Privacy, Data Control and Infrastructure Governance

Sphere.ai is designed with privacy at its core, minimizing persistent data capture while enabling secure, verifiable interactions across the platform. All personal messaging between fans and creators is protected via end-to-end encryption, and users have granular control over how their engagement data is collected and used.

A zero-knowledge-based reputation system ensures that users can demonstrate trust and activity without revealing their behavioral history or identity. Distinctions are also made between anonymous and logged-in users, enabling layered privacy settings and opt-out visibility controls.

All internal machine learning models operate solely on aggregated, non-identifiable usage patterns—no user-level data is used for training without explicit, informed opt-in consent.

• End-to-end encrypted fan-to-creator messaging

• Opt-out APIs for all engagement-based tracking

• Zero-knowledge reputation scoring to preserve user privacy

• Differentiated handling for anonymous vs. authenticated sessions

• No ML training on personal data without user consent