1
Customer & Contract Intelligence
Capture and organize
- Customer details
- Contract terms
- Credit periods
- Billing information
- Payment expectations
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Case Study
AI Accounts Receivable Automation
Applying AI to the Revenue-to-Cash Workflow
- Finance AI
- Accounts Receivable
- Intelligent Automation
- Document Intelligence
AI-powered workflows designed to improve collections and cash-flow visibility.
01
The Challenge
Accounts receivable teams often spend significant time tracking invoices, monitoring payment status, following up with customers and managing collections.
The underlying information can also be fragmented across:
- Invoices
- Contracts
- Purchase orders
- Customer records
- Email conversations
- Payment information
- ERP systems
- Spreadsheets
This creates an opportunity to use AI to bring these information sources together and automate parts of the revenue-to-cash workflow.
02
The Product Opportunity
Opportunity
The product vision was an AI-native accounts receivable platform that helps businesses improve visibility into receivables and automate repetitive collection workflows.
Core product flow
- 1Customer
- 2Contract
- 3Delivery
- 4PO
- 5Invoice
- 6Credit Terms
- 7Collections
- 8Payment
03
The Solution
2
Invoice Intelligence
AI can help extract and structure relevant information.
Invoices can be captured through
- ERP integrations
- File uploads
- Spreadsheet imports
- Other supported sources
3
Receivables Monitoring
Provide visibility into
- Outstanding invoices
- Aging
- Due dates
- Payment status
- Customer-level exposure
- Collection performance
4
Intelligent Collections
Human approval can be incorporated into sensitive collection workflows.
Potential workflow
- Invoice Status
- Customer Context
- Collection Strategy
- Communication
- Response
- Follow-up
Communication channels can include
- Voice
- Payment links
04
AI Architecture
AI capabilities
- LLMs
- Document intelligence
- Intelligent workflow automation
- Customer context
- AI-generated communication
- Human-in-the-loop
- Payment workflow integration
- Analytics
Key principle
Use AI to reduce repetitive work while keeping appropriate human controls.
Product intelligence
Aging
How long outstanding invoices have remained unpaid.
DSO
Days Sales Outstanding.
Collection Performance
How effectively outstanding receivables are being converted into payments.
Value Tracking
Baseline snapshots can be used to compare performance over time.
This creates a mechanism for connecting AI automation to business outcomes rather than simply measuring AI activity.
05
Product Thinking
The product connects AI automation to measurable business outcomes, while keeping people in control of sensitive steps.
- Business value before technology
- Human approval for sensitive collections
- Measure outcomes, not AI activity
- SaaS monetization considerations
06
My Role
Product Strategy & AI Product Design
Responsibilities
- Problem discovery
- Product vision
- Customer journey
- AR workflow design
- AI use-case definition
- Feature prioritization
- Product architecture
- AI workflow design
- MVP definition
- Prototype development
- Roadmap
- SaaS monetization considerations
07
Outcome
The product concept evolved into an AI-native AR platform focused on helping businesses improve receivables visibility and automate repetitive collection workflows.
Core principle: use AI to turn fragmented financial information into actionable collection workflows.
08
What This Demonstrates
- 1Financial Data
- 2AI Intelligence
- 3Prioritization
- 4Workflow
- 5Action
- 6Measurement
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