resumeRAG

graphRAG visualizations for recruiter workflows

Stack: Python, GraphRAG, FastAPI, React
Status: hackathon
Created: May 1, 2025

built for the github? hackathon. shoutout oren and daniel

Recruiters often waste time on irrelevant matches or miss strong candidates entirely, resulting in slower hiring and overlooked talent. ResumeRAG tackles the broken resume filtering process by moving beyond traditional keyword search to a graph-based approach using GraphRAG that actually understands relationships between skills, roles, and experiences.

Our solution builds a knowledge graph of resumes using GraphRAG, then lets users query it in natural language to discover and visualize relevant information. We implemented this with Python, GraphRAG, FastAPI, and React, layering LLM-driven context and visualization on top to make resume search more accurate, transparent, and useful.

What’s next for ResumeRAG would be allowing users to upload their own resume database, allowing them to clearly and efficiently identify talent from within their own hiring processes.