The modern travel and tourism industry is experiencing unprecedented growth, yet tourists frequently encounter significant challenges when planning trips to unfamiliar destinations. Navigating scattered information across multiple platforms, optimizing travel routes within strict budget constraints, and finding authentic, verified local guides remain major hurdles for travellers. To address these critical issues, this project introduces "RoamMate," an advanced, AI-driven tourism dashboard designed to centralize and automate the travel planning experience.

The platform is engineered around two core modules. The first is Planner.AI, an intelligent recommendation engine that dynamically generates customized, day-wise itineraries. By utilizing a constraint-satisfaction algorithm, Planner.AI processes user inputs—such as total budget, trip duration, and specific personal interests—to logically distribute activities without exceeding daily financial limits. The second core module is a Real-Time Local Guide Integration system. Powered by a robust Spring Boot backend and a MySQL relational database, this system allows tourists to seamlessly discover, verify, and connect with native experts via asynchronous RESTful APIs, bypassing traditional, high commission middlemen.

The frontend leverages modern web development technologies to deliver a highly responsive and immersive user experience, featuring glassmorphism UI principles and parallax scrolling. Furthermore, by integrating interactive booking notifications and an automated chat routing mechanism, the platform ensures seamless communication between tourists and guides. Ultimately, RoamMate successfully combines decentralized AI planning with realtime database management, serving as a comprehensive, scalable, and highly efficient digital travel companion.

Keywords—Smart Tourism, Group Recommendation, Hybrid Itinerary, Predictive Budgeting, Machine Learning, Travel Personalization