Your own infrastructure or the cloud? The AI deployment decision
bicaralabs · GUIDEShould your AI run on a cloud API, in your own private cloud, or on servers you control? It’s a real trade-off, and the honest answer depends on your data and your scale — not on anyone’s ideology.
Cloud APIs — fastest to start
Call a hosted model, pay per use, ship this week. It’s the right default for most projects: no infrastructure to run, always the latest models. The catch is that your prompts and data leave your boundary, and cost scales with usage.
Private / VPC deployment — your data stays home
The model runs inside your cloud account. Data doesn’t leave your control, which is what regulated industries and security teams need. More setup, more cost — and usually worth it the moment sensitive or personal data is involved.
Self-hosted / on-prem — full control
You run the model on your own hardware. Maximum control and data residency, and at very high volume it can be cheaper per call. But you own the ops, the scaling, and the upkeep.
How to actually decide
Two questions settle most of it:
- How sensitive is the data? Personal, financial, or regulated data pushes you toward private or self-hosted.
- What’s the volume? Low and spiky favours pay-per-use APIs; high and steady can justify running your own.
There’s no single right answer — there’s the right answer for your data and your numbers. We’re vendor-neutral, so we help you pick it and keep the exit door open, rather than locking you into whichever one we happen to sell.