Edgify Raises $9M to Put AI Where Retail Losses Happen

Jan de Vries · 2026-08-10

Retail shrinkage is a massive problem. In the United States alone, retailers lose billions of dollars every year to theft, fraud, and operational errors. Most AI solutions try to tackle this from the cloud, but what if the intelligence lived right where the transaction happens? That's the bet Edgify is making, and it just got a big vote of confidence. London-based Edgify, an edge AI infrastructure company, has raised $9 million in Series A+ funding to accelerate the rollout of its platform. The round was backed by Rank Ventures and Mangrove Capital Partners, bringing the company's total funding to $25 million. This isn't just another AI startup story; it's about fundamentally changing how physical stores detect and prevent loss. ### The Core Problem: Cloud AI Doesn't Fit Retail Most AI systems rely on heavy infrastructure, constant connectivity, and centralized control. That works fine for some industries, but it doesn't scale in the real world of a busy grocery store. Think about it: a typical store has dozens of smart devices—self-checkouts, cameras, scales, and point-of-sale systems. Sending all that data to the cloud for analysis creates latency, raises costs, and raises serious privacy concerns. Edgify flips the script. Instead of sending data to the cloud, it trains and runs AI models directly on the edge devices themselves. This means the hardware in a store can learn locally, share insights across the entire network, and make real-time decisions without a single byte of raw data leaving the building. It's a fleet of machines that can see, decide, and learn together. ### How Edgify's Edge AI Actually Works Founded in 2019, Edgify provides a single, hardware-agnostic platform that connects, orchestrates, and trains AI models across in-store equipment from various manufacturers, including major partners like Zebra Technologies and Bizerba. The company converts these isolated devices into one coordinated intelligence layer. Here's what that means in practice: - **Loss prevention at self-checkout:** The system recognizes produce, identifies scan avoidance, and flags product-switching in real time. - **Cart-based loss detection:** It can spot items that were never scanned and alert staff before the customer leaves. - **Operational efficiency:** By handling data locally, it reduces cloud infrastructure costs and lowers latency dramatically. This approach directly addresses a critical retail challenge. Competitors often rely on expensive servers in dedicated back rooms that take months to install. For a standard grocery store, that's just not practical. Edgify's solution runs on the equipment stores already have, which makes adoption much faster and more affordable. ### Beyond Retail: A Platform for the Physical World While retail is the proving ground, the underlying technology has much broader applications. Nadav Israel, CEO and Co-founder of Edgify, sees this as just the beginning. "The operational friction Edgify has solved in grocery and convenience stores can be replicated in any industry where fleets of devices meet the physical world," he said. That expansion is already happening. Edgify is moving into quick-service restaurants, distribution centers, and apparel. The vision is to turn millions of isolated machines into self-learning, real-time networks that operate independently of the cloud. This funding will fuel that growth, deploying the intelligence layer across the global industrial landscape. Mitchell Goldman, COO at Edgify, put it well: "Retail is the ultimate testing ground for edge AI, because it has more smart devices per site than almost any other industry, and real-world constraints on cost, latency, and privacy." Loss prevention is where the value shows up first, but the real breakthrough is the platform itself—translating isolated in-store hardware into a unified system for future AI applications. ### What's Next for Edgify Over the next few months, Edgify will expand its platform to manage the complete lifecycle of AI models across physical retail. Headquartered in London, the company already works with leading grocery retailers and technology partners across the United States and Europe. With this fresh capital, they're poised to take their edge AI infrastructure from a retail solution to a standard for any industry where devices meet the physical world.