The governance layer for AI systems that must protect the privacy of privacy itself.
A coordinate for platforms that reason about, govern, and enforce privacy at the architectural level — not just compliance with data rules, but the design of how AI systems handle privacy as a structural property.
Coordinated sets this position belongs to — the coverage it extends. Counts are the live cluster size in the graph.
Architectural context
Meta · Vertical-Specific · 2 compound moats. Cross-cutting: Privacy.
Layer position: Cross-cutting
Why this is canonical
Privacy in AI is no longer a checkbox — it is an architectural constraint that shapes system design, training data governance, inference behavior, and output handling. 'Metaprivacy' names the layer above individual privacy controls: the framework that defines how privacy is structured, enforced, and reconciled across an AI system's entire lifecycle. This is the coordinate for teams building privacy as a first-class AI property, not a downstream compliance afterthought.
Where it fits
A few directions this coordinate opens —
Illustrative, not exhaustive — held as a transferable canonical position, open to the buyer's own use.