Unlocking dependable responses with Gemini Enterprise Agent Platform’s Agentic RAG

Google Research has published an Agentic RAG framework on the Gemini Enterprise Agent Platform, with the focus being not simply dumping documents into a model to answer, but enabling the system to decompose questions like a research process, plan queries, route them to different data sources, and check whether the context is sufficient before answering. Google notes that traditional single-step RAG tends to fail when facing the multi-source, multi-hop questions common in enterprises—for example, a project document mentioned in the question only references a server ID, while the actual specifications live in another database; standard RAG might return only a partial answer or say it cannot find one.