Security Approach
AI data annotation projects may involve proprietary, operational, customer, medical, financial or policy-sensitive content. Security requirements should be defined during project scoping so access, transfer, retention and review workflows match the sensitivity of the data.
Common Project Controls
- Access control. Limit access to assigned project teams and necessary reviewers.
- Least-privilege access. Provide only the data and tooling access needed for the assigned task.
- Confidentiality obligations. Use project-specific confidentiality expectations for teams handling client data.
- Secure transfer. Agree on transfer methods appropriate to the customer's security requirements.
- Data storage and retention. Define how long project data and outputs should be retained or removed after delivery.
- Project separation. Keep project instructions, datasets and delivery workflows separated by customer or engagement.
- Auditability. Where supported by the toolchain, use activity logs, review records and delivery documentation.
- Incident response planning. Define escalation paths for suspected data handling issues.
Important Note
This page describes general project practices and planning considerations. It does not claim SOC 2, ISO 27001, HIPAA, GDPR or other certification status. Any regulated or certification-dependent requirement should be confirmed during procurement and legal review.
Related Pages
See quality assurance, data audit services, privacy policy and contact Northern Base AI Labs.