AI Data Policy
Control whether AI is disabled, private-only, enterprise-approved or supplied through a client API key.
Read AI policy →Centralized controls for encryption, AI processing, retention, access, auditability, data residency and enterprise assurance.
Control whether AI is disabled, private-only, enterprise-approved or supplied through a client API key.
Read AI policy →Delete after delivery, retain 30/90 days, or apply a client-managed policy.
Security issues should be routed through a documented vulnerability-reporting process.
Project files are kept outside the public web root, attachment tokens expire, uploaded files are validated structurally and production deployment requires malware scanning. Role-based access and audit events are built into the application layer.
HTTPS/TLS is expected at the production edge, secure cookies are enabled in production and security headers restrict framing, scripts and cross-origin behavior. Credentials and live secrets are intentionally not bundled with the release package.
Projects can disable AI or select a controlled processing route. The privacy mode, retention preference and data-region preference are captured during intake so the handling model is visible rather than implicit.
Security questionnaires, NDAs, data-processing requirements, subprocessor information, incident procedures and business-continuity evidence should be handled as documented procurement artifacts. We publish only controls that are actually implemented or can be evidenced.