Inspiration

Group decision-making is hard — we’ve all been stuck in endless WhatsApp threads trying to pick a movie, plan a trip, or choose where to eat. Everyone has different tastes, and too often, the “plan” never materializes.

We were inspired to create a system that doesn’t just recommend what’s popular — but what’s meaningful for a group based on their collective preferences. Our goal was to build a cultural mediator that helps groups find common ground and plan unforgettable experiences using AI.

What it does

CultureCircle is a multi-user, AI-powered experience planner that understands group preferences across domains like:

-Music

  • Movies & TV

  • Travel destinations

-Food & cuisine

-Fashion

  • Books & podcasts

It uses Qloo’s Taste AI™ and Gemini LLM to:

-Analyze everyone’s preferences and compute a Harmony Score.

-Recommend movies, destinations, playlists, fashion and more — personalized for the group.

How we built it

CultureCircle is a full-stack web app built with the following stack:

Frontend:

-React.js with Tailwind CSS for a dynamic UI.

Backend:

-Node.js + Express.js for REST APIs.

-Integration with:

-Qloo API

-Gemini 1.5 Pro via Vertex AI for LLM processing

Database & Auth:

-Firebase Authentication for login/signup (email & Google).

-Firestore for storing:

-User preferences (e.g., favorite artists, movies)

-Group composition

-Shared insights and session data

Challenges we ran into

-Mapping user-friendly input to valid Qloo entity IDs was tricky.

-Understanding how to tune Qloo’s signal and filter parameters per entity type.

-Balancing token limits and latency when querying Gemini with rich group data.

-Designing the Harmony Score formula to be interpretable and fair.

-Coordinating multi-user state in Firebase with live updates.

Accomplishments that we're proud of

-Built a functional end-to-end system combining two powerful AI platforms.

-Designed an intuitive UI/UX for group input and experience browsing.

-Created a novel Harmony Score metric with LLM-based explanations.

-Successfully integrated dynamic group suggestions in real time.

-Made AI feel like a cultural companion — not just a chatbot.

What we learned

-Hands-on experience with Qloo’s cultural graph and entity modeling.

-Prompt engineering with QLOO API to reason about group behavior.

-Firestore rules and schema design for real-time multi-user collaboration.

-Optimizing performance of AI workflows inside frontend/backend pipelines.

What's next for CultureCircle

-Integrate with Spotify, Netflix, and OpenTable for action-ready suggestions.

-Expand to support mood-based planning and live polls.

-Add deep analytics for taste evolution and time-based recommendations.

-Launch a mobile app version with notifications and geolocation features.

-Build a group AI personality that evolves with your circle.

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