Research tooling · Agentic RAG

ResearchMap AI

Turns a one-line description of a research field into a map of its literature: topics, trends and gaps. An agent answers questions about the field, citing only papers it actually retrieved.

• Built the full product solo: a FastAPI backend on PostgreSQL with pgvector, a React frontend, sign-in with Google OAuth and TOTP, plans with quotas, and an admin panel.
• Designed the analysis pipeline. An LLM plans the OpenAlex queries, papers are embedded and clustered with KMeans, an LLM names each topic, and research gaps are computed from topics that share no papers.
• Built an agentic RAG chat on OpenAI tool calling, with 7 tools and at most 4 rounds. Its citations come only from papers the tools returned, and it sits behind a relevance floor measured on real data.
• Benchmarked it with four harnesses and an LLM judge, and shipped it to Cloud Run through GitHub Actions and Workload Identity Federation.