Inside TOPTEN’s Fast-Fashion Supply Chain: How AI Boosts Sales and Minimizes Stock

In the world of fast fashion, speed is everything—but accessories move even faster. With 65 stores across Israel and new items introduced at least twice a week, Israeli retail chain TOPTEN is pushing the limits of agility and efficiency. Behind the scenes, smart inventory technology is helping the company deliver fresh styles to customers while keeping stock lean. We sat down with Shay Haham, TOPTEN CEO, and Yogev Madmon, the chain’s logistics director, to learn how the brand is using AI to optimize its supply chain.

TOPTEN updates its product range daily. That sounds like a massive logistical challenge. How do you manage it?

Shay: You're right. We're a fast-fashion accessories chain, which means we release new products across all categories—from handbags to jewellery—at least twice a week. That freshness is essential. Our main challenge is to maximize sales while working with the minimal inventory needed to maintain capital efficiency.

Yogev: The main challenge is that new products don't have historical sales data, so predicting performance is tough. We used to do this work manually. Then we built a semi-automated system in-house, and a few years ago, we switched to Buffers.ai for inventory optimization.

What led you to adopt Buffers.ai? Wasn't your ERP system enough?

Yogev: No, our ERP couldn't handle our unique needs—for example, identifying bestsellers and automatically distributing them to all stores, beyond standard replenishment. That was a process we used to execute manually. Now, Buffers.ai does it automatically, and we see the impact in sales. We first heard about Buffers.ai from Urbanica, another retail chain in our group, and we're glad we made the switch.

What makes Buffers.ai different from other inventory optimization tools?

Yogev: Buffers.ai is built for dynamic retail environments like ours. It generates tailored recommendations for each product, per store, based on real-time sales and pre-set inventory levels. One feature we love is how it prioritizes which stores get in-demand products when stock is low. For example, if a popular handbag is running out of stock, Buffers.ai prioritizes stronger stores and automatically allocates it to the branches where it’s most likely to sell, based on historical performance.

The system automatically identifies high-performing stores and generates restocking recommendations tailored to each store’s predefined days of inventory (DOI), maximizing sales across the entire network. Another unique feature: Buffers.ai can look back one month and identify the three consecutive days with the highest sales for a specific item at a specific store. That peak 3-day sales volume then determines the buffer stock level (minimum inventory), assuming the store operates on a 3-day inventory model. This method is far more effective than rigid, one-size-fits-all minimum stock rules—it prevents excess inventory in weaker stores and lost sales in high-performing ones.

How do you measure the ROI of this system?

Yogev: I can't give you an exact figure yet, but we're definitely seeing value. The system helps preserve and scale the hands-on knowledge I've gained over thousands of days in logistics—and it translates that into smart, automated replenishment and procurement decisions.

Shay: Eventually, we’re able to identify trends faster and achieve more sales with less inventory - that’s capital efficiency.

Can you give a specific example of the system’s impact?

Yogev: Sure. Take Purim, the Israeli equivalent of Halloween. Our sales double during that period. Buffers.ai already knows this based on years of sales data and automatically adjusts stock levels accordingly. Each store's inventory days are increased in advance, and the system calculates exactly how much of each item is needed - way more efficient than blindly pushing stock to stores.

Have you customized the platform to your needs?

Yogev: Yes, heavily. Buffers.ai has been very responsive to our specific logistics and distribution strategy. For example, we have special rules for how to manage piercing display units in every store. If the display isn't full or visually appealing, even the products that are there sell worse. So we added a rule that ensures a minimum total quantity for the entire display group—not just per SKU. Once we define it, the system handles updates automatically.

Any final thoughts on working with Buffers.ai?

Yogev: It's more than just software. It’s a smart, adaptable platform that understands the unique demands of fashion retail. The speed, the variability, the visual merchandising—it all matters. Buffers.ai has helped us make better decisions, faster, with less waste and more results.