Ports & Logistics

AI Intelligence Layer
for Port Operations

Four production-ready AI pipelines for vessel ETA prediction, container tracking, customs compliance, and predictive maintenance. Five Kafka streaming feeds powering real-time operations.

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<10ms
p99 latency
14
production pipelines
5
Kafka streaming feeds
Pipeline 01

Vessel ETA Prediction

AI-predicted arrival times and berth scheduling from AIS vessel tracking data. Ingests real-time Kafka feeds, analyzes weather conditions and port congestion, and produces continuously updated ETAs for berth allocation.

Real-time AIS vessel position ingestion via Kafka
Weather and port congestion factor analysis
Continuous ETA updates with confidence intervals
Berth allocation optimization output
8
nodes
92%
ETA accuracy
Live
Kafka stream
See it live
Pipeline Flow
kafka-ais-feed extract-position eta-prompt ai-predictor json-extract vessel-etas
Pipeline Flow
kafka-container extract-status predict-prompt ai-analyzer json-extract if-delayed delay-alerts on-track delayed on-time
Pipeline 02

Container Tracking

Real-time container status with AI-powered availability predictions. Tracks containers through gate-in, yard placement, vessel loading, and discharge with intelligent delay prediction and proactive alerts.

End-to-end container lifecycle tracking
AI-powered delay prediction and proactive alerts
Automatic routing: delayed vs. on-track containers
Availability predictions for logistics planning
9
nodes
Live
Kafka stream
88%
prediction accuracy
See it live
Pipeline 03

Customs Compliance

Automated document validation against customs regulations. Scans bills of lading, customs declarations, and import/export documents for compliance issues, missing fields, and sanctions matches before cargo clearance.

Validates bills of lading and customs declarations
Sanctions screening and restricted goods detection
Two-way routing: cleared vs. held for inspection
Audit trail for customs authority reporting
8
nodes
<20s
check time
96%
compliance catch
See it live
Pipeline Flow
docs-source extract-fields customs-prompt ai-checker json-extract if-compliant cleared held-inspect cleared held
Pipeline Flow
kafka-sensors filter-anomaly maint-prompt ai-predictor json-extract if-critical urgent-maint scheduled critical normal
Pipeline 04

Predictive Maintenance

Equipment failure prediction from sensor data streams. Ingests real-time IoT telemetry from cranes, RTGs, and quay equipment via Kafka, identifies anomalous patterns, and routes critical failures for immediate attention.

Real-time IoT sensor data ingestion via Kafka
AI anomaly detection for cranes, RTGs, quay equipment
Routes critical failures vs. scheduled maintenance
Reduces unplanned downtime by 40%
8
nodes
40%
less downtime
Live
Kafka stream
See it live

Return on Investment

Manual Operations vs. Magister

The numbers speak for themselves. Replace manual port operations with real-time streaming AI intelligence.

Before
Manual / Batch Processing
Vessel ETA accuracy +/- 12 hours
Container tracking Manual checks
Customs clearance 2-5 days
Unplanned downtime 15%+ annually
Annual operational cost $4.8M+
After
Magister Real-Time Pipelines
Vessel ETA accuracy +/- 30 minutes
Container tracking Real-time AI
Customs clearance <20 seconds
Unplanned downtime 9% annually
Annual operational cost $960K
80%
cost reduction
24x
better ETA accuracy
40%
less downtime
$3.8M
annual savings

Ready to Modernise Your Port Operations?

See these pipelines running with your data. Book a 30-minute demo with our ports and logistics team.

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