An AI agent built around a clear goal

We start by defining what the agent should accomplish, which sources it may consult and which actions it is allowed to take.

Reliable information and controlled access

An agent’s quality depends on the documents and systems it can access, clear instructions and validation rules. Permissions should be limited to what is necessary.

Practical examples

An agent might find a procedure, prepare a draft response, summarise a case or support research. Outputs should be tested against real scenarios.

Keep people involved where it matters

For sensitive or uncertain actions, workflows should include human review, useful logs and a straightforward way to stop or correct the agent.