Yariv Omer
CEO
Reigo Investments
Reigo Investments provides an AI‑powered platform for short‑term US real‑estate debt that uses big‑data analytics and machine‑learning to assess loan risk in minutes. Its proprietary Reigo Vulnerability Index predicts default probability and recovery outcomes, enabling hard‑money lenders, asset managers, and investors to reduce defaults, speed underwriting, and achieve higher risk‑adjusted returns while diversifying geographically.
- Artificial Intelligence
- Data & Analytics
- Enterprise Software
- Financial Technology
- Software Only
Updated 5 months ago
Funding
Raised to date
$13MRaised 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.
Funding rounds are not available yet.
Founders
Product
Problem
Investors in short‑term US real‑estate debt face high default rates and slow, manual underwriting processes, limiting returns and geographic diversification.
Solution
Reigo leverages a proprietary suite of big‑data analytics and machine learning models to evaluate loan risk within minutes. By ingesting over 600,000 historical loans and 300 external data points spanning two decades, the platform generates a Reigo Vulnerability Index that predicts default probability and potential recoveries. This enables lenders to close more deals, asset managers to diversify portfolios and cut underwriting time, and investors to achieve higher risk‑adjusted returns with default rates reduced to under 1% in testing. The solution is delivered as an end‑to‑end, cloud‑based asset‑management platform that provides real‑time risk scores, benchmarking against comparable hard‑money loans, and automated portfolio analytics.
Target Audience
Primary customers are hard‑money lenders, real‑estate asset managers, and institutional or accredited investors seeking exposure to short‑term real‑estate debt with improved risk controls.
Features
- Machine‑learning risk engine combining linear, random‑forest, and neural‑network models to produce a proprietary vulnerability index
- Integration of 300+ external data sources (borrower, property, market, macro indicators) covering the 2008 recession and COVID‑19 periods
- Real‑time loan risk assessment completed in minutes, dramatically shortening underwriting cycles
- Portfolio‑level analytics and benchmarking against peer hard‑money loans for both lenders and asset managers
- Geo‑diversification tools that allow users to expand exposure across local and national markets
- Automated prediction of default probability, recovery scenarios, and deal pros/cons