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US$1M collected in the first 3 months

AI Payment Collection and Reminders

The companion product to the AI front desk: it chases unpaid invoices with polite, timed reminders and a payment link, and stops the moment the customer pays or replies. It collected over US$1 million for the client in its first three months.

The problem

Small businesses are owed money by customers they want to keep. Chasing payment is awkward, easy to postpone and usually done late, by the same person who should be doing billable work, so receivables age and cash flow suffers.

What we built

An automated collections flow: reminders sent on a schedule the business sets, over the channels customers actually read, each carrying a secure payment link; replies are read and routed, disputes go to a person, and the sequence stops as soon as an invoice is paid.

Before: Chasing payment is awkward and late; Billable time lost to collections; Receivables age, cash flow suffers. After: US$1M collected in the first 3 months.

Before

  • Chasing payment is awkward and late
  • Billable time lost to collections
  • Receivables age, cash flow suffers

How it works

  1. Remind on the business’s schedule. Reminders go out on a cadence the business sets, over the channels its customers actually read.

  2. Pay through a secure link. Each reminder carries a payment-provider link; the agent never handles card details.

  3. Read the replies. Replies are read and routed, and disputes go to a person.

  4. Stop the moment it is paid. The sequence ends as soon as the invoice is paid or the customer replies.

After

US$1M collected in the first 3 months

Stack

AI AgentPaymentsAutomationMessaging

Why it holds up

Collections is where an AI agent can do real damage, so the agent holds no payment credentials — the payment provider takes the card, and the agent only ever sees status. Tone, frequency and stop rules are set by the business, not improvised by the model, so a loyal customer is never chased like a stranger.

Related service: Secure AI agent development

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