Why Most Enterprise RAG Deployments Underperform

The model isn't the problem

Teams spend weeks comparing foundation models and days on retrieval — and it shows. In our experience, retrieval quality accounts for the majority of RAG failures we're asked to diagnose.

Chunking strategy matters more than you think

Naive fixed-size chunking breaks tables, code blocks, and multi-paragraph clauses apart from their context. Document-aware chunking — respecting headings, tables, and lists — consistently outperforms fixed-size splitting in our evaluations.

Hybrid retrieval beats pure vector search

Combining keyword (BM25) and vector retrieval, then re-ranking, recovers exact-match cases that pure embedding similarity misses — think part numbers, clause references, and acronyms.

Evaluate on your own documents

Public RAG benchmarks tell you little about how a system performs on your contracts, runbooks, or policy documents. Build a small, representative evaluation set before you ship — even 30 hand-labeled question/answer pairs will surface issues a generic benchmark never would.