AI · June 23, 2026 · 8 min read
AI route optimization and ETA accuracy in practice
Predictive ETAs are one of the highest-ROI AI applications in logistics, provided the historical data describes what actually happened rather than what dispatch typed in.
Data first, model second
Accurate arrival and departure timestamps, dwell durations, and stop-level geofences matter more than model architecture. Most ETA projects are really instrumentation projects.
Model the dwell, not just the drive
Drive time is well solved by routing APIs. Variance lives in facility dwell, detention, and appointment behavior — which is exactly what a per-facility model can learn.
Optimize against real constraints
Hours of service, appointment windows, equipment types, and driver domicile turn a routing toy into a usable plan. Constraints beat clever objective functions.
Measure in customer terms
Track percentage of shipments arriving inside the promised window, not mean absolute error in minutes. The business only feels the former.
Building something like this?
Wve Labs designs and builds custom logistics apps, portals, and platforms. Tell us how your freight moves and we'll scope the build.