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{207093,
        author = {Ashwini Gajanan Chaudhari and Prof. Anaya kulkarni},
        title = {Multi-Agent Personalized Travel Planning System Using CrewAI, Gemini, and Retrieval-Augmented Generation (RAG)},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {2},
        pages = {3941-3946},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207093},
        abstract = {The traditional travel planning process is slow and ineffective as people have to search information from different sources. This paper introduces a Multi-Agent Personalized Travel Planning System, where the agents include CrewAI, Google Gemini, and Retrieval-Augmented Generation (RAG). The framework includes specialized agents to process user preferences, to conduct destination research, to plan travel, to provide suggestions for lodging, and to provide a travel itinerary. CrewAI coordinates agent work, while Gemini handles intelligent reasoning and RAG fetches the most current travel data to enhance the factual correctness. The results of the experiments indicate improvements in recommendation accuracy (93%), user satisfaction (94 %), planning efficiency (88%) and personalization score (95%). The proposed system is an intelligent and scalable solution for future tourism applications.},
        keywords = {CrewAI, Gemini, RAG, Multi-Agent Systems, Travel Planning, Smart Tourism.},
        month = {July},
        }