GraphRAG Production Playbook

## The Problem You've built a RAG prototype that works on three example questions. Now you need to ship it. You're staring down Neo4j clustering decisions, GPU vs. CPU serving tradeoffs, caching strategies you've never designed, and a CTO who wants to know the latency budget. Every blog post covers the happy path — none of them tell you what breaks at 10K QPS or how to debug a retrieval pipeline when recall drops overnight. ## What This Guide Does For You After reading this guide, you'll have the battle-tested architecture decisions, deployment patterns, and operational playbook to take a GraphRAG system from prototype to production — and the confidence to defend every tradeoff you make. This is what works after shipping GraphRAG under real traffic. ## What You'll Be Able To Do - **Make architecture decisions with conviction** — know exactly when to use vector search, graph traversal, or both for different query types - **Design production infrastructure** — Neo4j clustering, Qdrant/Pinecone selection, GPU vs CPU serving tradeoffs - **Decompose complex queries reliably** — break questions into sub-queries, generate Cypher at runtime, resolve entities - **Evaluate retrieval quality like a pro** — MRR, NDCG, LLM-as-judge pipelines, A/B testing for RAG - **Design a multi-level cache architecture** — embedding, query, and result caches with invalidation policies - **Observe everything in production** — OpenTelemetry traces, structured logging, Grafana dashboards for latency/quality/cost - **Optimize costs without sacrificing quality** — embedding budget allocation, model tiering, cache hit ratio targets - **Ship schema changes without downtime** — CI/CD for graph schemas, blue/green embedding model deploys, migration strategies ## Who Will Benefit Most Senior engineers and architects who already understand RAG basics and need to build production-grade GraphRAG systems. This is not an introduction — it's a battle-tested playbook for going live and staying live. ## What Success Looks Like You'll be the person on your team who knows how to ship GraphRAG — not just demo it. Production architecture decisions, operational runbooks, cost projections, and a system that stays up under real traffic. That's the difference between a prototype and a product, and this playbook is the bridge. ## Format & Delivery - 8 chapters, 60+ pages - Code examples in Python, Cypher, and TypeScript - Architecture diagrams and decision trees - Immediate digital download (PDF)