Expert-led. AI-amplified.
Your data stays yours.
We are open about both halves of this: we use AI heavily, on our side of the glass — and we can show you, control by control, why that never puts your data or your systems at risk. Most providers can honestly claim only one of the two. Many can claim neither.
AI does the thinking. Tested automation does the doing. An expert makes every call.
The fear about AI in operations is specific, and it's fair: an AI improvising commands on a production system nobody can afford to lose. We built the practice so that can't happen — not as a policy, but as an architecture with three distinct layers. This has been our design rule since day one, not a page written for the AI moment.
Deterministic automation
Everything that touches a client system is a tested, version-controlled runbook or monitoring rule — rehearsed in our lab until it's boring, same input, same result, every time, fully auditable. Alerting is deterministic too: clear rules fire, not model hunches. It is explicitly not an AI figuring out steps on the fly on your box.
AI, on our side of the glass
The AI reads advisories and CVE feeds at a scale no human can, cross-checks findings against reference data, maps failure modes, keeps documentation current, and drafts plans and reports. Its output is a prepared decision handed to a human — context after a rule fires, never an action. It proposes; it never disposes.
An expert in the middle
A senior engineer — decades on AIX and Power — validates the AI's work and gates everything that reaches your systems. That's not overhead; it's the product: experienced AIX engineers, amplified. You're not paying for an AI experiment on your infrastructure. Part of our job is making sure the AI behaves.
Why work this way? Because these systems reward experience, and experience is exactly what's leaving the industry. Our answer is not to replace the expert — it's to multiply one. The layers cut both ways: against a traditional provider, we bring leverage they don't have; against the autonomous-AI crowd, we bring the discipline they skipped. Leverage without recklessness.
- AI never acts on your production systems by itself. Every change is made or approved by a named engineer. No autonomous remediation, no unattended improvisation on client systems.
- Nothing unproven touches a client. New capabilities are drilled repeatedly in our lab before they're used on — or sold to — anyone. If we haven't proven it, we say "in development," not "done."
- The AI drafts; the human signs. Reports, plans, and analysis are AI-assisted and expert-reviewed — the name on the work is a person's.
The governance model, published.
Ask any provider who says "AI" one question: where does my data go? Here is our full answer. It's an architecture, not a policy promise.
1 — Local-first, by architecture
Your operational data — logs, metrics, configurations, the knowledge we build about your systems — lives on a hardened appliance inside your environment. That's the primary control: data that never leaves can't leak.
2 — Scrubbed before anything leaves
Anything that does cross the boundary passes through PowerTrue Shield, our scrubbing layer, on your appliance, before egress — secrets, credentials, and sensitive identifiers are redacted at the source, not after arrival.
3 — Models we operate, not the cloud's
Analysis of client data runs on AI models we run ourselves. Your data is never sent to an outside AI service without your explicit, contracted consent — and the default, which most clients never change, is that it simply isn't.
4 — Isolated per client
Each client's environment, data, and knowledge base are kept separate. Nothing about your systems informs, trains, or leaks into anyone else's.
5 — Recorded and attributable
Every action on your systems is tied to a named person, logged, and session-recorded — with the recordings kept on the appliance in your environment, not ours. You can audit us without asking us.
What we don't publish
The model, in full — but not the machinery. The specific detection intelligence and scrubbing internals are ours; publishing them would help exactly the wrong people. The controls above are contractual and inspectable.
Defense in depth, described honestly.
We won't tell you any scrubber catches everything — nobody's does, and a vendor who claims perfection is telling you they haven't tested theirs. That is precisely why the controls are ordered the way they are: keeping your data local is the primary control; the Shield scrub is the belt on top of it; isolation, consent gates, and recording sit underneath both. A miss in any one layer lands on another layer — not on you.
This is the same standard we hold everywhere on this site: cited statistics, labeled estimates, capabilities described as they are. A provider willing to describe the limits of its own controls is one whose other claims you can weigh accordingly.
- For regulated buyers. Hospitals and credit unions can't accept "trust us." The architecture answers the examiner's question — where does the data go? — with "it doesn't."
- Because the common model is the opposite. Typical AI-era tooling ships your data to someone's cloud and asks you to read a privacy policy. Ours keeps it in your walls and asks you to read an architecture.
- Because we'd rather under-claim. Every promise on this page is one we can keep on our worst day, not our best.
Judge the discipline on one of your systems.
The free AIXray assessment works exactly this way: read-only, nothing leaves your environment, a senior engineer walks you through it. It's the fastest way to see whether we practice what this page preaches.