Know a shipment is late before it is.
A tracking map tells you where a shipment is. Predictive ETA tells you where it will end up — and flags the ones trending late early enough to recover them. Paired with exception management, it surfaces only what needs attention, to the person who can act. A capability of WHIZAI.
What is predictive ETA & exception management?
Predictive ETA uses machine learning on live milestones, carrier behaviour, port and lane history and external signals to estimate a shipment's likely arrival — not the static promised date. Exception management then surfaces the shipments that need attention — late, at-risk, held, short — ranked by impact and routed to the person who can act.
Together, as a capability of WHIZAI, they convert visibility from a passive map into an early-warning system: the team intervenes while a shipment can still be recovered, instead of explaining a missed delivery afterwards.
From live signal to acted-on exception.
For everyone who owns a delivery promise.
Fewer surprises, fewer penalties, calmer operations.
Late shipments cost money in penalties, expedites and lost trust — and most of that cost comes from finding out too late. Predicting arrivals and managing by exception means the team acts early, recovers more shipments, and spends its day on the few that matter instead of watching the many that don't. See how WHIZAI applies across your operation →
Predictive ETA questions
What is predictive ETA?
Predictive ETA uses machine learning on live milestones, carrier behaviour, port and lane history and external signals to estimate when a shipment will actually arrive — not the static promised date, but the likely one. Paired with exception management, it flags the shipments trending late early enough to do something about them.
How is this different from carrier tracking?
Carrier tracking tells you where a shipment is now and repeats the carrier's own ETA. Predictive ETA learns from history how that carrier, lane and port actually behave, and continuously re-forecasts arrival — often spotting a delay before the carrier acknowledges one. It converts passive visibility into an early warning.
What is exception management?
Instead of your team scanning screens to find problems, the system watches the whole flow and surfaces only the shipments that need attention — late, at-risk, held, short — ranked by impact and routed to the person who can act, ideally with a recommended next step. Work becomes managing exceptions rather than hunting for them.
Which modes and data sources does it use?
It works across air, sea and road, drawing on carrier and port milestones, EDI events, AIS/vessel data where available, and your own historical performance by lane and partner. The more of your operation runs on the platform, the sharper the prediction.
Does it just alert, or does it help resolve?
Both. It flags the at-risk shipment early and can propose the next step — a re-booking, a customer notification, an expedited leg — with a human approving the consequential actions. The goal is to recover the shipment while there is still time, not to explain the delay afterwards.
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