Case study
Real-Time Logistics Orchestration & Predictive Analytics Engine
Built a high-performance Command and Control center for large-scale distribution networks, enabling real-time route optimization and 99.9% delivery reliability.
Overview
Modern logistics networks generate millions of data points per second, making it difficult to process data fast enough for real-time operational decisions.
Approach
Engineered a scalable event-driven architecture with a custom WebSocket implementation for sub-second telemetry sync, ensuring a Global Map View accurate to within 100ms.
Utilized Redis for high-throughput state management, reducing primary database load by 60%, and implemented a stream-processing layer for predictive bottleneck identification.
Tech Stack
Outcome
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