aakashsharan/research-vault
📦 Open Source Projectaakashsharan
An AI-powered research assistant that extracts structured insights from academic papers using RAG and LangGraph.
Research Vault is a sophisticated document-processing framework built to automate the extraction of structured data from academic literature. At its core, the system utilizes LangGraph to orchestrate complex agentic workflows, allowing for multi-step reasoning and deep analysis of PDF content. It integrates Claude for high-fidelity information extraction and uses Qdrant as a vector database to facilitate high-speed semantic search across research libraries.
The architecture is modular, featuring a FastAPI backend for robust API handling and a Next.js frontend for intuitive interaction. By automating the ingestion and indexing of research papers, Research Vault moves beyond simple keyword search, enabling users to perform semantic queries that surface relevant insights, methodologies, and findings across disparate documents. This tool is particularly effective for researchers managing large volumes of literature who need to maintain a structured, queryable repository of their findings.
💡Highlights
- ├─LangGraph-based agentic workflows
- ├─Structured PDF pattern extraction
- └─Qdrant-powered semantic search
🎯For
- ├─Academic Researchers
- ├─Data Scientists
- └─Knowledge Managers