{"slug":"late-payer-agent","name":"Polite Payment Recovery Agent","category":"Finance","customer":"Finance leads at small to mid-sized service businesses","problem":"Overdue invoices are chased inconsistently and smaller debts get written off.","value":"For finance leads at small to mid-sized service businesses, turn accounting aging reports and customer history into personalised reminders and escalation drafts that recover cash early. Address the recurring problem: overdue invoices are chased inconsistently and smaller debts get written off. The value hypothesis is faster payment and fewer write-offs with less manual follow-up; the pilot must establish whether that benefit is real.","format":"Operational coordination portal","screens":"Key screens: Aging dashboard, reminder composer, escalation queue. Use a dashboard showing overdue invoices by age and amount, a composer for personalised email and SMS drafts, and an escalation queue for phone call scripts and formal notices. Let users filter by customer and days late. Display sent, opened, replied and paid states. Provide a log of every action back to the customer record. In this product, the first view is aging dashboard, followed by reminder composer and escalation queue.","functionality":"1. Pull aging reports daily from accounting software. 2. Draft personalised email reminders varying tone by days late and history. 3. Send follow-up SMS after two days of no payment. 4. Generate natural-sounding phone call scripts for unpaid invoices. 5. Hold formal demand notices for human review and approval. 6. Log all actions and responses back to customer notes.","workflow":"Connect accounting platform, review aging report, approve reminder rules, let agent send emails and SMS, review phone scripts, approve formal notices, and monitor payment responses. Start with accounting aging reports and customer history and finish with personalised reminders and escalation drafts.","ai":"Use language models to compose uniquely worded emails, SMS and phone scripts that match customer language and payment history. Keep escalation logic in deterministic rules. A human reviews and approves any formal demand or legal threat before it is sent.","inputs":"Accounting aging reports and customer payment history","deliverables":"Personalised reminders, escalation drafts and an audit log of all follow-up actions","admin":"User roles for finance staff and approvers, reminder rule versions, approval states for formal notices, customer note updates, and a full audit trail of sent messages and responses.","mvp":"One buyer, finance leads at service businesses, first two modules are aging dashboard and reminder composer, with manual review of every draft before sending.","expansion":"Automate SMS sending and phone call placement after the paid pilot, then add rule tuning based on response rates and customer feedback.","usp":"The agent writes genuinely human-sounding reminders and knows exactly when to stop and ask for approval.","defensibility":"It gets harder to copy as it learns each customer's preferred tone and payment patterns, making escalation rules more effective over time.","alternatives":"Manual email chains and generic reminder templates; this differs by personalising every message and holding formal threats for human sign-off.","revenue":"Test pricing at $499 per month for up to 500 overdue invoices, as a hypothesis.","costs":"Main delivery costs are accounting platform integration, language model usage and phone call minutes.","integrations":"Starts with Xero or QuickBooks for aging reports, then adds email and SMS providers, and later a phone system.","dependencies":"Needs API access to accounting software, a reliable email delivery service, and a text-to-speech or voice agent for calls.","pilot":"A paid pilot with a service business proves it by comparing days sales outstanding before and after 30 days; the decision is to continue if overdue invoices reduce by at least 15 percent.","plan30":"Week 1: Connect to one accounting platform and build the aging dashboard. Week 2: Build the reminder composer for email drafts. Week 3: Add SMS drafting and customer history context. Week 4: Test with one friendly customer and log all actions.","metrics":"Two measurable outcomes are days sales outstanding reduction and percentage of overdue invoices paid within 14 days of first reminder.","channels":"Finance and operations communities, accounting software marketplaces, and small business forums.","leadMagnet":"A free aging report analysis showing how much cash could be recovered with automated reminders.","message":"Recover overdue invoices politely and consistently without sounding robotic.","retention":"It keeps earning by continuously tuning reminder tone and timing based on response data, and by adding new accounting integrations and escalation channels.","controls":"Limits on message frequency per customer, mandatory human approval for formal notices, permissions restricting who can edit rules, and a hard stop on any legal or threatening language without sign-off.","crossSector":"Operations; Customer Support","fn":["Pull aging reports daily from accounting software","Draft personalised email reminders varying tone by days late and history","Send follow-up SMS after two days of no payment","Generate natural-sounding phone call scripts for unpaid invoices","Hold formal demand notices for human review and approval","Log all actions and responses back to customer notes"],"sc":{"opp":6,"pain":7,"feas":6,"now":8},"phases":[{"name":"MVP","scope":"One buyer segment, one recurring use case. Manual review in the loop.","time":{"days":6,"label":"6 days"},"usd":10000},{"name":"Paid pilot","scope":"Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.","time":{"days":7,"label":"7 days"},"usd":13000},{"name":"Full product","scope":"Self-serve onboarding, billing, monitoring and the wider integration set.","time":{"days":12,"label":"2 weeks"},"usd":17500}],"running":[{"stage":"MVP and paid pilot","note":"about 3 customers","hosting":[50,100],"ai":[40,90],"total":[90,190]},{"stage":"Full product","note":"about 50 customers","hosting":[190,380],"ai":[280,560],"total":[470,940]}],"total":40500,"complexity":0.73,"days":25,"shot":true,"demo":true}