AI Governance & Adoption

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

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

Continuous compliance monitoring with automated evidence collection for regulatory requirements.

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

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

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

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

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

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

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

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

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

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

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