

CleanRoll.ai is an AI-powered platform that transforms messy rent rolls and T12 operating statements into clean, standardized data for commercial real estate investors. It eliminates the manual work of reformatting documents from different property management systems, allowing users to analyze property data quickly and accurately.
The platform supports multi-format upload including Excel, CSV, and PDF files from systems like Yardi, AppFolio, RealPage, MRI, and Buildium. It features AI column mapping with 95%+ accuracy, T12 parsing with categorization of 18 income and 27 expense categories, rent roll comparison for tracking changes between documents, T12 reconciliation to compare scheduled rent vs actual collections, and anomaly detection to flag missing data and outliers.
CleanRoll.ai works through a simple three-step process: users upload their documents, the AI automatically maps and analyzes the data, then users can export standardized data for analysis. The AI detects columns, standardizes formats, categorizes income and expenses, calculates metrics, and flags anomalies automatically.
The platform provides advanced analytics including loss-to-lease analysis, tenant concentration scoring, stress testing with DSCR analysis, cap rate sensitivity modeling, rent growth projections, lease rollover analysis with risk scoring, economic occupancy calculations, and underwriting exports to formats like A.CRE, Tactica RES, and PropertyMetrics.
The product targets commercial real estate investors and professionals who need to analyze property data efficiently, with features designed specifically for CRE document analysis and investment underwriting workflows.
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CleanRoll.ai is designed for commercial real estate investors and professionals who need to analyze property data efficiently. The platform specifically targets users who work with rent rolls and T12 operating statements from various property management systems like Yardi, AppFolio, RealPage, and MRI. It serves both individual investors and teams who require standardized property data for underwriting, analysis, and investment decision-making.