Retail AI benchmark for choosing the economically right LLM by workflow
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Updated
Jun 13, 2026 - Python
Retail AI benchmark for choosing the economically right LLM by workflow
Open-source FBO replenishment planning toolkit for marketplace sellers.
承接 Legacy ERP Headless Bridge,將客戶與銷售資料轉成補貨、分群、交叉推薦與預測表單的架構 Showcase。
结合销量、库存、交期和季节性,设计可解释的预测与补货决策。
Proposes min/max replenishment rules, writes them back to stock.warehouse.orderpoint.
Caso simulado de supply chain en Valencia: análisis y previsión de demanda, planificación de inventario y reposición bajo incertidumbre. Proyecto desarrollado en Python para apoyar decisiones logísticas y evaluar distintos escenarios operativos.
Plans the day's transfers on a six-tier priority ladder under transfer capacity, and reads inbound ETAs so it does not move stock that is about to arrive.
跨境电商海外仓智能补货与实时仿真原型:预测、补货、分仓、策略对打与数字孪生沙盘。
Improve inventory management by adjusting ordering thresholds thanks to trusted data and insights.
Supply and Inventory management software application
Decision-support toolkit for replenishment, built on traditional ML models.
◫ Preact inventory planner with demand analysis, safety stock, shortage forecasts, suppliers, and purchase orders.
S&OP replenishment decisions computed from inventory policy - every number in the explanation traceable to the arithmetic, nothing self-approves
Merchandising operations console for inventory replenishment, vendor performance, unit economics and promotion break-even, over one joined data model.
Inventory demand forecasting and replenishment planning case study using MySQL, Power BI, and DAX.
Local-first, human-approves-everything grocery replenishment as a ResonantOS add-on: runway analysis, fail-closed dietary checks, and a next-cart draft that structurally cannot check out. No accounts, no cloud, no telemetry — nothing leaves your machine.
MedCare Pharma supply chain decision system for demand sensing, forecasting, inventory monitoring, and replenishment planning.
Калькулятор поставок FBO на Ozon с разбивкой по кластерам: сколько везти каждого артикула в каждый кластер + перераспределение излишков
LLM-in-the-loop shelf replenishment POC: deterministic rules handle ~90% of restock decisions, a local LLM reasons over the ambiguous rest. Kafka, Postgres, FastAPI, Streamlit, Docker.
Dolibarr module to exclude specific warehouses from stock calculations system-wide (replenishment, order availability, TakePOS, MRP, API, etc.)
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