Ziqiware Labs
We build privacy infrastructure so organizations can use AI without handing it their customers' data.
Make the safe way to use AI the easy way
AI is already part of how work gets done: drafting replies, summarizing records, debugging code. That work is full of personal data, and most of it is sent to models that organizations don't control.
Policies and training help, but they depend on everyone remembering, every time. We think the protection belongs in the path itself, as a gateway that removes what shouldn't leave, proves that it did, and gets out of the way of everything else.
That's why we're called a lab. We're a small, engineering-led team. We ship working tools first, like the live demo on this site, and we only make claims we can show.
How we build
Show, don't claim
Every capability we describe is something you can see working, with its limits stated plainly.
Strict by default
When in doubt, don't send. Secrets block, inspection errors fail closed, and loosening a policy is always a deliberate choice.
Minimize what we hold
Logs keep masked values and keyed fingerprints. Data we never store is data that can't leak from us.
Model-agnostic
Your privacy controls shouldn't depend on which AI vendor you use this quarter.
Where we are and where we're going
Compliance Guard early access
- Prompt and response scanning
- Tokenize and restore
- Strict and Balanced policies with GDPR, HIPAA and PCI DSS scopes
- Hash-chained audit trail
Deeper detection, easier control
- Context-aware entity models
- Policy editor and admin console
- Per-tenant custom rules
- Audit export to your SIEM
Protection wherever AI is used
- Browser and desktop enforcement for AI chat tools
- Industry policy packs for healthcare and finance
- Independent security assessment
Work with us
If your team is weighing AI against data-protection risk, we'd like to hear from you.