Artificial intelligence is becoming an increasingly important part of e-commerce logistics, but some of the biggest opportunities lie beyond online storefronts. Warehouse operations, inventory handling, and returns processing remain among the most complex and labor-intensive parts of retail. Zalando’s latest investment in robotics startup Sereact reflects how retailers are looking to use AI to improve these behind-the-scenes processes.
Zalando has joined Sereact’s ongoing Series B funding round as a strategic investor, increasing the round to $116 million. The investment aims to accelerate the development of AI-powered robotics to automate warehouse tasks, particularly the handling of returned products. For Zalando, where returns are a significant part of its fashion e-commerce business, improving this process could meaningfully impact efficiency and operational costs.
Returns are an unavoidable part of online fashion retail. Unlike many other product categories, clothing often requires customers to order multiple sizes or styles before deciding what to keep. Every returned item must be inspected, sorted, and prepared for resale before it can return to inventory.
Many of these tasks are still performed manually because they require robots to recognize different products, assess their condition, and manipulate objects with varying shapes and materials.
Sereact is developing AI software designed to address exactly these challenges. Its Cortex platform enables warehouse robots to identify objects, adapt to unfamiliar items, and perform picking, sorting, inspection, and returns processing with minimal human intervention. Instead of relying on predefined rules for every product, the system learns from operational data and applies that knowledge to new situations.
Much of the recent discussion around AI has focused on chatbots, generative AI, and customer-facing applications. However, another area is advancing rapidly: physical AI.
Rather than generating text or images, physical AI allows machines to understand their surroundings and perform real-world tasks. In warehouses, this includes identifying products, navigating storage locations, and handling items with different sizes, packaging, and materials.
For retailers, this creates opportunities to automate processes that have traditionally been difficult for conventional robotics. Returns processing, mixed-item picking, and quality inspection all require systems that can respond to changing environments rather than follow fixed instructions.
As e-commerce volumes continue to grow, these capabilities are becoming increasingly valuable.
Although robotics relies heavily on computer vision and sensors, product information also plays an important role.
Warehouse systems need to distinguish among thousands of products, account for packaging variations, verify dimensions, and ensure items are placed in the correct location. Accurate product identifiers, specifications, and standardized attributes help AI systems make these decisions more reliably.
For retailers and brands, maintaining structured product data supports not only e-commerce websites but also warehouse technologies that are increasingly responsible for fulfillment operations.
As AI becomes more deeply integrated into logistics, product data is extending beyond customer-facing applications and into the infrastructure that supports warehouse automation.
Zalando’s investment highlights a broader shift in e-commerce. Retailers are no longer investing in AI only to improve search, recommendations, or customer service. Increasingly, they are applying AI to optimize fulfillment, reduce operational costs, and improve efficiency throughout the supply chain.
For companies handling millions of orders each year, even small improvements in warehouse productivity can have a significant business impact. AI-powered robotics offers one way to achieve those gains while helping retailers process growing order volumes more efficiently.
As AI continues to deepen its presence in e-commerce operations, the combination of intelligent automation and reliable product data will play an increasingly important role in shaping the next generation of fulfillment and logistics.
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