Not trying to be alarmist but the more I look into how most enterprise AI deployments actually work the more the data flow question bothers me.
You send a query > It goes to a third party server > The model processes it > You get a result back.
Somewhere in that chain your organization's data touched infrastructure you do not own or fully control.
For a lot of use cases that is probably fine. But the moment that data is sensitive, customer records, internal financials, legal documents, the whole arrangement starts feeling shaky from a compliance standpoint.
The architecture that actually solves this is running everything inside your own environment.
No external calls. Inference happening on your own infrastructure.
Recently came across lyzr(dot)ai's Sovereign AI thing which is built entirely around this,
Agents running inside the customer's own walls with full governance layer. The idea that you can connect agents you have already built on any framework and govern them from one place without routing anything externally seems like the right answer to a problem most vendors are not being honest about.
Is this something your org has had to think through or is it still mostly theoretical for most teams?
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