Feuille de route IA pour les entreprises du secteur Retail & E-commerce à Split

Retailers in Split face one of the most extreme seasonal demand curves in the Adriatic, where foot traffic in the Old City can increase by 400% during the peak months of July and August compared to January. We implement Long Short-Term Memory (LSTM) neural networks that ingest not only historical sales data but also real-time cruise ship docking schedules and flight arrival data from Split Airport (SPU). By correlating local weather patterns with tourist demographic shifts, our AI transformation models allow retailers to optimize stock levels for high-turnover luxury goods and souvenirs, reducing 'stock-out' lost revenue by an estimated 22% during the high season.

Split’s retail environment serves a hyper-diverse linguistic base, from local Dalmatians to international travelers from the US, UK, Germany, and Italy. We deploy custom-tuned Large Language Models (LLMs) that handle customer service in 15+ languages with native-level fluency. Beyond simple translation, these agents are trained on local retail nuances—such as tax-free shopping procedures (PDV refunds for non-EU citizens) and specific sizing conversions—ensuring that the digital experience on the Riva is as seamless as a boutique visit.