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OFFLINE

DIFFERENTIAL PRIVACY

CONSTELLATION

Opt-in to improve models. Only noisy, differentially private patterns leave your device. Never raw text. Never PII.

Constellation Opt-In

Fully offline. No data leaves your device.

CONTRIBUTIONS

0

updates sent

PRIVACY BUDGET

ε =

per contribution

MODEL

DP POLICY

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MODEL INFO

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HOW IT WORKS

1

Local Processing

All inference happens on your device. Raw prompts never leave.

2

Gradient Clipping

Gradients are clipped to bound sensitivity before any sharing.

3

Gaussian Noise

Calibrated noise is added to provide (ε, δ)-differential privacy.

4

Secure Aggregation

Only aggregated, noisy updates reach the server. Individual contributions are mathematically unrecoverable.

Constellation uses formal differential privacy guarantees. Read the whitepaper →