Enterprise GraphRAG: Production Knowledge Graphs & Hybrid Vector Search
Stop building enterprise AI on flat vector similarity. Fuse multi-hop graph traversals with dense vector search to give autonomous AI agents deterministic, lifelong memory.
💻 Complete Neo4j + Qdrant Codebase
⚡ Instant Digital Delivery
5 Core Engineering Modules Inside
1. Mathematical Anatomy of Vector Failure
Hyperspherical shell concentration proof (1536 dims), attention entropy decay across 128k windows, and 12-pattern failure taxonomy.
2. Automated ERC Extraction Pipelines
Multi-modal diagram extraction, Pydantic V2 Entity-Relationship-Claim enforcement, AST chunker, and Redis Streams async workers.
3. The Hybrid Retrieval Triad
2-hop Cypher traversal combined with Qdrant dense vectors, fused via Reciprocal Rank Fusion (RRF k=60) & ColBERT MaxSim.
4. Hierarchical Leiden Communities
Newman-Girvan modularity optimization and multi-scale gamma tuning to answer holistic dataset queries without context blowup.
5. Production FinOps & Hardening
3-Year TCO matrix (91.3% savings vs cloud APIs), Kubernetes StatefulSet manifests, OpenTelemetry tracing, and prompt-injection defense.
📦 Complete Turnkey Codebase Repository (Inside ZIP):
- 📁 Enterprise_GraphRAG_Interior_72Pages.pdf — 72-page Stripe Press standard monograph
- 📁 Enterprise_GraphRAG.epub — Standards-compliant reflowable Kindle eBook
- 📁 production-codebase/docker-compose.yml — Neo4j 5.24 APOC + Qdrant 1.12 + Redis stack
- 📁 production-codebase/triad_retriever.py — Async Cypher + Qdrant + RRF retriever
- 📁 production-codebase/leiden_clustering.py — Modularity Q optimization & Map-Reduce
- 📁 production-codebase/kubernetes/ — StatefulSet & Service manifests
- 📁 production-codebase/requirements.txt — Verified Python dependencies
100% Deterministic Knowledge & Commercial Developer License
Full lifetime license to deploy and customize across personal and enterprise infrastructure. Zero recurring cloud fees.