Socialtrait's infrastructure and practices are designed to meet the highest standards of data privacy and regulatory compliance, ensuring that client data remains secure, private, and isolated at all times.
1. Absolute Data Segregation Your confidential data is never used for general model training and is never shared or leveraged for any other client.
2. Isolated Instances Each client's AI community is built and maintained in a secure, isolated environment. Data usage is limited strictly to the project scope.
3. Data Encryption
In-Transit: TLS 1.2 encryption ensures secure data transmission.
At-Rest: AES-256 encryption protects stored data.
4. Internal Access Controls
Role-Based Access Control (RBAC): granular access permissions based on user roles.
Multi-Factor Authentication (MFA): required for all internal access.
IP Whitelisting: access is limited to pre-approved networks.
5. Data Refresh Practices Communities are refreshed on a configurable schedule (e.g., monthly, quarterly) to stay aligned with real-world shifts. Updates incorporate socioeconomic, cultural, and market trend data layers without compromising data privacy.