How Mithrandir handles access
People see only what their work already lets them see. Your company's hierarchy decides the rest. Permissions are mirrored from each tool automatically. There are no policies to write by hand and no metadata to tag.
Ethical walls you set apply on top of everything: no share, role or exception can cross them.
Most enterprise AI systems retrieve everything and then instruct the model to be discreet about what it shows. Prompt-level rules can be argued with. Mithrandir's access control is structural: permissions define what the system can retrieve for a given person, before any model is involved.
- Restricted content never enters the model's context. Information a person cannot open is never assembled into the prompt, so no jailbreak or paraphrase can extract what was never there.
- Answers are complete for each person. Two people asking the identical question each get an answer that is complete for what they may open: not an error, not a redaction, and never a leak. The example above shows it from CEO to sales intern.
Measured across more than 30,000 entries: 0 leaks, and 100% of answers sourced.
This is a description of the product's architecture, not a certification. You can verify these properties directly against your own data during onboarding.