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Security

Enterprise-grade infrastructure for regulated industries

Infrastructure Security

AICOMPLYR is built on enterprise-grade infrastructure designed to meet the security requirements of regulated industries including pharmaceuticals, healthcare, and financial services.

Encryption. All data is encrypted in transit (TLS 1.2+) and at rest (AES-256). Database connections use SSL with certificate verification.

Access Controls. The platform enforces role-based access controls (RBAC) at every layer. Row-level security (RLS) policies ensure complete tenant isolation — data physically cannot cross workspace boundaries.

Audit Trail. Every governance action, policy change, and compliance decision is logged with full context in a tamper-evident audit trail designed for regulatory inspection.

Compliance Architecture

295 RLS Policies. 100% table coverage across 86 database tables ensures no data leakage between enterprises, agencies, or workspaces.

Tamper-Evident Records. Proof bundles and Effective Policy Snapshots are hash-chained and immutable once generated, providing auditors with verifiable evidence chains.

eIDAS2 Ready. Architecture supports qualified electronic signatures and Verifiable Credentials via activation-gate pattern, with QTSP integration available on demand.

Operational Security

Error Monitoring. Real-time error monitoring via Sentry with OpenTelemetry instrumentation provides full visibility into platform health.

Rate Limiting. API endpoints are rate-limited to prevent abuse and ensure fair access for all users.

Dependency Management. Automated vulnerability scanning of all dependencies with regular updates to address known CVEs.

Reporting a Vulnerability

If you discover a security vulnerability, please report it responsibly. Contact our security team at security@aicomplyr.com. We take all reports seriously and will respond within 48 hours.

Security Contact

Email: security@aicomplyr.com

General inquiries: legal@aicomplyr.com

AICOMPLYR

Evidence-as-a-Service infrastructure layer governing AI tool decisions at the enterprise-partner boundary.

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