Retail AI Demand & Replenishment
This AI solution predicts item- and location-level demand across retail channels and automates replenishment decisions from store to DC. By combining market basket insights, seasonality, promotions, and supply constraints, it optimizes inventory levels and order quantities. Retailers reduce stockouts and overstocks while improving service levels, margins, and working capital efficiency.
The Problem
“Item-location demand forecasts that drive constraint-aware replenishment orders”
Organizations face these key challenges:
Frequent stockouts on promoted and fast-moving SKUs despite high overall inventory
Overstocks and markdowns driven by forecast bias and missed seasonality shifts
Planners spending hours in spreadsheets to reconcile signals (POS, promo, e-comm)
DC-to-store orders ignore constraints (lead time, case pack, min/max, capacity)
Impact When Solved
Technologies
Technologies commonly used in Retail AI Demand & Replenishment implementations: