Logistics ops · Production
Ocean Visibility by project44: Wan Hai container tracking with ML-powered predictive ETAs
The problem
Shippers and logistics teams lack real-time visibility into container location, ETA, and exceptions such as delays or D&D fee incursion for shipments moving through carriers like Wan Hai.
Workflow diagram · grounded in source
1
Container number lookup
trigger
“track your Wan Hai containers using the MBL / BL Number (Master Bill of Lading) or Container Number”
2
ML status and ETA update
ai_action
“Our machine learning algorithms automatically update shipment status and predictive ETAs in real-time”
3
Exception identification
output
“swiftly identify container shipments that are delayed or stuck in trans-shipment, incurring D&D fees”
Reported outcome
Ocean Visibility connects users to carriers including Wan Hai and applies machine learning to provide real-time shipment status updates and predictive ETAs, enabling proactive exception management.
Reported stack
Ocean Visibility
Frequently asked questions
What did this team achieve with this AI workflow?
Ocean Visibility connects users to carriers including Wan Hai and applies machine learning to provide real-time shipment status updates and predictive ETAs, enabling proactive exception management.
What tools did this team use?
Ocean Visibility.
How is this logistics ops AI workflow structured?
Container number lookup → ML status and ETA update → Exception identification.