QUANTAID

One-sentence pitch
A simple way to scan your AI data, encrypt it with post-quantum security, and anchor a proof on BlockDAG in a few seconds.

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What QUANTAID Solves

AI models rely heavily on the data used to train them.
That data is private, expensive and extremely sensitive.
The challenge is simple: today’s encryption will not survive future quantum computers.

Attackers are already collecting encrypted datasets now because once quantum machines mature, they can break classical encryption easily.
One breach is enough to destroy trust in any AI company.

QUANTAID protects AI data with encryption designed to survive future quantum threats.

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What QUANTAID Actually Does

When a user uploads data, everything happens safely inside their browser:

1. Upload any dataset
2. QUANTAID scans for PII, poisoning or bias
3. The dataset is encrypted with post-quantum security (Kyber-1024)
4. Only a tiny proof is sent to BlockDAG
5. The user receives a clean verification link they can share anywhere

Your AI stays powerful.
Your private data stays locked behind encryption that even future quantum computers can’t crack.

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Why BlockDAG Works Perfectly With This

We need speed, low cost and a chain that can handle real usage.

BlockDAG provides:

• Fast confirmation
• High throughput
• A smooth developer experience
• Reliability for long-term proof storage

This makes BlockDAG a solid home for permanent, tamper-proof AI data proofs.

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Ecosystem Value

Every team that uses QUANTAID becomes a repeat BlockDAG user.
More AI companies means more proofs, more volume and more consistent activity on the chain.

We’re not just storing proofs.
We’re building a path for AI companies to anchor their entire trust layer on BlockDAG.

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What We Completed in This Wave

For this wave, we focused on making QUANTAID easier to understand and stronger technically:

• Improved the encryption functionality
• Added clearer explanations based on Wave One feedback
• Wrote proper documentation and a readable README
• Created a clean landing page for quick understanding
• Built a mock backend and a basic AI simulation to show how the system will work
• Set the foundation for deeper technical upgrades in later waves

This wave focused on clarity, structure and strengthening the core security idea.

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Quick Start

git clone https://github.com/pioneerdevs/QuantAid
cd QuantAid/frontend
npm install && npm run dev