ZEOS has developed a dynamic inventory optimization system for e-commerce that addresses the complexities of managing vast inventories across multiple warehouses. The system leverages AI-driven demand forecasting and a cost-optimization framework to enhance replenishment decisions, aiming to minimize inventory costs while adapting to fluctuating demand and supply conditions. Key components include a scalable demand forecasting pipeline and a real-time inventory optimization service for partners.

The article discusses the role of designers in training machine learning models, exploring the balance between design and technical expertise. It highlights the importance of collaboration between designers and data scientists to create effective and user-friendly AI systems. The piece raises questions about the evolving skill sets required in the design field as technology advances.