🏪 Ranchi Dukaan Pro — Predicting Stock Demand with TabPFN-TS

说明与用途

Ranchi Dukaan Pro 使用 TabPFN-TS 预测七天需求并为小型零售商生成补货建议，在合成数据上显示出比简单基线更好的 MAE 和 WAPE，但尚未进行真实世界验证。

问题

Small retailers need to decide what to reorder, how much stock to keep, and when to place the next order, but lack tools to forecast demand and generate inventory recommendations.

结果

In a synthetic test with three products, TabPFN-TS achieved MAE 1.29 and WAPE 9.18%, outperforming a simple weekday‑one‑week‑earlier baseline (MAE 1.62, WAPE 11.56%). The model did not beat the baseline for Bread.

工作流

• Enter daily sales history for each product
• Use TabPFN-TS to generate a seven‑day demand forecast
• Check expected demand during the supplier’s lead time
• Combine that estimate with current stock, incoming stock, and safety stock
• Display a suggested reorder quantity and its estimated cost

证据

I generated synthetic daily sales data for three example products: Milk 500 ml, Bread, and Rice 1 kg.

来源

The results from this single test window were: Mean Absolute Error (MAE) 1.29 units for TabPFN-TS vs 1.62 units for baseline.

来源

Important limitation: these results come from synthetic data and one seven-day holdout.

来源