Safar AI: An AI-Powered Personalized Travel Itinerary Planner for Indian Destinations

Planning a trip within India usually means jumping between travel blogs, map apps, booking sites and WhatsApp groups, and still ending up with a plan that does not fit the budget or the time available. This paper presents Safar AI, a webbased system that turns a few inputs (destination, number of days, budget in Indian Rupees, group type, pace and interests) into a day-wise itinerary. The system uses the Gemini API to draft the plan in a fixed JSON format and then checks the draft before the user sees it: the structure is validated against a schema, each suggested place is matched against Google Maps data, stops are ordered to keep travel time reasonable, and the costs are added up and compared with the budget. The front end is built with Next.js, React and TypeScript, the back end with Node.js and Express, data is stored in PostgreSQL through Prisma, and sign-in is handled by Clerk. We describe the architecture, the prompt and verification design, and an evaluation plan with measurable metrics. The central idea is that a language model is more dependable for travel planning when its output is checked by ordinary code instead of being trusted directly