PayPredict AI — Intelligent Customer Payment Prediction Platform

Know which invoices will pay — and when.

PayPredict AI is an agentic receivables system that scores every open invoice on payment probability and predicted date, runs a daily collections worklist prioritized by impact, and rolls up to a bottom-up cashflow forecast CFOs actually trust.

Illustrative reference architecture. The system below represents how we design and deploy PayPredict AI in real engagements. Specific client deployments are confidential and not disclosed; the patterns, stack, and outcome ranges shown here reflect our active engineering practice.
Use cases

Built for real operations.

Where PayPredict AI fits — anywhere customer payment timing is unpredictable enough to break cashflow planning.

B2B payment forecasting
Predict which invoices will pay on time, late, or default — per customer, per invoice, with reasoning.
Subscription dunning
Time retry attempts and dunning sequences against each customer's real payment patterns, not generic schedules.
Cashflow planning
Roll predictions into a 13-week cash forecast that updates as invoices age and customer behavior shifts.
Collections prioritization
Surface the few accounts that materially move risk this quarter — instead of working the AR list top-down.
The problem

Finance teams find out about late payments after the due date.

By the time DSO has crept up, working capital is already stuck. By the time collections calls go out, the customer has already moved your invoice down their priority queue. Most finance teams operate the receivables function with a chronological worklist — call whoever's oldest first — when the real question is "who will actually pay if we call them today?"

PayPredict AI scores every open invoice on probability of on-time payment and predicted payment date. A collections agent generates the daily worklist prioritized by impact × probability × urgency. A forecasting agent rolls invoice-level predictions into bottom-up cashflow that updates every night.

The output isn't a dashboard. It's a list, in order, of which customers to call today — with the reasoning attached.

The architecture

How PayPredict AI is built.

Layered design, production tooling, native Azure integration. Every component is one we use in shipping client systems — not a theoretical reference stack.

Layer 1
Source Data
ERP invoices payment history customer master external credit signals industry data
Layer 2
ML Layer
Payment probability model predicted-date model risk segmentation embedding-based similarity
Layer 3
Agents
Scoring Agent Prioritization Agent Cashflow Aggregator Collections Workflow Router
Layer 4
Action
Collections worklist UI CFO cashflow dashboard Power Automate triggers ERP write-back
Capabilities

What it actually does.

Payment probability
ML models predict on-time payment likelihood for every open invoice.
Predicted payment date
Forecasts the actual day each invoice will clear — not just yes/no.
Customer risk segmentation
Groups customers by historical behavior, industry risk, and external signals.
Collections prioritization
Daily worklist auto-generated and ranked by impact × probability × urgency.
Cashflow forecasting
Aggregates invoice-level predictions into bottom-up cash forecasts CFOs trust.
ERP integration
Direct integration with SAP, Oracle, NetSuite, Dynamics, and Tally.
Expected outcomes

What this delivers in production.

Outcome ranges are illustrative — based on structural economics of the problem and what comparable production systems achieve. Actual results depend on baseline maturity, data quality, and integration depth.

10-25%
DSO reduction
Days Sales Outstanding cut through earlier intervention
Days
Forecast accuracy
Cashflow accurate to within days, not weeks
Collections output
Productivity doubled via prioritized worklists
Earlier
Intervention
On at-risk accounts before they go past due

Talk to us about PayPredict AI.

Tell us about your current setup and the outcome you'd want from PayPredict AI. We'll come back within one business day with a path forward.

Email us +91 6305242370