PVML creates virtual databases over existing infrastructure so teams can put generative AI to work on enterprise data without duplicating or relocating it. The problem it names is specific: the usual path to AI-ready data is another copy in another store, and every copy is a new security boundary, a new cost line and a new thing to keep in sync.
Built-in anonymisation and access controls sit at the virtual layer rather than being bolted on, which is the difference between governance that holds and governance that depends on nobody querying the underlying source directly.
It is pitched at CIOs and IT teams with established data estates and real compliance obligations. Organisations without those constraints will find the architecture more machinery than their situation calls for.
