GraphRAG
Graph memory & retrieval system
A graph-native retrieval-augmented generation system that stores and queries knowledge as interconnected entities rather than flat vectors.
Operational
Graph Metrics
Entities
2.4M
Relations
8.7M
Traversal Latency
42ms
Sync Interval
15s
Architecture Notes
Entities and relationships are first-class citizens — not just text chunks.
Multi-hop traversal enables reasoning chains that flat RAG cannot support.
Temporal context: knowledge nodes carry timestamps enabling recency-aware retrieval.
Graph structure survives session boundaries — the AI remembers across invocations.
Integrations
Neo4jLangGraphAnthropic APIFastAPIPostgreSQLRedisPythonNetworkX