An AI approver recommendation agent looks at the request's cost centre, project, category and requester, and finds the people with budget or functional authority over each.
A request needs approvers named.
The agent reads past approvals for similar requests.
It matches amount, category and department.
It lists likely approvers with reasons.
The buyer confirms or changes the approver.
The approver and reason are logged.
It proposes the most suitable approver or approvers, with a reason such as owner of the budget line or head of the function that will use the tool.
Where the choice is unclear, it presents options and flags the ambiguity. A person selects the approver; the agent does not assign authority.
Fixed approval chains cover the common cases, but real requests often cross teams, projects or budgets and the right approver is not obvious.
Spend crosses cost centres, and nobody is sure whose money it is.
A tool for a cross-team project has several plausible approvers.
Records show people in old roles, so suggestions point to the wrong person.
They pick a senior name they know, who may have no authority over the spend.
A request approved by someone without authority has to be approved again.
It takes the cost centre, project, category, amount and requester from the record.
The agent looks up budget owners and functional leads linked to those details.
It checks that the people named are current and within their authority limit.
One or more approvers are suggested, each with the reason for the suggestion.
Where several people qualify equally, the options are listed for a person to choose.
Bring a small sample and watch Flo work through it.
| Aspect | By hand | With the agent |
|---|---|---|
| Finding the approver | Buyers ask around to find who should sign off. | Likely approvers are listed from rules and past approvals. |
| Reasoning | The choice is not explained. | Each suggestion shows the rule or past case behind it. |
| Edge requests | Unusual requests have no obvious owner. | Close past cases are shown for reference. |
| Consistency | Similar requests get different approvers. | Similar requests produce the same suggestion. |
| Learning | Corrections are lost. | Buyer overrides feed the next suggestion. |
| If | Then | Who decides |
|---|---|---|
| Rule gives one approver | Suggest that person and cite the rule | Buyer confirms |
| Rule gives no approver | Suggest approvers from similar past requests | Buyer picks |
| Past approver has since moved roles | Skip and note the change | Buyer chooses a current holder |
| Suggested approver is the requester | Exclude and suggest the next | Buyer confirms |
| Several equally likely approvers | Show all with their differences | Buyer decides |
| Request is unusual with no close precedent | State that there is no precedent | Procurement lead names the approver |
History may include one-off approvals that should not repeat. The agent separates rule-based from exception cases, and the buyer judges relevance.
With no history, suggestions come from rules alone. The agent says so and the buyer relies on the mapping.
Suggestions may point to an absent person. The agent checks leave and proposes the cover, and the buyer confirms.
The rule names one person, but past practice another. The agent shows both and the lead decides which is correct.
Talk it through with the team. We will map it to your steps and show where a person stays in control.
Start where rules run out and buyers currently ask around.
Record every time a buyer picks someone else, and why.
Move clear suggestions into the routing step once overrides are rare.
Keep the past-approval data current and exclude one-off exceptions.
It shows how often the suggestion matched what procurement would have chosen. A low rate often traces to out-of-date org or budget data.
Quick answers to what people ask most about approver recommendation.
Book a demoIt is suggesting who should approve a purchase request when the rules do not name one person. An AI agent proposes approvers from budget and org data, with reasons, and a person confirms.
No. It suggests people who appear to hold the relevant authority. Procurement or the requester's manager confirms the choice.
It lists the options and flags the ambiguity. A person picks, and the decision and reason are recorded.
From your org structure, budget ownership and authority limits. Suggestions are only as accurate as those records, so keeping them current matters.
Approval escalation is the step that moves an overdue purchase approval to a more senior or alternative approver when the first has not acted.
→An approval threshold is the spend limit that decides which level of approval a purchase needs.
→An approval reminder is a prompt sent to an approver whose decision is still outstanding on a purchase request.
→Multi-level approval is a process in which a purchase must be approved by several people in sequence or in parallel, for example a manager, then finance, then a senior leader.
→Bring a small sample of real items. We will show what Flo handles on its own and where it hands over to your team.
