Permission Aware Knowledge Finder

The problem

Sharing company knowledge via AI often leads to accidental data leaks. Standard RAG systems often ignore user permissions, surfacing sensitive HR, financial, or legal data to unauthorized employees.

What it does

• Enforces role-based access control (RBAC) on all AI-retrieved information.
• Cross-references user roles against document sensitivity before generating answers.
• Automatically redacts specific sensitive data points while providing the rest of the authorized context.
• Implements a strict "Hard Refusal" protocol to prevent information leaking through inference.

Why this beats prompting it yourself

Manual prompts often fail when users try to "jailbreak" or nudge the AI into revealing clues about restricted data. This skill uses a rigid validation framework that forces a permission check and a structured redaction protocol before any content is output, ensuring compliance is never an afterthought.

Use cases

• Internal HR bots answering policy questions while protecting private employee records.
• Legal department knowledge bases that restrict access to specific case files by counsel level.
• Corporate wikis that need to serve different data to interns versus executives.

Known limitations

Requires the user role and document sensitivity levels to be explicitly provided in the context. It cannot guess permissions for unlabelled data.