Case StudyMulti-Asset CRE InvestorSan Mateo, CA
How Westlake Realty Group cut per-deal underwriting from 6-8 hours to 20 minutes
A multi-asset investor in San Mateo was spending six to eight hours of senior time on every offering it looked at. Deals now land in the firm's own eight-tab model with comps pulled and every number cited, and senior review takes about 20 minutes.
6-8h → 20m
5
100%
The Challenge
What was actually in the way.
Westlake Realty Group sees dozens of offerings a month across five asset classes. Each one took six to eight hours of senior time before anyone would put a number in front of a decision maker: rekeying the rent roll, rebuilding the model, pulling comparables, and then checking the whole thing again because a single mistyped figure changes the answer.
The binding constraint was capacity, not judgment. Marginal deals were dropped because there were not enough hours in the week to underwrite them, which meant the deals that got a real look were the ones that happened to arrive on a quiet week rather than the ones that deserved it.
The Solution
What PSV built.
PSV built the underwriting analyst against Westlake's own eight-tab institutional model rather than a generic template. The output arrives in the format the firm already argues over, so nothing has to be re-modeled before it can be reviewed.
Deal materials go in, the analyst parses them, populates the model, pulls comparables, and applies the firm's return thresholds. Every figure it writes carries a pointer back to the source document. When a reviewer questions a number, the answer is a page and a cell reference rather than a rebuild.
One engine covers all five asset classes the firm buys. There is no separate tool, template, or process to maintain per property type.
01
Deal intake and parsing
Offering memoranda, rent rolls, and operating statements are read on arrival and mapped to the fields the firm's model expects, whatever format the broker sent them in.
02
The firm's own eight-tab pro forma
The engine populates Westlake's existing institutional model, not a PSV template. Assumptions, structure, and outputs match what the team already reviews.
03
Comparables pulled per deal
Rent and sale comparables are gathered and filtered for the submarket, so the model arrives with its market support attached.
04
Return thresholds applied
The firm's own hurdles run against every deal, so the first thing a reviewer sees is where the deal sits against the criteria they actually use.
The Impact
From 6-8 hours to 20 minutes. On every deal.
Per-deal review dropped from six to eight hours to about 20 minutes, roughly 18 to 24 times faster on the senior time each deal costs.
Because every number is traceable, review became checking rather than rebuilding. The senior hours that used to go into assembling a model now go into the deals worth arguing about.
Capacity stopped acting as the filter. Offerings that would have been dropped for lack of hours get underwritten to the same standard as everything else.
6-8h → 20m
Per-deal review time
Senior time per offering, from a full manual build to a review of a model that is already populated.
5
Asset classes on one engine
One underwriting system covers everything the firm buys, rather than a separate workflow per property type.
100%
Numbers traced to source
Every figure in the model carries a pointer back to the document, page, and cell it came from.
In their words
“We can’t speak high enough of you guys. Our team is extremely impressed.”
Brandon Rowell, Analyst, Westlake Realty GroupThe system behind it
AI Underwriting Analyst, built for one firm at a time.
Nothing here is a product with a login. Every build starts from the firm’s own models, templates, and criteria, which is why the output lands in a format the team already trusts.
Read the AI Analyst case studyMore case studies
Keep reading.
Four AI Employees
How Accomplish Collective put four AI employees across its deal cycle
4 AI employees across the deal cycle
AI Employee
How Sunrise Affordable Housing cleared its data-privacy bar before deploying an AI employee
0 Client data used to train anything
Deal Origination & Market Intelligence
How a team at Cushman & Wakefield expanded origination with zero added hires
0 Hires added to expand origination
AI for CRE · Weekly newsletter
The PSV newsletter, read by CRE operators.
Workflow teardowns, vendor takes, and field notes from custom AI builds. Free. Drop your email and the next issue lands in your inbox.
No spam. Unsubscribe in one click.
Let's get to work.
Thirty minutes. We'll tell you whether PSV is the right partner for what you're trying to build.
Or reach us directly at zed@pacificsoftwareventures.com