Abstract

This study explores the development of an AI-driven logistics platform designed to enhance delivery efficiency and customer satisfaction through time-slot scheduling. Focusing on optimizing last-mile delivery, predictive analytics, and customer engagement, the platform addresses the growing demand for flexible and reliable delivery services. By analysing existing literature and systems, the study identifies critical features and challenges associated with modern logistics solutions. The proposed platform emphasizes a customer-centric design, offering dynamic time-slot selection, real-time tracking, and predictive route optimization. Detailed methodologies, including system architecture and AI implementation strategies, are presented. The anticipated outcomes suggest that such a platform can significantly reduce delivery failures, improve operational efficiency, and cater to the diverse needs of modern consumers while promoting sustainability in logistics.