Скачать или смотреть RAG Architectures: An Expert Analysis and Strategic Application

The source provides an expert analysis of Retrieval-Augmented Generation (RAG) systems, detailing their evolution and architectural complexity. It establishes a formal taxonomy by classifying RAG into three stages: Naive RAG (vector-based fundamentals), Advanced RAG (incorporating pre- and post-retrieval optimizations), and Modular RAG (composable, intelligent architectures). The analysis distinguishes between three major paradigms—Vector RAG, Agentic RAG, and Graph RAG—by explaining that they solve different problems: semantic search, dynamic problem-solving, and relational reasoning, respectively. Furthermore, the report clarifies that caching is not a separate architecture but a vital optimization strategy applicable to all RAG systems to reduce latency. Ultimately, the future of the technology is predicted to be in hybrid architectures that combine these strengths, often orchestrated by intelligent agents, to solve complex enterprise problems.