The forecast starts from your receivables, payables and bank balances, then applies how each customer actually pays — this one is reliably eleven days late, that one pays on time only when chased. You get an expected cash position by week, a range rather than a single line, and an early flag on the weeks where the balance goes where you would rather it did not.
Net 30 means forty-two days for one customer and twenty-eight for another. A forecast built on terms is systematically optimistic, and the error is largest exactly when cash is tight.
By the time receivables are pulled, pasted and reconciled, three payments have landed and two invoices have been raised. The effort is high and the shelf life is short.
One number per week says nothing about how wrong it might be. The useful question is not the expected balance but how bad the plausible bad case is, and when it arrives.
Accounting system, bank feeds, invoices and bills, plus recurring commitments like payroll, rent and tax dates. Nothing useful can be built from a monthly export.
Payment behaviour by customer and segment from your own history: typical delay, variance, how it shifts by invoice size, season and whether they were chased. This is where the accuracy comes from.
Expected inflows and outflows by week with a plausible low and high band. The band is the point: it tells you which weeks are genuinely at risk and which merely look tight.
Alerts when a projected balance falls under your threshold, with the biggest contributing invoices attached — so the response is chasing three specific customers, not a general worry.
Every week the previous forecast is scored against what happened. Accuracy is reported and the model corrects, so trust is earned with evidence instead of asserted.
We build in your stack rather than moving you onto ours. The list below is what this solution most often connects to — other systems are a scoping question, not a blocker.
Materially better than terms-based forecasting, and we report the number weekly rather than claiming one upfront. Accuracy depends on your history and how concentrated your customer base is.
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