Automate replenishment with MMF, Databricks Genie, and Amazon Quick
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Foundation models made catalog-wide demand forecasting easy; the hard part is now acting on the forecast. This post builds a closed detect-decide-act loop on Databricks and Amazon Quick that reconciles demand surges against live supplier availability and places replenishment orders unattended, escalating to a human only when no supplier can cover a surge.
AWS Machine Learning Blog: technical walkthrough. Commands and expected outputs are from a working deployment. Substitute your own account values throughout. Replenishment automation starts with a demand forecast, and in retail that forecast has a short shelf life. By the time a planner exports it, checks it against supplier availability, and works down tens of thousands of stock keeping units (SKUs), the fastest movers have stocked out. For years the hard part was the forecast itself.…
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