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Supply Chain Case Study

Skyline Logistics

Year2023
RoleBack-end & DevOps
Skyline Logistics

The Challenge

Inaccurate route planning was costing the company millions in fuel and lost time. They needed a system that could adapt to traffic and weather changes instantly.

The Solution

We developed a proprietary routing engine using Dijkstra algorithm variants and integrated it with real-time GPS streams. We utilized Kafka for high-throughput data processing.

The Impact

"Fuel costs decreased by 18% and delivery windows accuracy increased to 98.5%."

Tech Stack

PythonKafkaApache SparkKubernetesGoogle Cloud
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