Retail & CPG6 weeks
AI-Powered Smart Store Inventory Management
Client: FreshMart Grocers
Eliminate out‑of‑stocks and overstocks by forecasting demand and automating restocking and redistribution.
The Challenge
FreshMart Grocers needed to eliminate out-of-stocks and overstocks by accurately forecasting demand at a hyper-local, store-SKU level, accounting for seasonality, promotions, and local events. The challenge was to forecast demand precisely while optimizing inventory levels.
Key Challenges:
- Eliminate out-of-stocks and overstocks at store-SKU level
- Forecast demand accounting for seasonality, promotions, and local events
- Hyper-local demand prediction requiring sophisticated modeling
- Real-time inventory monitoring and restocking automation
Without accurate demand forecasting, the company faced customer dissatisfaction from out-of-stocks, financial losses from overstocks and food waste, and inefficient inventory management.
Our Solution
- Computer vision system with in-store cameras monitoring shelf stock levels
- Sales data integration providing comprehensive demand signals
- Prophet-based time-series forecasting for demand prediction
- Automated restocking order generation based on predicted demand
- Redistribution planning optimizing inventory across store network
- Real-time alerting for low stock and potential out-of-stock situations
Technology Stack
YOLOOpenCVTensorFlowProphetApache SparkAirflowCloud APIs
Client Testimonial
"Reduced out‑of‑stocks by 45% and food waste by 30%, boosting profitability and sustainability."
— Supply Chain Director, FreshMart Grocers