What is agentic search?
Conventional search retrieves. Agentic search reasons. The difference is architectural.
Defining agentic search
Agentic search is retrieval in which an autonomous AI agent reasons about the query, selects retrieval strategies, executes them, evaluates results, identifies gaps, re-queries, and continues until it reaches a confident, source-attributed answer.
The agentic search loop
Query interpretation → strategy selection → parallel retrieval → fusion and evaluation → gap identification and re-query → answer synthesis with provenance.
Why conventional search is not enough for enterprise AI
Enterprise questions are rarely single-pass. Multi-hop questions require traversing history, integrating signals, and synthesising — what an agentic search loop is designed to do.
Frequently asked questions
What is the difference between agentic search and RAG?
RAG retrieves and grounds a model response. Agentic search adds reasoning, iteration, and multi-path retrieval that RAG alone does not provide.
Is agentic search slower than conventional search?
Simple queries use fast paths at comparable speed. Complex queries add latency but return answers single-pass retrieval cannot produce.
What is Reciprocal Rank Fusion?
RRF combines ranked result lists from multiple retrieval systems using rank position — consistently outperforming individual methods on benchmark tasks.
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