@Tender_Swaycrhq

SmartStore AI is a simulation-based robotics startup prototype built to address one of retail’s most common and costly challenges: inefficient shelf monitoring and delayed restocking. Retail stores frequently experience out-of-stock situations that lead to lost sales and poor customer experience due to manual and reactive monitoring processes. SmartStore AI solves this by introducing an AI-driven system that continuously monitors shelf status, tracks customer traffic intensity, and measures how long shelves remain empty. Using a priority-based decision engine, the system automatically generates restocking tasks and simulates an autonomous robot executing them through a structured workflow (Dock → Shelf → Restock → Return). Built with Python and Streamlit, the platform includes a live interactive dashboard that displays shelf conditions, traffic levels, robot position, restocking activity, and performance metrics in real time. Designed as a simulation-first solution, SmartStore AI validates autonomous retail operations in a safe and scalable environment, while laying the foundation for future expansion into multi-robot systems, digital twin environments, computer vision integration, and demand forecasting. The project represents a production-minded, startup-ready robotics solution that bridges AI, automation, and retail intelligence.

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