Joel Bar-El

Trax Retail provides computer vision and AI analytics for physical retail shelf management, using in-store cameras and mobile image capture to analyse product placement, out-of-stock conditions, planogram compliance, and competitive share of shelf in real time, allowing consumer goods companies and retailers to optimise in-store execution across thousands of stores globally. The Singapore company processes billions of shelf images annually through its AI vision platform.\n\nThe company raised approximately $900 million in funding from investors including Softbank Vision Fund, Boyu Capital, and DC Thomson Ventures, reaching a valuation of approximately $2 billion. Trax serves major consumer packaged goods companies including Coca-Cola, Nestle, and P&G, as well as retailers in Europe, Asia, and the Americas that use the platform to measure and improve in-store execution quality. The platform connects field sales teams with real-time alerts about shelf conditions that require immediate corrective action.\n\nTrax competes in the retail AI and in-store analytics market against Focal Systems, Shelfgram, and Datasembly, as well as the retail analytics divisions of large data companies including Nielsen and IRI. Its global deployment scale across diverse retail formats and geographies, combined with AI models trained on billions of labelled shelf images, creates a data advantage that newer market entrants have not had sufficient deployment history to replicate. Consumer packaged goods companies represent a large budget segment for in-store execution measurement, where visibility into shelf conditions directly affects sales volumes.