
Pinaka AI
Predict Payments with AI, to Protect Cash Flow.

About Pinaka AI
Introduction to Pinaka AI
Pinaka AI is a payment risk prediction platform designed for B2B enterprises that need to manage late invoice payments and optimize working capital. It analyzes operational and financial data to predict customer payment delays weeks in advance and provides preventive recommendations to protect cash flow.
Built on Oracle Cloud and accessible through a generative AI interface, Pinaka AI serves finance and operations teams such as Accounts Receivable, Order-to-Cash, Credit and Collections, Treasury, and Shared Services. The platform emphasizes prevention over resolution by identifying invoice and customer risks before delays occur.
Key Takeaways
- Predicts customer payment delays with a reported 96% accuracy, weeks in advance
- Focuses on delay prevention rather than post-delay resolution
- Hosted on Oracle Cloud with a Gen AI interface for analysis and action guidance
- Integrates with CRM, ERP, workflow tools, credit agencies, and newswires to unify data
- Uses machine learning and statistical tests to score risk and recommend preventive actions
- Aims to optimize cash flow by 2.8% of revenue and reduce working capital and short‑term debt burden
- Reports up to 40% improvements in operational efficiency and lower costs in finance operations
- Designed to work without significant changes to existing IT infrastructure or staffing
How Pinaka AI Works
Pinaka AI ingests and unifies data from core enterprise systems and external sources, including ERP, CRM, workflow tools, credit agencies, and newswires. It also considers operational signals such as payment methods, dispute history, credit ratings, and customer feedback about collections. This consolidated view establishes a single source of truth for risk assessment.
The platform applies machine learning models and statistical testing to predict invoice and customer payment risks weeks ahead of due dates. Results are presented through dashboards and a Gen AI interface that explains risk drivers and suggests preventive actions, such as prioritizing outreach, validating billing data, or adjusting credit and terms. Recommendations can be embedded into existing workflows to support proactive collections and issue resolution.
Core Benefits and Applications
Pinaka AI is suited for enterprises seeking to reduce Days Sales Outstanding (DSO), improve cash conversion, and lower operational effort in collections and dispute management. Typical applications include:
- Proactive collections: Prioritize accounts and invoices by predicted delay risk to focus team efforts.
- Dispute prevention: Surface likely billing or data quality issues before invoices are sent or become overdue.
- Credit and terms management: Monitor customers’ changing risk profiles using internal and external data.
- Operational efficiency: Reduce exception loops and manual follow-ups by acting earlier on at‑risk invoices.
- Working capital optimization: Mitigate short-term debt needs by accelerating and stabilizing cash inflows.
- Planning and scenario analysis: Use the Business Impact Simulator to estimate value from DSO improvements, working capital reductions, and operational cost optimizations.
| Component | Examples | Outcome |
|---|---|---|
| Data inputs | ERP, CRM, workflows, credit agencies, newswires; payment methods; dispute history; credit ratings; collections feedback | Unified dataset for risk modeling |
| Analytics | Machine learning and statistical tests | Predicted payment delays and invoice risk scores |
| Delivery | Oracle Cloud; Gen AI interface; dashboards; workflow integration | Preventive recommendations and prioritized actions |