Security & privacy

Private by design.
Built for trust.

MindMesh is designed for people who want the benefits of AI at work without giving up control of their data, permissions, or daily workflow.

See How MindMesh Protects Your Data

Local-first architecture, designed for privacy.

MindMesh is built around a local-first model that keeps indexed work context close to the user and prioritizes privacy-conscious processing.

Your vector memory stays on your device by default; traffic to Google and MindMesh uses encrypted (TLS) connections.

Public Cloud
ENCRYPTED (TLS)
Local Mesh

Read-only access where it matters.

Supported Gmail and Google Calendar connections use read-only permissions, helping users search, summarize, and stay organized without granting unnecessary control.

No write permissions requested

Modern protection for sensitive security paths.

MindMesh uses modern encryption protections, including AES-256-GCM in key flows such as sensitive token protection and some encrypted local storage paths.

Learn About Permissions

Desktop trust signals built in.

MindMesh uses signed desktop updates and a deliberate desktop architecture designed to feel more secure, more controlled, and more transparent than typical browser-first AI tools.

Certification

OS Signed Binary

Reliability

Secure Updates

  • OS Signed Binary
  • Secure Updates
  • Desktop-first architecture

What MindMesh can access, and what it cannot do.

Transparency is our standard. We maintain explicit boundaries with your data.

MindMesh can

  • Read supported email and calendar data you choose to connect

  • Keep your memory/index on your device by default.

  • Help summarize what matters today and what happened yesterday

  • Help you find old work context quickly.

MindMesh cannot

  • Claim ownership of your work data

  • Train on your personal inbox data

  • Delete or change your emails.

  • Send Gmail messages or edit Google Calendar events through the standard read-only connection flow

Built to help you work with your data, not extract value from it.

Privacy is not an add-on in MindMesh. It is a product principle that shapes permissions, architecture, and user experience from the beginning.

Try Private AI for Work