Research Paper Intelligence Multi-Agent System
A multi-agent system helping AI researchers manage the enormous stream of incoming research papers.
The problem
AI research output is growing faster than any individual researcher can read. Important papers get buried in a firehose of preprints, making it hard to track trends, find relevant prior work, or stay current in a fast-moving subfield.
Our solution
A coordinated set of specialized agents continuously discovers new papers, summarizes them, clusters them by topic, filters for relevance to your research interests, and surfaces emerging trends — turning an overwhelming stream into a personalized, organized feed.
Key features
Target users
AI researchers, PhD students, applied research teams, and technical leads who need to stay current without spending hours a day scanning preprint servers.
Example workflow
1. The discovery agent monitors arXiv and other sources for new papers.
2. The summarization agent produces a concise abstract-plus-key-findings digest.
3. The clustering agent groups related papers by topic and method.
4. The relevance agent ranks papers against your stated research interests.
5. You receive a personalized weekly research feed with trend highlights.
Demo / screenshot
Pricing
Pricing available on request