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AI Governance, Security & Compliance Readiness
Put guardrails around AI before it reaches production: access boundaries, evaluation, monitoring, and the documentation that supports a compliance path.
The problem
Leaders want AI's upside without unmanaged risk, unclear data exposure, or surprises in an audit.
The outcome
A governed adoption model where AI systems are scoped, evaluated, monitored, and documented, so the organization can move with confidence.
What we build
- Assured Workloads overlays for regulated workloads, with CMEK and Secret Manager
- Data-handling controls: residency, VPC Service Controls, DLP, and policy tags
- Document-level access boundaries and logging/retention policy
- Model-safety evaluation before production, plus quality, drift, and misuse monitoring
- Gated dev-to-production promotion, vulnerability scanning, and Workload Identity Federation
- Documentation aligned to recognized frameworks and a responsible-use operating model
Technical foundation
Security Command CenterAssured WorkloadsVPC Service ControlsCloud KMSIAM
Typical deliverables
- AI risk and controls assessment
- Evaluation and monitoring setup
- Governance documentation package
- Responsible-use policy and operating model
Example use cases
- Standing up an AI governance baseline
- Preparing AI workloads for review or audit
- Giving security and legal teams real visibility
Governance & security
We design with NIST/FedRAMP/CMMC-aligned controls and support teams pursuing compliance. Lanthos is not a certifying body; certification depends on your authorization boundary and configuration.
Start here
Scope a AI Governance, Security & Compliance Readiness engagement.
Tell us what you are trying to ground in AI. We will tell you the honest path to production.