Grocery Supply Chain Automation

The hardest part is balancing waste against availability on perishables, across thousands of store-SKU combinations every day. Perishable demand is volatile and shelf lives are very short, and promotions add complexity on top. A small error in a replenishment quantity compounds into large shrink or lost sales. Planning tools that run weekly batches cannot keep pace with demand that moves hour by hour in a store.

Solvoyo forecasts demand at the store-day and intraday level. The forecast draws on weather signals, promotional calendars, local events and seasonal patterns, so it senses demand shifts before they hit availability. AI/ML models automatically pick the best forecasting method for each SKU, from stable everyday items to volatile perishable categories and short-lifecycle promotional products. Accuracy improves across the full assortment, including the items outside the high-velocity ones that get manual attention.

Solvoyo cuts perishable waste with three connected planning decisions. Store-day demand forecasts reduce over-ordering. Automated replenishment models the waste versus lost sales trade-off for each SKU. Shelf-life-based markdown recommendations, generated at the store level, recover value before spoilage. Blanket ordering and reactive write-off policies drive most grocery waste. Together, the three decisions replace them with a continuous, store-specific optimization loop.

Solvoyo plans promotional and in-and-out products in dedicated workflows. Each item gets a store-level demand forecast for its offer period, anchored on the performance of similar historic items. Allocation is automated against those forecasts and sends each store the right volume, based on predicted demand, capacity and minimum presentation requirements. Exit dates and stock positions are monitored continuously, and automated alerts trigger markdown or transfer recommendations before unsold inventory becomes shrink.

Solvoyo manages circular planning as a structured weekly workflow in a shared online environment, where category managers and central planners collaborate. They review promotional selections, quantities, pricing and budget allocations in a single process, without emails and spreadsheets. AI models evaluate each promotion for gross lift, cannibalization and pantry-loading effects. That shows the net impact on volume, revenue and profitability before budget is committed, and every campaign has a complete audit trail.

Solvoyo customers reach 95%+ automation on daily operational planning decisions, because planners trust the recommendations enough to accept and execute them. Those decisions include initial allocation, store replenishment, transfers and markdown optimization. Planners are left to manage exceptions and strategy.

Yes. Solvoyo works with businesses at every level of digital maturity, including teams that plan entirely in spreadsheets. In the Digitize step of our process, we run automated data diagnostics on your existing data, wherever it lives, to find gaps, inconsistencies and quality issues. Our AI then helps fill in missing data points and improve the quality of your input data, so you don’t need years of system cleanup before you start. That shortens the path from where you are today to fully autonomous, no-touch planning.

Solvoyo tracks how much of your stock is actually sellable, because on-hand numbers for perishables rarely tell the whole story. It works with batch-level data: each lot’s age, expiry date and remaining shelf life. On top of that, AI models learn from your historical data to estimate waste and spoilage rates by category or product type, so expected losses are factored in even where batch data is incomplete. That gives an accurate picture of true sellable inventory. You get fewer stockouts from overestimated availability and less write-off from overordering, and replenishment across your fresh and short-shelf-life assortment gets more accurate.

Run it centrally, at store-level detail. With decentralized replenishment, where each store writes its own orders, the people who see the shelf make the call. But store orders tend to follow habit, and nobody weighs one store’s order against DC stock, truck space or next week’s promotion. Central replenishment fixes that only if the system plans each item, in each store, for each day. Solvoyo’s AI/ML forecasts drive store and DC orders automatically from live demand signals, promotions and shelf-life limits. It predicts sellable stock for fresh and loose items where the stock record drifts, and plans the trucks in the same optimization. Store teams handle exceptions instead of daily order lists. At İstegelsin, which had no planners in its dark stores, fresh product availability rose 14 points, from 72% to 86%, within one year of go-live.

Solvoyo forecasts short-life categories such as bakery, deli and prepared foods at store-day and intraday level, using weather, local events and each store’s own sales patterns. For each production or receipt batch it projects how much will go unsold before expiry, from forecast demand, inventory age and remaining shelf life, or estimates spoilage where batch data is missing. Markdowns are then timed store by store to recover value on the units still at risk.

Solvoyo automates dark store replenishment with AI demand models that use real-time sales and inventory status. Products are segmented by dark store, so each store can run its own service level. Cross-dock allocation lowers the risk of a stockout at the moment stock is received.