Supply Chain Case Study
Skyline Logistics
Year2023
RoleBack-end & DevOps
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
EcoVibe
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