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AI Governance Framework

AI Governance & Adoption

Govern AI agents before they become your next breach vector. Deploy autonomous AI with confidence using policy-driven controls aligned with ISO 42001, OWASP Top 10 for LLM, and Australian AI Ethics Principles.

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Security Controls & Risk Management

Five integrated controls that mitigate AI-specific risks and ensure compliance.

Governance Framework

Policy-driven controls aligned with ISO 42001, OWASP Top 10 for LLM, and Australian AI Ethics Principles.

Security Controls

Defence in depth for AI agents with input validation, output sanitisation, and behavioural monitoring.

Audit & Compliance

Continuous compliance monitoring with automated evidence collection for regulatory requirements.

Risk Management

Identify, assess, and mitigate AI-specific risks including prompt injection, excessive agency, and shadow AI.

Platform Agnostic

Works across AWS Bedrock, Google Vertex AI, Azure AI Agents, LangChain, Strands, and more.

What We Deliver

End-to-end AI governance from design through to production operations.

Agent Design & Planning

Define agent use cases, governance policies, and secure architectures. Structured assessment of capabilities, data access requirements, and risk classification.

Input Validation & Safety

Prompt injection prevention, input sanitisation, and adversarial input detection. Protect against malicious inputs that manipulate agent behaviour.

Output Controls & Filtering

Output filtering, PII detection, and content safety guardrails. Ensure agents produce safe, compliant responses aligned with policies.

Access Controls & Identity

Least-privilege enforcement, identity verification, and session management. Control what agents can access and what actions they can perform.

Runtime Monitoring

Real-time monitoring of agent behaviour, token usage, and anomaly detection. Identify and respond to security incidents as they occur.

Compliance & Audit

Automated evidence collection, compliance reporting, and audit trails. Demonstrate adherence to ISO 42001, SOC2, and regulatory requirements.

The AI Agent Risk Landscape

New attack surfaces require comprehensive governance frameworks.

LLM01 — Prompt Injection

Adversaries manipulate agent behaviour through crafted inputs, bypassing safety controls and extracting sensitive information.

LLM08 — Excessive Agency

Agents with unconstrained permissions executing unintended actions, modifying critical systems, or escalating privileges.

Shadow AI — Unmanaged

Unsanctioned agent deployments bypassing security controls, creating blind spots and compliance gaps across the organisation.

AI Agent Lifecycle Stages

Comprehensive governance from design to production.

1

Design & Planning

  • Use Case Definition
  • Policy Framework
  • Architecture Review
2

Build & Validate

  • Input Validation
  • Output Controls
  • Behavioral Testing
3

Deploy & Monitor

  • Runtime Monitoring
  • Access Controls
  • Incident Response

Related Services

Complementary capabilities for comprehensive AI adoption.

AI Engineering

Strategy, platforms, security and governance for enterprise AI adoption across the full lifecycle.

Security Engineering

Secure CI/CD, secrets management, and AI security including prompt injection detection and guardrails.