Next Generation AI warehouse automation
Paper is the new enemy.
Our client, a leading European distribution center, was struggling with inefficient order processing that resulted in delayed dispatches and missed delivery windows. Manual inventory tracking and paper-based picking systems were creating bottlenecks during peak hours, causing customer dissatisfaction and lost revenue. We implemented an AI-powered warehouse management system that integrated computer vision for real-time inventory monitoring, predictive algorithms for optimal route planning, and automated dispatch scheduling.
From Manual Chaos to Automated PrecisionRetry
The solution reduced average processing time by 67%, cutting dispatch delays from 4 hours to just 80 minutes. Smart picking routes optimized warehouse floor movement, while machine learning models predicted demand patterns to pre-stage high-volume items. Within three months of deployment, on-time delivery rates increased from 78% to 96%, and the warehouse achieved a 40% improvement in daily throughput without additional staffing costs.