1 Customer to Cash AI Agent, Live in Production.

Credit assessment tends to happen either too late or too shallow. Too late means terms are agreed commercially and credit reviews them afterwards, at which point saying no costs a relationship the sales team has already built. Too shallow means the assessment reads the filed accounts, which are historic and often a year old, and stops there. The more predictive signal is usually payment behaviour — how this customer has actually paid, or how comparable customers in their sector do — and it frequently disagrees with what the accounts suggest. A business with a healthy balance sheet can be a persistently slow payer, and averaging the two signals into a single score hides exactly the thing a credit controller needs to know.

Credit Worthiness Assessment assesses a prospective customer before terms are offered: what the accounts show, what their payment behaviour shows, and what the limit should be if the two disagree. Surfacing the disagreement rather than resolving it silently is the useful behaviour, because the appropriate response differs — a strong balance sheet with slow payment is a terms problem, not a limit problem. This is one agent for the process, and it recommends; the limit is set by a person who can weigh the commercial context alongside it.