Data Minimization
The principle of collecting and processing only the data actually needed for a purpose - a GDPR requirement that maps directly onto scoping what AI can see.
Data minimization is the privacy principle that an organization should collect, process, and retain only the data necessary for a specific, declared purpose - and no more. It is an explicit GDPR requirement and a recurring theme across privacy regulation, on the logic that data you never hold cannot be leaked, misused, or subpoenaed.
AI runs against this principle by default: a model or agent on a broad connection tends to see far more than a task requires. Enforcing minimization means scoping each request to the minimum data its purpose needs - row, column, and field limits bound to identity and purpose - so a model receives only what it must, turning a legal principle into a runtime access decision.
Govern AI like infrastructure.
Talk to our team about deploying DataStrict across your enterprise stack.