Capability 03 · Assure real work
Process & Policy Assurance
Check the work that actually happened.
Minarai compares observed activity from native work tools with reviewed reference processes and policies. Findings show what differed, why it matters, and which evidence supports the conclusion.
Design-partner preview
Evidence-linked assurance
Accepted reference
Compliance approval before release
Observed activity
Pack released, then approval requested
Sequence differs from accepted process
Release was observed before the required approval event. Reviewer classification is needed.
For
Compliance, risk, process excellence, and operations leaders
When
Policies exist, but leaders cannot see whether day-to-day work followed them until a problem surfaces.
Outcome
Evidence-linked findings for missing, extra, out-of-order, exceptional, or potentially better ways of working.
How it works
A governed path from source to useful output.
Minarai keeps the source, the AI suggestion, and the human decision distinct. That boundary makes every downstream use easier to trust.
- 01
Accept the reference
Use a reviewed process and rule set as the explicit standard. Unapproved drafts cannot silently become policy.
- 02
Observe the activity
Capture bounded evidence from work such as emails, meetings, documents, or agent logs without forcing work into a checklist app.
- 03
Review the finding
Trace each difference to its source, classify the impact, and decide whether to correct the work or improve the reference.
Useful outputs
Work products people can inspect, correct, and reuse.
Missing and extra activity
Order and variant findings
Policy exceptions and unknowns
Better-way review candidates
Why Minarai
Assurance follows the work, not just the checklist.
The reference and the observed activity remain distinct and evidence-linked. A finding can connect a document-derived rule, an expert-captured process step, and the activity that differed.
How it strengthens the platform
Process & Policy Assurance consumes the accepted knowledge created through interviews, documents, and direct review—then feeds learning back into that same model.