AI Assurance
Evidence that the system does what you say it does
Assurance is the difference between believing an AI system works and being able to demonstrate it — to a regulator, an insurer, a customer, or a court.
What this covers
Four assurance capabilities
AI system assurance
End-to-end examination of a deployed system: its data, its model, the controls around it, and the human decisions it informs.
Conformity assessments
Structured assessment against a named standard or regulation, producing the documentation set that regime expects.
Independent verification & validation
Verification that the system was built to specification; validation that the specification was the right one.
Continuous assurance
Ongoing testing against the same criteria, so a passing result in one quarter is not mistaken for a passing result today.
What we examine
The system, not the demonstration
A curated demonstration tells you what a system can do on a good day. Assurance is concerned with what it does on an ordinary one — under distribution shift, adversarial input, degraded infrastructure, and operator fatigue.
- Model performance under drift
- Robustness to edge and adversarial input
- Fairness and disparate impact
- Explainability and traceability
- Data lineage and quality
- Human oversight in practice
- Failure and fallback behaviour
- Change management and versioning
Standards
Assessed against published criteria
- ISO/IEC 42001:2023
- Artificial intelligence management system (AIMS) — the certifiable organisational standard for governing AI.
- NIST AI RMF 1.0
- The Govern, Map, Measure, Manage functions, plus the Generative AI Profile (NIST AI 600-1).
- EU AI Act
- Regulation (EU) 2024/1689 — the first comprehensive, risk-tiered statutory regime for AI.
- prEN 18286
- The draft European harmonised standard for AI quality management systems under the AI Act.
Deliverables
What you receive
Assurance report
Scope, method, evidence, findings, limitations, and an explicit opinion — written to be read by a non-technical board and defended to a technical regulator.
Evidence package
The underlying test artefacts, versioned and retained, so a third party can reconstruct how a conclusion was reached.
Remediation plan
Findings ranked by consequence, with the specific evidence that would close each one.
Related capabilities
Deploy AI with confidence.
Start with an independent assessment of your highest-stakes AI system.