AI without assurance is just risk at scale.
Nine pillars of AI assurance, mapped across the full delivery lifecycle — from the boardroom decision to invest, through to what’s still running in production a year later.
Every AI assurance firm assesses a model and hands over a report.
We built something different.
Nine pillars that cover governance, engineering, security, operations, infrastructure and delivery — so assurance is present everywhere an AI system actually lives, not just at the moment before it ships.
01
Governance, Risk & Oversight
The Problem
Boards approve AI investment with no repeatable way to classify risk, assign accountability, or produce evidence for auditors.
What we offer
- AI Assurance Readiness Assessment
- AI Assurance Maturity Assessment
- AI Vendor Due Diligence
- AI Risk & Control Framework Design
Board-ready governance and accountability
02
Architecture, Tooling & Platform
The Problem
Fragmented AI tooling and no shared control points make governance impossible to enforce, however well it’s written down.
What we offer
- AI Assurance Reference Architecture
- Tooling Blueprint & Evaluation Harnesses
- Underpins every other pillar
Operational backbone for every pillar
03
AI Quality Engineering
The Problem
AI fails in ways traditional QA was never built to catch — hallucination, non-determinism, silent accuracy drift.
What we offer
- AI Testing Assessment
- AI Test Strategy & Assurance Planning
- AI System Validation / Testing
- Test Automation Framework
Testable AI quality and defensible release decisions
04
AI Security & Resilience
The Problem
Agentic AI multiplies the attack surface — prompt injection, shadow AI and supply-chain risk have no equivalent in traditional security.
What we offer
- AI Security Testing
- Agentic Assurance Shadow
- AI Discovery & Governance
- AI-BOM & Supply Chain Audit
Reduced AI attack surface and resilient controls
05
Operations & Posture
The Problem
Once AI reaches production, most organisations stop watching it — only 27% monitor every output it generates.
What we offer
- AI Assurance Managed Service
- AI Risk Posture Management
- Continuous Monitoring Across All Services
Continuous evidence, posture and managed assurance
06
AI Infrastructure & Platform Assurance
The Problem
Nobody assures the platform AI actually runs on — compute, data pipelines, identity and failover are left unchecked.
What we offer
- AI Infrastructure & Platform Assurance
- Compute, Data Pipeline, Identity & Access Assurance
- Resilience, Failover & Model Artefact Governance
Assures the platform the model depends on
07
AI DevSecOps Pipeline Assurance
The Problem
AI quality gets bolted on right before release instead of built into delivery — by the time it’s caught, it’s already shipped.
What we offer
- AI DevSecOps Pipeline Assurance
- AI Quality Gates Embedded into CI/CD
- CAB AI Impact Assessment & Release Evidence
Assurance inside delivery, not after delivery
08
Commercial & Procurement Governance
The Problem
Enterprises buy AI and third-party models with no standard way to assess vendor or supply-chain risk before signing.
What we offer
- AI Vendor Due Diligence
- AI-BOM & Supplier Control Requirements
- Underpins every commercial engagement
Procurement confidence and third-party risk control
09
Education & Change Enablement
The Problem
AI governance fails without a workforce that actually understands and adopts it — policy without capability is just paper.
What we offer
- AI Training & Executive Awareness
- Role-Based Learning & Assurance Academy
Capability adoption and buyer education
