CargoAi's new AI-driven tracking service forecasts air cargo delays and operational risks, enhancing shipment management for airlines and forwarders.
CargoAi has introduced a predictive tracking service that utilizes artificial intelligence to anticipate operational risks and shipment delays in air cargo. The new module is accessible through CargoMART and the CargoCONNECT Track and Trace API, as reported by London's Air Cargo News.
The service integrates machine learning models trained on millions of past shipments with live airline flight updates to forecast the timing of key milestones in the cargo journey. These milestones include documentation submission, acceptance, manifesting, departure, arrival, freight availability, and final delivery.
Predictions are refreshed as new data is received, enabling operational teams to detect risks earlier. Airlines can identify shipments at risk of missing flights if they have not reached acceptance or manifesting before cutoff times. Alerts can be triggered to stations or GSAs to release blocked capacity or prioritize high-risk cargo.
CargoAi stated that the data can also be utilized to benchmark station performance and identify recurring bottlenecks. Forwarders gain visibility on shipments flagged as at risk, while ground handlers can use predictions to prioritize acceptance, automate pre-alerts, and feed risk levels into internal dashboards.
