PRODA automates the collection, extraction, standardization, and error-checking of rent roll data from various formats, including Excel and PDFs, to enhance data quality and accessibility. This technology eliminates manual data preparation, allowing real estate companies to quickly analyze accurate data and improve operational efficiency.
Funding
$8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Real estate companies face challenges in efficiently collecting, standardizing, and validating rent roll data from various sources like Excel files, PDFs, and property management systems. Manual data preparation is time-consuming, error-prone, and hinders timely analysis, impacting operational efficiency and decision-making.
Solution
PRODA automates the entire rent roll data process, from collection and extraction to standardization and error-checking, regardless of the source format. The platform extracts data from Excel, PDFs, and property management systems, transforming it into a consistent, structured format ready for analysis. By eliminating manual data entry and validation, PRODA enables real estate companies to quickly access accurate, reliable data, improving the speed and quality of their analysis and reporting. The system uses machine learning to continuously improve its data processing capabilities, ensuring high accuracy and efficiency.
Target Audience
PRODA targets real estate companies, including property owners, investors, asset managers, and lenders, who need to efficiently manage and analyze rent roll data for underwriting, asset management, and reporting purposes.
Features
- Automated data extraction from various rent roll formats, including Excel, PDF, MRI, and Yardi
- Data standardization to ensure consistency across different sources and formats
- Automated error-checking to identify and flag potential inconsistencies and inaccuracies
- Integration with existing property management systems
- Secure data collection and storage
- Machine learning-powered continuous improvement of data processing accuracy