Simon is a human-led, post-generation AI governance layer that evaluates and conditions AI outputs before delivery to end users. Unlike model fine-tuning or guardrails embedded inside LLMs, Simon operates after a response is generated — at the human decision boundary. It does not retrain models or generate content. Instead, it applies governance controls focused on clarity, emotional alignment, epistemic restraint, and preservation of human authority. The system is model-agnostic and integrates with existing AI workflows to: Moderate tone and escalation risk Reduce overconfidence and speculative output Enforce policy and authority boundaries Provide transparent governance signals and audit metadata Simon is designed for organizations deploying AI in customer-facing, advisory, or high-stakes environments where trust, judgment, and communication integrity matter.