AI Agent Builders by GammaDX

An agent your risk team can interrogate.

Controls ship with the workflow. Every permission, decision, exception and unit of spend has an owner and a record.

Audit trail

Every run, input, decision and confidence score is written to a log your team can query.

Human in the loop

Defined thresholds decide what the agent does alone and what goes to a named person.

Data boundaries

Your data stays in your tenancy. Access is scoped, logged and revocable per system.

Cost control

Usage budgets and alerts are set per agent, making spend visible before it drifts.

Evidence from input to outcome

The active route stays visible. Low-confidence work leaves the automated path and enters a named human queue.

YOUR SYSTEMSApproved sourceScoped accessBusiness rulesAllowed actionHuman reviewgoverned agentreason · verify · routeOUTPUT
every run loggedsource data unchangedconfidence scored

What your reviewers should be able to ask

What data did this decision use?
Which account and permission accessed it?
Why did the agent act rather than escalate?
Which prompt, rules and model version ran?
What did the run cost?
Who can pause or revoke the workflow?

Bring risk and security into week one.

A 45-minute scoping call, with an engineer in the room. You leave with a written view of what an agent would do, what it connects to and what it would take to build.

01Which job, done by whom, how often
02Which systems it touches and who owns them
03What must never happen without a human
04How you would know it is working