Clear accountability
Decision rights and roles should be understandable and actionable. If nobody owns it, it is not governed.
Principles
Responsible technology
We position governance as an enabler of confident growth. These are the principles we hold ourselves to when delivering across software, SaaS and AI — including where our own work is AI-assisted.
Evidence and traceability
Important decisions should be supported by records, context and reviewable reasoning — not recollection.
Privacy and data awareness
Privacy and data handling are considered from the outset, including what we should decline to collect.
Proportionate controls
Control intensity should fit the organisation's size, maturity, risk and operating model.
Human review
Technology-assisted recommendations are reviewed by a person before they inform a client decision.
Continuous improvement
Governance practice adapts as technology, regulation and operating conditions change.
How we use AI in our own delivery
- Where we use itData normalisation, reconciliation candidate generation, anomaly surfacing and internal drafting.
- Where we do notFinal licence positions, compliance conclusions and client recommendations are not issued without consultant review.
- What we discloseIf AI materially shaped an analysis you receive, we say so in the deliverable.
- Client dataHandled per the Trust Centre; we do not train general models on client data.
What we will tell you plainly
- When our data confidence is low, and why
- When a saving depends on an interpretation a publisher may dispute
- When the right answer is to do nothing this cycle
- When a capability is under development rather than available