AI-Powered Commercial Real Estate Underwriting
How Deligence Technologies helped a commercial real estate investor reduce underwriting timelines from days and weeks to just 1–2 hours while making it easy to compare multiple investment scenarios side by side.
KEY OUTCOMES
At a Glance
Industry
Real Estate
Location
Québec City, QC, Canada
Service
Commercial Real Estate AI Underwriting
Success Highlights
Days & Weeks to 1–2 Hours Per Underwrite
Multiple Scenario Comparisons Side by Side
Consistent Assumptions Across Deals
Investor-Ready Outputs Generated Automatically
ABOUT CRE AI UNDERWRITING
Project Overview
In commercial real estate, fast and accurate underwriting can make the difference between winning and losing a deal. We worked with a multi-tenant industrial investor whose underwriting process was highly manual, requiring extensive spreadsheet work, document review, financial modeling, and repeated assumption changes.
We built an AI-powered underwriting platform that automates the workflow—from extracting data from offering memorandums and rent rolls to generating financial models and investor-ready reports. The platform also enables users to quickly create and compare scenarios based on interest rates, rent growth, vacancy, hold periods, financing structures, and LP/GP waterfalls.
As a result, the client reduced underwriting time from days or weeks to just 1–2 hours. The team can now evaluate opportunities faster, compare scenarios instantly, and make more confident acquisition decisions.
THE CHALLENGES
Four Problems Slowing Every Deal
The existing process worked, but it was becoming impossible to scale efficiently as deal volume increased.
If your acquisition team is spending days rebuilding spreadsheets just to compare financing assumptions, the underwriting process itself has become the bottleneck.
THE OPPORTUNITY
The Need for Speed in Deal Underwriting
The client operated in a fast-moving commercial real estate market where every acquisition required extensive analysis—from reviewing offering memorandums and rent rolls to modeling debt, forecasting cash flow, and evaluating value-add opportunities. The team also needed to test financing scenarios and compare returns as market conditions changed.
1
Automate manual underwriting workflows across every acquisition
2
Accelerate financial modeling by generating deal models in minutes instead of hours.
3
Enable instant scenario analysis for rates, hold periods, rent growth, vacancy, and financing.
4
Eliminate repetitive spreadsheet work and reduce manual model rebuilding.
5
Improve investment decision-making with faster comparison of returns, cash flow, and IRR.
THE WORKFLOW
Building the System, Step by Step
We designed a purpose-built underwriting automation platform specifically for how commercial real estate investors evaluate acquisitions.
1
Standardized Underwriting Engine
We built a centralized underwriting framework with standardized assumptions for rents, vacancy, escalations, financing, and operating expenses.This ensures every deal is evaluated consistently.
Standardized Framework
Unified Assumptions
Consistent Analysis
2
Automated Financial Modeling
3
Multi-Version Scenario Modeling
4
Intelligent Document Extraction
5
Investor Waterfall & Return Modeling
THE IMPACT
From Days & Weeks of Underwriting to 1–2 Hours
Transforming underwriting from a time-intensive process into a faster, more consistent, and data-driven acquisition workflow.
TECHNOLOGY STACK
Built With the Right Technology
A robust technology stack designed to deliver a fast, scalable, and reliable platform.
Frontend/Backend:
React.js/Node.js
Database:
PostgreSQL
AI Layer:
Open AI
Automation Workflows:
Make.com
Financial Engine:
Custom CRE Modeling Engine