We built Cashvyne because AR software hasn't changed since Excel.
Most AR tools give you a cleaner view of what's already overdue. We built Cashvyne to fix the part that happens earlier — scoring invoice risk while accounts are still in their net-30 window, before a single payment has been missed.
James Okonkwo
CEO & Co-Founder
James spent years working in finance operations at mid-market distribution companies across the Midwest, watching AR teams run the same ineffective dunning process on every overdue account. The five-day reminder. The escalation at 45 days. The write-off at 90.
The pattern he kept seeing: by the time an invoice showed up as a problem, the signals had been there for weeks. Payment behavior — slower partial payments, shorter check amounts, delayed acknowledgments — told you a customer was heading for trouble before the due date ever passed. Nobody was reading those signals systematically.
Cashvyne is the tool he wished he'd had. Built in Chicago in 2025. Independently funded — we move at our own pace. We're not trying to replace your ERP or rebuild your AR workflow from scratch. One capability, done precisely: flag the invoices heading for trouble before your dunning window closes.
The invoice that goes 90 days past due told you it was coming at day 12. We just learned to listen. — James Okonkwo, CEO & Co-Founder
How we build.
Three things we won't compromise on when deciding what to build — and what not to build.
01
Precision over volume
One prediction done right beats 20 generic reminders. AR teams don't need more noise — they need to know which three invoices out of three hundred are actually going to be a problem. Cashvyne optimizes for that signal, not for sending more emails.
02
Finance teams are practitioners, not ticket-closers
The tool should fit the workflow, not reshape it. Cashvyne layers on top of the AR processes your team already runs — the same aging report, the same dunning logic — with better data underneath. We don't ask controllers to learn a new way of working. We make the work they already do more precise.
03
Transparent model, honest numbers
We show you how our prediction scores are calculated — which payment behavior signals contributed to an invoice's risk rating, and how accurate our model has been against your specific portfolio. No black box. No vendor-defined "AI insights." You should be able to explain every flag to your CFO.
Based in Chicago.
321 N Clark Street, Suite 2800Chicago, IL 60654
United States
[email protected]
+1 (312) 847-3863