Machine-learning debt recovery platform that helps small businesses collect outstanding invoices through personalized digital outreach
Copy the full spec as Markdown — paste into Claude Code, Cursor, or any AI tool to start building
Core features, MVP scope, and platform targets
Technology choices optimized for speed-to-market and scalability
Third-party services to connect for maximum value
Phase-by-phase breakdown from design to launch
Tasks
Deliverables
Tasks
Deliverables
Tasks
Deliverables
Tasks
Deliverables
Key roles needed to build and launch
Full-time
$10,000-$15,000
Full-time
$12,000-$18,000
Part-time / Contract
$3,000-$6,000
Part-time
$4,000-$8,000
Part-time / Founder
$2,000-$5,000
Startup costs and monthly operating expenses
Break-Even Timeline
12-18 months
Target MRR
$60K-$250K
Recommended pricing tiers and positioning
$0/mo
$29-$79/mo
$149-$299/mo
Custom pricing
Key components of the business model
An AI-powered platform that connects to QuickBooks/Xero/Stripe, automatically identifies overdue invoices, and sends personalized, escalating payment reminders via email, SMS, and letter. Uses ML to optimize timing, channel, and messaging tone based on debtor behavior. Offers self-serve payment portals with flexible payment plans, all while maintaining FDCPA compliance. Unlike competitors, we focus on small businesses with 1-50 employees with a streamlined, affordable solution.
Deep domain expertise and technical moat create high barriers to entry for new competitors
• Primary: Success-based fees (15-25% of collected debt) + SaaS subscription ($99-$499/mo)
• Secondary: Premium feature upsells
• Tertiary: API access for enterprise
• Data insights and benchmarking reports
• Small businesses with 1-50 employees, freelancers, and agencies with $10K-$500K in annual receivables, particularly service-based businesses
• Early adopters willing to try new solutions
• Teams frustrated with incumbent pricing
• Zoom API (integration partner)
• Google Meet API (integration partner)
• Microsoft Teams API (integration partner)
• Zapier (integration partner)
• Engineering team salaries (60-70% of costs)
• Cloud infrastructure and API costs
• Marketing and customer acquisition
• Customer support operations
Estimated MRR growth over 24 months
| Timeline | MRR | Customers |
|---|---|---|
| Month 1-2 | $0 | Beta users (free) |
| Month 3 | $1,200 | 5-15 |
| Month 6 | $4,800 | 20-60 |
| Month 9 | $12,000 | 50-150 |
| Month 12 | $24,000 | 100-300 |
| Month 18 | $48,000 | 250-700 |
| Month 24 | $90,000 | 500-1,500 |
Pre-launch, launch day, and growth playbook
Month 1
100 registered users
Month 2-3
First 10 paying customers
Month 4-6
50 paying customers
Month 6-9
$10K MRR
Month 9-12
Product-market fit signal (40% 'very disappointed')
Month 12-18
$60K MRR
Metrics to track for growth and health
Monthly Recurring Revenue (MRR)
Weekly
Customer Acquisition Cost (CAC)
Monthly
Monthly Active Users (MAU)
Weekly
Churn Rate
Monthly
Net Promoter Score (NPS)
Quarterly
LTV:CAC Ratio
Monthly
Time to Value
Weekly
Feature Adoption Rate
Monthly
Support Ticket Resolution Time
Weekly
Organic Traffic Growth
Monthly
Regulatory and legal considerations