Policy, retention, plus governance
Define wetin dem allow, how long dem dey keep artifact, and how dem dey review exception.
Dem dey usually bolt compliance on top
Plenty AI platform dey treat governance like checklist — separate from how di runtime dey behave (if dem even touch am at all).
Policy configuration dey drift comot from wetin actually dey execute, audit trail dem no complete, and na by hand dem dey enforce retention rule.
How Threada take dey handle am different
Dem dey resolve policy for runtime — every WorkItem dey check retention class, approval requirement, and escalation threshold before e go execute.
Di same control wey dey govern na di same control wey dey route, approve, and execute work — no be separate layer wey you go dey maintain.
Retention control dem
- Set how long data go stay, by data class and policy scope
- Run archival and deletion workflow wey get audit record
- Make retention dey tally with business and regulatory requirement
Governance control dem
- Policy overlay dem with clear scope and precedence
- Approval requirement for action and workflow wey carry high risk
- Review queue for case wey low-confidence abi where policy get exception
Wetin you get
- 01 Every policy decision dey traceable — who define am, when e resolve, and wetin e allow
- 02 Retention and archival dey run by demselves based on data classification
- 03 Approval chain dem dey join body with your identity and role infrastructure wey already dey
- 04 Exception dey follow escalation path wey dem define, instead of silent fallback
Inside Threada, governance no be separate checklist. Na policy resolution dey decide routing, approval, and execution outcome for real time.
Question dem about governance
Threada dey replace our compliance tool wey already dey?
How dem dey version policy dem?
We fit export audit record dem?
Govern AI work with mind wey settle
Define policy, enforce retention, and keep audit trail — everything for one place.