Find out what's actually broken in your AI systems —
before a customer does.
A fixed two-week audit of the AI features you've shipped — scored, ranked, and written for the person who has to act on the findings, not the person who already understands the system.
Most AI features shipped in the last 18 months were never actually audited.
They were built fast, by a small team, against a deadline. Nobody went back afterward and asked what happens when the data source changes, when usage spikes, or when the model gets something confidently wrong in front of a customer. That gap doesn't show up in a demo — it shows up in a security questionnaire you can't answer, or an outage with no clear owner.
Four risk surfaces. Every system, every time.
The same framework applied consistently, so findings are comparable and nothing gets missed because it wasn't the obvious place to look.
Data exposure
What the AI layer can read and write, whether access matches intent, and whether permissions have drifted since launch.
Architecture brittleness
Single points of failure, vendor lock-in, undocumented dependencies, and what breaks if one person leaves.
Output reliability
Where a wrong answer reaches a customer, what it costs if it's wrong, and whether anyone would notice first.
Operational readiness
Headroom at 10x load, clear ownership, and whether there's a rollback path if a change makes things worse.
Know exactly where the risk is before someone else finds it.
A 20-minute call to see if an audit makes sense for what you've built.
Book a 20-minute call