Build trusted AI. Equip your teams. Turn governance into practice.
We help organisations move from AI experiments to governed adoption: an AI management system aligned with ISO/IEC 42001, and hands-on training so people use enterprise AI platforms securely and well.
Leaders who are accountable for AI, and the teams who deliver it
CISOs and security leaders
Turn AI risk into controls, evidence and supplier oversight your auditors can follow.
CROs and compliance leaders
Build a defensible AI risk method, clear ownership and a management system aligned with ISO/IEC 42001.
CTOs and engineering managers
Ship AI features with evaluation, guardrails and release gates that do not slow delivery to a crawl.
Learning and development teams
Role-based programmes for Claude, Gemini Enterprise Agent Platform, Amazon Bedrock, Microsoft Copilot and Microsoft Foundry.
Business and operations heads
Know which AI use cases to approve, who owns them and how to measure value and risk.
Not sure where to start?
Start with a conversation. Book an AI Governance Consultation.
Two connected offerings
AI Governance and ISO/IEC 42001 Implementation
From scope and readiness assessment to inventory, risk assessment, policies, controls, internal audit and certification-audit preparation. Eleven stages, each with defined deliverables.
- AI system inventory with accountable owners
- Risk and impact assessments
- Policies turned into operating controls and evidence
Enterprise AI Training and Enablement
31 courses across five AI platforms and three architecture and delivery tracks (TOGAF, SAFe on-demand, AI solution architecture), with exercises and takeaway materials. On site, live online or on demand.
- Executives, risk and security, engineers, business users
- Current product and framework names, verified October 2026
- ArniTech completion certificates
From policy on paper to controls in daily work
- Know
Inventory your AI systems and name owners. - Assess
Rate risks and impacts, then decide what to allow, change or stop. - Control
Embed review gates, oversight and monitoring in how teams already work. - Enable
Train people by role so the controls are understood and used.
The kinds of engagements we design
These are illustrative scenarios, not client case studies or achieved results.
A SaaS firm answering enterprise buyers
Customers ask for evidence of AI governance. Intended outcome: a scoped AIMS, a register of AI features and a clear evidence pack ready for questionnaires.
A bank rolling out a Copilot
Leaders worry about oversharing and misuse. Intended outcome: a permissions review, usage policy and role-based training before wider rollout.
An engineering team building RAG
Prototypes work but nobody trusts them for production. Intended outcome: evaluation sets, guardrail testing and a release gate the team owns.