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    AI risk and assurance

    Worried about how your business uses AI?

    Confidential data in tools, outputs nobody checks, agents with too much access. Find the risks, put controls in place and get an independent review when you need one.

    an AI agent inside a translucent permission boundary with a human review stamp outside it.

    What do you need help with?

    • Risk and gap assessment

      Find the tools and agents in use, their owners, the data they can reach and the controls that are missing.

      Try the governance self-check
    • Governance and security review

      Review approvals, permissions, connected tools, release controls and the ability to stop an unwanted action.

      See the review areas
    • ISO 42001 and NIST AI RMF preparation

      Identify gaps in your management system or risk practices, with an action list for the people responsible.

      Framework assessments
    • Policy and implementation help

      Create usable policies, a system inventory and an approval process, then help teams put them into practice.

      Policies and controls
    • Staff and leadership training

      Help employees protect confidential information, check outputs and know when to ask for human review.

      Company workshops

    What we look at.

    A system's governance should match what it can actually do. We review decisions, permissions and operating records together.

    Technical review areas
    • Authorized work ticket & agent authorization

      Trace selected tasks to an approved purpose, accountable owner and the agent actions permitted for that task. Review how changes in task scope are authorized.

      Records: Approved work tickets, acceptance criteria, agent execution policies and task authorization records.

    • The exact change & review

      Trace the commit or revision to the task and the artifact released. Inspect the review decision and whether reviewers could see the actual change before approving it.

      Records: Commit identifiers, pull requests, revision history, reviewer records and artifact references.

    • Test integrity

      Inspect whether tests relate to the reviewed change, whether results can be bypassed or altered, and how failed tests are handled. Reperform selected checks with authorization.

      Records: Pipeline definitions, protected test settings, test outputs, failure records and exception approvals.

    • Release approval

      Trace sampled releases to the tested artifact and approval. Review who can deploy, override a gate or authorize an emergency change.

      Records: Release approvals, deployment records, artifact digests, pipeline access and emergency-change records.

    • Human and agent permissions

      Compare human and service identities with their intended roles. Inspect privilege boundaries, delegation, access reviews and removal of access; test selected boundaries where authorized.

      Records: Role definitions, identity configuration, service-account grants, access reviews and records of employee onboarding, role changes and departures.

    • Skills, plugins, connectors & MCP servers

      Review which capabilities an agent can invoke, who approves them and how their versions and permissions are controlled. Inspect the boundary between a requested action and an allowed tool call.

      Records: Capability inventories, connector configuration, Model Context Protocol (MCP) server settings, approval records and tool-call traces.

    • Secrets and data

      Review credential handling and the data available to the workflow. Inspect classification, retrieval boundaries and external transfers; use authorized non-sensitive test cases for selected access checks.

      Records: Secret-store configuration, redacted access records, data-flow diagrams, retention settings and retrieval access rules.

    • Runtime evidence

      Trace selected actions through logs, traces and monitoring. Review whether records identify the acting identity, tool, outcome and relevant revision, and whether alerts reach an accountable person.

      Records: Redacted execution logs, correlated traces, monitoring configuration, alert records and retention settings.

    • Intervention and recovery

      Review how a person can stop an agent, revoke its access, roll back a change and handle an incident. Inspect exercises and authorized tests of those actions.

      Records: Stop and rollback procedures, revocation records, recovery exercises, incident tickets and follow-up actions.

    Governance review areas
    • System inventory

      Inspect use-case records for owners, purposes, data, models and dependencies. Follow unexplained differences between recorded systems and observed use back to the responsible team.

    • Ownership

      Review decision rights, risk acceptance, reporting and responsibility across business and technical teams.

    • Acceptable use

      Check whether permitted and prohibited uses, approval paths and exceptions are understood and reflected in practice.

    • Risk assessment

      Inspect risk assessments, affected stakeholders, evaluation criteria and decisions about treatment or acceptance.

    • Third parties

      Review vendor responsibilities, data use, access, change notifications and dependency risks.

    • Human oversight

      Review who intervenes, what they can observe, when they must act and whether intervention is recorded.

    • Incident handling

      Inspect reporting, escalation, containment, recovery and lessons learned for incidents involving automated systems.

    What you receive.

    A report of the weaknesses found, the risks they create and recommended actions. Policy support produces documents, owners and review records your team can use.

    Limits

    We do not certify model outputs or issue audit opinions, SOC reports or certificates. Findings cover the systems and records reviewed.

    Sample findings and deliverables
    an AI agent monitoring console showing an action trace with pause and rollback controls.
    Permissions, intervention and human oversight

    For firms

    Assurance support with AIGC™.

    AIGC is our assessment approach for AI general controls, rather than an external standard or accreditation.

    We help your team review system inventories, permissions, connected tools, change controls and human oversight. The working papers follow your procedures and go through professional review before handover.

    What concerns you about the systems in use?

    Tell us the tools, the problem and any deadline. We reply by email with how we can help.