chapter seven
7 Enterprise RAG: Agentic Routing, Semantic Caching, and Query Rewriting
This chapter covers:
- Understanding the limitations of naive RAG architectures and the full landscape of Enterprise RAG capabilities
- Building enterprise-grade RAG systems with agentic routing capabilities
- Deploying semantic caching for performance optimization, cost reduction, and latency compliance
- Implementing intelligent query rewriting and classification with LLM-based intent detection and multi-path routing
- Integrating all three into Enterprise RAG ecosystem
The RAG systems we've explored in previous chapters are a significant step forward from traditional language models, successfully grounding responses in factual information and eliminating many hallucination issues. But as we move from proof-of-concept implementations to enterprise-grade deployments, the limitations of these "naive" RAG approaches become increasingly apparent. The Travelle hotel search and research paper agent show what RAG can do, yet both operate within relatively constrained environments: single-domain knowledge bases, straightforward query patterns, and predictable user interactions.