Guide
Your own private AI: three ways to get there
“My own private AI” is a legitimate demand: data stays with you, the bill is predictable, and nobody else learns from your documents. There are three ways to get there, and all three make sense, just not for the same company.
The three paths
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Buy it and run it yourself
An AI workstation with a local model runner, in the office. The best path if you have a capable person who likes hardware, and an office that can host it. Excellent for learning, workable for one or two internal users. The weak point is year two: patching, backups, GPU failures, model updates, and nobody answers at 3 a.m.
Right when downtime does not hurt and someone is genuinely responsible for its care.
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Your server, someone else maintains it
Someone installs an open-source AI stack on your server and maintains it remotely. You still carry the machine and the risk, and there is no redundancy behind it. Before signing, ask who runs the company and what stands behind the availability promise.
Right if you insist on a single box and accept that operations remain a shared responsibility.
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A platform on your own hardware
A packaged platform on your own servers, or on your service provider’s, delivered as software with migration and third-line support. It loads the models, meters their use and takes apps to production.
Right when you want the outcome on your own machines, with a predictable bill. This is the ATAILA path, as ATAILA Enterprise or, through your provider, ATAILA Service Provider.
The bill over time
The box’s price is more than the box: the machine, the power, the time of whoever cares for it, and the downtime when it does not run. The maintained-server path looks cheaper until you add the machine, the monthly fee and the fact that the risk stayed with you.
The platform path is simpler to add up. Priced per CPU socket, not per user or token. A one-to-four-week implementation, billed weekly. The operations stay with your team or your provider, who already run your other systems. Run your own numbers; if the first path wins for your case, we will say so.
What “your own” should cover
Whichever path you take, ask what “your own” covers: the machines, yes, but also the models you loaded, the documents you attached, the apps you built and the record of who used what. On the ATAILA platform all of it stays yours, in your repositories and on your servers. An exit guarantee, written into the contract.
Not sure which path is yours?
Tell us your situation. We tell you which of the three paths fits, even when it is not ours.