ForeStock: Smart Sales Quantity Forecaster for Warehouse Stock Management

This project presents ForeStock, a smart AI system designed to forecast the monthly warehouse sales quantities by analyzing historic sales data of the warehouses and identifying important market patterns to avoid stock management problems like overstocking and stockouts. Using the XGBoost algorithm combined with advanced time-series feature engineering to improve the accuracy of the system and as well make model understand market patterns well. The system offers a web-based dashboard via Streamlit on cloud services, that provides custom sales understanding visual statistics like tables, sales charts and pie charts, which helps the warehouse managers to validate the forecasts backed by previous sales statistics. It utilizes very less computing power to forecast, making it a best choice for small to medium scale enterprises compared to other approaches. Prediction accuracy of 94.91% by the system makes it significantly improve supply chain management efficiency and resource planning.