Skip to main content


Digitizing Physical Retail with Autonomous Satellite Stores

micro retail

Physical retailers have long lagged behind their digital counterparts in areas like customer experience and cost efficiency. Where e-commerce can offer personalized experiences, frictionless purchasing, and automated inventory management, physical stores often struggle with inefficient manual processes as well as disconnected customer experiences.

But thanks to today’s advanced AI and computer vision capabilities, physical retail is now becoming more digital. For example, autonomous retail store solution provider Cloudpick bridges the gap between physical and digital retail with its autonomous satellite stores, offering a cashier-less micro-retail experience.

“Retailers are eager to bring their online business intelligence into the offline world, but traditional store formats with high rental costs and inflexible layouts make that very difficult,” explains Mark Perry, Cloudpick’s Head of International Business Development. “Our satellite stores let them expand sales channels at minimal risk.”

Cloudpick bridges the gap between physical and #digital #retail with its #autonomous satellite stores, offering a cashier-less micro-retail experience. @CloudpickTech via @insightdottech

Expanding Retail’s Reach with Satellite Stores

Unlike traditional brick-and-mortar stores or supermarkets, Cloudpick’s satellite stores focus on the “micro market,” meaning they are small, flexible, and movable. Therefore, these AI-powered micro-markets allow brands to tap into the burgeoning “micro-retail” or “pop-up” trend in a cost-effective manner.

These tiny stores are gaining popularity because they can be deployed in unconventional locations like corporate office lobbies, hotel entrances, and university campuses. This introduces new potential revenue streams for retailers in high-footfall areas while providing convenience to customers, according to Perry.

But finding a good location for these small stores can be a risky process. Despite their diminutive dimensions, setting up a traditional pop-up store is an expensive, time-consuming process—one that often suffers from unexpected delays and costs. Worse, if sales are disappointing, relocating the store can be difficult if not impossible. For example, traditional retail setups require lengthy leases and substantial upfront capital, make pivoting practically impossible.

The Plug-and-Play Autonomous Store

That’s where Cloudpick’s off-the-shelf model comes in. Cloudpick provisions a complete, pre-integrated hardware and software package that includes everything from the shelving infrastructure and refrigeration units to the cameras and edge AI systems. It operates as a plug-and-play solution that retailers can customize with their branding and product assortment. Everything is standardized and pre-configured, keeping customers’ total costs predictable.

Customers simply select their desired satellite store dimensions and Cloudpick handles the rest through an on-site installation team. Thanks to modular construction, a satellite store can be set up in less than eight hours and redeployed in a new location within half a day, according to Perry.

Moreover, the ability to rapidly disassemble and redeploy satellite stores reduces the risk of selecting a poor location. If a particular spot underperforms, Cloudpick can move the satellite store to another area, almost like relocating a food truck.

This unique flexibility allows retailers to experiment with locations in a low-risk manner while capitalizing on emerging customer micro-markets and high-traffic zones.

There’s a strategic benefit this format can bring to the traditional retailers. Not only for convenience store operators but large franchises like Walmart or Les Mousquetaires, that want to penetrate new markets and create brand awareness in urban areas.

The Cloudpick solution’s pre-configured format is built around on standardization, which allows both new market entrants and existing retailers to capture previously untouched locations. “An example of an existing convenience chain playing this game is Zabka in Poland, which has rapidly launched 60 Nano stores within a course of two years,” says Perry. The retailer aims to rapidly roll-out their stores in high-traffic urban locations. This additional density of stores within a small radius area creates more effective supply chain management.

AI Delivers an Enjoyable, Cost-Effective Consumer Experience

Once deployed, these satellite, micro-retail stores provide an AI-powered user experience. Customers can enter the store, scan a QR code, or swipe a card. While they shop, Cloudpick keeps track of the items they’ve picked up, using a combination of cameras and weight sensors in the shelves.

Perry explains that this multimodal sensing approach increases accuracy and can determine whether a customer picked up three candy bars or just one. Additionally, it gives retailers virtually unlimited flexibility in the stock they can carry, allowing shoppers to enjoy a broad selection of items that can be easily updated to keep up with their shopping preferences.

To check out, the customer simply walks out of the store—no cashier required, and no need to scan items. This is possible through Cloudpick’s AI system, which processes unified data to map product movements and ownership to specific customers, automatically checking out those individuals through an app as they exit.

With built-in mechanisms for coping with occlusions, crowd detection, and multi-camera syncing, Perry says Cloudpick’s satellite stores maintain a 98.5% accuracy rate for checkout recognition and billing despite the complexity of the autonomous shopping experience.

Maximizing ROI for a Satellite Store

By providing a cashier-less experience, retailers need only to hire staff to visit the store and resupply stock. These on-site visits can be optimized by a smart inventory management system that helps minimize product waste, overstock, and out-of-stock situations.

The computer vision and AI back end also analyze shopping patterns, demographic details like age and gender, and customer traffic flows. This provides retailers with data insights similar to online retail’s user analytics and remarketing capabilities—but in physical locations.

The platform is designed to bring the data-driven profiling and marketing precision of e-commerce into brick-and-mortar retail. “Retailers can integrate our APIs to optimize product assortments, layouts, pricing strategies, and promotions based on real-world shopper behaviors,” says Perry.

All of this is made possible by Intel technology. Perry explains that high-performance, power-efficient Intel® processors are key to running Cloudpick’s computer vision models for object recognition, customer tracking, and checkout automation. What’s more, tools like the Intel® Distribution of OpenVINO™ toolkit enable Cloudpick to constantly evolve its offerings.

The Future of AI-powered Satellite Stores

Between autonomous operations, data-driven inventory optimization, and minimal real estate footprint, Cloudpick’s satellite stores provide retailers with an affordable, future-proof roadmap to micro-retail. Future integrations could include interactive digital signage for personalized promotions and immersive product storytelling, Perry envisions.

Satellite stores are just the beginning of the AI transformation of how we buy in the real world in the retail industry.

This article was edited by Christina Cardoza, Editorial Director for

About the Author

Brandon is a long-time contributor to going back to its days as Embedded Innovator, with more than a decade of high-tech journalism and media experience in previous roles as Editor-in-Chief of electronics engineering publication Embedded Computing Design, co-host of the Embedded Insiders podcast, and co-chair of live and virtual events such as Industrial IoT University at Sensors Expo and the IoT Device Security Conference. Brandon currently serves as marketing officer for electronic hardware standards organization, PICMG, where he helps evangelize the use of open standards-based technology. Brandon’s coverage focuses on artificial intelligence and machine learning, the Internet of Things, cybersecurity, embedded processors, edge computing, prototyping kits, and safety-critical systems, but extends to any topic of interest to the electronic design community. Drop him a line at, DM him on Twitter @techielew, or connect with him on LinkedIn.

Profile Photo of Brandon Lewis