RAG-only architectures
What is RAG-only architectures?
RAG-only architectures are systems built entirely around retrieval-augmented generation, where AI models answer questions by first searching through external documents or databases rather than relying solely on their training data.
As enterprises deploy RAG systems for production use, understanding how to architect, secure, and optimize them end-to-end is becoming a critical practical skill rather than just a theoretical concept.
References
- KGCaRe: Explainable Complex Conditional Question Answering using Automatic Knowledge Graph Construction and Context Retrieval with LLMs — ArXiv
- Chunking and Metadata : Backbone of RAG — Part 2 — Medium: LLM
- Coding a RAG Pipeline That Cites Every Single Answer — YouTube
- Building a Production RAG Pipeline From Scratch (With Source Code) — YouTube
- Migrating to Qdrant Cloud Vector DB — From Local to Cloud | HR Policy RAG Assistant Part 5 — YouTube
- What Is Chunkless RAG? How Docling & AI Agents Navigate Documents — YouTube
- RAG Explained from Scratch with LangChain — YouTube
- RAG pipeline and langchain @ 10:30 AM (IST) by Mr. Mayur on 09th August 2026 — YouTube