Enterprise Relationship Graph
GraphRAG-powered knowledge graph mapping 500+ business entities and 2,000+ relationships across the Jacksonville ecosystem. LLM-driven entity extraction, Leiden community detection, and three search paradigms (local, global, drift) enable multi-hop discovery of partnership networks, funding flows, and industry clusters.
Challenge
Jacksonville's business ecosystem has thousands of organizations, but no unified way to understand how they connect — partnerships, shared board members, investment relationships, and industry clusters are invisible. Traditional search returns isolated facts without revealing the multi-hop relationship paths between entities.
Approach
Built a GraphRAG pipeline: 1. Ingested public business data from multiple sources. 2. Used LLM-powered entity extraction (OpenAI GPT-4) to identify organizations, people, programs, and funding relationships. 3. Applied Leiden community detection to discover thematic clusters — Healthcare, Financial Services, Logistics, Innovation Programs, Investment, and Leadership. 4. Deployed three retrieval paradigms: Local Search for entity traversal, Global Search across community summaries, and Drift Search for iterative multi-hop discovery.
Outcome
500+ business entities mapped with 2,000+ relationships across 6 detected communities. Economic development professionals use multi-hop graph traversal to discover partnership opportunities invisible to keyword search — e.g., tracing a 4-hop path from investment funding through accelerator programs to healthcare innovation. The graph auto-updates as new data sources are ingested.
Architecture
Interactive Demo
GraphRAG Pipeline
Three Search Paradigms
Local Search
Traverses entity neighborhoods in the graph — e.g., "Who are Mayo Clinic's partners?" follows direct edges to related organizations, programs, and people.
Global Search
Queries community-level summaries generated by Leiden detection — ideal for broad thematic questions spanning the entire ecosystem.
Drift Search
Iteratively refines queries across community boundaries, following multi-hop paths to uncover deep, non-obvious connections.
Technology Stack
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