From AI pilots to production: Why retrieval quality matters

Amy Machado

Research Director

IDC

James Williams

Director, Solutions Architecture

Elastic

Matias Webe

Director of Machine Learning

Canals

AI is only as good as the data it can find. Weak retrieval raises the risk of hallucinations, stalled projects, and rising costs. For IT leaders, that's often the gap between a promising pilot and a system people actually trust.

Join IDC's guest speaker Amy Machado, Elastic's James Williams, and Canals' Matias Weber, whose AI-powered order entry platform supports 90 million products across distributor catalogs. Together, they'll unpack new research on search quality across healthcare, financial services, retail, government, and insurance. Learn what retrieval quality means for production readiness and how standardizing search, vector, and inference in one platform can support growing demand, while reducing the work of maintaining separate components.

Highlights

• See new IDC research showing a 40% average reduction in time to a minimum viable AI product.
• Hear how Canals increased top-three product match accuracy from 63% to 96% using hybrid retrieval.
• Learn how study participants reduced cost per query by 15% while search volume grew 18%.
• Understand why the retrieval layer, not the model, often determines AI accuracy.

Additional resources

• Study: The Business Value of the Elasticsearch Platform for Search and AI Experiences
• Blog: The search multiplier: Driving revenue, productivity, and AI at scale