LitRadar is a literature analysis tool that maps themes, surfaces candidate gaps, and links every conclusion back to the excerpts that support it. It produces deterministic, repeatable reports — not chat responses — so you can defend your analysis to an advisor and re-run it when your corpus changes.
The problem
Literature reviews are one of the hardest parts of research, and the tools haven't kept up.
You download 40 PDFs. You skim, highlight, and take notes in a dozen tabs. Two weeks later your research question shifts and you start over. You know there are patterns in the pile — themes that cluster, intersections nobody has explored — but finding them means re-reading everything, and there's no way to show your advisor how you arrived at your conclusions.
Chat tools can summarize individual papers, but they don't give you a structured, reproducible map of an entire corpus. LitRadar does.
Core capabilities
Three properties that set it apart from asking an AI chatbot to summarize your papers.
Every theme summary and gap hypothesis cites the exact text excerpts it was derived from. You can verify any claim in seconds.
Fixed seeds, corpus manifests, and stability scores mean the same papers produce the same report. When your corpus changes, the manifest tells you.
Download a PDF report with figures, citations, and a reproducibility panel. Hand it to your advisor, committee, or collaborators.
Not a chatbot
LitRadar is a structured analysis pipeline, not a conversation.
Chat-based AI tools are great for Q&A, but they produce ephemeral answers that change every time you ask. LitRadar takes a different approach: it runs a deterministic pipeline over your corpus and generates a stable artifact you can cite, share, and re-run.
Built for real researchers
Whether you're starting your first literature review or managing a multi-year research program.
Quickly orient to a new topic. See how themes connect across your reading list without keyword tunnel vision.
Compress the "scan phase" from weeks to hours and validate candidate gaps with evidence-linked outputs you can show your advisor.
Compare corpora across projects, track how coverage evolves over time, and document reproducible analysis choices in your methods section.
What we believe
Make literature analysis faster without making it less rigorous. Researchers should spend their time thinking, not re-reading. And every tool-generated claim should be traceable back to the evidence that supports it.