Fliggy Searchv1.0.2

An AI agent automatically searches one-way and round-trip flights across multiple cities and dates to compose an optimized travel itinerary for a user. It uses flight-detail queries to filter by airline, aircraft type, or specific flight number, returning structured results for comparison.

A booking assistant searches hotels in target cities with district or landmark keywords (e.g., 亚奥) and date ranges, then drills into hotel-detail to summarize prices and availability. This helps users compare options near a venue or attraction before booking.

An agent periodically searches ticket keywords like "故宫门票" or "黄山门票" to check pricing, rating, sales volume, and tags such as 免预约 or 随买随用. It can alert the user when booking conditions match their needs.

A travel planner searches holiday products such as 三亚跟团游 or 云南5天4晚 and parses full detail pages for itinerary length, departure city, ratings, sales, and hotel comfort level. It then ranks packages by 纯玩/无购物 tags for family-friendly trips.

An internal tool integrates Fliggy search via CLI to fulfill employee flight and hotel requests with headless background execution after one-time login. Results are aggregated into approval-ready summaries, reducing manual browsing for travel admins.

A consumer service charges monthly or per-trip fees to plan personalized itineraries using automated Fliggy searches across flights, hotels, tickets, and holiday packages. The platform combines search results with AI recommendations to deliver complete trip plans.

An AI-powered travel portal runs Fliggy searches to surface products, then routes users to book tickets or packages via affiliate links. Revenue is earned through referral commissions from completed bookings without holding inventory.

A B2B platform embeds Fliggy CLI searches into expense and approval workflows for companies, automating flight, hotel, and ticket lookups for employees. It saves travel admins time while ensuring policy-compliant options are presented.