Grounded Research Assistant

An agentic, evidence grounded research assistant that converts research papers into structured, traceable outputs using RAG.

Problem

Research teams spend significant time extracting summaries, experimental setup, limitations, and critique from academic papers. This work is repetitive, hard to standardize, and easy to get wrong.

Solution

A workflow that ingests research PDFs and produces structured, evidence backed outputs such as summaries, findings, limitations, and replication notes.

System Architecture

• Stateful orchestration with LangGraph (agent workflow).
• Retrieval augmented generation (RAG) to ground outputs in paper passages.
• Structured outputs enforced with Pydantic schemas.
• Local inference using Ollama for offline/cost controlled execution.

Key Design Decisions

• Use agentic planning rather than a single prompt to mirror real research workflows.
• Prefer structured outputs over free form text to reduce hallucination risk and simplify downstream use.
• Persist paper-specific retrieval context to support follow up Q&A.

Outcomes

Enables repeatable, traceable analysis of research papers for literature reviews, reproducibility checks, and due diligence workflows.