Real finance teams, real cash decisions.
Five companies, five different reasons they needed better cash visibility — and the specific numbers that changed once they had it.
“We used to find out we were tight on cash the week it happened. Now Scenario Studio shows us the trough four months before the fabric order even ships, while there's still time to do something about it.”
Klima Denim buys fabric and production capacity five to seven months ahead of a season, in USD, while most of its revenue lands in three sharp spikes around drop dates. Their spreadsheet forecast was rebuilt manually every Friday and consistently missed the size of the pre-drop cash dip, which twice forced a same-week draw on their credit line at a worse rate than they'd have gotten by planning it.
Klima connected two French business accounts and their Pennylane ledger. Cash Flow Copilot picked up the seasonal pattern directly from 18 months of transaction history without anyone modeling it by hand, and the finance team now runs a Scenario Studio pass before every production order to see the exact cash trough it creates and whether the credit line needs to be drawn ahead of time.
“The duplicate payment alone paid for two years of the subscription in one flag. What convinced us to keep it wasn't that catch — it was that we stopped getting alerts for things that turned out to be nothing.”
Voss & Cie processes around 900 vendor invoices a month across three warehouses, with several vendors on rolling contracts that get re-invoiced monthly. A duplicate payment or a re-sent invoice paid twice was, in their own words, "a when, not an if" — and their existing three-way-match process only caught it at quarterly close, months after the money had left.
Anomaly Radar started flagging duplicate and near-duplicate payments from week one, cross-checked against vendor, amount, and timing rather than a strict exact match. In its first full month live, it caught a €41,200 duplicate payment to a logistics vendor — the same invoice paid twice, three weeks apart, after a reference number was changed slightly on a resend.
“Every scenario question the board had, we answered in the meeting instead of promising a follow-up. That changed how the whole conversation went.”
Ahead of a Series B raise, Ferra's board wanted three hiring scenarios modeled against runway: an aggressive 14-hire plan, a conservative 6-hire plan, and a middle path tied to a signed pilot contract converting. Building each version in a shared spreadsheet took the finance lead most of a week per revision, and every board question meant another round-trip.
Ferra built all three hiring plans as saved Scenario Studio scenarios, with exact start dates, French employer contribution costs, and the pilot-contract revenue modeled as a conditional branch. Board members got read access to compare scenarios directly, and follow-up questions were answered live with Ask Dibein instead of a follow-up email three days later.
“I stopped dreading the week before board meetings. The first draft of the cash narrative is basically done before I open the laptop.”
Nordwell's monthly board pack required the finance lead to manually assemble cash commentary, variance explanations, and forward-looking runway numbers from four different exports. Most months it took a full two days, usually the two days right before the board meeting when everyone least wanted to wait on finance.
The board narrative now starts from a single Ask Dibein query — a summary of the quarter's cash position with every figure linked to source — which the finance lead edits rather than writes from scratch. Variance questions that used to require digging through the ledger are answered inline in the same session.
“We'd run this business on instinct for three generations. Seeing the payment pattern for each customer laid out plainly changed how we handle collections, not just how we forecast.”
A third-generation family distributor, Alma & Fils had never formally forecast cash beyond "what's in the account and what looks due." A handful of large restaurant and hospitality accounts routinely paid 15 to 30 days past terms with no warning, and the finance team found out how tight a month would be only in the final week of it.
Cash Flow Copilot's per-customer payment-behavior profiles gave Alma visibility into which specific accounts were drifting late before it hit the bank balance, and Anomaly Radar picked up a supplier's quietly-inflated recurring invoice that had gone unnoticed for four months.