Policy
Responsible AI Statement.
The principles that govern how we design and operate AI systems.
Human oversight
We design AI systems with human oversight and human-in-the-loop approvals at consequential steps.
Evaluation before release
We evaluate LLM, RAG, and agentic systems before release, and monitor them after deployment.
Grounding and source traceability
We ground answers in governed sources and design for source traceability.
Access control
We design access control and data classification into AI systems so models respect entitlements.
Bias and fairness
We support bias and fairness review where relevant to the use case and its impact.
Incident escalation
We define escalation paths for unsafe, unexpected, or out-of-policy behaviour.
Monitoring and continuous improvement
We monitor behaviour, drift, cost, and quality, and route findings back into improvement.
We align governance work to recognised frameworks such as ISO 42001 and the NIST AI RMF.
Last reviewed: July 2026