A futuristic AI agent concept for flight search, charter booking, and travel routing. Designed to explore how AI manages non-standard scenarios, calendar integrations, and complex data with user permission.
Standard travel booking interfaces rely on rigid forms and filters. When it comes to complex, non-standard cases — like flexible charters, multi-city dynamic routes, or matching flights with personal calendar events — traditional UI breaks down and forces users to do the heavy lifting.
Core Challenge: Design a conversational and agentic interface that seamlessly handles complex flight bookings, proactively manages passenger data, and builds routes while maintaining a high level of trust and transparency.
AeroFlight Concierge: an AI agent that acts as a personal travel manager. It uses natural language to understand nuanced requests, securely accesses calendars to avoid conflicts, and handles passenger details automatically with user consent.
Instead of rigid origin and destination fields, users state travel goals in natural language — the agent parses complex intent and builds dynamic multi-city routes. With permission, it cross-references connected calendars to avoid schedule conflicts and highlight optimal departure windows, while automatically retrieving stored passenger profiles to eliminate manual data entry during checkout.
Complex travel requests are easier to explain in natural language than to piece together using rigid filters.
Trust is paramount. The agent always asks before accessing calendars or sensitive passenger documents.
Leveraged OpenCode and Antigravity to rapidly prototype and iterate on the agent's interactive behaviors and UI.
A proof-of-concept demonstrating the near-future of travel. It shows how agents can transition from simple chatbots to proactive, context-aware tools that manage complex commercial and personal tasks.