# Agentic RAG

Agentic RAG extends standard Retrieval-Augmented Generation by incorporating agentic behaviour into the retrieval process itself. Instead of a single, static retrieval step, an agentic RAG system dynamically plans which knowledge sources to query, refines its retrieval strategy based on initial results, cross-references multiple sources, validates the quality of retrieved content, and iterates until a sufficiently grounded answer is assembled. This approach significantly improves accuracy on complex, multi-faceted queries. Agentic RAG is a key capability in NiCE Cognigy's Knowledge AI module, enabling AI Agents to handle the depth and complexity that enterprise customer service demands — grounding every answer in verified, enterprise-approved knowledge.

For enterprise teams, Agentic RAG matters because real-world outcomes depend on how the capability is integrated, governed, and measured — not just on the underlying technology. This approach significantly improves accuracy on complex, multi-faceted queries.

## Key Points

- Extends standard RAG with autonomous, iterative retrieval planning by an AI Agent
- Dynamically selects and cross-references multiple knowledge sources per query
- Validates retrieved content quality before including it in the response
- Significantly reduces hallucination on complex, multi-part customer questions
- Powers NiCE Cognigy Knowledge AI for deep, grounded enterprise knowledge retrieval

### See how it works in action

- [Watch the demo](https://www.youtube.com/watch?v=U87psHIQF3w)
- [Speak with an expert](/content/contact-us/index.html)
- [Explore Solutions](/content/solutions/ai-agents/index.html)
- [Explore Platform](/content/platform/cognigy-ai/index.html)