Inventory Refill Automation — AI-Powered Inventory Management

Overview

Developed an AI-powered inventory management system that automatically tracks stock levels, predicts demand, and orders refills from suppliers. The system eliminates manual inventory tracking and reduces stockouts through intelligent forecasting and automated procurement.

The Challenge

Restaurants frequently face stockouts due to manual inventory tracking and unpredictable demand patterns. Managing inventory across multiple suppliers is time-consuming and error-prone. The challenge was to create an automated system that could predict demand, track inventory levels, and automatically order refills before stockouts occur.

My Role

• Designed AI inventory prediction system
• Developed Python-based automation engine
• Integrated with supplier APIs for automated ordering
• Built inventory tracking and alerting system
• Created dashboard for monitoring and management
• Implemented demand forecasting algorithms

The Solution

The solution combined AI prediction with automated ordering workflows:

• Phase 1 — Inventory Tracking: Built automated inventory tracking system that monitors stock levels in real-time and integrates with POS and ordering systems.
• Phase 2 — AI Prediction Engine: Developed AI-powered demand forecasting using historical data, seasonal patterns, and business trends to predict future inventory needs.
• Phase 3 — Automated Ordering: Integrated with supplier APIs to automatically place orders when inventory reaches threshold levels, with intelligent timing to avoid stockouts.

Tech Stack

Results

• 90% reduction in stockouts
• 60% reduction in inventory management time
• 25% reduction in excess inventory
• Improved supplier relationship through consistent ordering

Lessons Learned

• Demand forecasting accuracy improves with more historical data.
• Automated ordering requires reliable supplier API integrations.
• Real-time inventory tracking prevents prediction errors.