School AI Security & Data Governance

Encryption, access controls, audit logs, and human oversight - documented data governance for K-12 schools and charter networks.

• Encrypted in Transit & at Rest
• Role-Based Access Controls
• Tamper-Evident Audit Logs
• Human Staff in Control

Request a Security Review FERPA & COPPA Support

A Governed Approach to School AI

School AI security and data governance is the set of technical controls, data rules, and human review practices that protect school information and govern how AI accesses, processes, retains, and acts on it. Campus Hive AI separates platform controls, school responsibilities, and integration responsibilities so every team knows what to verify.

• Encryption & Data Protection School data is encrypted in transit and at rest. All AI inference runs on organization-controlled infrastructure - your data does not reach public model endpoints.
• Access Controls & Permissions Access corresponds to approved school, campus, and network roles. Authorized administrators grant, change, and remove permissions. Elevated administrative actions require elevated permissions.
• Auditability & Activity Records User actions, administrative changes, integration events, and AI-generated recommendations are recorded. Authorized school teams can review activity within their scope to trace sources, approvals, and outcomes.
• Data Retention & Deletion Retention periods apply by data category and are documented in your service agreement. Schools can request deletion. Removing an integration or ending a contract triggers documented data-handling procedures.
• AI Model Governance School data is not used to train or improve AI models. Prompts, source data, and generated outputs stay within your contracted processing boundary. Facts, trends, and recommendations remain distinguishable in every output.
• Human Oversight & Accountable Action AI supports school staff - it does not replace their expertise. Staff review recommendations, approve actions, correct outputs, and handle sensitive family questions or escalations directly.

Integrations, Model Use, and Compliance Support

Campus Hive AI connects with approved student information systems and school tools. Each integration specifies which data fields and workflows it can access. Schools can review, change, and remove connections at any time.

• Secure School Integrations Approved integrations operate within documented data scopes. Schools see which fields each connection can read, and removing a connection stops data flow immediately. Responsibilities are shared between Campus Hive AI, the school, and the integration provider.
• AI Model Use Campus Hive AI runs closed-circuit inference. School data is not shared with public AI models, not used for training, and not retained outside your contracted processing scope. Every AI output traces back to its source data.
• Auditability Every AI-assisted board report or enrollment recommendation includes its source data. Authorized teams can trace which data informed a recommendation, which staff member reviewed it, and when the action occurred.
• Privacy Evaluation The documented controls on this page support your school's own privacy and FERPA (Family Educational Rights and Privacy Act) evaluation. Campus Hive AI does not make a blanket certification claim - your team verifies controls against your specific obligations.

Security Questions

Answers for school technology, operations, data, and executive teams evaluating Campus Hive AI.

What is school AI security and data governance?

How does Campus Hive AI approach protecting school data?

Who can access school data in Campus Hive AI?

Does Campus Hive AI use school data to train AI models?

Can school teams audit activity in Campus Hive AI?

How long does Campus Hive AI retain school data?

What role does human oversight play?

How are school integrations secured?

Is Campus Hive AI FERPA compliant?

What should a school request during a security review?

Request a Security Review

School technology, operations, data, and executive teams can schedule a dedicated session covering encryption, access controls, audit records, retention, model data use, and integration permissions.