// DOCUMENTATION

Turn deal-room financials into underwriting-ready output.

These guides explain the workflow behind finvuw: what files work best, how classifications are assigned, how user changes are saved, and what to do when a statement needs review.

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Getting Started

Create an account, upload a spreadsheet, choose a sheet, review accounts, and download output.

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Supported Files

Learn what trended statements work best and which layouts may need a closer review.

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Classification

See how rules, AI, confidence, coverage, and user changes work together.

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Saved Mappings

Manage future-upload overrides while keeping one-file changes scoped to that job.

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Outputs

Compare data-only XLSX, CSV, P&L view, and template exports.

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Troubleshooting

Handle upload failures, low coverage, load errors, and failed downloads.

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Guides

finvuw turns trended financial statements into a consistent, underwriting-ready dataset. Upload a monthly P&L, operating statement, or T12 file, and finvuw detects the layout, normalizes the data, maps accounts into a standard taxonomy, and produces clean web views and downloadable outputs.

The workflow is useful beyond formal underwriting. Clean normalized data can support portfolio reporting, consolidating files from different operators, forecast preparation, variance review, trend analysis, and recurring financial review work.

finvuw does not replace analyst judgment. It removes repetitive data-prep work so users can spend more time on assumptions, diligence questions, valuation, and decision-making.
  1. Create a finvuw account or sign in from the app.
  2. Upload an Excel file containing a trended P&L or T12 financial statement.
  3. Select the correct sheet if the workbook has multiple tabs.
  4. Review the classified accounts and adjust any account that needs a different category.
  5. Open the P&L view or download a data-only file or template export.
For launch, senior living is the first supported taxonomy. Additional real estate asset classes will be added as their rule sets mature.

finvuw is designed for monthly or trended financial statements: T12s, monthly operating statements, and income statements with account rows and date columns. .xlsx, .xlsm, and .csv files are supported.

  • Best results: clear account names, monthly columns, and a visible revenue through NOI structure.
  • Usually workable: operator-specific formats, department-heavy statements, and workbooks with extra tabs.
  • May require review: highly summarized statements, budget or variance files, missing account names, merged headers, or non-P&L schedules.

finvuw classifies accounts in stages. Deterministic rules and exact matches run first. AI is used to review low-confidence matches or classify accounts that remain unknown. User updates are applied last so your review wins over the automated stages.

  • Coverage shows the percentage of rows that received a classification.
  • Method shows where the classification came from, such as rule, AI, or user.
  • Confidence is a directional review signal, not a substitute for final user judgment.

When reviewing results, a user can adjust an account's category. One-file changes stay scoped to the current job. Future-upload mappings are saved separately and can be managed from the Mapping page.

  • The Mapping page is for enabling or disabling saved future-upload mappings.
  • Changing the category itself still happens on the Results page.
  • Disabling a saved mapping prevents it from applying to future uploads, but does not rewrite prior jobs.
  • Data-only XLSX: structured classified data for analysis or model import.
  • CSV: the same classified rows in a lightweight format.
  • T12 P&L template: a formatted workbook populated with the job's classified data.
  • P&L view: an in-app statement view with dollar and common-size toggles.
Some Excel templates may require enabling editing or calculation when opened, depending on local Excel security settings.
  • Upload failed: confirm the file is a supported spreadsheet or CSV and try again.
  • Processing failed: use the retry option from the job status or history page.
  • Low coverage: confirm the correct detail sheet was selected. If coverage is unexpectedly low on a normal-looking file, retry the job before manually classifying many accounts.
  • Wrong classification: correct it on the Results page. For obvious/common misses, email the file name, account name, current classification, and expected classification to [email protected].
  • P&L did not load: use the retry button; transient load errors are usually temporary.
  • Download failed: refresh the page and retry the download once the job is complete.

Ready to try the workflow?

Process a file, review the classified accounts, and download a normalized output.

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