Logistics
FleetIQ — Logistics ML
Demand forecasting pipelines with feature store and model monitoring.
2022–2024
Problem
- Manual forecasts with high variance and late updates.
- No drift detection or rollback strategy.
Approach
- Pipelines with backtesting; registry for lineage.
- Canary model serving + A/B evaluation.
- Data drift and performance dashboards.
Results
−22%
Forecast MAPE
Daily → Hourly
Update Cadence
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