AI in logistics.

Evaluate routing and dispatch through service levels, delivery exceptions, and human intervention.

Example workflow

Where agents work.

Route planner: Generates driver routes from stop count, time windows, and vehicle constraints, and re-routes around live disruption.
Shipment-status agent: Monitors carrier feeds, answers customer order-status questions, and escalates outliers to operations.
Exception triager: Detects missed pickups, late tenders, and damaged-on-arrival reports, and prioritizes those requiring immediate attention.
Driver dispatch copilot: Suggests the next assignment, accounts for hours-of-service limits, and pauses when a dispatcher overrides.
Inventory replenishment: Predicts SKU stock-outs and drafts purchase orders for planner approval.

On-time delivery: Agent-routed shipments delivered inside the promised window.
Exception turnaround: Median time from exception event to operations action.
Dispatch override rate: Frequency of dispatcher rejections of agent recommendations.
Customer-update latency: Time from carrier event to customer-visible update.
Cost per stop / per shipment: Operating-cost delta versus baseline routing.

Measurement depends on your source records and mapping. These are signals to evaluate, not automatically collected metrics.

Source coverage and outcome attribution depend on the records you provide.

We’ll review your source data and agree what to measure.