All case studies
Maritime / Port Operations

Real-Time Cargo and Berth Analytics for a Port Authority

31%
Reduction in average vessel turnaround time
18
Berths managed in real time
1,200+
Vessel calls per year processed automatically
4x
Faster incident reporting

A busy port running on spreadsheets and phone calls

A mid-sized European port authority handling over 1,200 vessel calls per year was managing berth allocation, cargo throughput, and port operations using a combination of spreadsheets, whiteboard schedules, and manual coordination between teams. The harbour master's office had no real-time visibility into berth occupancy, vessel ETA accuracy, or cargo handling progress across the terminal.

The knock-on effects were significant. Vessels waited at anchorage longer than necessary because berth readiness information was not centralized. Cargo handlers were deployed reactively, based on phone calls rather than data. When incidents occurred, assembling the operational record for insurers or port state authorities took days of manual effort. Competing ports in the region were investing in digital infrastructure, and the authority's leadership understood the window to close the gap was narrowing.

A live operational picture across every berth

BASAWE built a real-time port operations intelligence platform, ingesting AIS vessel tracking data, port management system records, and cargo handling system feeds into a unified Snowflake data layer. ETAs were calculated dynamically using AIS speed and position data, updated every 10 minutes, and pushed to berth planning dashboards automatically.

A berth management module gave the harbour master's office a live view of all 18 berths: current occupancy, incoming vessels, predicted arrival windows, and readiness status. Berth assignments that had previously been coordinated verbally were now managed through a shared interface with a complete audit trail.

On the cargo side, throughput tracking was built against terminal handling system data, giving operations managers a real-time view of container moves, dwell times, and crane utilization by shift. Incident reporting was automated using structured templates populated from the operational data layer, reducing what had been a 4-hour manual process to under an hour.

Measurable outcomes

Built with

Snowflake Python dbt AIS API integration Power BI Azure Data Factory PostgreSQL

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