Difference Between Agentic RAG & Intelligent Chunking

Agentic RAG:

Involves autonomous agents that iteratively refine queries, retrievals, and responses.

Agents can re-query, chain multiple retrievals, or generate additional context before answering.

Example: If a document chunk is insufficient, an agent may decide to fetch related sections, summarize, or ask follow-up queries.

Intelligent Chunking (Hierarchical RAG):

Focuses on better preprocessing of documents by identifying logically linked sections before embedding.

Helps improve retrieval quality by maintaining document structure and relationships.

Example: Instead of blindly chunking by fixed tokens, the system understands sections like "Introduction" and "Methodology" belong together.

Can They Be Combined?

Yes! A hybrid approach would:

Use Intelligent Chunking to pre-process documents efficiently.

Employ Agentic RAG to refine retrieval dynamically during query time.

Would you like an example using LangChain or LlamaIndex to implement this? 

references:

OpenaAI