Agentic RAG
Agentic RAG enhances AI agents by connecting reasoning systems to external knowledge sources.
Amy McDonald
Feb 17, 2026
Extending Agents with Retrieval-Augmented Intelligence
Agentic RAG (Retrieval-Augmented Generation) enhances AI agents by connecting reasoning systems to external knowledge sources. Rather than relying solely on model training data, agents dynamically retrieve relevant information before generating outputs or making decisions.
Contextual and Verifiable Outputs
By querying documents, databases, or internal knowledge bases, agents produce responses grounded in real sources. This reduces hallucinations and allows teams to trace insights back to original materials — a key requirement in enterprise environments.
Continuous Knowledge Integration
Agentic RAG enables agents to operate in rapidly changing domains where static knowledge quickly becomes outdated. As new data becomes available, agents incorporate it immediately, supporting real-time analysis and more reliable decision-making workflows.
