Private AI Server
A private AI server is a physical machine in your building, bought in your name, configured to run open-source AI models locally. Other vendors rent you a seat on their server and your data travels to it. This one is your property from the day it is installed, which means the documents it reads never leave the premises and the capability does not disappear if a vendor changes their terms.
Where this one earns its keep.
Every sector we work in has a version of this problem. These four feel it hardest, and they are where we have built it most often.
What sending your data outside actually risks.
No invented example here. The method is below; the numbers are yours to put into it.
What to count. hours a month your team spends on work they will not put through a public tool × loaded hourly cost. That is the arithmetic, and it is yours to run — we would rather hand you the method than a number invented for a page.
The ROI calculator models the same shape across a whole team, and its assumptions are published in full underneath it. The number that actually matters comes out of an AI Readiness Audit, which measures your workflows instead of averaging them.
Discover, build, evolve.
The same three phases as every other engagement. Nothing about this build gets its own process.
Discover. We walk the workflow as it runs today — who touches it, where it stalls, what it costs when it slips. That is the AI Readiness Audit, and it ends in a written document you own.
Build. A fixed quote in writing before work begins, then the system goes into your real operation rather than a demo environment. A person stays in the loop on anything a customer sees.
Evolve. Once it is live it needs watching: what it handles, what it escalates, what changed in your business since. That is Managed Services, and it is optional.
Delivered through AI Implementation Sprint.
This build has no price of its own. It is scoped and delivered inside a published service, at the published price.
An AI Readiness Audit runs $3,500–$8,500 and tells you whether this build is the right first move. The build itself is delivered in AI Implementation Sprint. $18,000–$60,000, quoted fixed in writing before work begins.
Private AI Server, asked plainly.
01Do we own the hardware?
Yes. It is bought in your name and it is your property, not a leased seat. That is the difference between this and every subscription alternative.
02What happens if you stop working with us?
The machine stays where it is and keeps running. You own the hardware and the models on it are open-source, so nothing switches off when an engagement ends.
03Is a local model good enough?
For the work small and mid-size businesses actually need — reading documents, drafting, classifying, answering from your own records — yes. Where a task genuinely needs a frontier model, the privacy filter sends cleaned text out and keeps identifiers in.
04What does it cost?
It is delivered through an AI Implementation Sprint, quoted fixed in writing before work begins. Hardware is quoted as part of that scope, not billed as a surprise afterwards.
30 minutes. A straight answer.
A senior advisor walks your workflows and tells you whether this build is worth doing — including when the answer is not yet.