Cash Application Matcher
Build an internal tool that imports your customer payments and open invoices, auto-matches each remittance to the invoices it clears, handles partials and short-pays, and hands you only the judgment calls to approve before it exports a clean cash-application file.
Import payments and open invoices, let the agent propose how to apply each payment (clearing one or many invoices, handling partials, overpayments, and short-pays), review only the proposals and exceptions, approve, then export a cash-application file in your AR system's columns plus an updated remaining-open AR list - with a full audit trail.
Before you start
- A payments / remittance export as CSV (customer, amount, date, reference/memo)
- An open-invoices (open AR) export as CSV (customer, invoice number, date, amount, balance due)
- Free Vercel, Supabase, and Resend accounts (all have free tiers)
- No coding experience required - you'll paste prompts into an AI agent
The problem this kills
Cash application is the AR job that never gets easier. The lockbox file, the ACH batch, and the wire notices land, and now you have to figure out what each payment is for. Customer ABC sent one check for $14,206.50 that's supposed to cover seven invoices - except it's $43.50 short, and the remittance stub only lists five invoice numbers. Customer XYZ paid by wire with a memo that just says "PMT 6/14" and nothing else. Someone underpaid by exactly the amount of a disputed freight charge. Someone overpaid and now you're sitting on an unapplied credit.
So you open the open-AR report, you open the remittance file, and you start the matching game: read the memo, hunt for the invoice numbers, add up the balances, see if the total ties, decide whether the difference is a short-pay you write off, a deduction you route to disputes, or a keying error. Every payment is a tiny puzzle, and at month-end there are hundreds of them. The slow ones - the lump sums, the partials, the cryptic memos - are exactly the ones a spreadsheet can't help with.
This tool flips that. It reads the remittance memo, lines the payment up against that customer's open invoices, and proposes the application - which invoices clear, what's left short, what's an overpayment - so you spend your time approving the obvious ones and judging the genuinely messy ones, instead of re-keying all of them by hand.
What you'll build
A private, login-gated web app where you (and only your team) can:
- Import a payments / remittance CSV and an open-invoices CSV for a chosen period.
- Parse the remittance memo for invoice numbers and customer hints, then match each payment to the open invoices it's meant to clear - including one payment against many invoices (lump sums) and partial payments against a single invoice.
- Propose an application for every payment with a plain-English reason: which invoices it clears in full, which it pays partially, and any remaining balance.
- Handle the hard money - flag short-pays (and auto-create a deduction record to route to disputes), overpayments, and on-account credits, plus payments it can't confidently apply (unapplied).
- Review and approve - the screen shows each proposal with the invoices it touches; you accept, re-allocate, or send a payment back to unapplied. Nothing posts until you approve.
- Export a clean cash-application file in your AR system's exact columns, plus an updated remaining-open AR list and a deductions log.
Every parse, match, override, and approval is written to an audit trail with who and when.
What's inside the Implementation Plan
- It interviews you first. Before it builds anything, the plan has the AI agent ask you about your AR system, your remittance and open-AR exports, your exact column names, the way invoice numbers actually appear in customer memos, your short-pay and deduction policies, your typical and peak payment volumes, and your messiest edge cases (lockbox lumps, partials, on-account credits, duplicate references). It reads a short tailored spec back to you, you give a thumbs-up, and only then does it build - so you get a tool shaped to how you actually apply cash, not a generic template.
- A step-by-step build with a ready-to-paste prompt at the end of every step.
- The full data model: payments, open invoices, proposed applications (one payment to many invoices), deductions, and the audit log.
- The matching engine - memo parsing, exact and amount-based matching, lump-sum allocation, and partial / short-pay / overpayment handling - with tolerances you can tune.
- A "No API yet?" fallback so the whole thing works from CSV imports today, with no lockbox or ERP integration required.
- A verification checklist so you know every applied dollar ties out before you trust it.
The governance it includes (this is the point)
This isn't a throwaway script - it's an internal tool you can defend in an audit:
- Login so only your team can open it.
- Row-level security so each organization only ever sees its own payments, invoices, and deductions.
- A complete audit trail - every memo parse, auto-match, human re-allocation, and approval, with the user and timestamp.
- A hard human-in-the-loop gate - the AI only proposes an application; nothing is exported to your AR system until a person reviews it, the math ties, and they approve. An approved application is locked.
- Duplicate guards - a fingerprint on every payment reference means the same remittance can't be imported and applied twice.
Who it's for
AR specialists, cash-application clerks, and AR managers who apply customer payments against open invoices by hand every day - and especially anyone drowning in lockbox lump sums, partial payments, and cryptic remittance memos. If you can export two CSVs and you want the machine to propose the obvious applications while you make the judgment calls on the short-pays and deductions, this is for you. No development background needed.
You've got this - paste the first prompt and let the agent interview you.