AI robotics brings shoebox handling into fashion logistics
S.OLIVER GROUP is expanding automation at its logistics facility in Dettelbach, Germany, with an AI-powered robotic system from Nomagic. The project is designed to automate induction activities across a varied fashion assortment, including shoeboxes.
For fashion warehouses, product diversity is a persistent obstacle to automation. Garments and accessories can differ sharply in size, shape, packaging and rigidity. Shoeboxes are a particularly significant challenge for general-purpose picking systems, limiting the proportion of stock that can be processed automatically.
Robotic picking for a difficult product category
Nomagic’s Shoebox Picker combines AI-based visual perception with adaptable robotic handling. Its role in the S.OLIVER GROUP installation is to make shoebox processing part of the same broader operational flow as other fashion items. This could reduce the need for repeated manual handling while allowing the company to automate a larger share of its assortment.
The stated objective is not simply to replace an individual task. By applying robotics to induction, S.OLIVER GROUP is building a more scalable logistics setup that can accommodate future increases in volume. A wider automated flow can also support more consistent processes in an environment where seasonal demand and product variety put pressure on warehouse operations.
Automation strategy aimed at growth
Nomagic chief executive and co-founder Kacper Nowicki said the project demonstrates the use of the company’s “Physical AI” approach in a real logistics environment, with reliability across a broader range of fashion products. Markus Steinmann, S.OLIVER GROUP’s managing director for logistics, described the collaboration as a continuation of the retailer’s automation strategy.
According to Steinmann, repetitive logistics activities offer scope for higher efficiency, greater flexibility and stronger operational performance. The Dettelbach project therefore illustrates a wider industrial trend: AI-enabled robots are moving beyond standardised objects and into mixed-product workflows where adaptability is as important as speed.
