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( Case Study · 2025 )

AI Research Agent

AI Research Agent

Overview

A retrieval-augmented (RAG) platform that turns a pile of research papers into an interactive, queryable knowledge base — ask a question, get a source-grounded answer.

How it works

  • Ingest — extract text from uploaded PDFs.
  • Analyse — a LangGraph workflow evaluates each paper against your query and scores relevance.
  • Synthesise — a second node summarises the matches into a final verdict with reasoning.
  • Stack

    Python · LangChain + LangGraph · Groq (Llama 3.3) · Sentence Transformers + FAISS · Streamlit

    Highlights

  • Stateful two-node graph: per-paper analysis → cross-paper summary.
  • Low-temperature, structured prompts for consistent relevance scoring.
  • Per-paper error isolation and large-context handling for long documents.