- Payment authority Kept human
- The system assesses, evidences and recommends. It does not approve a payment, release funds or issue a reduction, at any value, on any claim. There is no threshold under which this becomes automatic, and the demo above has no auto-approve path for a clean claim for that reason.
- Applicant data boundary
- What the workflow may see, what stays masked, how long it is kept and under which privacy regime. Programs usually hold personal information about participants as well as commercial information about recipients, and the two often have different rules.
- Recourse and appeal
- A recipient whose claim is reduced is entitled to a reason and usually to a route to challenge it. Every recommendation carries the clause and the evidence behind it, so the reason exists before it is asked for rather than being reconstructed afterwards.
- Rule versioning
- Which version of the guidelines an assessment was made under, recorded on the assessment. Programs change their rules mid-term, and an assessment that cannot say which rules it applied cannot be defended.
- Audit trail
- What was submitted, what was checked, which clause produced which answer, what was recommended, who decided and what they decided. Built from the first pilot rather than added when an auditor asks.
- Escalation path
- What happens when a rule is ambiguous, evidence is partial, or a submission raises something the guidelines did not anticipate. Ambiguity in a funding agreement is common, and a workflow that resolves it silently is making policy.
What counts as working. Accepted output against your own baseline is the
proof. The first build is usually tested against decisions your officers have already
made, so you can see where the system and the officers disagree before it touches a live
claim, and so a disagreement is a finding rather than an incident.
How we measure AI work sets out the method.