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✈️ SkyMatch

🌟 Inspiration

Planning a group trip is notoriously difficult—everyone has different budgets, departure airports, and travel preferences. SkyMatch was born from a desire to take the stress out of this process. Built in response to a challenge proposed by Skyscanner, our project aims to find destination options that work for everyone in a group, not just the loudest voice.

💡 What it does

SkyMatch helps groups of friends discover the perfect travel destination based on:

Each person’s origin airport
Their budget
Individual travel preferences (e.g., adventure vs. relaxation, modern city vs. historic town)

By combining these inputs, SkyMatch identifies destinations that are:

Reachable from all departure points
Within everyone's budget
Aligned with the group’s collective travel style through a dynamic scoring system

🛠️ How we built it

Frontend: Developed using Expo, React Native, and TypeScript for a performant, cross-platform mobile experience.
Flight Data: Integrated the Skyscanner API to access real-time flight options and pricing.
Airport Dataset: Compiled a list of airports and enhanced it with geolocation and qualitative “vibe” attributes (e.g., nightlife, scenery, cuisine). These vibes were generated using a local LLM (Large Language Model) to simulate expert travel curation at scale.
Recommendation Engine: Implemented a flexible algorithm that scores destinations based on group alignment, affordability, and travel feasibility.

⚠️ Challenges we ran into

Designing an algorithm that fairly balances individual preferences with group constraints
Assigning subjective “vibe” attributes to destinations lacking structured data
Using reverse geocoding to enrich airport data with country information
Handling API rate limits and varying data quality across multiple origins
Managing live data flows across simultaneous users

🏆 Accomplishments we’re proud of

Delivered a working prototype that intelligently recommends shared destinations in real-time
Successfully enriched our dataset with country info and travel vibes using automated tools and LLMs
Built a clean and intuitive mobile UI that simplifies complex travel decisions
Seamlessly integrated real-world flight data from Skyscanner into a group-oriented workflow

📚 What we learned

How to combine structured travel data with subjective user preferences
Building scalable, interactive flows using React Native + TypeScript
Leveraging LLMs for batch data enrichment and decision-support
Designing systems that accommodate multiple users with live inputs
Navigating and optimizing API-driven development

🚀 What’s next for SkyMatch

Add functionality to suggest ideal travel dates for all group members
Enable community profiles and personalized traveler preferences
Support flexible departure windows and multi-date searches
Introduce collaborative budget tracking and group trip planning tools
Automatically generate trip highlights and day-by-day planning recommendations