AI retail specialist Zobrist has launched a module to automate digital merchandising on its Smart Merchandiser platform. The Smart Merchandiser AI (SM AI) module reacts to real-time signals and enables faster product decisions using a privacy-first, AI model.

The new module is built for teams managing Direct-to-Consumer (DTC) storefronts and combines a pre-trained catalogue-only AI model with performance signals from Google Analytics 4 (GA4) and Omniture. It provides three new capabilities: AI-powered substitutions for out-of-stock items; Boost & Bury product ranking suggestions; and plug-and-play recommendation Application Program Interfaces (APIs) including Bestsellers, Trending, and Frequently Bought Together.

The module’s APIs can be embedded into product detail pages to allow customer discovery and increase average order value. Custom development is not required.

SM AI does not rely on session tracking or behavioural data. It operates on product information and analytics alone, addressing privacy concerns and accelerating time to value. All recommendations are embedded directly within the Smart Merchandiser interface. Teams can preview, apply, or automate changes without leaving their workflow.

“Merchandisers need AI that works with the data they already trust,” said Teresa Zobrist, CEO of Zobrist Software Group. “SM AI focuses on the moments that move the needle—protecting revenue when items stock out, boosting high performers, and helping shoppers discover relevant alternatives. And most importantly, it does this without replacing the merchandiser’s judgement.”