K
KolossusWork AI that Delivers
AI Guides & EducationGuide

Agentic RAG: When AI Agents Meet Retrieval-Augmented Generation

How Agentic RAG combines autonomous AI agents with retrieval systems for more intelligent, context-aware enterprise AI applications.

January 12, 2026
12 min
Guide
AI Guides & Education

What is Agentic RAG?

Agentic RAG combines the retrieval capabilities of RAG with the autonomous decision-making of AI agents. The result: AI that can intelligently decide what information to retrieve and how to use it.

How It Differs from Standard RAG

Standard RAG

Simple query → retrieve → generate flow.

Agentic RAG

Query → reason about what's needed → retrieve strategically → evaluate results → retrieve more if needed → generate comprehensive response.

Key Capabilities

  • Query Decomposition: Break complex questions into sub-queries
  • Multi-hop Retrieval: Follow chains of information
  • Self-Reflection: Evaluate if retrieval was sufficient
  • Tool Use: Access multiple knowledge sources

Use Cases

  • Complex research questions
  • Multi-document synthesis
  • Competitive intelligence
  • Legal research

Implementation

Start with a solid RAG foundation, then add agent capabilities for query planning and result evaluation.

See agentic RAG demo

Ready to implement what you've learned? Let us show you how Kolossus can help.

See agentic RAG demo

Ready to see AI agents in action?

See how Kolossus AI agents can transform your workflows with faster automation, deeper insights, and better outcomes.