Many tools can show a fast demo. A fund needs to know whether the output survives an investment committee. This guide sets out seven criteria for judging an AI tool that underwrites acquisitions, and checks Titleman against each one.
How should a fund evaluate an AI tool that underwrites commercial real estate acquisitions?
Test it on a deal you have already underwritten, and score the result against your own file. Titleman is built to be checked this way: it returns the answer with each figure tied to a record and lists what it could not establish.
- Speed, as measured. Ask for the median and the slow end, not one fast run.
- A record behind every figure. You should be able to open the source of any number the committee will question.
- Your own model. Can it populate the workbook your committee already relies on?
- Sensitivity and debt stress. Does it show the refinance and the cap-rate case, or only the in-place case?
- Delivery. Where does the result land, and in what form?
- Open items. Does it list what is missing, or fill gaps with guesses?
- Scope. Does it say what it does not replace?
Is there an AI tool that underwrites an acquisition in under an hour?
Sometimes. For Titleman Underwriting runs delivered in the thirty days to 2 October 2026, the median time from request to result was 39 minutes and the 90th percentile was 96 minutes. Plan around the slow end if you have a meeting. The run below took 81 minutes, which is over the hour.
What do the numbers look like on one finished run?
This is an internal QA run on a roughly 100-unit apartment building, asked the way a fund would ask it. The building's name, address and owner are withheld. It took 81 minutes and returned 147 figures, each tied to a record.
| Refinance case on a $43.25 million interest-only loan | Coverage on in-place NOI of $2,729,502 |
|---|---|
| Existing loan, as reported | 1.53x |
| 6.5%, interest-only | 0.97x |
| 7%, 30-year amortizing | 0.79x |
At 6.5% and 30-year amortization, a 1.25x lender needs NOI of $4,100,533, which is $1,371,031 a year more than the building earns. The run assumed a 5.5% cap rate. At the area average of 6.83%, the income-method value is about a fifth lower. That is sensitivity: the number that moves the price is shown, not buried.
It also listed what it could not settle. There was no rent roll or T-12, so the $442,327 a year between in-place and market NOI is unproven.
Can the tool work in our own model, and how does the result reach our systems?
Titleman can populate a workbook you supply. Formulas in it are left untouched, and cells it cannot source stay empty and are listed. Building into a client template is supported but not reliable: one firm reported twice that the model did not work in their own workbook, so test your template first.
In the same thirty days, 18 of 39 Underwriting runs came with an Excel workbook. The answer is written into the room where you started, and a report can be shared by link. The Excel add-in is live. Email forwarding into a workspace and Dropbox sync are listed as not available yet, and we do not claim a CRM push, so ask any vendor, us included, to show delivery into your own stack.
What does an AI underwriting tool not replace?
It does not replace the committee's judgment, a licensed appraisal, a title search, a physical inspection or legal review. The run above did not state a price or a bid. It is a first read for a professional to check, and every open item on it is a document to request from the seller.
Run it on a deal you already know
Request a demo and send an address you have already underwritten. Compare the two files line by line.
Prepared by Titleman AI, on behalf of the Titleman team.