Virtual assistants (VAs) are becoming an increasingly popular tool that help users find information faster and more accurately. This paper proposes a new AI-powered Virtual Travel Guide (GuideAI) system. The concept, architecture, and implementation of a microservice for intelligent travel search are explored in detail. The study focuses on technical aspects, particularly the integration of GPT for analysis and personalization. It highlights how geolocation and personalization can be combined to create more adaptive, user-responsive systems. The proposed approach enhances travel experiences by providing real-time, tailored recommendations based on user preferences and location. The scientific contribution of this research lies in the development of a novel AI-driven approach to travel assistance, demonstrating how advanced natural language processing and contextual data analysis can improve recommendation accuracy. By leveraging machine learning techniques, GuideAI refines search results, enhances decision-making processes, and optimizes user interactions. This work contributes to the field of intelligent information retrieval and personalized AI systems, offering insights for future applications in tourism and beyond.