Dockflow
Predictive Port Logistics Platform Across 12 Terminals
A predictive logistics SaaS platform that optimizes container terminal operations using real-time data, ML forecasting, and intelligent scheduling across the Rotterdam port ecosystem.
The Challenge
Port terminal operators faced 30% average idle time on cranes and vehicles due to unpredictable vessel arrivals, weather disruptions, and manual scheduling. Each hour of idle time cost €12K across the terminal network.
Our Solution
Dockflow combines AIS vessel tracking, weather data, historical patterns, and terminal sensor feeds into a predictive scheduling engine. The platform generates optimized crane and truck assignments 48 hours ahead, continuously adjusting as conditions change.
Architecture
- Real-time data ingestion from 200+ IoT sensors per terminal
- ML forecasting engine (vessel ETA, weather impact, throughput)
- Next.js dashboard with real-time terminal visualization
- Event-driven microservices on Kubernetes (AWS EKS)
- Integration with TOS (Terminal Operating Systems) via custom APIs
Results
-35%
Idle time
22%
Fuel savings
Series B
Raised post-launch
Client Testimonial
“Since deploying Dockflow, our terminal efficiency improved dramatically. The predictive scheduling alone saved us €4.2M in the first year.”
Pieter van den Berg
COO, Dockflow