RAG Architecture

Designing Retrieval-Augmented Generation systems that combine large language models with external knowledge bases for accurate, grounded AI responses.

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Why It Matters

Enterprise AI adoption depends on grounding LLM outputs in real data; engineers who can architect reliable RAG pipelines are critical to deploying AI that organizations actually trust.

How to Get Started

Build a RAG pipeline using LangChain or LlamaIndex with a vector database like Pinecone or Weaviate, and study the original RAG paper by Lewis et al. for foundational understanding.

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