Enterprise AI security review readiness

Enterprise security review is not a vibe check on your model vendor. It is a test of data flow, identity, retention, tool permissions, subprocessors, and whether you can reconstruct an incident.

If your architecture diagram and your runtime diverge, the review will find it. Brilliant teams still fail when the attack surface was never audited.

Data flow diagram for the AI path. Model and tool inventory with versions. Authn/authz model for agents. Retention and redaction policy. Audit trail sample for one critical action. Incident runbook that names who pulls which log.

Keep it boring and true. Reviewers prefer a short honest gap list over a glossy claim set.

Tool calling expands the blast radius. An agent that can send email, create Stripe objects, or write to a vault needs the same controls as a junior employee with production credentials.

ListingRizz-style systems only become real when MCP tools sit behind auth, money, storage, and a durable schema — then clear cash. Local demos collapse the moment those appear. Build the product shell before the review, then measure sell-through.

Clinical and billing AI do not get to pretend. Separable packages, encryption envelopes, EHR clients, and hash-chained audit are architecture. Checklists without package boundaries are decoration.