Governance infrastructure for autonomous systems.

We build deterministic governance layers for AI agent architectures — structural authority separation that is enforced by design, not by behavioral constraints.

Autonomous AI agents propose actions, evaluate those actions, and execute them through the same computational pathway. When proposal, decision, and execution share a substrate, there is no structural mechanism to prevent unauthorized behavior. Behavioral guardrails — system prompts, RLHF, sandboxing — can be circumvented by the same process they are intended to constrain.

PROPOSE ≠ DECIDE ≠ PROMOTE. We separate these authorities into distinct components where the decision layer is deterministic, auditable, and independent of the AI model. Every state transition is witnessed. The system fails closed — failures produce denial, never unauthorized approval.

This is not a wrapper. It is a governance architecture.

• governance-guard — Authority separation skill for OpenClaw agents. Deterministic policy evaluation, hash-chained audit trails, fail-closed semantics. → Spec · Install guide

We provide governance architecture consulting for organizations deploying autonomous AI agents in production.

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