A distribution roll-up had ~$40M tied up in receivables at 62 days DSO, spread across fourteen business units on four different ERPs. We built one layer that sees the whole book, and a collections agent that puts the highest-value work in front of every collector, every morning.
A small central team worked the largest accounts and let the long tail age. Collectors worked alphabetically. Dunning was a generic template on a fixed calendar. Dispute reasons lived in inboxes, so the same hold-ups recurred every month with no root-cause view. No prioritization, no leverage — and $40M of the sponsor's cash sitting in other people's bank accounts.
The Shape Of It
Four ERPs, one book
Every morning
The layer came first. Customer, invoice, and payment data normalized across four ERPs — so one agent could see one book, not fourteen fragments.
What We Built
The agent reads each customer's full history across every business unit — payment behavior, order patterns, past disputes — and scores the risk on every open invoice. An account that pays one unit promptly and stalls another is finally visible as one customer.
Risk stops being a gut feel held by whoever has worked the account the longest. It becomes a number the whole team can rank against.
The generic template on a fixed schedule is gone. The agent drafts a sequence per account — the right tone for a thirty-year customer, the right firmness for a chronic slow payer, the right timing for how that account actually pays.
Invoice copies attached, balances reconciled, payment options included. The message a customer receives is the one most likely to get that customer to pay.
When a customer replies — wrong price, short shipment, missing proof of delivery — the agent reads it, classifies the dispute, and routes it to the person who can actually resolve it. Nothing dies in an inbox.
And because every dispute is now categorized, leadership finally has a root-cause view. The pricing error that generated the same dispute every month gets fixed at the source — instead of collected around forever.
Each collector starts the day with a queue sorted by expected recovery — highest first. The call is prepped, the email is drafted, the account history is one glance away. The alphabet no longer decides who gets paid.
The collector decides; the agent prepares. Every action is logged. The same team now covers three times the accounts — and the long tail gets worked for the first time.
The Morning Queue
This morning's queue
34 accounts
Ranked by
Expected recovery
In play today
$1.9M
Commercial roofing distributor
BU-07
Regional mechanical contractor
BU-03
National facilities operator
BU-11
Independent lumber yard
BU-02
Municipal water authority
BU-09
What It Released
Thirteen days, pulled forward
~$26M
Working capital released from receivables — cash the sponsor didn't have to borrow, at today's rates.
The Tail Stopped Aging
The long tail was where the money was dying. With every account worked — not just the top fifty — the aged book stopped compounding. Balances over 90 days fell 40% while the current bucket grew.
Working capital is the highest-ROI AI project in finance — and nobody funds it.
Who's In Charge
The collector decides. The agent prepares.
No message goes out that a collector didn't choose to send. Every score, every draft, every routing decision is logged and reviewable. Customer relationships that took decades to build stay in human hands — the agent just makes sure those hands are working the right accounts.
The Impact
DSO went from 62 days to 49 across the platform — roughly $26M in working capital released. That's dry powder for the next bolt-on, and interest expense that never gets paid.
The same collections team covers three times the accounts. Balances over 90 days are down 40%, because the long tail finally gets worked instead of written off.
And when the next acquisition closes on a fifth ERP, its receivables plug into the same layer — and the same agent starts working the new book on day one.
We design and deploy AI-native systems for companies moving fast in competitive markets.
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