Authors: Yash Sharma, Mr. Ritesh Kumar Chandel
Abstract: Travel planning requires synthesizing large and diverse datasets including destinations, transportation, budgets, accommodations, user preferences, and seasonal variations. Traditional tools depend on static rules and manual inputs, making them inefficient for personalized planning. This research introduces an AI-powered RAG-based trip planner that integrates vector retrieval with generative reasoning. The system mitigates hallucinations, enhances real-world grounding, and produces optimized, personalized itineraries.
