RAG & Retrieval (Enterprise)
15 Techniques for a Fast, Cheap RAG System
The complete enterprise RAG optimization checklist.
This is a complete checklist of 15 techniques to build a fast, accurate and cost-efficient enterprise RAG system — the full optimization toolkit on one page.
In simple terms
The 15-technique checklist for a production-grade RAG system.
How it works
- 1Retrieval: hybrid search, re-ranking, smart chunking, embedding optimization, query understanding.
- 2Efficiency: context pruning, deduplication, semantic cache, prompt cache, response compression.
- 3Targeting: metadata filtering, permission-aware retrieval, route to the right index, tool selection.
- 4Quality: observability and evaluations to monitor and improve continuously.
- 5Together they take latency from ~15s to ~2.8s and cost from ~$60K to ~$14K per month.
Key points
- Combine retrieval quality (hybrid, rerank, chunking) with efficiency (caching, pruning, compression).
- Enforce permissions and route queries to the right index.
- Continuously monitor latency, cost and quality with evals.
- Result: higher accuracy, better UX, lower cost.
Why it matters
A single checklist of proven techniques gives teams a roadmap to make RAG production-ready — fast, accurate and affordable at enterprise scale.
Frequently asked questions
- What are the technique categories?
- Retrieval quality, efficiency (caching, pruning, compression), targeting (filtering, routing) and quality (observability, evals).
- What's the impact?
- Together they can cut latency and cost dramatically while raising accuracy.
More in RAG & Retrieval (Enterprise)
Where Hallucinations Come From
Failures across the query, retrieval and model layers.
RAG Retrieval Optimization Layer
Retrieve the right context with high recall and relevance.
RAG: Retrieval Re-ranking
Re-rank retrieved docs to keep only the most relevant.
RAG Optimization 1 · Hybrid Search
Keyword + semantic search for higher recall.
RAG Optimization 2 · Re-ranking
Find the most relevant docs before the LLM.
RAG Optimization 3 · Context Pruning
Remove noise; keep only what matters.