Every order backed by data.
Pick a row in the replenishment table to see its forecast
A demand-planning prototype built on historical sales data.
Favorita retail data for 54 stores and 13 food categories, through 2017-08-15; forecasts cover 08-16 to 08-22. Categories are product families, not SKUs, and sales keep their source units.
A direct 7-day model using only sales known on the Wednesday order date, plus planned promotions, store-matched holidays and paydays. Retrained on 5 historical windows: 11.7% mean WAPE vs 19.9% for last-week-same-day. The p10–p90 band covered 77% of actuals (target 80%).
Stock, shelf life, lead time and MOQ are simulated. Orders cover demand until the next delivery plus a per-category buffer learned in the backtest (the policy behind the 51% cost saving). Promotion what-ifs re-score the model with a changed promotion plan. Recommendations are not turned into purchase orders.
An LLM agent answers through tools over the v3 artifacts; numbers are checked against tool results. If the LLM is unavailable, a labelled template fallback is used. Tool calls and raw results can be expanded under each answer.