Before AI touches customers, know what it will say.
We put the controls around AI that is already running or about to be: test sets built from your real work, scoring of every change, limits on what a model can say or do, redaction of sensitive data and an audit trail you can show a client, an insurer or a regulator.
What it costs to leave it as it is.
No way to know it works
Without a test set, every prompt change is a guess and every model update is a risk.
Sensitive data in the prompt
Names, account numbers and health details end up in places they should never be sent.
Nobody owns the answer
When the AI gets something wrong in front of a customer, there is no log, no policy and no one accountable.
Four steps, run by an operator who has done it before.
With an engineering bench building in the background. Scope and timeline are written into your agreement before we start.
Write the policy
What the AI may and may not do, say and see, in language your team and your lawyer both accept.
Build the test set
Real questions and cases with known good answers, including the awkward ones.
Add the controls
Filters, redaction, permission checks and hand-off to a person, built into the flow.
Monitor and report
Scores on every change, alerts when quality drops and a log you can hand over.
The disciplines behind this build.
From the three phases every engagement runs. Tap a card for the diagram; each is explained in full in the playbook.