Your GRC was written before AI. Model goes where it cannot.
Most governance systems were designed for software that changes on a release schedule. AI does not. Model is the assurance layer built for AI, and it reports back into the tools you already run.
- Claims triage v4CurrentISO 42001 · high risk · as at 12 Feb 2026
- Branch vision · safetyAgeingEU AI Act · limited risk · as at 30 Oct 2025
- Service assistant (LLM)LapsedEvaluation overdue · as at 18 Jul 2025
- Shadow model · financeUnknownDiscovered, unregistered · as at never
AI introduces conditions your GRC was never written to read.
Traditional controls assume a system behaves predictably and changes on a schedule. Models drift, training provenance is often opaque, outputs can be confidently wrong, and unregistered AI spreads faster than any register can track. New standards exist because the older controls do not reach.
ISO/IEC 42001
A management system written specifically for AI.
EU AI Act
Phased, risk based obligations for AI systems placed on the market.
NIST AI RMF
Risk management practices for AI, from mapping through measurement.
Deep on AI. Built to fit what you already run.
Model does not ask you to remove your GRC or IRM platform. It sits as a specialist layer beneath it, goes considerably deeper on AI than a general system can, then pushes a structured record upward so AI risk appears alongside everything else you govern.
AI risk lands as a row, not an email
Evidence already gathered and dated
One line on condition, defensible
Deeper on AI than a general platform can go, without replacing it.
Every model, agent and vision system, with owner and lineage
ISO 42001, EU AI Act, NIST AI RMF, mapped control by control
Evaluations, drift and behavioural evidence, dated
A structured record pushed upward into what you already run
Cameras, detection, safety systems
Assistants, summarisation, drafting
Tools acting on your systems
AI assurance begins one project at a time.
Assurance starts where AI risk actually lives, at the project. Hold a single project against the right controls before it reaches production, learn how your institution governs AI, then take that model and scale it. Project level records roll up into one organisational view.
From edge cameras to large language models.
Computer vision cameras, on the ground.
Safety cameras and operational vision systems. Model holds accuracy, privacy and consent, edge data handling and drift over time.
- Accuracy and validation
- Privacy and consent
- Edge data handling
- Drift monitoring
Assistants and agents built on large language models.
Model holds data leakage, prompt injection, output accuracy, model provenance and human oversight.
- Data leakage controls
- Prompt injection defence
- Output evaluation
- Provenance and oversight
Whatever AI your institution is running.
Map the assurance model to any AI project, agent or system that needs to be held before it goes live, or while it is already running.
- Project based onboarding
- Control mapping to any stack
- Continuous evidence
- Roll up to the risk view
We build the capability, not only the controls.
Governing AI well needs people who understand it. Alongside the platform, Testamark runs training that lifts your teams' AI governance capability, so the discipline holds after we leave the room.
Partner with us to set the standard.
We are building a partner network to lift AI governance across industry. If you advise, audit, implement or regulate in this field, we would like to work with you.
Pressure test how you govern AI today.
A working session with our AI governance leads, mapped to your own AI estate and standards program.