Anomaly Detection
Automatically flag missing data, outliers, and suspicious values in your rent rolls before they impact your analysis. Get a data quality score with every upload.
Data Quality Score
Every rent roll upload receives a data quality score from 0-100. Higher scores mean fewer issues and more reliable analysis. Scores below 70 indicate significant data problems that should be addressed.
Detected Issues Example
See exactly what issues are flagged, with actionable suggestions for each.
What Gets Detected
Missing Data
Empty cells for critical fields like unit ID, rent amount, or lease dates that could skew your analysis.
Rent Outliers
Units with rents significantly above or below the property average that may indicate errors or special terms.
Suspicious Values
Negative rents, future lease start dates in the past column, or square footage that seems implausible.
Date Inconsistencies
Lease end dates before start dates, expired leases marked as active, or impossible date combinations.
Use Cases
Due Diligence
Catch data quality issues in seller-provided rent rolls before they impact your underwriting assumptions.
Quality Assurance
Validate property manager exports before importing into your portfolio management system.
Lender Submissions
Ensure your rent roll is clean and error-free before submitting to lenders for financing.
Portfolio Monitoring
Identify data entry errors across your portfolio and maintain consistent reporting standards.
How It Works
Upload Your Rent Roll
Upload any rent roll in Excel, CSV, or PDF format. Our AI standardizes the data automatically.
AI Scans for Issues
Our AI analyzes every field for missing data, statistical outliers, and values that seem inconsistent.
Review Flagged Items
See a clear summary of detected issues with severity levels. Accept, dismiss, or investigate each flag.
Catch Data Issues Before They Cost You
Upload your rent roll and get a data quality score in seconds. Identify problems before they impact your underwriting.