Security & AI Governance
Adopt AI without inheriting the risk.
For regulated buyers, governance is the difference between an AI program and an AI incident. Here is how we handle your data, your systems, and your risk.
Data & delivery security
How we handle your data.
Your data stays yours
Client data is processed within client-controlled environments. Private AI deployments keep models, prompts, and outputs inside your perimeter — on-prem, VPC, or air-gapped.
Least-privilege everything
Engineers and AI agents alike operate on scoped, auditable credentials. Access is granted per engagement and revoked at close.
Compliance-aligned architecture
HIPAA-aware healthcare systems, GDPR-aligned data handling, and sector-specific controls for government and finance — designed in, not retrofitted.
Secure delivery pipeline
Dependency scanning, secrets hygiene, code review, and security testing as standing parts of our SDLC.
AI governance
Controls built into every AI system we ship.
The same framework we offer as a service — applied to our own deliveries first.
Human-in-the-loop approvals
Agentic systems pause for sign-off at compliance-sensitive gates you define.
Guardrails outside the model
Hard policy limits on inputs, outputs, and actions — enforced in code, not prompts.
Complete audit trails
Every AI interaction and agent action logged, attributable, and reviewable.
PII detection & handling
Masking, minimization, and retention controls for sensitive data in AI flows.
Model evaluation & red-teaming
Structured accuracy, bias, and abuse testing before deployment — and monitoring after.
Rollback & sandboxing
Agents prove themselves in test environments; production changes have clean reversal paths.
Review your AI governance.
Bring your compliance team. We'll walk through controls, audit trails, and deployment options together.