PrivateAI

Inspiration

Students often need to share personal information when checking eligibility for scholarships, programs, or other opportunities. We wanted to explore how AI could make this process easier while giving users more control over sensitive information.

What We Built

PrivateAI is an AI-powered student assistant designed around privacy. It helps users understand eligibility requirements and get useful guidance without unnecessarily exposing sensitive personal information.

The project combines a simple web interface with AI-assisted processing and a privacy-focused workflow inspired by Midnight's approach to confidential data and verifiable computation.

How We Built It

We built the application with a modern web stack and focused on making the experience simple for students. The frontend provides an easy-to-use interface for entering information and receiving results.

For the hackathon, we are exploring Midnight's privacy technology to demonstrate how sensitive information can be handled more securely while still allowing useful verification.

What We Learned

This project helped us understand the importance of privacy when building AI applications. We also learned about blockchain, zero-knowledge concepts, and how privacy-preserving technologies can complement AI systems.

Challenges

One of our biggest challenges was finding a simple way to combine an AI-powered user experience with privacy-focused verification. Since this was our first experience building with Midnight, understanding the ecosystem and integrating it into a working application was also a learning experience.

What's Next

We would like to expand PrivateAI with stronger privacy-preserving verification, more student use cases, and additional AI capabilities while keeping users in control of their sensitive information.

Built With

• css
• html
• javascript
• midnight
• node.js
• react