We design, harden, and operate AI systems under policy, identity, and encryption – so models add value without adding risk.
Risk and assurance, from the first use case.
Define allowable uses, data handling, retention, and approval; set measurable guardrails.
Classify and mask PII/PHI, enforce residency, and prove lineage from source to prompt.
Manage registry and versioning; run evaluation harnesses, bias/robustness tests, and change approval.
Keep humans-in-the-loop for sensitive steps; generate on-demand explanations and outcome traceability.
Red team models, defend against prompt injection/jailbreaks, and isolate untrusted connectors.
Track quality, drift, safety violations, costs, and performance with alerting and rollback paths.
Deploy policy-aware chat/agents with SSO, DLP, and auditable connector scopes.
Assess vendor models and SaaS add-ons; contract for evidence and exit options.
You get trustworthy AI that teams can adopt and auditors can approve.
Set allowed tasks, data classes, retention, and approval chains. Map guardrails to risk tiers.
Enforce least-privilege access for users, services, and agents. Protect secrets and keys; isolate tenants and environments.
Mask PII/PHI at ingest, log lineage, and restrict cross-border flows. Keep golden sources authoritative.
Register and version models; run quality, bias, and safety evaluations pre- and post-deployment; require approvals for change.
Apply input/output policy checks, content filters, rate limits, and tools/connectors isolation. Keep humans-in-the-loop where impact is high.
Write immutable logs, capture e-signatures and approvals, package CSV and GxP-style documentation for reviews.
