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Hand-drawn illustration of a route line that bends around obstacles

AI for Logistics

Real-Time Route Optimization: How AI Adapts to Traffic, Weather, and Capacity

The dispatch-time route is the easy half. Re-routing through a day of disruptions is where AI logistics actually earns its seat. Here's the architecture that handles it.

5 min read • Mar 21, 2026

Hand-drawn illustration of a chart with peaks and valleys

AI for Logistics

Demand Forecasting in Logistics: Where AI Beats Spreadsheets

Most logistics operators run demand forecasting in Excel. ML upgrades typically deliver 10-25% accuracy improvement, which compounds through inventory, capacity, and labor.

5 min read • Mar 16, 2026

Hand-drawn illustration of routes connecting points on a small map

AI for Logistics

AI for Logistics: Route Optimization and Demand Forecasting

AI in logistics is two distinct problems sharing a domain — route optimization runs on heuristics and ML, demand forecasting runs on classical ML. Both deliver, neither does what vendors claim alone.

7 min read • Mar 10, 2026

Hand-drawn illustration of a delivery van approaching a small house

AI for Logistics

AI for Last-Mile Delivery: Cutting Cost and Improving Accuracy

Last-mile is the most expensive segment of logistics — typically 40-60% of total delivery cost. AI's biggest logistics wins live here. The four levers that actually move the metrics.

5 min read • Mar 5, 2026