How FERMÀT Unlocked $500K+ in Cash Collections Without Adding Headcount
About FERMÀT Commerce
They recently raised a $45M Series B from investors such as WMG, Greylock, and Bain Capital.
With a lean finance team and rapid customer expansion, they needed systems that could scale far faster than headcount.
The Challenge: Collections Was a Job That No One Wanted to Do And a Growing Issue
When Evelyn stepped into her role at FERMÀT, she became responsible for everything that wasn’t building or selling software — revenue operations, business operations, finance, accounting, the entire back office.
For a long stretch, collections simply sat lower on the priority list. Not because it wasn’t important, but because it’s the kind of work no one is excited to do and it wasn’t the most pressing issue for the business.
Eight quarters in, however, the numbers made it clear:
collections had turned from a background annoyance into a real business problem.
Evelyn found herself in the classic finance dilemma:
- Hiring someone full-time to manage collections felt like the wrong use of headcount.
- Outsourcing was unlikely to be effective
- Managing it herself meant trading away time that had far more leverage elsewhere.
So the work happened sporadically, whenever someone had a spare hour to chase old invoices. Meanwhile, receivables kept growing quietly in the background.
Why AI Was the Perfect Fit for AR
But AR is not accounting
- It’s repetitive
- High-volume
- Emotionally draining
- Requires persistence, not perfection
- And is exactly the kind of work humans avoid and AI thrives at
AR became the first place where AI wasn’t risky — it was obviously better.
Implementation: Fast, Simple, No Headaches
Most finance tools take weeks to configure and months to trust.
Evelyn expected the same.
Instead, Invoice Butler connected to FERMÀT’s systems and went live in 1–2 weeks with near-zero manual setup.
The Turning Point: Customers Finally Started Responding
This wasn’t spam-filter luck or a random uptick.
This was Invoice Butler:
- referencing exact invoice context
- pulling contract details
- inserting dates of previous outreach
- adjusting tone based on customer sentiment
- asking the right follow-up questions
- and doing it instantly, with no fatigue
The system wasn’t sending reminders…. it was restarting stalled relationships.
The Results: $500K+ Recovered and a Scalable Collections System
1. Real Cash in the Door — Fast
FERMÀT collected over $500,000 in the first month from invoices that had been stuck for months.
2. 2–3× Faster Collections Conversations
AI maintained a persistent, contextual cadence no human could match.
3. Humans Only Step In for Real Judgment Calls
Invoice Butler handled everything else:
- follow-ups
- vendor portal blockers
- W-9 and documentation requests
- clarifications and disputes
- continuous context-aware replies
4. No Hiring Needed
The alternative was hiring someone full-time to do this work manually — a job that’s hard to hire for and even harder to retain. The speed
Systems Scale Better Than People
She wanted a collections capability that:
- never gets tired
- never forgets to follow up
- never loses context
- never burns out
Invoice Butler delivered exactly that: a collections engine that grows as the company grows.