penny

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  penny

🚀 Inspiration

Penny started with a childhood misconception.

When I was younger, I genuinely thought ATM machines gave out free money. You put in a card, pressed a few buttons, and cash appeared; it felt almost magical. I didn’t understand where that money came from, how bank accounts worked, or why spending decisions mattered until much later.

Looking back, I realized that if I had learned about money through something interactive—like a bank account game—I would have understood saving, spending, and limits much earlier. That idea stayed with me.

For ElleHacks 2026, under the Tech for Equity & Social Good theme, Penny was built to turn that childhood confusion into clarity. Instead of overwhelming dashboards or adult-focused finance tools, Penny introduces money as something you learn by doing: seeing balances change, reflecting on habits, and receiving friendly, age-appropriate guidance.

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🎮 What it does

Penny is an adventure-based financial literacy platform that allows young learners to “walk the life” and understand financial decision-making through play.

It combines:

• An Agar.io–style adventure game
• A virtual bank account tied directly to gameplay decisions

Every in-game action affects spending, saving, and balances. Players experience financial consequences in a safe environment, learning how choices shape outcomes without real-world risk.

Penny also offers:

• Personalized, AI-generated financial guidance
  
• AI-generated randomized bills to be paid
  
• Monthly summaries to encourage reflection
  
• Optional voice feedback, making learning feel more human and approachable
  

Instead of reading about money, users experience it.

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🛠️ How I built it

• Frontend: Next.js (App Router) with TypeScript and Tailwind CSS for a clean, responsive UI
  
• Backend: Next.js API routes for authentication, statements, and monthly summaries
  
• Database: MongoDB Atlas to store users, simulated bank statements, and progress
  
• AI Guidance: Gemini API generates personalized financial advice based on spending context
  
• Voice Output: ElevenLabs converts AI guidance into spoken feedback
  
• Validation: Zod ensures safe and structured inputs to the AI and backend
  

The system tightly connects gameplay actions with financial data to reinforce cause-and-effect learning.

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⚠️ Challenges I ran into

• Balancing fun and education: The game needed to stay engaging without turning into a lecture
  
• Designing supportive AI advice: Financial feedback had to feel encouraging, not judgmental—especially for younger users
  
• Integrating multiple services: Connecting MongoDB Atlas, Gemini, and ElevenLabs reliably within hackathon constraints
  
• Avoiding feature overload: Simplicity was essential to keep the platform accessible and intuitive
  

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🏆 Accomplishments that I’m proud of

• Built a full-stack application with real user authentication and persistent data
  
• Successfully integrated AI-generated financial guidance that adapts to context
  
• Added voice feedback to make learning more inclusive and engaging
  
• Created a system that teaches financial literacy through lived experience, not abstraction
  

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📚 What I learned

• Kids don’t lack intelligence; they lack exposure to financial systems
  
• Games and simulations teach faster than lectures
  
• Tone matters: supportive feedback keeps users engaged
  
• Small insights are more effective than complex dashboards for beginners
  
• AI is most effective when it delivers short, actionable guidance
  

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🔮 What’s next for Penny

• Deeper adventure mechanics and real-life scenarios
  
• Interactive bank account challenges (saving goals, spending limits)
  
• Progress tracking, habit streaks, and milestones
  
• Accessibility-focused modes and explanations
  
• Optional guardian view with privacy-first design
  
• Expanded features like investments and long-term planning
  

Built With

• elevenlabs
• gemini
• mongodb
• next.js
• node.js
• tailwind
• typescript