Topic

RAG Architecture & Pipeline Design

7 posts on rag architecture & pipeline design — part of glossary on the n4n AI blog.

Naive RAG vs advanced RAG: architectural differences

A practitioner's comparison of naive vs advanced RAG architectures across retrieval quality, latency, cost, and operational complexity with a clear verdict by use case.

July 28, 20265 min read

GlossaryHow-to

How to design a RAG pipeline for enterprise documents

A step-by-step guide to building a production RAG pipeline for enterprise documents, covering ingestion, chunking, embedding, retrieval, and evaluation with runnable code.

July 28, 20264 min read

GlossaryHow-to

How to choose an embedding model for your RAG pipeline

A step-by-step guide to selecting the right embedding model for your RAG pipeline, with benchmarks, code, and validation strategies.

July 28, 20265 min read

GlossaryHow-to

How embedding models fit into a RAG pipeline

A step-by-step guide to integrating embedding models into a RAG pipeline, from model selection and chunking to indexing, retrieval, and evaluation.

July 28, 20264 min read

GlossaryAnalysis

Common failure points in RAG pipeline design

Senior engineer breaks down the real-world failure points in RAG pipelines — chunking, retrieval, generation, and evaluation — with code examples and honest tradeoffs.

July 28, 20265 min read

GlossaryDefinition

Agentic RAG: adding reasoning steps to retrieval

Agentic RAG adds multi-step reasoning to retrieval, letting agents plan, decompose queries, and iterate on results instead of single-pass lookup.

July 28, 20265 min read

GlossaryAnalysis

Anatomy of a production RAG architecture

A senior engineer dissects the components, tradeoffs, and failure modes of a production RAG architecture — from ingestion to retrieval to generation — with code patterns and hard-won lessons.

July 27, 20264 min read