TY  - JOUR
AU  - Enuguru Hanuman Sai Gupta
AU  - Garaka Sneha Latha
AU  - Pratti Gayatri
AU  - Teki Vijayaratnam
AU  - Tanimki Prabhu Das
AU  - Satti Bhanu Prakash Reddy
PY  - 2026
DA  - 2026/02/09
TI  - AI TRAVELMATE - An Intelligent Agent for Smart Travel Planning and Assistance
JO  - Global Journal of Engineering Innovations and Interdisciplinary Research
VL  - 6
IS  - 2
AB  - Planning a trip typically involves travelers going through several platforms for flights, hotels, and
tourist attractions, which is cumbersome and overwhelming. Current travel planning resources mainly
offer standard results and are not equipped with the feature to conform to specific user tastes or live
updates. This study presents an AI TRAVELMATE that can offer completely personalized and dynamic
travel schedules using the combination of Streamlit, SerpAPI, and Google's Gemini AI models. The
application takes necessary inputs from the user, including departure and destination cities, travel dates,
trip length, budget, and activities, and subsequently processes these in intelligent agents. The SerpAPI
module is utilized to retrieve actual flights in real-time to provide users with the most accurate and
economical means of travel. At the same time, Gemini-driven AI agents deal with creating itineraries: the
Research Agent recommends appropriate activities and attractions, the Planner Agent plans a day-wise
itinerary, and the Hotel & Restaurant Agent recommends places to stay and eat based on user inputs. It
is hosted on Streamlit for delivering the interactive and visually engaging interface so that it eases the
trip planning experience.In contrast to traditional tools, the suggested system integrates real-time data
access along with smart natural language processing, which guarantees flexibility, individualization,
and effectiveness. The findings indicate that the planner is capable of delivering customized advice,
trip schedule optimization, and streamlined decision-making for travelers. This method illustrates how
AI integration and real-time API can turn conventional trip planning into a streamlined, adaptive, and
enjoyable experience for contemporary travelers.
SN  - 3066-1226
UR  - https://dx.doi.org/10.33425/3066-1226.1198
DO  - 10.33425/3066-1226.1198