Article’s

Abstract – Abstract— In the contemporary digital era, travelers consistently face challenges regarding fragmented itinerary planning and rigid, generalized travel packages. This paper proposes a comprehensive, intelligent AI-Based Tour and Travel Management System designed to revolutionize the user travel experience by replacing manual planning with automated, data-driven personalization. The application is engineered on a robust Django web framework utilizing Python to orchestrate complex server-side business logic and seamlessly integrate machine learning models. The system relies on a secure MySQL relational database management system (RDBMS), structured to enforce strict transactional integrity, optimize indexing, and efficiently handle high-concurrency read-write logs during real-time ticket and hotel resource allocation. The core intelligence leverages Machine Learning (ML) algorithms, utilizing content-based filtering to deliver customized destination, hotel, and itinerary recommendations tailored specifically to individual user preferences, budget constraints, and historical behaviors. Experimental results and system evaluations demonstrate that the integrated AI model significantly reduces itinerary planning latency while enhancing user satisfaction metrics compared to traditional, static travel portals. Ultimately, this system serves as a scalable, end-to-end enterprise solution that optimizes resource management for service providers while providing a highly responsive, personalized, and intuitive interface for global travelers. Key Words: Artificial Intelligence, Machine Learning, Django Framework, MySQL Database, Recommendation Systems, Full-Stack Development.