2 Expense Management AI Agents, Live in Production.
2 live agents automate expense management within procurement. They all run on demand. Each one publishes the inputs it needs, the steps it works through and what it hands back.
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Procurement Budget Allocation
Allocate a procurement budget across competing requests with the constraint enforced up front — what fits, what does not, and what the organisation is actually choosing not to do.
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Procurement Spend Analysis
Read a spend extract for the patterns worth acting on — where spend is going off-contract, where a category is fragmented, and which savings opportunities the data actually supports rather than merely suggests.
Naming what the budget is choosing not to fund, in the same breath
Procurement budgeting fails in a way that is hard to see from the inside: the constraint is applied after the requests are in, so the conversation becomes a negotiation about whose number gets trimmed rather than a decision about what the organisation will not do. Meanwhile the spend data that ought to inform the next cycle sits in an extract nobody has time to interrogate. Savings opportunities are asserted from memory — this category feels fragmented, that supplier feels expensive — and when finance asks what the claim rests on, the answer is an impression. Both problems are the same problem: the analysis is slow enough that it happens after the decision it was supposed to inform.
These two agents run that analysis first. Procurement Budget Allocation enforces the budget as a constraint at the point of allocation, showing utilisation, the allocation request by request, and an explicit list of what is not funded — the part most budget processes leave unwritten and later dispute. Procurement Spend Analysis reads the spend extract for the patterns worth acting on: where a category is fragmented, where buying has gone off-contract, and which opportunities the evidence supports rather than merely suggests, each with the evidence attached. Neither sets the target or makes the trade-off. They make the trade-off visible while there is still time to argue about it.
What this moves
- Requests measured against the constraint
- Competing requests are allocated with the budget enforced up front, so the output states what fits, what does not, and what the organisation is therefore deciding not to do this period.
- Savings claims the data supports
- A spend extract is read for opportunities the evidence actually carries, kept separate from the ones it merely suggests — which is the distinction that decides whether a savings target survives contact with finance.
- Fragmentation visible by category
- Where a category is split across suppliers and where spend is running off-contract are surfaced as patterns in your own data rather than as a suspicion someone raises in a review.
Procurement
How AI agents handle expense management
Drawn from the 2 agents above — what they require, how they run, and what comes back.
What they need
- Budget requests
- The budget
- Spend extract
- Analysis settings
What comes back
- Does the budget cover the requests?
- The allocation, and what it costs
- Allocation by request
- Budget utilisation
- Not funded
- What to do about it
- Categories by opportunity
- Opportunities, with the evidence behind each
How they run
- Run on demand
- 2
- Steps per run
- 3
- Credits per run
- 8
Where expense management fits in procurement
Most of a procurement week goes on chasing documents, keying supplier paperwork and assembling comparisons by hand. Agents do that part, which is what leaves time for the negotiation and category work the role is actually for.
Next Step
Deploying expense management agents
These run as-is against the inputs listed above. Most deployments adapt one — a different source system, a different tolerance, a different approval path. The first call establishes which.