Frequently asked questions
For a sensitive-request review, what does the AI guide prepare?
It prepares a request evidence packet, policy match, risk notes, approval record, and reversible action plan from authorized inputs. For a sensitive-request review, it identifies itself as AI, shows uncertainty, and leaves consequential decisions with the responsible person.
For a sensitive-request review, who is this workflow for?
It is designed for security teams, IT leaders, operations owners, and compliance managers who repeatedly need help with policy-aware triage of a sensitive request and can name a responsible reviewer.
For a sensitive-request review, what information should I provide?
Start with the request purpose, permissioned context, relevant policy, source provenance, affected entitlement, and named approver. For a sensitive-request review, provide only material you are authorized to use for the stated purpose.
For a sensitive-request review, does the AI take action on its own?
No. The AI prepares an allow, narrow, hold, or deny recommendation; an authorized person decides. Grants and revocations require human approval and verified connectors, and a missing source or approver moves the request to hold. For a sensitive-request review, a draft or simulation is never presented as a completed action.
For a sensitive-request review, what happens when evidence is missing?
For a sensitive-request review, the AI guide asks a question, marks the gap, or holds the step. For a sensitive-request review, it does not fill missing facts with an invention.
For a sensitive-request review, can I inspect a demonstration first?
Yes. The site presents the clearly labeled simulated Gatekeeper Decision Review and sample approval queue. For a sensitive-request review, demonstration material is labeled and does not claim a real customer outcome.
For a sensitive-request review, how are sources handled?
For a sensitive-request review, relevant sources keep provenance, scope, and revision context so a reviewer can trace important statements and correct them.
For a sensitive-request review, what should a reviewer check?
For a sensitive-request review, check source support, stated uncertainty, scope, permissions, boundary conditions, and the difference between a draft, approval, and verified outcome.
For a sensitive-request review, are integrations guaranteed to be available?
No. For a sensitive-request review, connector and integration availability must be tested with appropriate permissions. For a sensitive-request review, the content does not imply an unverified connection works.
For a sensitive-request review, what is the next step?
Run the bounded workflow demo with the on-page AI guide.