Shipping AI
Know which carrier is about to let you down.
A late parcel is not a shipping problem, it is a support ticket, a refund and sometimes a lost customer. Shipping AI scores the risk on your lanes while you can still do something about it.
Shipping AI
The cheapest label is not the cheapest shipment.
A late parcel costs you a support ticket, a refund and sometimes the customer. Zineps reads how each service has actually been performing on your lane and says so before you buy the label, not after the buyer emails you.
- Delay risk scored per service, per lane
- An alternative offered when the risk is real
- Customs and VAT checks before the parcel leaves
- Return patterns fed back into the next recommendation
Zineps moved this shipment to Routewise Standard. One day later, and far more likely to actually arrive on it.
Example performance data. Illustrates the feature, not a live model output.
What it watches, and what it does about it.
Predictive delay detection
Historical and live performance per carrier, per lane. When a service starts slipping, the shipment is flagged before the label is bought and an alternative is offered.
Smart routing
The fastest and least expensive route for the shipment in front of you, adjusted for the conditions on that lane rather than a rate card average.
Rate intelligence
Weight, volume, destination and urgency scored together, because the cheapest rate card line is regularly not the cheapest shipment.
Cross-border compliance
Customs data, VAT treatment and import restrictions checked before dispatch, which is where held parcels and surprise returns actually start.
Learning from returns
Return patterns feed back into the recommendations, so the services that quietly generate returns stop being recommended.
Explainable, not magic
Every recommendation shows the numbers behind it: on-time rate, price difference, transit days. You can disagree with it and pick something else.
It shows its working.
A recommendation you cannot interrogate is just an opinion with better formatting. Every suggestion carries the numbers that produced it, so you can check them and overrule them.
- On-time performance for the service, on your lane, over a stated window
- The price difference against the option you were going to pick
- Transit days, and how reliably that window has been met
- Why the flagged option was flagged, in a sentence
WHY THIS RECOMMENDATION
- 01PerformanceSwiftline Express held 71% of its window on AMS to VIE over the last 30 days, against a 94% baseline for the lane.
- 02CauseNine consecutive days of hub congestion, not a one-off weather event.
- 03AlternativeRoutewise Standard held 96% over the same window and costs €1.20 less.
- 04Trade-offOne extra day in transit. Stated, not hidden.
Example reasoning. Illustrates the output, not a live model.
Reasonable scepticism, answered
Only if you tell it to. By default it recommends and shows its reasoning. You can let a rule take the recommendation automatically, or leave the decision with a person.
Carrier and service performance on your lanes, transit times, rate differences, customs and restriction data, and return patterns. It is delivery data, not a language model guessing.
AI delay prediction and advanced analytics are on the Scale-up and Enterprise plans. Rate comparison and matching are on every plan, including the free one.
You see the score, not just the verdict, so a recommendation you disagree with is easy to overrule. Outcomes feed back in, which is how the scoring on your lanes improves.
Stop finding out from the customer.
Delay prediction and advanced analytics are on Scale-up and above. Rate matching is on every plan, including free.