privacy-mask-ai

Every day people share personal information online without realizing the privacy risks. Emails, phone numbers, names, and identification numbers can be exposed and misused.

We wanted to create a tool that allows users to use AI while keeping their sensitive information private. Privacy Mask AI is an AI-powered privacy protection application that detects sensitive personal information and anonymizes it before AI processing.

The application identifies data such as:

• Names
• Email addresses
• Phone numbers
• Personal identification numbers

Instead of sending the original information to AI, the system replaces it with anonymous placeholders:

Example:

Before: Jan Kowalski
Email: jan@gmail.com
PESEL: 99010112345

After: [PERSON]
[EMAIL]
[PERSONAL_ID]

The AI only receives anonymized information and never sees the original personal data.

We built Privacy Mask AI using:

• Next.js
• React
• TypeScript
• Tailwind CSS
• Groq API
• Llama AI model

The application uses a privacy-first architecture where sensitive information is detected locally before any AI analysis happens.

One of the biggest challenges was creating a workflow where AI could still provide useful privacy recommendations without accessing private user information.

We solved this by creating an anonymization layer that removes sensitive values and sends only safe placeholders to the AI model.

This project showed us that AI does not need access to private information to provide useful insights. Privacy and artificial intelligence can work together when data processing is designed responsibly.

Future versions could include:

• Credit card detection
• Address detection
• Document scanning
• Local AI models
• Browser extension support
• End-to-end encryption

Built With

• ai
• application
• artificial
• css
• data
• groq
• intelligence
• learning
• llama
• machine
• next.js
• privacy
• protection
• react
• tailwind
• typescript
• web