AI Assortment Planning &
Store-Level Allocation
for Modern Retail

Assortment planning is the retail process of deciding which products (SKUs), in what quantities and mix, should be carried by each store or channel for a given season. It combines demand forecasting, store clustering, size and color curves, and merchandising rules to maximize sales and reduce dead stock and markdowns.

Merchandise planning is the broader financial plan — open-to-buy, category budgets, sales and margin targets. Assortment planning sits inside it and translates those plans into specific product mixes, depth, and store-level allocations. Assort Agent focuses on the assortment and allocation layer and integrates with upstream merchandise planning systems.

Store-level allocation is the process of distributing inventory to individual stores based on their demand profile, size capacity, customer mix, and visual merchandising standards — instead of a flat distribution. Assort Agent generates store-level allocations from a master catalog by applying brand, price, size curve, and seasonal logic in one pass.

Yes. Assort Agent is built for the realities of India retail: tier-1, tier-2, and tier-3 city demand variance, regional festival cycles, GST-aware reporting, multi-format stores, and high-velocity replenishment.

Assort Agent applies machine learning to historical sales, store clusters, and product attributes to predict demand at SKU and store level. An optimization layer assembles assortments that respect merchandising rules — brand mix, price ladders, size curves, capacity — and outputs store-ready allocations.