RunLLM provides a multi-layered data protection solution:
- Content Filtering System: Enable keyword masking (e.g. credit card numbers, regular expressions for API keys) in "Security Settings" and the AI will automatically refuse to answer questions that contain them. A fintech company used this feature to stop 100+ potential breaches.
- Minimize storage strategy: Set the "Ephemeral Processing" mode so that the AI only processes the data temporarily in memory and clears the record as soon as the answer is generated. Note that this will sacrifice some learning ability.
- Privilege Sandbox: Restrict the operation privileges of different members through "Access Control Lists", e.g. only senior engineers are allowed to view the code execution logs.
Compliance advice: Regularly scan the knowledge base with the Compliance Checker tool to ensure compliance with regulatory requirements such as GDPR.
This answer comes from the articleRunLLM: Creating an enterprise-grade AI technical support assistantThe
May not be reproduced without permission:AI productivity tools " How can I prevent sensitive data from being leaked while processing technical support requests?
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