Until recently, the advent of Generative AI changed the landscape of enterprise AI solutions. One of the most transformative approaches is retrieval-augmented generation (RAG). Of these, one of the most revolutionary paradigms of recent origin is RAG. It marries strengths from large language models (LLMs) with accurate information retrieval, thereby enabling companies to build wiser and more context-driven AI applications. 

But what if we could add an extra layer of intelligence on top? Enter Agentic RAG, the state-of-the-art evolution of RAG, now imbued with agents that understand and can perform tasks independently.

https://dzone.com/articles/advancing-enterprise-ai-solutions-with-agentic-rag