Go Ask Simon – Post-generation AI governance layer for safer outputs

Summary: Go Ask Simon reviews large language model outputs after generation to detect uncertainty, boundary compliance, and decision risks. It enforces deterministic results and provides audit-ready metadata with optional verification receipts to ensure governance before delivery.

What it does

It evaluates AI-generated responses for uncertainty, boundary issues, escalation risk, and authority drift, enforcing deterministic outcomes and attaching audit metadata before output reaches users.

Who it's for

Teams deploying AI that interacts with users in regulated, high-stakes, or sensitive environments.

Why it matters

It preserves human authority and governance at the decision boundary, addressing risks not covered by training or monitoring tools.