What we heard, and what we're proposing.
We picked this one on purpose: it's not the hardest problem we solve, it's the most common — a pattern we see across most businesses that take in payments against invoices. The mechanism below is the same standard solution we'd build for almost any business with this pattern, tuned to your real numbers and your real tools.
What you told us "Our AR team manually logs every incoming customer invoice payment against open invoices, and we keep finding mismatches weeks later when the books don't reconcile."
The problem
There's no automated match step between the bank feed and open invoices — every payment gets eyeballed by hand, whether it's a clean match or a genuine exception. The team isn't slow; the process makes no distinction between the two.
Business functionFinance / Accounts Receivable
Grounded in a proven approach
Define, Measure, Analyze, Improve, Control
The standard method for fixing a broken process without guessing — measure what's actually happening today, find the specific step causing the failure, fix that step, then control it so it doesn't drift back. Not reinvented per client; applied the same way every time this pattern shows up.
How we'd apply it
Automated payment-to-invoice matching, with real AI agents doing the work
Four agents, each with one job: Data Extraction reads the payment off the bank feed, Reconciliation/Matching checks it against open invoices, Exception/Diagnosis flags anything that doesn't clear automatically, and Notification routes the real exceptions to a person. Press Run below to watch one actual payment move through it.
See it work
The interactive walkthrough
One real payment, run through the actual mechanism — press Run in the "See it run" tab.
Why we picked this one
- Common, not hardPayment reconciliation is one of the highest-frequency finance-ops problems we see — not a showcase edge case, the exact pattern most businesses taking payments against invoices already have.
- Standard solutionSame four-agent mechanism every time this pattern shows up. What changes per client is the numbers and the tools, not the approach.
The honest objections
- "Isn't this just AI hype?"The agents aren't doing anything a human couldn't — they're doing it on every payment, instantly, and only escalating the ones that actually need judgement.
- "What about the exceptions it gets wrong?"It doesn't guess on exceptions — it escalates them, with the discrepancy already diagnosed, to a named person.
This is exactly what your own solution document would look like — built around your actual problem, not this sample one.
Start now →Or, if you'd rather just talk it through first —