policy, retention, and governance
Define what dey allowed, how long artifacts dey retained, and how exceptions dey reviewed.
Compliance dey usually bolted on
Most AI platforms treat governance as a checklist — separate from runtime behaviour (if addressed at all).
Policy configurations drift from what actually executes, audit trails dey incomplete, and retention rules dey enforced manually.
How Threada handles it differently wey dey
Policy dey resolved at runtime — every WorkItem checks retention class, approval requirements, and escalation thresholds before execution.
Governance controls dey di same controls wey route, approve, and execute work — no a separate layer to maintain.
Retention controls dem
- Set retention by data class plus policy scope
- Apply archival plus deletion workflows with audit records
- Keep retention aligned with business plus regulatory requirements
Governance controls wey dey
- policy overlays with clear scope and precedence
- Approval requirements for high-risk actions plus workflows
- Review queues for low-confidence or policy-exception scenarios wey dey
Wetin you get
- Every policy decision dey traceable — wey defined it, when it resolved, and what it allowed
- Retention plus archival run automatically based on data classification
- Approval chains integrate with existing identity plus role infrastructure
- Exception handling follows defined escalation paths instead of silent fallbacks wey dey
Policy dey part of runtime behaviour
In Threada, governance dey no a separate checklist. Policy resolution determines routing, approvals, and execution outcomes in real time.
Governance FAQ wey dey
Does Threada replace our existing compliance tooling dey?
How dey policies versioned?
Fit we export audit records?
Govern AI work with confidence wey dey
Define policy, enforce retention, plus maintain audit trails — all inside one place.