Most organizations take their first step into AI with cloud services. An account is opened, a few trials are run, the results are impressive. The real question comes with the second step: if this system is going to work with the organization's real data, every day, for hundreds of people, where should it run?
Where the cloud is strong
Cloud services need no installation. You reach the latest models in minutes, you buy no hardware, and capacity grows on its own as usage grows. For trials, for work based on general knowledge and for use that involves no personal data, that is a real advantage.
Where your own servers are strong
An organization's most valuable knowledge lives in contracts, customer records, financial data and internal correspondence. An AI that works with that data raises the question of where the data goes. On your own servers, data does not leave the organization, logs stay with you, and you decide who can reach what. Where personal data is involved, this also simplifies compliance with Turkey's data protection law (KVKK): as long as data does not leave the organization, the rules on transfers abroad do not come into play.
There is a difference in cost, too. With usage-based services, the bill grows with usage and becomes hard to predict. On your own servers, cost is largely known up front: hardware, installation and operation.
Four questions as a yardstick
To decide which path is right, ask these four questions for each piece of work:
- Does this work involve personal or confidential data? If so, on-premise should come first.
- How often is it used? For work used heavily every day, a fixed cost pays off.
- Will an audit need evidence? Keeping logs in-house makes audits easier.
- Is the very latest model essential? For some work, open models running on-premise are enough; for some, they are not.
For most organizations: both, governed by rules
In practice, the healthiest setup is on-premise by default, with the route to cloud models opened only for work that is allowed to use them. That requires every AI request to pass through a single gate: who may use which model, for which work, is set by rules and logged.
That is our approach at Bizz AI: on-premise by default, every route to the outside documented and opened only by your decision.