You open a rent roll and it looks familiar in the worst way. Columns shift, headers change names, charges land in odd places, and half the fields you need are missing or buried. Before you can underwrite, you have to clean. That cleaning step drags. It is repetitive, easy to mess up, and different every time because each property management system exports its own format. Underwriting ~5 min to run Parse Multifamily Rent Roll into Standard Schema Vic prompt Use Vic to parse this multifamily rent roll into a standardized two-tab Excel file. Purpose A human analyst needs roughly 30 minutes to complete the same cleaning and standardization; this task finishes in about 5 minutes and produces data that feeds directly into underwriting or asset reviews without further reformatting. Inputs Rent Roll File Required Include Future Residents Optional Additional Context Optional Outputs A two-tab Excel file with a standardized rent roll on one tab and a unit mix summary on the other, ready for direct use in models or reports. Time saved Cuts about 30 minutes of manual cleaning to about 5 minutes. How it works Give Vic the rent roll file and any context you have. The file can be Excel, CSV, or a PDF export from systems like Yardi. If you want future residents included, say so. If there are quirks in the file, note them in Additional Context. Run it with: Use Vic to parse this multifamily rent roll into a standardized two-tab Excel file. Vic converts the file into a two-tab Excel output built for underwriting. The first tab is a one-row-per-unit dataset on a fixed schema. It includes unit number, unit type, size, status, tenant, lease dates, rent, and other charges. Column names and number formats are consistent, so your model reads it without edits. The second tab is a unit mix summary. It rolls up unit counts, occupancy, average square footage, and average rents by unit type and by size range. It is the quick check you already do, now produced alongside the cleaned data. The real gain is consistency. Manual standardization forces calls about how to map columns, how to treat odd charges, and where to put missing values. Those calls vary by analyst and by day. With a fixed schema, outputs line up across deals. Because the output is structured, it drops straight into underwriting models or asset review templates. No column renaming, no reordering, no date or currency fixes. If you keep a house model, this turns rebuilds into a paste. Comparisons get easier. When every deal is normalized the same way, unit mix summaries line up. You can compare occupancy, average rents, and size bands without reconciling definitions each time. Inputs are simple. Provide the rent roll file. Optionally include future residents. Add any notes that matter. The run takes about five minutes and returns a single Excel file with both tabs. For acquisitions and underwriting, this replaces a routine half hour per deal. For asset management, it standardizes ongoing reporting without asking teams to change source systems. Small task, direct payoff: less cleaning, fewer errors, and a file you can use right away.