Raddad - AI School & Student Assistant

Inspiration

In school environments and student organizations, managing back-and-forth communication regarding assignments, announcements, and club activities takes a tremendous amount of time. We wanted to build a smart, automated assistant that streamlines inquiry responses and workflow tasks for students and school administrators.

What it does

Raddad is an AI-powered communication and workflow automation tool. It integrates Gemini AI to automatically process incoming student and school inquiries, answer questions in natural language, and manage task notifications efficiently, reducing administrative friction in school life.

How we built it

• Frontend: Built with Flutter for a clean, responsive cross-platform user experience.
• Backend: Powered by Node.js and Express handling REST APIs and request routing.
• AI Engine: Integrated Google Gemini API for intent classification, query processing, and automated smart responses.

Challenges we ran into

• Optimizing API response latency to deliver real-time automated replies.
• Structuring prompt context so the AI accurately handles school and student inquiry contexts without hallucination.

Accomplishments that we're proud of

• Successfully designing a full-stack architecture (Flutter + Node.js + Gemini API) that works seamlessly end-to-end.
• Creating an intuitive workflow interface that simplifies complex task automation.

What we learned

• How to structure scalable API endpoints for AI models.
• Deepened our understanding of state management in Flutter and prompt engineering for real-world automation.

What's next for Raddad

• Expanding integration with school platforms and messaging channels.
• Preparing the core architecture for scalable deployment as a micro-SaaS product!

Built With

• api
• automation
• express.js
• flutter
• gemini
• google
• javascript
• node.js
• rest