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AI automation · Logistics optimization

Quantyf Logistics Optimization Backend

Python service layer and optimization algorithms for logistics planning workloads (Sept–Dec 2024).

The Challenge

Quantyf needed backend services that could run optimization workloads reliably under planning-session bursts.

The Proven Solution

We implemented Python backend modules and APIs for optimization runs with clear job boundaries and performance-sensitive paths.

PythonOptimizationREST APIsLogistics planning

The Technical Proof

  • Production-oriented API design for optimization workloads.
  • Performance focus on planning-session throughput.
  • Three-month remote delivery (Sept–Dec 2024).

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