What Happens in Vegas

Inspiration

Gen-Z travelers are redefining trip planning—moving away from rigid itineraries and embracing spontaneity, personalization, and collaboration. Existing travel apps fail to offer real-time adaptability, seamless group coordination, and hyperlocal experiences. We saw an opportunity to create a next-generation travel platform that blends AI-driven recommendations with dynamic social features, making trip planning effortless and engaging.

What It Does

Our app personalizes and streamlines group travel experiences with these core features:

AI-Powered Itinerary Generator – Uses Llama 3.1 to generate personalized trip plans based on duration, region, interests, budget, and group demographics.
Collaborative Planning – Users can upvote/downvote activities to finalize an itinerary that best suits the group.
Hyperlocal Recommendations – AI-driven restaurant, attraction, and deal suggestions based on real-time location and traveler preferences.
Location Sharing & Coordination – Helps groups find common meeting points and stay connected throughout the trip.
Integrated Ride Sharing – Schedules rides for the group based on the planned itinerary and shares real-time locations.
Unified Photo Album – A trip-specific QR code allows users to upload photos to a shared Google Cloud storage, reducing device storage concerns.
Seamless Communication – A built-in chat feature that either functions independently or syncs with WhatsApp for easy messaging.

How We Built It

Frontend: Developed in Swift for a seamless iOS experience.
Backend: Built using Swift and Python, ensuring high performance and flexibility.
LLM-Powered AI: Llama 3.1 generates customized itineraries, contextual recommendations, and dynamic travel insights.
Maps & Geolocation: Google Maps API for real-time location tracking and geofencing.
Cloud Storage: Hosted on Google Cloud for easy photo sharing and trip data storage.

Challenges We Ran Into

Optimizing Llama 3.1 for Travel Planning – Fine-tuning the model to provide highly relevant, personalized travel recommendations.
Real-Time Coordination – Ensuring smooth location sharing and ride scheduling across different time zones.
Balancing Personalization & Group Consensus – Designing a fair yet flexible voting-based itinerary system.
Performance Optimization – Handling large amounts of travel data and real-time user interactions without lag.

Accomplishments That We're Proud Of

Successfully implemented Llama 3.1 for context-aware, AI-powered travel planning.
Developed a collaborative itinerary system with an upvote/downvote mechanism.
Seamlessly integrated ride-sharing and location tracking for better group coordination.
Created a Google Cloud-based photo-sharing system, eliminating the need for manual uploads and storage concerns.

What We Learned

The power of LLMs like Llama 3.1 in generating dynamic, personalized travel plans.
How Swift and Python can be leveraged to build a scalable, high-performance travel app.
The need for seamless group coordination tools to enhance the user experience.

What's Next for Our Travel App

Augmented Reality (AR) Experiences – Adding AR-powered location insights and interactive travel guides.
Gamification Features – Introducing challenges, leaderboards, and rewards to encourage exploration.
Smart Budgeting Tools – Integrating AI-powered spending predictions and budgeting assistance.
Expanded Social Integration – Deeper integration with platforms like Instagram and Snapchat for real-time content sharing.

By merging LLM-driven personalization with real-time collaboration, our app redefines modern travel planning, making it smarter, more interactive, and truly seamless for group adventures. 🚀