Responsible AI

People stay accountable

Every AI system we put into production has a named business owner who can switch it off. Decisions that matter stay with people: in regulated work such as healthcare, audit and public services, AI output is a draft that a qualified person accepts, edits or rejects.

Risk is assessed before we build

Each use case is classified by its impact, the sensitivity of the data it touches and how much it may do without a person. That classification sets the approval gates, the controls and the level of human review a system needs before it reaches users.

Answers are grounded and transparent

Where a system answers from an organisation’s documents or data, it retrieves only what the user is permitted to see and shows the sources it used. It is designed to say when it does not know rather than guess, and users are told when they are interacting with AI.

Autonomy is bounded

Agents are given a defined task and stopping condition, and hold no more access than the person they act for. Every action is logged and reviewable; reversible steps can be rolled back, and irreversible actions require explicit human approval.

Systems are evaluated before release, and after every change

Systems are tested for correctness, grounding, bias and safety before release. The same tests run again whenever a prompt, model, tool or data source changes, so a change that reduces quality is caught before users see it.

Data stays inside the agreed boundary

Data is processed where the client’s policy allows — cloud, private cloud, on-premises or a sovereign environment — and personal and confidential data is handled under the client’s own policies.

Quality is monitored in operation

In production we measure quality against an agreed baseline, watch for drift as content, models and usage change, and review incidents to find and fix their cause. What we learn is added to the system’s evaluation suite.

We apply the same principles to ourselves

In our own hiring, the AI interview produces a score and a transcript that a recruiter reads; no candidate is rejected by the model alone, and adjusted formats are available on request. The assistant on this website generates its answers with AI, can make mistakes, and can put you in touch with a person.

Questions

To discuss how these practices would apply in your organisation, contact our team. For the governance work we do for clients, see AI Governance & Responsible AI.