• Teku Prashanth
• Thurai Prakash
• Subburu Manoj Kumar
• Shailaja Mantha
• Mohan Dholvan Professor

The process of travel planning can be overwhelming, requiring extensive research and coordination of various elements such as accommodations, attractions, and weather conditions. TripTrail is an AI-powered platform designed to streamline travel planning by generating personalized itineraries based on user preferences. By incorporating Artificial Intelligence (AI), Machine Learning (ML), and real-time data from APIs, TripTrail delivers structured, day-wise travel plans, up-to-date weather forecasts, tailored hotel and restaurant recommendations, and nearby attractions. Additionally, a chatbot provides instant assistance, making the travel experience more interactive and user-friendly. The system leverages advanced data analysis techniques to refine recommendations, ensuring users receive the most relevant travel suggestions. By continuously adapting to user feedback and preferences, TripTrail enhances the overall travel experience. This paper discusses the system’s architecture, key functionalities, and its potential to enhance the efficiency and convenience of travel planning. The integration of intelligent automation not only reduces the time required for trip organization but also improves travel satisfaction through seamless itinerary customization.

AI-driven travel planning, personalized itinerary, machine learning, chatbot support, real-time data, travel recommendations.

"TripTrail: AI-Based Smart Travel Planner", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.g449-g459, May-2025, Available :http://www.jetir.org/papers/JETIR2505743.pdf

"TripTrail: AI-Based Smart Travel Planner", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppg449-g459, May-2025, Available at : http://www.jetir.org/papers/JETIR2505743.pdf