Overview
Retrieval Augmented Generation (RAG) is the architecture of choice for professional AI systems. RAG combines the reasoning capabilities of large language models with precise information retrieval from authoritative knowledge bases. This approach delivers cited, verifiable responses grounded in real sources.
RAG Architecture Components
- •Knowledge base of authoritative source documents
- •Embedding model for semantic representation
- •Vector database for similarity search
- •Retrieval pipeline for finding relevant information
- •LLM for synthesis and response generation
- •Citation system for source attribution