Aurora Logistics — Intelligent Routing & Automation
Codexium partnered with Aurora Logistics to strengthen operational efficiency, implement real-time route optimization, and deploy predictive forecasting systems that transformed their logistics network end-to-end.
Overview
Aurora Logistics operates a nationwide distribution network of retail, food-supply, and multi-stop delivery routes. As demand accelerated following a national expansion, Aurora experienced mounting pressure on delivery times, fuel efficiency, driver scheduling, and warehouse coordination.
Codexium engaged with their leadership to modernize the company's routing intelligence, operational dashboards, and long-term forecasting capabilities—all without disrupting ongoing distribution operations.
Key Challenges
- Routing decisions required manual driver expertise, causing delays and inconsistencies.
- Data across fleet, warehouse, and customer systems was fragmented and lacked real-time syncing.
- Fuel consumption spiked 14% due to inefficient route clustering.
- Warehouse load planning could not anticipate demand surges or late-day delivery bottlenecks.
Impact & KPIs
27%
Faster Delivery Times18%
Fuel Efficiency Improvement34%
Warehouse Throughput BoostCodexium’s Solution
Codexium delivered a fully integrated, three-pronged modernization approach:
Intelligent Routing Engine
We implemented a real-time route optimization system using demand clustering, traffic data, and driver scheduling constraints.
Predictive Demand Forecasting
Forecasting models anticipated load surges, labor demand, and late-day bottlenecks with up to 92% accuracy.
Unified Operational Dashboard
Leadership gained a real-time command center across fleet status, route performance, warehouse capacity, and delivery SLAs.
Results
Within 120 days, Aurora Logistics saw measurable improvements across delivery performance, cost optimization, and customer satisfaction.
- Delivery times improved by 27% with smarter route sequencing.
- Fuel efficiency increased by 18% through precision route clustering.
- Warehouse processing throughput increased by 34% through improved forecasting.
- Driver satisfaction improved due to more predictable schedules and reduced overtime routing.