COMMERCIAL REAL ESTATE · ASSET INTELLIGENCE
Automate deal origination, underwriting and asset operations in commercial real estate
A parcel shows distress in a court filing months before it reaches a broker. A pro forma claims a NOI the trailing statements do not support. OutcomeCatalyst reads the filings, the comps, the T-12 and the leases, so you find deals early and underwrite them against the record instead of the marketing.
Asset intelligence, in plain terms
A deal arrives as an offering memorandum, a rent roll PDF and a T-12 scan. The numbers that decide whether it works are inside those documents, and so are the numbers that prove the marketing wrong. Asset intelligence reads them, tests every assumption against the record, and finds parcels before a broker has them.
From a PDF to an underwriting, in four steps
Your model stays your model. This tests the inputs before they reach it.
Why this matters in commercial real estate
Deal flow in commercial real estate is adverse-selected by structure. Anything a broker markets is seen by every buyer in the market simultaneously, so the price already reflects the best-informed bid. The only durable edge is finding the asset earlier, which means reading signals in public records rather than waiting for an offering.
Those signals exist and are public. Lis pendens filings, deed history, mortgage maturities, permit activity and tenure all indicate an owner approaching a transaction. They are just distributed across county systems and court dockets in formats nobody reads at scale, which is why they stay a genuine edge.
Underwriting has a different asymmetry. The broker's pro forma is a marketing document and always works, because the assumptions were chosen so that it would. The information needed to disprove it is usually in the package the broker themselves provided, sitting in a T-12 scan that supports different numbers than the summary page.
On the operating side, lease exposure is knowable years ahead and still routinely handled reactively. Expiries, escalation structures and option windows are all written into documents you already hold. The difference between repricing a lease on your timeline and discovering it at renewal is the difference between a decision and a scramble.
Built for the stack a CRE firm actually runs
These are the systems referenced in the workflow above. County and court sources vary by jurisdiction and are handled per market.
Questions investment and asset teams ask first
Does this replace ARGUS?
No. ARGUS models the assumptions you give it, and it does that well. The problem is upstream: whether those assumptions match the record. This tests each input against comps, trailing statements and public records before it reaches your model.
How reliable is extraction from a scanned T-12?
Extraction confidence is scored per line item, and anything low-confidence is surfaced for human confirmation rather than used silently. Every figure links back to the page it came from, so an analyst can verify in seconds rather than re-keying.
Are county and court records really usable at scale?
They vary considerably by jurisdiction, which is exactly why they remain an edge. Coverage is built market by market, and the honest answer is that some counties are straightforward and others require more work. We are explicit about which markets are covered before you rely on it.
How is this different from CoStar or a data subscription?
A data subscription gives you the same information every competitor has, which by definition cannot be an advantage. The edge is joining that market data to public records and to the specific documents in your own deal package.
Does this make investment decisions?
No. It produces a tested underwriting and a drafted memo with sources attached. The investment committee decides. Every variance is traceable to a comp, a statement line or a filing so the reasoning can be challenged.
We are a small team. Is this only for large platforms?
Small teams tend to benefit most, because the constraint is analyst hours rather than capital. Reading every T-12 and every lease is what a small team cannot do at volume, and it is exactly what this removes.
How long does implementation take?
Most engagements are live on a first workflow in four to six weeks. Underwriting variance is the usual starting point because you can test it immediately against a deal you have already underwritten by hand.
What about assets we already own?
That is the lease exposure workflow. Every lease in the portfolio is read for expiry, escalation, option and recovery terms, so you can see which assets are below market and renewing inside a window where you can still act.
AI asset intelligence for commercial real estate: common questions
What is asset intelligence?
It is one system that scores every parcel in your markets on signal and fit, tests each assumption in a broker pro forma against actual comps and trailing statements, reads leases down to the clauses that move NOI, and shows what expires before you can react.
Where does the data come from?
From what a firm already runs. CoStar and CompStak carry comps, county records carry ownership and liens, court dockets carry distress. The broker OM and the T-12 carry the deal itself. Yardi carries what the asset actually does and ARGUS carries your model.
How is this different from ARGUS?
ARGUS models the assumptions you give it. It cannot tell you the market rent in the OM is 8.6% above what comparable leases actually signed at, because that lives in comps and a T-12 scan. This tests every assumption against a source before it reaches your model.
