New Workflow: Instantly Build a Full STNL Financial Model from an OM

If you’ve ever spent an afternoon manually entering deal assumptions into an Excel model, flipping between pages of the OM, double-checking decimal points, and wondering if you caught every input, you’ll appreciate this one.

Now, the process of building a financial model for single-tenant net lease (STNL) properties just got a major upgrade. The CRE Agents digital coworker, the smartest AI Agent in Commercial Real Estate, is ready to help!

The Old Way: Manual, Tedious, and Risky

Traditionally, building a model for a property meant a lot of copy-pasting, guesswork, and potential for error. Analysts had to:

Parse scattered information from PDFs and other data sources
Manually retype dozens of assumptions
Double-check for accuracy
Cross their fingers that nothing got missed

One overlooked lease term or decimal error could throw off the entire valuation. Not to mention it can be a mind-numbing, time-consuming task.

The New Workflow: Extract, Validate, Model

We built a better way. Our new STNL modeling workflow allows your digital coworker to do the heavy lifting. Here’s what it does:

Extracts property data, such as city, state, year built, asking price, tenant name, rent roll details, cap rates, loan terms, and more.
Validates assumptions, flagging missing values, converting formats (e.g., % to decimals, acres to SF), and checking for logic gaps.
Populates Excel model by inputting assumptions directly into our pre-built STNL template.
Delivers final output, a fully populated Excel file with key metrics and valuation outputs ready to go.

The Numbers Behind It

The workflow captures over 60 critical data points, from lease terms and rent escalations to retenanting assumptions and residual cap rates. Whether it’s acquisition fees, amortization schedules, or credit ratings, it’s all included. Cleaned, formatted, and accurate.

Meet Vic: Trained to Perform Workflows like this 24/7

The magic behind the scenes? Vic, our digital coworker.

Vic is trained to perform workflows just like this one: to extract and model STNL assumptions with high accuracy. He’s available 24/7 and doesn’t take coffee breaks. At the end of each workflow, Vic runs a final Error Check comparing valuation metrics and cash flows to confirm alignment before the model hits your inbox.