Example: Demand Forecasting & Inventory Optimization
An ML-powered demand forecasting and inventory optimization engine - illustrating how we would approach a retail forecasting problem at scale.
The Problem
A retail chain is losing revenue to stockouts and overstock simultaneously - a classic inventory visibility problem at scale - with an existing system that relies on simple moving averages and no seasonality or promotions modelling.
Our Approach
We would build a forecasting pipeline using gradient boosting models trained on historical sales data, promotions, regional events, and weather signals, feeding an optimization layer that generates purchase orders per SKU per location.
What This Demonstrates
- -Gradient-boosting forecasting pipeline (seasonality + promotions aware)
- -SKU/location-level purchase-order optimization
- -MLOps setup for retraining and drift monitoring
Industry Focus
E-Commerce
Illustrative example, not a delivered client project
Tech Stack
Service
AI & ML SolutionsNext Step
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