What If Your Local Kirana Store Could Predict Tomorrow's Demand? Meet DukaanDost

Описание и применение

DukaanDost преобразует CSV с продажами из небольшого магазина в прогноз спроса и рекомендации по заказу, помогая владельцу избежать излишков и дефицита товаров.

Задача

Shop owners rely on billing exports that show past sales but not guidance on what to buy next, in which pack size, or how to avoid stockouts.

Результат

The shop owner used the forecast to restock candles and oils, reducing guesswork and aligning inventory with upcoming festivals.

Рабочий процесс

• Export billing CSV from shop system
• Preview and map columns, identify bad rows
• Generate features: lags, rolling pace, calendar
• Run TabPFN v2 for demand forecast (fallback to baseline if unavailable)
• Calculate reorder quantity: lead‑time demand + safety stock, rounded to pack size
• Generate explanation via Gemma or fallback template
• Export inventory, forecasts, recommendations as CSV
• Use output to place restocking orders

Доказательства

DukaanDost takes a billing CSV and writes item-level demand, a reorder quantity, and a short explanation.

Источник

He used it. He read the forecast against his sales and the festivals coming up, and he restocked candles and oils, because the prediction put those items in demand.

Источник

TabPFN reads the billing table, and Gemma writes the explanation.

Источник