RAG for Knowledge Bases in 2026: What Actually Improves Quality

RAG is often marketed as “chat with your docs”.

In reality, quality comes from discipline:

• what you index
• how you chunk
• how you rank
• how you verify

TL;DR

• clean docs first
• chunking is the #1 lever
• metadata filtering prevents “relevant but wrong”
• reranking is a high-ROI upgrade

Practical Checklist

• dedupe + version your docs
• chunk by structure and meaning
• store metadata (product, region, version)
• filter before retrieval
• rerank candidates
• log sources and measure quality with a test set

RAG is not a component. It’s a system.