NotBuyChance

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  Additional Profile Info

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  Profile Info

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  Simple Step Process

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  Gift Proposal Page

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  Homepage

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  Saved Page

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  Astological_Numerological Insight

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  Surprise Category Selection

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  Astological Influence Selection

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  Agent's Reasons for suggestions

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  Profile Info_cultural influence

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  Gift Proposal Cards

Inspiration

Finding the perfect gift for someone can be surprisingly difficult. We often browse endless shopping websites or settle for generic suggestions.

I wanted to approach this differently: What if we started by understanding the person instead of searching for products?

That's how NotBuyChance was born—an AI-powered discovery agent designed to help people find thoughtful gifts and experiences for those they care about.

What it does

NotBuyChance uses Qloo's cultural taste intelligence and AI to discover gifts and experiences based on someone's interests, preferences, cultural influences, occasion, and budget.

Users can explore recommendations across music, books, fashion, dining, entertainment, and more.

The app offers three discovery modes:

• Taste: Recommendations informed by personal interests and Qloo's cultural insights.
• Cosmic: Astrology- and numerology-inspired discoveries.
• Fusion: Combines both approaches.

Users can also explore unexpected discoveries, understand why something was recommended, refine suggestions through feedback, and save their results.

How we built it

NotBuyChance was developed using Next.js, React, TypeScript, Tailwind CSS, and Firebase.

Qloo's API powers cultural taste discovery, while an AI agent interprets user preferences, explores relevant connections, and generates personalized recommendations.

The interface was designed to be colorful, minimal, responsive, and intuitive, with a guided onboarding experience.

Challenges we ran into

The biggest challenge was turning Qloo's cultural affinities into meaningful gift recommendations rather than simply listing related artists, brands, or places.

We also had to account for limited data in certain categories and locations, distinguish verified information from AI-generated suggestions, and balance sophisticated personalization with a simple user experience.

Accomplishments that we're proud of

• Building a personalized gift discovery experience powered by Qloo.
• Exploring connections across different cultural categories.
• Introducing Taste, Cosmic, and Fusion discovery modes.
• Creating explainable recommendations and unexpected discoveries.
• Supporting feedback-driven refinement.
• Designing a clean, friendly interface accessible to everyday users.

What we learned

We learned that meaningful personalization requires more than generating suggestions. It involves understanding context, connecting interests, respecting individual preferences, and explaining why an idea might be relevant.

Working with Qloo demonstrated how cultural intelligence can help make AI recommendations more thoughtful and interesting.

What's next for NotBuyChance

We plan to expand real-world event and shopping integrations, improve recommendation accuracy, introduce deeper preference learning, and make saved recipient profiles even more useful.

Our long-term vision is to make NotBuyChance a personal discovery companion that helps people find meaningful ways to celebrate and connect with others.

Because the perfect gift isn't by chance.

Built With

• ai-agents
• api-integration
• firebase
• firestore
• generative-ai
• gift-discovery
• llm
• nextjs
• personalization
• qloo
• react
• recommendation-system
• tailwindcss
• taste-intelligence
• typescript
• vercel