Industry / Retail
AI-native retail decisions. Building the proof.
Mid-market retail wins on decision velocity, not dashboard volume. Merchandising, store ops, and customer experience are the operator surfaces where AI-assisted decisions land daily.
Where we're going deep.
- —Merchandising decisions — assortment, allocation, markdown timing. Decision agents over the SKU/store/week grid.
- —Customer experience — service triage, return-and-exchange narrative, loyalty next-action.
- —Store and inventory operations — replenishment, labor scheduling, shrink investigation.
What makes this MI-shaped work.
The mid-market retailer doesn't have a Tier-1's data science org.
The wedge is a DecisionFabric-style substrate plus a small library of decision agents tuned to the operator's daily flow.
Open note
[OPEN — no published retail use case today. Add the first landed engagement here before any proof claim.]