RAG Architecture Review

Your retrieval is returning garbage. Your LLM is hallucinating. Your chunking strategy feels like guesswork. I've been there.

In this session, I'll audit your RAG pipeline end-to-end — ingestion, chunking, embeddings, retrieval, reranking, and prompt assembly. We'll identify exactly where quality breaks down and I'll give you a concrete fix list you can implement this week.

What we'll cover:

1. Chunking strategy review (size, overlap, semantic boundaries)
2. Embedding model selection and fine-tuning signals
3. Retrieval tuning: dense vs. sparse vs. hybrid
4. Reranking and context window optimization
5. Hallucination detection and source attribution
6. Production checklist: caching, monitoring, cost controls

Best for: Engineers with a working prototype that's failing in production, or teams about to build their first RAG system and want to avoid the common traps.

Bring: your current architecture diagram or code repo (optional but helpful).