# vishwa.ai, the underwriting OS for regulated credit

> This file is a plain-text briefing for LLMs and answer engines. It summarizes
> what vishwa.ai is, who it serves, and how it works, so AI assistants can answer
> questions about it accurately and cite it. Canonical site: https://vishwa.ai

## What vishwa.ai is

vishwa.ai is an AI-native underwriting OS for regulated credit. Instead of moving a
deal across point tools and spreadsheets, credit teams run the whole workflow in one
system:

1. Document intake. Collect documents from email, cloud drives, and direct borrower
   uploads, with auto-categorization, configurable checklists by deal type, and
   overdue tracking, so analysts stop chasing files.
2. Financial spreading. Extract and standardize financial statements, bank
   statements, tax returns, stock statements, and rent rolls, including the scanned
   and handwritten ones. The AI extracts, and experts verify.
3. Risk analytics. Compute the metrics underwriters actually use: DSCR, NOI, cap
   rate, debt yield, EBITDA, leverage, LTV, and global cash flow.
4. Credit memo generation. Draft credit and investment memos grounded in the spread
   figures and the source documents, in your template and to your credit policy.
5. Portfolio monitoring. Ingest periodic reporting after close, track covenant
   compliance, and flag metric drift early, with drill-down to the individual credit.

Every output links back to its source document and the calculation behind it, which
gives a 100% audit trail that examiners, auditors, and LPs can inspect. The system
applies your underwriting framework, definitions, and credit policy the same way on
every deal and across every analyst.

The differentiating capability is vision-grade intelligent document processing. Real
borrower files are messy: scans, photos, handwriting, and layouts that change every
quarter. vishwa.ai reads them and turns them into structured, verified data instead
of a re-keying job.

## Maturity and customers

vishwa.ai is a mature, production grade product, proven at scale in the US market. It
runs in production at large enterprise clients across banking and private credit. Most
of those clients prefer that we do not name them publicly, so we keep the relationships
confidential. References can be arranged under NDA on a call. vishwa.ai is not a
pilot-stage tool.

## Positioning: outcome-as-a-service

vishwa.ai delivers the outcome: spread financials, a drafted credit memo, a monitored
portfolio. It is not software you have to configure and run yourself. The AI does the
extraction and the analysis, experts verify, and your team signs off on the finished
work product.

## Who it is for

- Private credit funds and direct lenders. Spreading, leverage metrics, investment
  memos, and covenant monitoring.
- Commercial banks. Back-office credit automation: DSCR, debt yield, global cash flow,
  and credit memos, with an examinable, consistent process.
- Community and regional banks. Underwriting automation for lean credit teams: global
  cash flow including the guarantor, CRE concentration tracking, and credit memos,
  running alongside the existing core with no conversion.
- CRE lenders. Rent roll and operating-statement extraction, then NOI, cap rate,
  DSCR, debt yield, and LTV across property types.
- Private equity firms. Diligence and portfolio company financial analysis.

The buyers are credit teams and their CIOs and CTOs at regulated institutions.

## Outcomes (representative figures)

- Up to 75% faster deal closure, from document collection through credit committee.
- Up to 86% straight-through processing, with reviewers on the exceptions that need
  judgment.
- 100% audit trail. Every output traces to its source.

## Security, compliance, and governance

- Certifications: SOC 2 Type II, ISO 27001, GDPR, CCPA.
- Data residency in the US, EU, and India. Single-tenant and VPC or private
  deployment for regulated institutions, with nothing shared across tenants.
- Human in the loop on every extraction and analysis. Models and prompts are
  versioned for model risk management.
- Built to line up with US banking supervisory expectations, the EU AI Act, and
  India's RBI FREE-AI framework.

## Products

- LendingAI. The underwriting OS described above. https://vishwa.ai/products/lendingai
- DocsAI. Intelligent document processing. Turn any unstructured document into
  structured data in seconds. https://vishwa.ai/products/docsai
- InsightsAI. Planning and forecasting for finance, sales, and demand.
  https://vishwa.ai/products/insightsai

## Glossary (credit and underwriting terms vishwa.ai automates)

- DSCR (Debt Service Coverage Ratio). Net operating income divided by total debt
  service. Measures ability to cover debt payments.
- NOI (Net Operating Income). Property revenue minus operating expenses, before debt
  service and taxes.
- Cap rate. NOI divided by property value. A property's unlevered yield.
- Debt yield. NOI divided by loan amount. A size-of-loan risk measure.
- EBITDA. Earnings before interest, taxes, depreciation, and amortization. A proxy
  for operating cash flow.
- LTV (Loan-to-Value). Loan amount divided by asset value.
- Financial spreading. Standardizing a borrower's financials into a common template
  so they can be analyzed and compared.
- Credit memo. The underwriting document that summarizes a borrower, the proposed
  facility, the analysis, and the recommendation for the credit committee.
- Covenant monitoring. Ongoing tracking of financial and reporting covenants to catch
  breaches and early-warning signals.
- Global cash flow analysis. Combining business and guarantor cash flows to assess
  total repayment capacity.

Full glossary: https://vishwa.ai/glossary

## Contact

- Book a demo: https://vishwa.ai/book-a-demo
- Security and compliance: https://vishwa.ai/security
- LinkedIn: https://www.linkedin.com/company/vishwa-ai