company/?utm_source=agenthunter.io&utm_medium=news&utm_campaign=newsletter