AI Cash Intelligence
Technical Architecture Overview
A localhost TypeScript application providing automated daily cash position analysis, forecasting, and decision support for treasury operations.
Application runs entirely on local machine. No external servers. No data storage outside corporate network.
All PII and sensitive identifiers removed before any API call. Only numerical patterns and anonymized structures sent.
Uses corporate-approved OpenAI Enterprise endpoint. Data processing compliant with existing API usage policies.
treasuryease.com
From three source systems to a sanitized API call
Payment Data
GL Transactions
Entity Mapping
Parse, normalize, validate
- • Remove entity names
- • Strip account numbers
- • Anonymize counterparties
- • Hash identifiers
Sanitized data only
- • Numerical patterns
- • Anonymized structures
- • Generic categories
Alerts / Recommendations
What stays local vs. what is sent to API
- Entity names & legal identifiers
- Bank account numbers (IBAN, etc.)
- Counterparty names
- Internal cost centers
- Employee / user identifiers
- Credit facility details
- Historical raw transactions
- Original file exports
- Anonymized balances (Entity_A, Entity_B)
- Aggregated flow patterns
- Date ranges (relative, not absolute)
- Currency codes (EUR, USD, etc.)
- Hashed category identifiers
- Numerical thresholds (limits as %)
- Generic transaction types
All API calls use approved corporate OpenAI Enterprise endpoint. No data persisted on external servers.
What you know now
"Where does our treasury data actually go?" is a vague worry
→ You can trace it: COUPA/SAP/config → localhost sanitize → OpenAI Enterprise → alerts
"Is this safe?" gets answered with a general assurance
→ You can name the exact 8 fields that never leave, and the 7 that do (sanitized)
A localhost AI app sounds like a compliance risk by default
→ You know localhost + sanitization + an approved enterprise endpoint is the pattern that makes it compliant
AI Agents for Treasury
The same sanitize-then-send pipeline, traced through a full agent example.
Next step · CourseAI Agents in Treasury & Finance
The full architecture, stack, and implementation roadmap this fits into.
Built by a treasurer, for treasurers. · treasuryease.com