Security-first AI memory: how Ziqara protects your data
A deep dive into encryption, access control, and auditability in Ziqara’s AI memory stack—built so security teams can trust what engineers ship.
An AI memory layer is only useful if security teams can trust it. Ziqara is built on a security-first architecture designed for modern enterprises.
Principles we follow
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Least privilege by default
Every operation - read, write, index, search - respects role-based access controls. No “magic super index” that sees what users shouldn’t. -
Isolation between workspaces
Data from one customer never mixes with another’s. Embeddings, indexes, and metadata are all scoped per workspace boundary. -
No surprise training
Your data is never used to train general-purpose models. Period.
Layers of protection
- Encryption in transit (TLS) and at rest.
- Key management integrated with cloud-native KMS options.
- Audit logs that track key events: uploads, permission changes, search queries, and exports.
Admins get visibility into how knowledge flows without needing to inspect every document.
Security-conscious AI features
We design AI features so they are safe by default:
- Response grounding to your own content, with optional citation links.
- Access checks applied before retrieval and ranking.
- Configurable redaction patterns for sensitive identifiers.
Built for security teams, not just end users
Security and compliance teams can:
- Review architecture diagrams and data flows.
- Export logs for SIEM integration.
- Configure retention and deletion policies that apply across Chat, Search, Cloud, and Note-Taker.
AI memory doesn’t have to be a security headache. With Ziqara, it becomes a controlled, auditable part of your infrastructure.