weR and RGIS Expand AI Retail Shelf Intelligence

weR and RGIS expand strategic collaboration, deploying AI-powered retail shelf intelligence to modernize store audits across Europe and the United States.

weR's Shelf Engine runs on-device AI and AR on standard mobile phones, identifying products and detecting shelf execution gaps in real time.
RGIS, with 34,000 employees across 40+ countries and 230,000+ annual inventory cycles, scales the deployment through its global retail network.
Out-of-stock events cost retailers more than $1 trillion annually; the AI-integrated shelf optimization market is forecast to reach $13.1 billion by 2033.

Lead

weR AR Cloud and RGIS Inventory Specialists on June 10, 2026 announced an expansion of their strategic collaboration to bring retail shelf AI technology to large-format retailers across Europe and the United States. The joint deployment combines weR's mobile-first Shelf Engine platform with RGIS's large-scale retail execution infrastructure, targeting one of the industry's costliest persistent problems: the gap between what inventory systems record and what store shelves physically show.

What Happened

The expanded arrangement deepens an existing relationship, now integrating the weR Shelf Engine into RGIS Count Assurance, the company's inventory-validation offering. The combined solution runs directly on standard mobile phones — no fixed cameras, robotics, or specialized hardware required — using on-device AI models trained to recognize thousands of SKUs and shelf conditions in live retail environments.

Field teams using Count Assurance validate inventory at shelf level while augmented reality overlays product identification on the device's live camera view, flagging discrepancies and guiding corrective actions in real time. Traditional shelf audits, planogram validations, and operational inventory checks typically demand significant manual labor and store-team overhead; the joint platform is designed to compress that burden while improving execution consistency, product visibility, and retail intelligence at the store level. The technology has been validated across hundreds of stores globally ahead of the broader commercial rollout.

Strategic Context

The announcement arrives as retailers face compounding pressure to close the physical-digital execution gap. Out-of-stock events cost global retailers more than $1 trillion per year, with chronic shelf execution failures eroding revenue, brand equity, and shopper retention. The broader AI in retail market reached $18.4 billion in 2026, while the shelf image recognition AI segment alone expanded from $1.82 billion in 2025 to $2.3 billion in 2026 — a 26.6% annual growth rate. AI-integrated retail shelf optimization systems are projected to grow at 20.2% CAGR through 2033, reaching $13.1 billion.

RGIS brings operational scale that few competitors can match. The company performs more than 230,000 inventories globally per year across more than 40 countries, supported by more than 200 offices and 34,000 employees. That infrastructure allows the weR RGIS deployment to move rapidly from validation into broad commercial rollout — a bottleneck that has historically constrained competing point solutions dependent on building their own field networks.

AI and Technology Angle

The weR Shelf Engine operates on-device rather than through continuous cloud connectivity, enabling real-time shelf analysis even in stores with limited bandwidth. Specialized AI models have been trained to recognize product appearances, planogram layouts, and out-of-stock or misplaced conditions at shelf level. Augmented reality surfaces identified gaps directly in the field associate's line of sight, reducing interpretation time and enabling immediate corrective action without manual reporting workflows.

Amit Chachek, Founder and CEO of weR AR Cloud, described the deployment as part of a broader industry inflection: AI in retail is beginning to understand the physical world at scale, with store shelves among the first large-scale environments where spatial AI can bridge physical operations with real-time decision-making. The technology roadmap extends the current mobile-phone form factor toward AI wearables and smart glasses, which would eliminate the step of raising a handset entirely.

What Comes Next

The joint deployment is structured to scale through RGIS's established retail network in Europe and the United States, with additional markets accessible through the company's 40-country operational footprint. As the retail shelf AI segment expands and hardware form factors evolve, the weR-RGIS platform is positioned to grow its addressable base without requiring new infrastructure investment from retail clients. Integration with downstream data systems — including replenishment, demand planning, and supplier compliance platforms — represents a logical next step as real-time retail intelligence becomes a standard operational expectation.

Outlook

The weR and RGIS expansion targets a structurally significant cost center in global retail through a mobile-first approach that lowers the adoption barrier by eliminating dedicated hardware requirements. With RGIS's network providing immediate distribution reach and the Shelf Engine already validated across hundreds of stores, the collaboration is positioned to capture a meaningful share of the $13.1 billion shelf optimization market analysts project by 2033. Execution at scale, and eventual integration with enterprise data environments, will determine how quickly that potential is realized.