A legacy multi-step dispatch workflow relied entirely on manual routing rules, leading to driver idle times, unpredictable traffic bottlenecks, and lack of end-to-end visibility.
The Challenge
Manual Bottlenecks in High-Velocity Cross-Dock Logistics
Key Problem Constraints:
- • Fragmented routing dispatch relying on human intuition
- • High API latency connecting IoT telematics hardware
- • Escalating fuel costs caused by suboptimal sub-route allocations
- • Lack of real-time multi-tenant driver dispatch UI
The Engineered Solution
The Neural Dispatch Engine
01. Real-Time Telemetry Stream
Decoupled Apache Kafka cluster ingesting live GPS telematics from 3,500+ active trucks at 50ms intervals with automated deduplication.
02. Genetic RL Routing Solver
Heuristic optimization engine executing sub-200ms dispatch re-evaluations against live weather, traffic anomalies, and driver shift constraints.
03. Automated Dispatcher Web UI
Responsive React SPA with WebSockets providing live map overlays, single-click route overrides, and automated anomaly push alerts.
Infrastructure Blueprint
System Infrastructure Blueprint
Apache Kafka
Python / PyTorch
Go Microservices
PostgreSQL (TimescaleDB)
Kubernetes (EKS)
AWS Cloud (Fargate)
42%
Transit Latency Reduction
1.4M
Shipments Routed Monthly
$3.8M
Estimated Annual Savings
99.99%
Platform Engine Uptime
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