Agentic RAG combines retrieval-augmented generation with autonomous AI agents that can search knowledge sources, reason over context, act on systems through tools and APIs, and loop until a task is complete — instead of stopping at a single generated answer.

Traditional RAG retrieves documents and generates one text answer. Agentic RAG uses multi-step adaptive retrieval, native tool integration, and continues until workflow criteria are met — producing answers plus system actions and auditable status.

Production deployments require continuous knowledge sync, permission-aware retrieval, human-in-the-loop approvals for high-risk actions, and audit trails that log every retrieval, reasoning step, tool call, and outcome.

BotIntelli combines synchronized enterprise knowledge bases, no-code AI agents with tool and workflow access, multi-step orchestration with approval gates, and Glass Box audit trails — delivering agentic RAG as a governed production platform, not a research prototype.