AI Governance Readiness Assessment
Know what AI you have, how risky it is, and what it takes to govern it. Inventory, risk tiering, a 26-control gap assessment, draft policies, and a prioritized roadmap.
Scope and deliverables →Every engagement starts with a free gap check and a written statement of work. Final fees depend on scope, number of AI systems, and organizational complexity.
Know what AI you have, how risky it is, and what it takes to govern it. Inventory, risk tiering, a 26-control gap assessment, draft policies, and a prioritized roadmap.
Scope and deliverables →Threat model, control review, and authorized adversarial testing for an LLM application, RAG system, or AI agent, mapped to MITRE ATLAS and the OWASP Top 10 for LLM Applications.
Scope and deliverables →Extend your data governance program to the LLM boundary: classification with AI handling rules, lineage for AI data flows, and approval, retention, and monitoring controls.
Scope and deliverables →Answer bank and enterprise AI due-diligence questions accurately and consistently, backed by policies and evidence that survive follow-up.
Scope and deliverables →Senior AI risk leadership on a retainer: governance committee, use-case intake and approval, key risk indicators, vendor AI reviews, and examination preparation.
Scope and deliverables →Find your cryptography, prioritize what quantum computing puts at risk, and build a crypto-agile migration roadmap aligned to NIST's post-quantum standards.
Scope and deliverables →AI agents and workflow automations built with governance controls from day one: approved-model allowlists, data classification at the LLM boundary, prompt-injection defenses, human approval for consequential actions, and audit logging.
Scope and deliverables →Prefer to run the program yourself? The comply platform provides the 26-control framework, guided artifact generation, training, and audit package export on an annual subscription.
About the platform →Starting prices cover a defined baseline scope described on each service page, typically one business unit or a stated number of AI systems. The statement of work fixes the fee before work begins; there are no hourly overruns.
Yes. The practice is built on financial-services rigor, and that applies directly to healthcare, insurance, SaaS, and any organization facing AI due diligence from regulated customers.
No. Engagements provide governance, risk, and security advisory services. Regulatory interpretations should be confirmed with your legal counsel, and deliverables are designed to support that review.
Work is performed under NDA, preferably within your systems. Client data is never entered into AI tools without your written approval and only in tools you approve.
Yes. See Partner With Us for subcontracting and white-label delivery.