To achieve real success with an AI system like agentic or generative AI, enterprises need advanced RAG that can help them overcome challenges like siloed sources, a huge volume of data, numerous touchpoints, and much more. Enterprise-grade RAG incorporates methods like document chunking, hybrid retrieval, and ML models to build relevance across the entire corpus of enterprise knowledge.
In an agentic RAG architecture, the different aspects of RAG are left up to the agent. The agent can perform multiple retrievals, and at multiple steps within the workflow, as needed to reach the goal it’s been assigned to complete.