AI that routes smarter, dispatches faster, and sees exceptions before they happen.
Routing, dispatch, ETA prediction, exception handling.
Logistics AI has to make millions of decisions per day, in real time, on incomplete data. Route optimization that ignores traffic. ETA models that don't account for driver behavior. Exception handling that requires a human on every call. We've built AI logistics systems that actually reduce cost-per-delivery and customer escalations.
Use cases
Real-time route recalculation with traffic, weather, vehicle capacity, and time-window constraints — not just shortest-path algorithms.
Shipment-level ETA models trained on your historical delivery data that predict arrival within a 15-minute window 89% of the time.
Proactive detection of at-risk shipments 4–6 hours before SLA breach — with automated carrier communication and rerouting suggestions.
Location-level volume forecasts that optimize fleet positioning, driver scheduling, and hub inventory allocation.
Proactive delivery notifications, exception alerts, and AI-handled inquiry responses — cutting inbound customer service volume.
Carrier-level on-time performance, damage rate, and cost analytics — with AI-driven carrier allocation recommendations.
Why Evolve Edge
Real-time decision systems Our logistics AI makes decisions in milliseconds on live data — not batch jobs that are stale by the time the driver leaves the depot.
Driver and carrier behavior models ETA models that account for actual driver behavior, historical performance, and carrier-specific patterns — not just distance and speed limits.
Exception handling depth We've built exception handling systems that catch 'this shipment will miss SLA' 4 hours before it happens — when there's still time to act.
Client perspective
“ETA accuracy went from 71% to 89% within eight weeks. Fewer angry customers, fewer costly escalations. The math is simple.”
FAQ
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