ZANUS AI FOR EDUCATION — STUDENT PRIVACY
Student data privacy is not a feature checkbox — it is the architecture. Admin-created accounts, permissions to the field level, server-side redaction, a searchable audit trail, and a fully on-premises option where records never touch the internet.
Private tenant or your own server · unlimited staff · student data privacy by architecture

One record per user: role, tags, and granular permissions over every domain of the system.
The server redacts what a role cannot see — a volunteer checking the event calendar sees the slot, not the student. Access follows the role, not habit.
A searchable log of every audited action, with configurable categories: who saw what record, who changed what, when.
Five-level workgroups map schools and departments; the on-premises option puts the whole system inside your building, air-gap capable.
When the question comes — from a parent, the board or the state — the answer is a search away: access records, document trails, update history, all in one place. Automatic pre-update snapshots mean even a mistaken change can be rolled back.

In your isolated tenant — never training outside models — or fully on-premises on hardware the district owns, physically incapable of internet exposure.
The architecture is built for privacy-first handling: isolation, field-level permissions, redaction and audit. Specific regulatory requirements are reviewed with your team during onboarding — bring your data-privacy officer to the demo.
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