Published by Titleman, which makes one of the tools described below. We have tried to write the page we wanted when we were choosing, which means naming the categories where we are not the answer.
Most "top AI tools" lists rank products that do different jobs, which is why they are hard to act on. CRE teams buy for five jobs, and the useful first question is which one is costing you the most hours.
1. Market And Comparable Data
The subscriptions that answer what traded, at what price, and what is leasing.
Established names: CoStar, CompStak, Reonomy, Crexi, Cherre. This is the oldest category and the one with the deepest coverage, and it is usually the largest line in a CRE software budget.
What to check: how current the lease comps are in your markets rather than nationally, whether a figure is a recorded transaction or an asking price, and what the contract does at renewal.
Where it stops: a data subscription tells you what happened. It does not tell you what this property is worth or whether the deal works.
2. Underwriting And Modelling
Turning a rent roll, an offering memorandum and a set of assumptions into a cash flow and a value.
ARGUS Enterprise (Altus Group) remains the standard for lease-by-lease discounted cash flow on institutional assets, and for counterparties who expect a recognised model format there is no real substitute. Newer entrants — Blooma for lender-side underwriting, Enodo and Proda AI for rent roll standardisation and predictive inputs — automate parts of the work around it.
What to check: whether the tool produces something a lender or an investment committee will accept as-is, and how long a new analyst takes to become useful in it. Ramp-up is usually the larger cost.
Where it stops: modelling suites assume the inputs are already assembled and trustworthy. Establishing the parcel, the zoning and a defensible comparable set happens before any of them open.
3. Lease Abstraction And Document Review
Reading leases, contracts and title documents and turning them into structured fields.
Prophia, Propaya and the abstraction services inside the property-management platforms lead here. This is the category where AI has changed the economics most clearly, because the work was previously outsourced by the page.
What to check: accuracy on your leases, not a benchmark — ask for a test on three of your own, including one badly scanned. Ask what happens on an ambiguous clause: a tool that silently picks an interpretation is worse than one that flags it.
Where it stops: an abstract is not a legal opinion, and the clauses that matter most are usually the ones a model finds hardest.
4. Deal Sourcing And Owner Research
Finding assets before they are marketed, and resolving who actually owns them through the entity.
Data platforms cover part of this; Dealpath covers the pipeline side. Owner resolution through LLCs is the part that stays stubbornly manual, and the tools that claim it should be tested on entities you already know.
What to check: whether the ownership chain is evidenced from public records you can look up, or asserted. An unverifiable owner record is a wrong phone call at best.
Where it stops: sourcing produces a list. Everything that decides whether the list is worth anything is the next two jobs.
5. Diligence On One Specific Site
Parcel and boundary, zoning and overlays, utilities, environmental exposure — assembled for a property you are actually considering.
This is the least consolidated category and the most fragmented: county records, zoning codes, flood maps and permit systems, each in its own format. It is also where Titleman works. We assemble the property record from public sources, gather and name comparables, read the documents, and produce underwriting, a value opinion or a deal screen with every figure traceable to the source it came from — and where the evidence is thin we say so rather than producing a confident number.
We are not a replacement for a data subscription, and we are not a replacement for institutional lease-by-lease modelling. We say that here because it is the first thing a buyer in this category needs to know.
How To Actually Choose
Ignore feature lists. Run one property you already know the answer to through any tool you are considering, and compare:
- Does every figure name where it came from?
- Is the comparable set auditable — can you look each one up, and is any of them a listing that never traded, or the subject property itself?
- How long until the first usable output, counting setup?
- What does it do when the data is thin?
- Can a licensed professional review and sign the output, or does it need rebuilding first?
What None Of Them Replace
A licensed appraisal where a lender or standard requires one. A title search and the policy behind it. Legal, environmental and engineering diligence. And the judgement of the person who signs the conclusion — which is the thing every tool on this page exists to serve, not to substitute.