Cash Flow and Finance AI Agent

The Cash Flow and Finance AI Agent supports AI cash flow forecasting for construction and project-based companies, as part of DANAOS ProjectVIEW AI. It aims to build best, expected and worst-case cash flow forecasts from billing, certification, committed cost and payment terms in ProjectVIEW ERP. It also flags funding gaps early. The financial officer approves every forecast and action.

The agent uses the data in the Accounting and Finance Management module of ProjectVIEW ERP, together with receivables, payables and project cost linked to BoQ, WBS and Cost Codes.

• Client billing, certification and collection history
• Committed cost from purchase orders and subcontracts
• Supplier and subcontractor payment terms
• Retention, advance payments and guarantees
• Bank balances and financing lines

The agent follows the ProjectVIEW AI agent cycle. Applied to cash flow:

1. Detect: find periods where expected outflows exceed inflows, or where collections are slipping.
2. Investigate: trace the gap to delayed certifications, late payers, large commitments or retention.
3. Explain: state the drivers of each scenario in plain language.
4. Recommend: propose actions such as chasing a certification, rescheduling a payment or drawing on a facility.
5. Request approval: send the forecast and recommendations to the financial officer.
6. Execute: after approval, update the forecast and create follow-up tasks in ProjectVIEW ERP.
7. Audit: keep the assumptions, scenarios and decisions.

This is not because AI predicts the future like magic. The agent builds scenarios from your own data and assumptions, so finance can see what changes the outcome.

Main inputs, outputs and decision points:

The Cash Flow and Finance AI Agent works inside ProjectVIEW ERP governance, following the chain Identity → Role → Permission → Data → AI → Action. It sees only the data the user’s role allows and proposes only actions that role could take. AI should operate inside enterprise governance, not around it.

• Consequential actions always need human approval.
• Also, the system records every recommendation, approval and change for audit.
• Data stays in the client’s private environment and never goes to public consumer AI services.

Illustrative example. A contractor runs several projects, including Project G, where an interim certificate is awaiting client approval.

The agent builds three scenarios. In the worst case, the client delays the certificate one more month while a large subcontractor payment falls due, creating a short funding gap.

It explains the drivers and recommends chasing the certificate, agreeing a revised payment date with the subcontractor and preparing to use an existing facility if needed. The financial officer approves the forecast and the follow-up actions. Finally, the system logs the decisions.

The agent serves finance and executive teams:

• Accounting and financial officers who prepare cash flow forecasts and manage payments
• C-level executives who need early sight of funding needs

It applies to construction and other project-based industries where cash depends on certification and retention.