Status: implemented / controlled deployment.
The governance workflow is the risk-adaptive policy and review component of the cybiont governance stack. It enforces access, review, escalation, and evidence capture across client-controlled deployments, scaling validation requirements with the risk signal — confidence, exposure, regulatory class — rather than applying static thresholds uniformly across decisions, and composing human reviewers with AI agents under explicit accountability rules.
What the workflow does
- Applies validation policy at the human–AI boundary that scales with the risk signal.
- Composes human reviewers, operational owners, and AI agents in the decision path.
- Routes high-stakes events to designated human sign-off paths.
- Emits decision-state evidence into the compliance ledger.
Design targets and research directions
The following are design targets of the workflow, surfaced here for technical context. Detailed implementation status, methodology, and protocol mechanics are reviewed only under mutual NDA.
- Dynamic validation scaling. Thresholds expand or contract in response to risk indicators, confidence scores, and regulatory exposure.
- Structured diversity safeguards. Compositional guardrails preventing single-channel dominance in the decision path.
- Drift monitoring. Continuous assessment of language-model behaviour for factual drift, with anomalies flagged before propagating through the governance chain.