Most tools were designed for ideal conditions. Afresh was built for the real ones.
Built on advanced AI models designed for grocery, Afresh connects and coordinates DC buying, store ordering, and inventory management in one system.
It continuously cleans data, analyzes signals, and simulates thousands of scenarios, so every decision is the best decision—across your entire supply chain.
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Say a DC buyer gets a hot buy offer on frozen turkeys from a vendor. Most buyers juggle spreadsheets and instinct to decide. Afresh actually models different scenarios—weighing demand, quantity, price, and promotion—to surface the strategies that maximize margin.
The buyer and category manager can review recommendations and easily decide to take the hot buy and run a store promo for frozen turkeys.
When the DC takes that hot buy, Afresh coordinates store orders automatically. It knows additional frozen turkey supply is incoming, so item quantities adjust to avoid excess inventory and account for related products likely to see a lift or cannibalization.
Store associates receive the frozen turkey shipment in Afresh, logging quantities and flagging variances on the spot. From there, teams use Afresh for all inventory management tasks, too.
As signals come in, adaptive data models continuously correct for errors like mispicks and pack changes, while probabilistic modeling accounts for incomplete data — so every store and DC decision starts with an accurate picture.
As the promotion runs, corporate teams see fill rates, inventory positions, and order adherence across every store and DC. No separate reports to reconcile, no weekly rollup to wait for.
When the next opportunity buy comes in, Afresh’s models have already learned and improved based on this one.
See why Afresh is the cornerstone solution for leading retailers.