In this hackathon, we built LearnArc, an AI-powered education platform designed to make learning more flexible, affordable, and accessible — especially for students who cannot afford expensive upfront course fees.
🚀 Try it out
👉 Live Demo: https://nano-payments-arc-fe.vercel.app/
💡 The Idea
Most online learning platforms charge users for full courses, even if they only consume a small portion. We wanted to change that.
LearnArc introduces a usage-based model:
🎥 Pay per minute of video watched
📄 Pay per PDF page read
🤖 Pay per AI tutor interaction
This approach makes learning fair, transparent, and cost-efficient, especially for users in remote or underserved areas.
🏗️
Tech Stack & Deployment
We built a modern full-stack system:
Frontend: Next.js deployed on Vercel
Backend: FastAPI deployed on Render
Database: MongoDB
AI Models: Integrated via multiple providers
Payments: Designed around USDT-based microtransactions
The backend follows a clean architecture:
Controller → Service → Repository, making it scalable and easy to extend.
🤖 AI Integration (Featherless + AIMLAPI)
One of the most interesting parts of our project was working with Featherless and AIMLAPI.
🔹 Featherless Platform
Featherless provides access to multiple AI models in one place, making it easier to:
Switch between models
Test different responses
Build AI-powered features quickly
Instead of being locked into a single provider, we could experiment and design our AI tutor more flexibly.
AIMLAPI
We also explored AIMLAPI, which offers:
Unified API access to multiple LLMs
Simplified integration
Faster prototyping for AI applications
Together, these platforms helped us accelerate development and focus more on product logic rather than low-level integrations.
⚡ Key Features
💬 AI Tutor for real-time learning support
💰 Usage-based billing system
🔐 JWT Authentication
📊 Wallet & transaction tracking
📚 Course & lesson management
⚠️ Challenges We Faced
Like any hackathon project, we faced a few issues:
Deployment issues (initially with backend hosting)
API timeout/debugging challenges
Time constraints while balancing other commitments
Handling usage tracking accuracy for billing
✅ How We Solved Them
Switched deployment strategy and stabilized backend on Render
Improved logging and debugging for API calls
Simplified architecture to focus on core features
Designed a flexible transaction system for future scaling
🔮 Future Scope
We are planning to take LearnArc beyond the hackathon:
🔗 Integrate real crypto micropayments (USDT/USDC)
⚡ Improve performance and scalability
📱 Enhance UI/UX for better accessibility
🌍 Focus on remote education use cases
❤️ Final Thoughts
LearnArc is more than just a hackathon project. It’s a step toward a future where:
Education is accessible, affordable, and truly pay-as-you-learn.
By combining AI + microtransactions + modern cloud platforms, we believe this model can make a real impact especially in regions where every small cost matters.
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