Agentic Memory & Knowledge Graph Telemetry

Enterprise GraphRAG vs Vector DB Benchmark

Simulate and benchmark indexing token multipliers, k-hop retrieval latency, and multi-hop reasoning accuracy comparing Dense Vector RAG, Hybrid BM25+Dense, and Knowledge Graph Triplet Extraction.

Retrieval Architecture Comparison & Multi-Hop Accuracy

Knowledge Graph Triplet Extraction (GraphRAG)

Hierarchical Leiden community clusters and k-hop subgraph traversal achieve 95% multi-hop reasoning accuracy across enterprise corpora, eliminating cross-document entity blindness.

Accuracy: 95% | Latency: 380ms | Triplet Extraction

Hybrid BM25 + Dense Vector RAG

Reciprocal Rank Fusion with cross-encoder reranking delivers fast point lookups for technical IDs, but lacks graph topology for relational reasoning.

Accuracy: 61% | Latency: 70ms | Point Lookup