analiza aiqbench
This is a vendor-published announcement of an analyst ranking, so the claims about Elastic's placement come from Elastic's framing of Gartner's report, not from the report itself. The substantive point for AI readers is the argument that retrieval quality, not model choice, often drives grounding and token costs in production AI agents. Readers evaluating retrieval infrastructure should check the Gartner reports directly and test hybrid search performance on their own data.
Elastic named a Leader in the 2026 Gartner® Magic Quadrant™ for Enterprise AI Search
Elastic was named a Leader in the 2026 Gartner® Magic Quadrant™ for Enterprise AI Search. We ranked #1 in the AI Automation Use Case in the companion Critical Capabilities report.
Elastic has been named a Leader in the 2026 Gartner® Magic Quadrant™ for Enterprise AI Search. Out of the entire evaluated market, only three vendors were named a Leader. Elastic positioned highest for Ability to Execute and furthest for Completeness of Vision. In the companion Critical Capabilities report, Elastic ranked first in the AI Automation Use Case. The enterprise AI search market looks different than it did even a year ago. Organizations are increasingly moving AI applications and agents toward production, and the retrieval layer underneath them has become critical infrastructure. Teams realize AI needs search to deliver accurate results at lower cost, and they are asking which platform they can trust to power it reliably, at scale, and across all the data that matters. We…
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