16 AI Tools for Commercial Real Estate Lenders in 2026, by the Job They Do

The short answer. This page covers 16 AI tools commercial real estate lenders use in 2026, by the seven jobs they do. The loan origination system: Baker Hill, Abrigo, Rockport. AI underwriting for CRE loans: Blooma, Clik.ai. Reading the borrower's documents: PRODA, Ocrolus, V7 Go. Leases: Prophia, Propaya. Loan and market data: Trepp, CRED iQ. Drafting: ChatGPT, Claude, Gemini. One file, tied out: Titleman.

Published by Titleman, which makes one of the tools below. A commercial real estate lender does not ask what a property could earn. It asks whether the borrower's file supports the loan, and whether it will keep supporting it. This page sorts sixteen tools by the part of that question they answer. Every quoted description of another company is that company's own wording, read on its site on 11 October 2026 and linked; the lines on what a tool fits, what it does not cover, and what counts for and against it are our reading of that wording. Nothing here is a ranking: the test that decides is one loan file you already know the answer to, and it is described near the end.

Written by the Titleman team. AI was used to draft this page. Every quoted description of another company was then checked, word for word, against that company's own page on the date shown. The lines on fit, coverage, and points for and against are our reading, not the vendor's words.

If you only have a minute: a lender usually already owns a system for the workflow. The gap is usually earlier, in reading the borrower's package and checking that its documents agree with each other. Start there.

The 16 tools at a glance

Free plans and trials, as each vendor shows them

Vendors change what they offer, so every entry here carries the date we read it: 11 October 2026. This table shows one thing anyone can check from outside: whether the vendor's own site states a free plan or a trial. "Not stated" means we found no such statement on the pages we read; it does not mean there is none. Each tool name links to the vendor's home page.

How we checked, and what we did not

Three rules, so you can judge the list as well as the tools.

1. A tool is listed by the job it does, in its own words. The quoted words come mainly from the title and the search description each company wrote for the linked page, so some of them will not be found in the text you see on that page. Where a company's site did not answer on the day we read it, we left the company out instead of describing it from memory.
2. No scores. We have not run every product below on the same loan file, so we do not pretend to rank them. Where we have a view, it is about the category: what to check and where it stops.
3. We say where we are not the answer. Titleman is one row of seven. If your problem sits in one of the other six, buy there.

The same scheme for every tool, ours included. Each entry below has the same five lines: who it fits, what its description does not cover, its free plan or trial as stated on its site, the one thing anyone can check from outside (is there a free plan or trial), and what our evidence is. For every tool but our own, the evidence is the vendor's pages and nothing more: we have not run those products, so this page does not say which is better. Titleman is measured on the same point and does no better on it than the others.

What a lender's software has to do

A commercial real estate loan goes through the same five steps at a bank, a debt fund or an agency lender, and each row below serves one or two of them.

1. Take in the package. An offering memorandum or loan request, a rent roll, a trailing twelve months of income and expenses, the borrower's financials. They arrive in different formats, and somebody has to read them. What a T-12 operating statement is and how to read a rent roll cover the two documents that matter most.
2. Tie it out. The rent roll, the T-12 and the memorandum should describe the same property. Often they do not, and the differences are the credit story.
3. Size the loan. Net operating income the lender believes, against the coverage, yield and leverage tests of the credit policy. The three measures are explained here: DSCR, debt yield and loan to value.
4. Decide and document. A credit memo that a committee can question, and a trail an examiner can follow.
5. Monitor. Covenants, rollover, maturity, and the market around the collateral.

The expensive mistakes happen at step 2, and much of the software is sold for steps 3 to 5.

1. The loan origination system

The system of record: application, approvals, documents, conditions, booking, and the hand-off to servicing.

1. Baker Hill

Baker Hill offers "centralized loan origination software (LOS) for commercial, small business, and consumer loans".

• Fits: banks and credit unions that need a loan origination system.
• Its description does not cover: investors and brokers.
• Free plan or trial: not stated.
• On the one point we could check. In favor: none. Against: no free plan or trial stated.
• Evidence: the vendor's own pages. We have not run it.

2. Abrigo

Abrigo says "from AML to fraud detection and lending, we help financial institutions manage risk and drive growth".

• Fits: financial institutions managing lending, fraud and compliance risk.
• Its description does not cover: analysis of one property.
• Free plan or trial: not stated.
• On the one point we could check. In favor: none. Against: no free plan or trial stated.
• Evidence: the vendor's own pages. We have not run it.

3. Rockport

Rockport describes its products as "top-tier CRE management software and lending solutions".

• Fits: lenders and equity investors who run origination and asset management on one system.
• Its description does not cover: one investor analyzing one deal.
• Free plan or trial: not stated.
• On the one point we could check. In favor: none. Against: no free plan or trial stated.
• Evidence: the vendor's own pages. We have not run it.

What to check. How commercial real estate is handled inside a system built for many loan types: whether a rent roll and an operating statement are data the system understands, or attachments it stores. How the credit policy is expressed, and who can change it. And what the examiner sees: the trail from the approved figures back to the documents they came from.

Where it stops. A system of record keeps what the analyst concluded. It does not read the offering memorandum, and it does not tell you that the broker's income is a fifth higher than the trailing statement supports.

2. AI underwriting for CRE loans

Products built for the commercial real estate credit process itself: reading the package, spreading it, sizing, and watching the portfolio.

4. Blooma

Blooma calls itself an "AI-powered CRE lending platform" for "deal origination, portfolio monitoring, and underwriting".

• Fits: commercial lenders: origination, underwriting and portfolio monitoring.
• Its description does not cover: equity investors and developers: it is described as a lending platform.
• Free plan or trial: no free trial.
• On the one point we could check. In favor: none. Against: no free trial.
• Evidence: the vendor's own pages. We have not run it.

5. Clik.ai

Clik.ai says its "AI-powered platform automates underwriting, deal analysis, loan origination, & document processing", for commercial real estate firms and for banks.

• Fits: commercial real estate firms and banks extracting figures from documents into underwriting.
• Its description does not cover: finding deals, or parcel and zoning research.
• Free plan or trial: not stated.
• On the one point we could check. In favor: none. Against: no free plan or trial stated.
• Evidence: the vendor's own pages. We have not run it.

What to check. Whose income the tool sizes on. A platform that spreads the borrower's figures faster has saved typing; a platform that derives its own figure from the trailing statement and shows the difference has done underwriting. Ask to see the second on a file of yours. Check also how each figure is tied to its source, down to the page or the cell, because that is what a credit committee and an examiner will ask for.

Where it stops. These are platforms for an institution, with the integration and the rollout that implies. They are a decision for the head of credit, not for an analyst with a file due on Friday.

3. Reading the borrower's documents

Before anything is sized, somebody types. This row replaces the typing.

6. PRODA

PRODA says it will "turn any rent roll or operating statement into standardized, error-checked data in minutes", in "any format, asset class, language or currency".

• Fits: teams that receive rent rolls and operating statements in many formats and need them standardized.
• Its description does not cover: the model itself: it prepares what goes into one.
• Free plan or trial: free trial by booking.
• On the one point we could check. In favor: free plan or trial. Against: none.
• Evidence: the vendor's own pages. We have not run it.

7. Ocrolus

Ocrolus calls itself an "AI workflow and analytics platform for lenders" that will "automate financial document analysis".

• Fits: lenders automating the reading of financial documents.
• Its description does not cover: property and market data.
• Free plan or trial: not stated.
• On the one point we could check. In favor: none. Against: no free plan or trial stated.
• Evidence: the vendor's own pages. We have not run it.

8. V7 Go

V7 Go is a general document tool, not a real estate one: "AI workflows for due diligence, underwriting, and claims".

• Fits: teams with repeatable document work who will write their own instructions.
• Its description does not cover: real estate data: it is a general document tool and brings none.
• Free plan or trial: not stated.
• On the one point we could check. In favor: none. Against: no free plan or trial stated.
• Evidence: the vendor's own pages. We have not run it.

What to check. Give the tool a scanned document as well as a clean export, and count the fields a person has to correct. Ask where a figure came from: a good extraction shows the page or the cell. Ask what happens to a line the tool does not recognize, because the dangerous failure is not an error message but a number filed under the wrong heading. Six checks before you trust a rent roll extraction is the longer version.

Where it stops. Clean data is an input. Deciding that the insurance line is too low, or that the taxes will reset, is still underwriting, and it happens after this row has done its work.

4. Leases

For office, retail and industrial collateral, the income is a set of contracts, and the risk is in their clauses: expiry, renewal options, termination rights, co-tenancy, caps on recoveries.

9. Prophia

Prophia describes "AI-powered lease abstraction and insights for CRE", aimed at keeping "trusted portfolio data".

• Fits: owners and asset managers who need leases abstracted and kept current across a portfolio.
• Its description does not cover: deciding whether to buy the building.
• Free plan or trial: not stated.
• On the one point we could check. In favor: none. Against: no free plan or trial stated.
• Evidence: the vendor's own pages. We have not run it.

10. Propaya

Propaya promises "lease review in minutes" for "lease review and lease abstraction".

• Fits: teams reviewing and abstracting leases one deal at a time.
• Its description does not cover: anything beyond the lease.
• Free plan or trial: free trial.
• On the one point we could check. In favor: free plan or trial. Against: none.
• Evidence: the vendor's own pages. We have not run it.

What to check. Whether the abstract links each field to the clause it came from, so a reviewer can check the ten fields that matter without rereading the lease. Whether amendments are read together with the original. And how the tool reports a clause it could not classify. What lease abstraction is covers the basics.

Where it stops. Many lease abstraction products are built for administering a portfolio after closing. Using one against a closing deadline is a different job, and the fields that matter are not the same: lease abstraction for acquisition due diligence explains the difference, and it applies to a lender's diligence as much as a buyer's.

5. Loan and market data

What is maturing, what is delinquent, what comparable loans looked like at origination, and what the market around the collateral is doing.

11. Trepp

Trepp says it was founded in 1979 and is "a leading provider of data, insights, and technology solutions to the structured finance, commercial real estate, and banking markets".

• Fits: lenders, investors and analysts working with securitized and bank commercial loans.
• Its description does not cover: work on a building that has no loan in its data.
• Free plan or trial: free trial offered.
• On the one point we could check. In favor: free plan or trial. Against: none.
• Evidence: the vendor's own pages. We have not run it.

12. CRED iQ

CRED iQ describes itself in four words: "commercial real estate intelligence".

• Fits: analysts, brokers and lenders tracking commercial loans and the properties behind them.
• Its description does not cover: a property that has no loan in its data.
• Free plan or trial: not stated.
• On the one point we could check. In favor: none. Against: no free plan or trial stated.
• Evidence: the vendor's own pages. We have not run it.

What to check. Which loans the data covers. Securitized loans are reported in detail and bank balance-sheet loans are not, so a data set built on the first says little about the second. Check the date of each figure, because loan data runs behind. And read the labels with care. A loan in workout is not necessarily in trouble on cash flow.

Where it stops. Market data tells you what happened to other loans. It frames the question about this one and does not answer it.

6. General assistants

ChatGPT, Claude and Gemini are in many credit teams now, for drafting a memo, summarizing an appraisal or an environmental report, or testing the logic of a structure. They are good at it.

13. ChatGPT

ChatGPT is OpenAI's general assistant. Its plans page describes the free plan as "Intelligence for everyday tasks".

• Fits: drafting, summarizing and reasoning over documents you hand it.
• Its description does not cover: being a source of property records. It knows what is in the conversation, not what is in the county's records.
• Free plan or trial: free plan.
• On the one point we could check. In favor: free plan or trial. Against: none.
• Evidence: the vendor's own plans page. We ran no test of the three assistants against each other.

14. Claude

Claude is Anthropic's general assistant. Its plans page describes the Pro plan as "For everyday work".

• Fits: drafting, summarizing and reasoning over documents you hand it.
• Its description does not cover: being a source of property records. It knows what is in the conversation, not what is in the county's records.
• Free plan or trial: free plan.
• On the one point we could check. In favor: free plan or trial. Against: none.
• Evidence: the vendor's own plans page. We ran no test of the three assistants against each other. Titleman offers a connector for Claude, described below; we say so because it is a tie between this entry and us.

15. Gemini

Gemini is Google's general assistant. Its subscriptions page says the free tier is there to "Get everyday help from Google AI to tackle tasks at work, school or home."

• Fits: drafting, summarizing and reasoning over documents you hand it.
• Its description does not cover: being a source of property records. It knows what is in the conversation, not what is in the county's records.
• Free plan or trial: free with a Google Account.
• On the one point we could check. In favor: free plan or trial. Against: none.
• Evidence: the vendor's own plans page. We ran no test of the three assistants against each other.

What to check. Your institution's policy on what may be put into them, before anything else. Then what the assistant was actually given. It knows what is in the conversation and what it can reach through a connection you set up. It does not know the borrower's rent roll or the county's tax records unless they are put in front of it, and when it is asked for a figure it does not have, it may still produce one.

Where it stops. At the source. A figure with no document behind it cannot go in a credit memo. The useful pattern is to connect the assistant to a system that holds the evidence. Titleman can be used that way from inside Claude, through a connector: the guide is here.

7. One file, tied out: where Titleman works

This is the row where Titleman works, and it is step 2 of the five: the tie-out. The lender check takes the borrower's package, reads the offering memorandum, the rent roll and the T-12 end to end, and ties them against each other. What comes back is in four parts.

• What ties. Units and occupancy, in-place rent, the rent roll against the trailing statement, the expense totals: each with the page or the cell it was read from.
• What does not. The findings, in order of weight. In the sample file below they are expense cuts that the trailing statement does not show, insurance carried at a quote nobody has produced, and taxes that look abated.
• What the income supports. The broker's figure, the trailing actual and a lender's figure side by side, with the loan sized by debt coverage and debt yield at two rates. The rates are illustrative, and you put in your own.
• Questions for the borrower. The documents that would settle each finding.

Here it is on a sample file. Every money figure is scaled and the borrower is not named.

Around that check, Titleman assembles the property record from 2,100+ sources and names the comparables, so the collateral can be looked at as well as the file. On a land or construction loan, development due diligence assembled from the record describes the same work for the site itself: parcel, title condition, zoning and overlays, utilities and environmental exposure. What a lender and an investment committee each need from the same analysis explains how the two readers differ, and what to demand from software that writes a committee memo applies to a credit memo word for word.

Where Titleman stops. It is not a loan origination system and holds no system of record for your loans. It does not replace your credit policy: it shows what the file supports and leaves the decision with you. It is not a loan data subscription. Coverage of property records is United States first, and uneven by state: this page says which states are wired and which already hold records. On diligence material its limits are stated here: what an AI due-diligence check covers, and what it does not. Its outputs are drafts for a licensed professional to review and sign. The lender's page is here, and finished examples are in the sample library.

16. Titleman, by the same scheme

• Fits: commercial property, one address at a time: the records, the documents and the analysis in one file, with the source beside each figure.
• Does not cover: it is not a loan origination system, not a property management system and not a tool for single-family rentals.
• Free plan or trial: not stated here.
• On the one point we could check. In favor: none. Against: no free plan or trial stated.
• Evidence: first-hand, because it is ours: the film on this page and the pages linked in this section.

What this page leaves out

Other lists of AI tools for real estate mix in software for different work, and a reader who came looking for it should know it is missing here on purpose. This page covers tools used to work a commercial real estate loan file, from the borrower's package to monitoring. It leaves out five kinds of software that other lists include: leasing assistants, property management and accounting systems, listing photography and virtual tour tools, consumer mortgage and home-loan tools, and deal pipeline platforms built for investment teams and not for credit teams. A lender may still meet those in a borrower's office; they are not what a credit team buys for itself.

How to choose: one loan file you already know

Ignore feature lists. Take one closed loan, or one you declined, where you know what the file turned out to hide, and run it through each tool you are considering. Remove what your policy requires you to remove first. Then ask six questions.

1. Did it find what your analyst found? The expense that was moved, the lease about to roll, the tax abatement about to end.
2. Do the documents tie, and does the tool say where they do not? A tool that only spreads has left the tie-out with you.
3. Does every figure name its page or cell? That is what a committee and an examiner ask for.
4. Whose income is the loan sized on? The borrower's, or one the tool derived and can explain.
5. What does it do when a document is missing or unreadable? Saying so is the right answer.
6. How long until the first usable output, counting setup and approvals?

Then ask where the output goes. A finding that has to be retyped into the system of record will be retyped wrongly sooner or later.

What none of them replace

A licensed appraisal where regulation or policy requires one. A title search and the policy behind it. Environmental and engineering reports. Legal review of the loan documents. Your credit policy, and the judgment of the people who sign the approval, which is the thing every tool on this page exists to serve.

For the borrower's side of the same documents, see 15 real estate underwriting software tools in 2026, by the job they do, and for the wider field, 20 AI tools for commercial real estate in 2026. For the equity side of the same deal, see 18 AI tools for real estate investors in 2026, by the job they do.

Frequently asked questions

What are the best AI tools for commercial real estate lenders in 2026?

There is no single best tool, because lenders buy for seven different jobs: the loan origination system, AI underwriting platforms for CRE loans, document reading, lease abstraction, loan and market data, general drafting, and tying out one borrower's file. A lender usually already owns the first. Decide which step is slowest, compare tools inside that row only, and test each on a loan file you already know.

Can AI underwrite a commercial real estate loan?

AI can read the package, spread the figures, check the documents against each other and size the loan against the tests you set. It should not make the credit decision, and any figure it produces without a named page or cell should be treated as unverified. The approval stays with the people your policy names.

What is the best software for rent roll analysis?

The one that ties the rent roll to the operating statement for the same month and shows you where they differ. Extraction speed matters less than that tie. Test with a messy rent roll, with concessions, vacant units and a lease that started mid-month, and count the corrections a person has to make.

What is the best lease abstraction software?

It depends on the deadline. Products built for portfolio administration keep every field of every lease current. For a closing, a short list of fields matters: expiry, options, termination rights, recoveries and anything that moves the income. Whatever you use, each field should link to the clause it came from.

How do lenders find commercial loans that are maturing?

For securitized loans, from the loan data that several data providers assemble. For loans held on a bank's own balance sheet, loan-level data of that kind is not available to outsiders. Read the labels with care: a loan in workout is not necessarily unable to pay.

Does AI due diligence replace an appraisal or a title search?

No. It assembles what the records and the documents show and names what is missing. A licensed appraisal, a title search and policy, and environmental and engineering reports remain separate work by licensed professionals.

Where does Titleman fit for a lender?

Titleman's lender check reads a borrower's offering memorandum, rent roll and T-12, ties them against each other, lists what does not tie with the page or the cell, and sizes the loan by debt coverage and debt yield at two rates. It is not a loan origination system or a data subscription, and it does not make the credit decision.

Can AI read scanned loan documents, PDFs and spreadsheets?

The tools in section 3 are built for documents: PRODA describes turning a rent roll or an operating statement into standardized data, and Ocrolus describes automating the analysis of financial documents. What their pages cannot tell you is how they do on your documents. Test with a scanned rent roll and an operating statement from a closed loan, and count the cells you had to correct.

Do lenders need CRE-specific tools, or is a general assistant enough?

A general assistant can draft and summarize from the files you give it. It has no loan data, no property records and no credit policy of its own. A CRE lending tool is built around the documents and the calculations of a loan file. The test is the same for both: give it a closed file and see whether the debt service coverage and the findings match what your credit team concluded.

Does a lender need one AI platform or several tools?

The seven sections of this page are seven jobs, and each tool is described by its maker for one of them. A loan origination system holds the file and the workflow, document tools feed it, and data services sit beside it. Start from the job that holds up your credit memo and add from there.

What does AI change in commercial loan underwriting?

It moves the first pass. Software reads the rent roll and the statements, spreads them, compares them with each other and with what the borrower claims, and lists what does not tie. The credit decision, the policy exceptions and the signature stay with people. How much time that saves depends on your files and has to be measured on them.

Sources

Each company below is quoted on this page in the words of its own site; the lines on fit, coverage, and points for and against are our reading of those words. Pages read on 11 October 2026.

• Blooma: www.blooma.ai
• PRODA: www.proda.ai
• V7 Go: www.v7labs.com/go
• Prophia: www.prophia.com
• Propaya: www.propaya.com
• Trepp: www.trepp.com
• Clik.ai: www.clik.ai
• Rockport: www.rockportval.com
• Baker Hill: www.bakerhill.com
• Abrigo: www.abrigo.com
• Ocrolus: www.ocrolus.com
• CRED iQ: cred-iq.com