How a RE PE Shop Accelerated Underwriting Without Exposing Deal Data
Moving faster on deals while keeping proprietary underwriting assumptions completely private.
A Houston-based real estate private equity firm focused on value-add multifamily and industrial acquisitions. $800M in AUM, evaluating 15-20 deals per month, closing 2-3 per quarter.
The Challenge
Deal analysts were spending full days extracting data from OMs, building comparable analyses, and drafting investment committee memos. The team had started using Claude and ChatGPT to accelerate OM summarization and draft IC memos — but the firm's CIO raised the alarm when he realized proprietary underwriting assumptions and deal terms were being entered into third-party systems accessible to competing bidders.
The Solution
Metrovolo deployed a private AI environment with document ingestion configured for the firm's typical deal document formats — OMs, rent rolls, T-12s, loan documents, and market studies. Analysts could now upload deal packages and get structured summaries, key term extractions, and draft IC memo sections in minutes.
The Results
75% faster screening
OM review and initial screening reduced from 4-6 hours to under 1 hour per deal
15 min IC memos
IC memo first drafts generated in 15 minutes vs. 3-4 hours manually
25+ deals/month
Deal evaluation throughput increased — team now reviews 25+ deals per month
Fully private
All proprietary deal data remains within the firm's controlled infrastructure
“Speed is everything in our business. We're seeing more deals, moving faster on the ones we like, and our competitors can't see our underwriting.”
— Head of Acquisitions