AI Governance & Assurance
Core servicesWe give you a defensible, evidenced answer to the questions your board, your regulator and your customers are already asking: which AI you run, what risk it carries, who owns it, and how you can prove it.
Problems we solve
- "We rolled out AI across the company and nobody can list what is in use." Copilots, embedded vendor features and staff-side tools multiplied faster than approvals — no register, no owner, and no idea which uses touch personal data or make decisions about people.
- "The board asked whether we comply with the EU AI Act and we could not answer." You do not need a legal opinion as much as a classification: which systems are prohibited, high-risk, limited or minimal — and what that obliges you to do.
- "A customer or partner sent us an AI due-diligence questionnaire we cannot complete." Enterprise procurement and partner onboarding now ask for AI governance evidence. Without an inventory and a policy, the deal stalls or the answer is guesswork.
- "An AI system influences decisions about people and we cannot explain it or show human review." Swiss data-protection law already gives individuals rights over automated decisions. You need the controls, not an apology.
- "Our AI vendors change models underneath us and we cannot track the risk." Model supply chains shift without notice; without third-party AI risk terms you inherit exposure you never assessed.
What we deliver
- AI System & Model Inventory — a live, risk-classified register of every AI use case, tool, model and vendor, with named owners, purpose, data categories, geography and lifecycle stage.
- AI Risk & Regulatory Classification — each system placed on the EU AI Act tier model and checked against Swiss data-protection and sector rules, with the resulting obligations mapped to an owner.
- AI Governance Operating Model & Policy Suite — the written rules and structures: AI policy, acceptable use, approval workflow, human-oversight design, roles and a governing body, built to ISO/IEC 42001 and the NIST AI RMF.
- AI Assurance & Audit-Readiness Pack — the evidence an independent party can inspect (testing and monitoring records, oversight logs, documented decisions), plus an AI-specific incident-response playbook and reporting duties.
Suited to
Boards, risk owners, compliance leads and CISOs deploying AI into decisions about people or into regulated processes.
Frameworks we work against
What you end up with
A defensible position on your AI: what you run, what risk each system carries, who owns it, and the evidence that proves it.
How you know it worked
- A complete AI register exists, every entry has a named owner, and there is no unapproved AI in use.
- Every system carries a risk tier and either a "no action" rationale or a dated remediation plan.
- A written AI policy is formally approved by management, not drafted and shelved.
- An AI due-diligence questionnaire can be answered from documents, not reassembled in a rush.
- An evidence pack exists that supports an ISO/IEC 42001 gap analysis or a certification-readiness review by an accredited body.
Engagement shape
Four phases, run end to end. We agree the systems in scope and the accountable executive first, then work up from the register to a policy suite and an evidence pack.
- Scope and mobilisation — agree the systems in scope, the risk criteria and the accountable executive.
- Inventory and classification — build the register, classify every system, and produce the gap and remediation view.
- Governance and policy build — operating model, policy suite, approval workflow, oversight and vendor-risk terms.
- Assurance and readiness — evidence pack, incident playbook, and a documented readiness position against ISO/IEC 42001 or a customer due-diligence standard.
Entry point: Available as a fixed-scope entry engagement: a stand-alone AI Inventory & Classification Sprint that produces the register and the classification, and nothing else.