NEW YORK, June 10, 2026 /PRNewswire/ — Following successful validation with leading global retailers and enterprise partners across Europe and the United States, weR and RGIS are expanding their collaboration to help retailers modernize shelf operations through artificial intelligence-powered mobile technology.
The collaboration brings together RGIS’s large-scale retail execution capabilities with weR’s proprietary Shelf Engine platform, an artificial intelligence- and augmented reality-based system designed to digitize shelf conditions, identify execution gaps in real time, and guide corrective actions directly from standard mobile phones.
Traditional shelf audits, inventory checks and planogram validations often require significant manual labor and operational overhead from store teams. Through this joint deployment, retailers can reduce the amount of time traditionally spent on shelf auditing and operational shelf checks, while improving execution consistency, product visibility, and real-time store intelligence.
Unlike fixed camera systems, robotics infrastructure or manual reporting workflows, the platform runs directly on mobile devices using specialized on-device AI models trained to recognize thousands of products and shelf conditions in real retail environments.
The technology has already been validated across hundreds of stores globally and is designed to scale rapidly through RGIS’s retail execution network across Europe and the United States.
“This is part of a much larger industry transition where AI is beginning to understand the physical world,” said Amit Chachek, Founder and CEO of weR AR Cloud LTD. “Retail shelves are becoming one of the first large-scale environments where AI can bridge physical operations with real-time intelligence, execution, and decision-making.”
This collaboration marks an important step toward a broader shift in retail: spatial AI systems operating through mobile devices, AI wearables, and future smart glasses capable of understanding products, environments, and operational workflows in real time.
“RGIS Count Assurance demonstrates how augmented reality can transform inventory counting. By overlaying digital intelligence onto the physical inventory environment, we can provide instant verification, improve count accuracy, and give customers greater confidence in their inventory data. This is more than an enhancement to the stocktaking process, it is a glimpse into the future of inventory management,” said Asaf Cohen, CEO of RGIS.
As AI moves beyond screens and internet-based interactions into physical spaces, technologies combining computer vision, spatial understanding and wearable computing are positioned to become a foundational layer for the future of retail and frontline operations.
About weR AR Cloud LTD
weR AR Cloud LTD develops AI-powered shelf intelligence and augmented reality technology for retail operations. Its proprietary Shelf Engine platform enables retailers, brands, and field teams to digitize shelf conditions, detect execution gaps, validate planograms, and guide corrective actions directly from mobile devices. Visit www.wer.io for more information.
About RGIS
RGIS is a global market leader in inventory and data collection services, delivering technology-enabled solutions that help organizations gain greater visibility, accuracy, and control over their inventory and operational processes. With a presence in more than 66 countries and decades of industry expertise, RGIS supports businesses worldwide with inventory management, retail execution, supply chain optimization, and data intelligence services. Visit rgis.com for more information.
Media Contact
Amit Chachek
Founder and Chief Executive Officer, weR AR Cloud LTD
551-580-2290
416435@email4pr.com
Gil Gavish
Founder and Consultant, weR AR Cloud LTD
917-561-0085
416435@email4pr.com
Karen Hancock-Tims
Marketing & Sales Support Manager – International, RGIS Inventory Specialists Limited
011-44-7432-552524
416435@email4pr.com
Neil Storey
Chief Revenue Officer, RGIS Inventory Specialists Limited
416435@email4pr.com
SOURCE RGIS