Proprietary frameworks built from practice, not theory
Each methodology has been developed and refined through hands-on application in complex, high-stakes environments.
The Regulated AI Governance Model™
A comprehensive, structured approach to governing AI risk in regulated financial services.
Designed for organisations adopting AI in complex or regulated environments, this model provides:
- AI risk taxonomy and classification framework
- Control library mapped to common AI use cases
- Board and executive reporting structure
- Regulatory alignment mapping (ISO 42001, NIST AI RMF, EU AI Act)
- Implementation roadmap and maturity assessment tool
Suitable for: Financial services, enterprise organisations, and any entity adopting or scaling AI that needs governance with depth.
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Cyber Clarity™ Board Briefing System
A methodology for translating complex cyber risk into language that drives board-level decision-making.
Most cyber risk reporting fails at the board level — too technical, too alarmist, or too vague to support informed decisions. Cyber Clarity™ provides:
- Structured reporting templates aligned to board governance obligations
- Risk quantification approaches suitable for non-technical audiences
- Incident communication frameworks
- Regulatory posture summaries
- Strategic cyber investment decision frameworks
Suitable for: Any board seeking to improve cyber governance without increasing noise.
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AI Readiness Accelerator™
A rapid assessment and implementation methodology for organisations operationalising AI.
The AI Readiness Accelerator™ takes organisations from intent to execution with governance built in:
- Organisational AI maturity assessment
- Governance and policy gap analysis
- Skills and capability readiness evaluation
- Security and data readiness assessment
- Prioritised implementation roadmap
- Quick-win AI solution identification and delivery
Suitable for: Organisations ready to move beyond AI experimentation into governed, production-ready deployment.
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