Quick Commerce

Case Study 4: Automating Quick Commerce for SwiftKart Industry: Quick Commerce Technologies Used: Python, Django, AI-Powered Demand PredictionClient’s Problem: SwiftKart struggled with demand prediction and last-mile delivery ineciencies, leading tohigh operational costs and customer dissatisfaction. Our Solution:1. Demand Forecasting: Used AI to predict inventory requirements based on trends.2. Delivery Route Optimization: Implemented algorithms to optimize delivery schedules.3. Real-Time Updates: Built a real-time order tracking system for customers.Results:– Delivery eciency improved by 35%.– Customer satisfaction scores increased to 4.8/5.– Reduced inventory holding costs by 20%.