Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{197199,
        author = {P.Meghana and P.Mahitha and P.Kinnera and K.Durga Prasad},
        title = {AI TRIP PLANNER},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {5483-5489},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=197199},
        abstract = {As a consequence of time, money limit and need for customisation travel planning has become a complex task. Most of the times the travel applications have information about popular places to see and reviews by other users but they don't provide a day wise plan to the user based on his preferences. This paper describes an AI enabled Trip Planner application implemented using Large Language Models, RAG & Prompt Designing technique for creating intelligent and changing travel plans. Application described here takes Destination, Trip Duration, Budget and preference of User as an input and will give out a day wise travel plan in structured way including landmarks as well as hidden gems along with Things To-Do, Cost Estimates etc. It also includes Real-time trip modifications and exports them as PDF.},
        keywords = {AI Trip Planner, MERN Stack, Artificial Intelligence, Travel Recommendation System, Customized itinerary, LLM (Large language model), RAG (Retrieval Augmented Generation), prompt engineer, Smart Tourism, Vector database, Travel Optimization, User experience.},
        month = {April},
        }