Enterprise-level data security controls
For sensitive content such as customer information and financial data, the platform provides multi-dimensional protection:
- spatial isolationCreate encrypted workspaces such as "Legal Audit" (password + secondary verification) so that conversation logs don't appear in the global search.
- Content Filtering: Administrators can add sensitive words (e.g., ID number format) to the "Team Settings", and AI-generated content will be automatically fuzzy.
- permission watermark: Add dynamic watermark (with user ID and timestamp) when exporting files, and share screenshots to quickly trace the source of leaks.
- Localized Deployment: Enterprise Edition supports private deployment, all data processing is done on internal servers (need to contact sales for customization)
A financial institution has successfully passed ISO27001 certification after implementing this program. Suggested Supporting Measures: 1) Update the sensitive word database every month 2) Set "/clear history" to clear the cache periodically 3) Enable the operation log auditing function to record all the model invocation behaviors.
This answer comes from the articleGlobalChat: A Collaboration Platform for Unified Management of Multiple AI ModelsThe
May not be reproduced without permission:AI productivity tools " How to prevent accidental leakage of sensitive data during team AI collaboration?
