USE CASES
You have seen the AI automation pitches. What you have not seen, until now, is what it actually looks like inside a finance team that runs it: which workflows moved, what broke, what the controller saw before anything posted.
These are real deployments across accounts payable, revenue recognition, reconciliation, collections, month-end close, and billing. Company names are anonymized. The numbers, quotes, and workflows are not.
At a glance
Spreadsheets were running as core financial infrastructure before automation
$5.6 billion in payments reconciled across five rails at one customer
$2.4 million collected per month through automated cash application at another
4,000 rows in a manual reconciliation spreadsheet, replaced by a four-way match
6 weeks was the typical time from decision to production
Accounts Payable & Invoice Processing
A legal technology company processing 12,000 depositions a month eliminated its entire manual billing queue with a browser agent that needs no API access.
Read the case studyRevenue Recognition & Contract-to-Cash
A legal services firm bills 1% of estate value, a figure that is not known until midway through the engagement. Automation now catches the moment it is.
Read the case studyPayment Reconciliation & Cash Application
A fintech payment processor outgrew its reconciliation platform. Loopfour built the matching engine it needed instead.
Read the case studyBilling & Collections
A money services business automated contract-to-cash for a billing model too complex for its founder to keep tracking by hand.
Read the case studySalesforce-to-ERP Billing
A digital signage media company cut its month-end billing cycle from a full day of manual review to under sixty seconds of exception handling.
Read the case studyLoan Lifecycle & Notifications
A lending marketplace launched with a complete, white-labeled loan communication system instead of building one from scratch.
Read the case studyUSE CASES
You have seen the AI automation pitches. What you have not seen, until now, is what it actually looks like inside a finance team that runs it: which workflows moved, what broke, what the controller saw before anything posted.
These are real deployments across accounts payable, revenue recognition, reconciliation, collections, month-end close, and billing. Company names are anonymized. The numbers, quotes, and workflows are not.
A legal technology company processing 12,000 depositions a month eliminated its entire manual billing queue with a browser agent that needs no API access.
Read the case studyAn entertainment staffing company routes payroll invoices across four QuickBooks entities and books the matching JE the same day.
Read the case studyA healthcare technology company replaced a manual four-way reconciliation with a deterministic match across pricing, orders, GL, and invoices.
Read the case studyA legal services firm bills 1% of estate value, a figure that is not known until midway through the engagement. Automation now catches the moment it is.
Read the case studyAn industrial manufacturer replaced hours of manual revenue recognition workarounds with a six-step pipeline from Epicor to posted, auditable journal entries.
Read the case studyA health diagnostics company automated the full credit lifecycle from Stripe invoice to deferred-to-recognized revenue.
Read the case studyAn accounting services platform automated R&D study billing and tax partner splits that used to live in one spreadsheet per partner.
Read the case studyA fintech payment processor outgrew its reconciliation platform. Loopfour built the matching engine it needed instead.
Read the case studyA cybersecurity software company automated 19 workflows across e-invoicing, collections, and cash application.
Read the case studyAn AI infrastructure company automated contract-to-reconciliation before growth made the old manual process the bottleneck.
Read the case studyA food hall operator automated percentage-of-sales rent, tax compliance, and bank reconciliation across two corporate entities.
Read the case studyA money services business automated contract-to-cash for a billing model too complex for its founder to keep tracking by hand.
Read the case studyA creator economy platform automated brand invoicing and creator payouts running on two different timelines.
Read the case studyA benefits administration platform built its reimbursement pipeline around one requirement: full audit trail, because it is a compliance company first.
Read the case studyA digital signage media company cut its month-end billing cycle from a full day of manual review to under sixty seconds of exception handling.
Read the case studyA healthcare SaaS company scaled billing without scaling headcount, migrating from Sage to NetSuite in the process.
Read the case studyA lending marketplace launched with a complete, white-labeled loan communication system instead of building one from scratch.
Read the case studyA global travel technology company replaced a fragile in-house middleware layer with an auditable, repeatable close process.
Read the case studyA PropTech platform automated the full lease-to-payment lifecycle, escalating only genuine exceptions to a property manager.
Read the case studyUSE CASES
| Pattern | How often it shows up |
|---|---|
| Spreadsheets doing the job of financial infrastructure | Recurring pattern |
| Critical systems with no API access | Multiple companies, solved with browser automation |
| Key-person risk on a single internal tool or engineer | Named directly in fintech, travel tech, and accounting platform deployments |
| Manual bank-to-GL reconciliation eating 10 to 20+ hours a month | Fintech, media, food and beverage |
| Compliance work with no evidentiary chain behind it | SOX, SOC 1, and PE due diligence contexts |
Every deployment above kept one thing in common: nothing posts without a rule, and nothing posts without a trail. That is the part general-purpose AI agents were never built to guarantee, and it is the part your auditors will ask about first.
