AI Deal Screening Case Study | Real Estate Automation
Back to Case StudiesFirst-Pass Underwriting with AI (CRE Quick Qualifier)
AI-assisted deal screening that reduced analyst workload by 70% and cut screening time from 45 minutes to under 3 minutes.
This Commercial Real Estate AI automation case study explores First-Pass Underwriting with AI (CRE Quick Qualifier). Tags: Commercial Real Estate, Document Processing, AI Implementation, Workflow Automation, OpenAI, Make.com, HubSpot, Retool, AI Automation.
70%
Analyst Workload Reduction
<3 min
Screening Time per Deal
70+
Deals Processed Monthly
Overview
A CRE investment firm reviewing >70 deals/month needed to automate their 'first pass' underwriting before sending to analysts. The manual process was inconsistent, time-consuming, and couldn't scale with deal flow.
Challenges
Analysts overwhelmed reviewing raw data
Completely inconsistent deal packets from brokers
No quick way to identify non-starters
Email-based flow impossible to scale
What We Delivered
AI engine to extract Rent Roll, OM, T12, unit mix
Quick Qualifier scoring model: location, cap rate, rent growth, NOI
Automated Slack & CRM alerts for recommended deals
Central dashboard showing all deals in screening
Workflow to assign promising deals to analysts automatically
Tech Stack
OpenAI, Make.com, HubSpot, Dropbox, Google Vision, Retool
Tags
Results
70%
Analyst Workload Reduction
<3 min
Screening Time per Deal
70+
Deals Processed Monthly
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