Data Security in AI-Powered Grant Systems

Security is non‑negotiable: encrypt data, limit access and audit activity while keeping AI within clear guardrails.

• Encryption at rest and in transit with modern standards.
• Role‑based access and MFA for staff and reviewers.
• Logged prompts and outputs for AI features.

Core technical controls

Adopt proven, well‑managed practices rather than bespoke setups.

• Region‑hosted data with regular backups and disaster recovery.
• Principle of least privilege for users and API keys.
• Segregated environments for test and production.

Key takeaway: rely on platform security, not ad‑hoc scripts.

Privacy and responsible AI

Protect personal data and keep humans in control.

• Do not train third‑party models on sensitive data.
• Provide notices explaining AI use and appeal routes.
• Minimise data collection and retention.

Key takeaway: Plinth aligns AI features with privacy by design.

Supplier due diligence

Check vendors’ certifications and incident response readiness.

• Review penetration tests and security disclosures.
• Define SLAs and breach notification timelines.
• Ensure data portability and exit plans.

Key takeaway: good suppliers welcome scrutiny and clear contracts.

FAQs

Is on‑premise more secure?

Rarely. Well‑managed cloud infrastructure is usually safer and more resilient.

How do reviewers access data safely?

Use time‑limited accounts, 2FA and restricted scopes.

Can applicants request deletion?

Yes—respect lawful requests and retain only what’s required.