Hi HN, I'm Flynn. I built Arbor because literature review was the most painful part of my PhD.
Arbor takes a research question and builds a knowledge graph:
1. Decomposes the question into 4 focused sub-inquiries
2. Searches arXiv + Semantic Scholar in parallel
3. Screens papers for relevance and extracts findings
4. Synthesizes everything into structured markdown
All stages stream in real-time via SSE. The graph is interactive — click any node to see sources, findings, and connections.
It's free, no signup, no login. Rate limited to 5 queries/hour per IP.
Limitations I'm aware of: only searches arXiv and Semantic Scholar (no PubMed, no Google Scholar), graph layout can get crowded on large queries, and LLM extraction quality varies.
I'd love feedback on: research quality, graph UX, missing features, anything. What would make this useful for your work?
FlynnLachendro•1h ago
Arbor takes a research question and builds a knowledge graph:
All stages stream in real-time via SSE. The graph is interactive — click any node to see sources, findings, and connections.Stack: React 19 + TypeScript + React Flow (frontend), FastAPI + SQLAlchemy + aiosqlite (backend), hosted on Vercel + Railway.
It's free, no signup, no login. Rate limited to 5 queries/hour per IP.
Limitations I'm aware of: only searches arXiv and Semantic Scholar (no PubMed, no Google Scholar), graph layout can get crowded on large queries, and LLM extraction quality varies.
I'd love feedback on: research quality, graph UX, missing features, anything. What would make this useful for your work?