Construction loan underwriting software
vishwa.ai reads the budget, the sponsor financials, and the takeout terms, computes loan-to-cost, stabilized DSCR, and debt yield, and drafts the memo.
Documents received
- Construction budget, hard and soft costsSpread
- Draw scheduleSpread
- Pro forma operating statementSpread
- Sponsor financial statements and returnsSpread
- Guarantor personal financial statementsSpread
Computed for the memo
Exceptions verified by our credit experts
Every figure links to its source line. Your credit team makes the decision.
Sample project: 180-unit multifamily, ground-up
| Line item | Amount | Share of cost |
|---|---|---|
| Land | 2,400,0001 | 12.0% |
| Hard costs | 13,800,0001 | 69.0% |
| Soft costs | 2,600,0001 | 13.0% |
| Contingency | 1,200,0001 | 6.0% |
| Total project cost | 20,000,000 | 100.0% |
| Loan request | 13,000,0002 | |
| Loan-to-cost | 65.0% | |
| Stabilized NOI | 1,520,0003 | |
| Stabilized debt yield | 11.7% | |
| Takeout debt service | 1,080,0004 | |
| Stabilized DSCR | 1.41x |
Same rigor, a fraction of the time
With a full audit trail your auditors, examiners, and LPs can inspect.
- Faster deal closure
- 75%
- Reduce time from document intake to credit committee
- Accuracy with expert review
- 100%
- AI extracts, domain experts verify every output
- Audit trail coverage
- Full
- Every decision linked to source documents
The problem
Where construction underwriting loses time
How it works
How vishwa.ai automates it
The analysis
The numbers on the credit memo
Frequently asked questions
Still deciding? Talk to our team.
Can vishwa.ai underwrite construction loans?
Yes. Vishwa AI reads the construction budget and the sponsor and guarantor financials, computes loan-to-cost, tests stabilized DSCR and debt yield on the pro forma, and drafts a credit memo that covers the construction period and the takeout.
How does vishwa.ai compute loan-to-cost?
Loan-to-cost is the loan amount divided by total project cost from the budget, with hard costs, soft costs, and contingency included. The budget lines and the formula stay visible, so a reviewer can see exactly what was counted.
Does vishwa.ai analyze the guarantors on a construction loan?
Yes. Guarantor returns and personal financial statements are spread and rolled into global cash flow, so the credit memo shows what stands behind the completion guaranty.
Does vishwa.ai track construction and land development concentration?
Yes. As part of portfolio monitoring, construction and land development exposure is tracked against the interagency CRE concentration guidance, with drill-down to the loans that drive it.
Is AI underwriting auditable and explainable?
Yes. Every figure links to the source document and the calculation behind it, so when an examiner, an auditor, or an LP asks how you got a number, you can show them in one click. Vishwa AI applies the same logic to every deal and keeps a complete audit trail, which is usually the part manual spreading cannot reproduce six months later.
How accurate is the extraction, and is there human review?
AI extracts, our experts verify, and your analysts review the exceptions. In practice that turns a multi-day spreading exercise into a quick validation, with people focused on the cases that need judgment rather than re-keying a T-12 into Excel.
Keep exploring
Related
Underwrite a construction deal on a call
Bring the budget, the pro forma, and the sponsor package. We will compute loan-to-cost and the stabilized case and draft the credit memo, with every input sourced.
