AI diligence, IC reporting, and monitoring for private equity
The workflow, in one system
- 1
Ingest the data room
- 2
Spread the target
- 3
Run the diligence analysis
- 4
Draft the IC memo
- 5
Report and monitor
The problem
What slows private equity down
Diligence is a data-room slog
Associates re-key financials from CIMs, management decks, and Excel models under deal timelines, leaving little time for judgment.
Every target reports differently
Inconsistent statements and add-backs make it hard to normalize quality of earnings or compare targets.
IC and LP reporting is manual
Building investment committee memos and quarterly LP reporting packs is a copy-paste exercise that gets reworked every time a number changes.
Portfolio monitoring lags
Tracking portfolio company performance and covenants across the book lives in scattered spreadsheets, so problems surface late.
How it works
How vishwa.ai automates it
- 1
Ingest the data room
Collect CIMs, financial models, management accounts, and supporting documents from the data room, auto-categorized and tracked against a checklist.
- 2
Spread the target
AI extracts and standardizes target financials from PDFs, scans, and Excel, including messy management accounts, and experts verify the exceptions.
- 3
Run the diligence analysis
Compute EBITDA and adjusted EBITDA, leverage, margins, working capital, and growth, with every add-back itemized and traceable.
- 4
Draft the IC memo
Generate a first-draft investment committee memo from the spread figures and source documents, in your template, ready for the deal team to refine.
- 5
Report and monitor
Produce IC and LP reporting packs on your cadence, and after close ingest portfolio company reporting to track performance, leverage, and covenants with early-warning signals across the book.
Outcomes
Same rigor, a fraction of the time
- 75%
- faster from data room to investment committee
- 100%
- audit trail, with every figure traced to its source document
- Any format
- CIMs, Excel models, scans, and management accounts
Frequently asked questions
Does vishwa.ai have customers?+
Yes. Vishwa AI runs in production at large enterprise clients across banking and private credit. Most of them prefer that we do not name them publicly, so we keep those relationships confidential. The product is mature and proven in the US market, and we are glad to walk through relevant, anonymized references under NDA on a call.
Who uses vishwa.ai?+
Large banks and private credit firms use Vishwa AI for live underwriting and portfolio monitoring. We do not publish a client list because our customers prefer to keep their use of the platform confidential. It is an established, production grade system in regulated US lending, not a pilot.
Can you share customer references or case studies?+
Our enterprise clients in banking and private credit prefer to stay anonymous, so we do not post named case studies. We can take you through real, anonymized outcomes and arrange references under NDA during a demo. Vishwa AI is a proven product in the US market, with enterprise deployments already in production.
Is vishwa.ai proven, or is it early-stage?+
Vishwa AI is a mature, production grade platform used by large enterprises across US banking and private credit. It is not a pilot stage tool. We keep client names confidential at their request, but the product is proven at scale in regulated US lending.
How does vishwa.ai help private equity firms?+
Vishwa AI turns a data room into investment-grade analysis. It extracts and spreads target financials from CIMs, Excel models, and PDFs, computes adjusted EBITDA and leverage, drafts the investment committee memo, produces IC and LP reporting, and monitors portfolio company performance after close, with every figure traced to its source document.
Can vishwa.ai read a CIM and a full data room?+
Yes. Vishwa AI ingests CIMs, financial models, management accounts, and supporting documents from the data room in whatever format they arrive, including scans and Excel, and structures them for analysis. AI extracts, experts verify.
Does vishwa.ai produce IC and LP reporting?+
Yes. Vishwa AI drafts investment committee memos from the spread diligence and produces IC and LP reporting packs on your cadence. Every figure is traced back to its source document, so the numbers are defensible to your IC and your LPs.
Does vishwa.ai handle quality-of-earnings style add-backs?+
Vishwa AI itemizes EBITDA add-backs so they are visible and reviewable rather than buried, which keeps adjusted EBITDA and leverage defensible in the IC memo and to lenders.
Can vishwa.ai monitor portfolio companies after close?+
Yes. Vishwa AI ingests portfolio company reporting on its cadence, tracks performance, leverage, and covenants, and flags drift early across the portfolio, with drill-down to each company and into IC and LP reporting.
Run diligence and IC reporting faster
Send a CIM and a data room and see vishwa.ai spread the target, draft the IC memo, and build the reporting, with every figure traced to source.
