Your closed deals, rebuilt as one data layer.Every number opens its receipt.
Nobody sent us a spreadsheet. This page was built this morning from your public closed-deal pages, used as a proxy data source until we connect your real systems: 43 deal cards across three pages, reduced to 21 distinct deals, every figure recomputed twice by two independent programs, and every row able to show the exact card it came from.
The same page can tell you $172.9M or $89.1M.
Your public deal pages present 43 cards across three pages. 22 of them are the same deals listed again. A pipeline that reads the pages as presented books nearly twice the volume, and the total looks perfectly reasonable, which is exactly why nobody catches it.
Counted once per record behind each card, the answer is 21 distinct deals worth $89.13M. That is the number every chart on this page is built on.
Pick any figure. It will show you its formula, the rows it used, the rows it refused, and the card each row came from.
This is what "accurate data one hundred percent of the time" has to mean in practice. Not a promise that nothing is ever wrong, but a number that can always be walked back to the page it was read from, in front of whoever is asking.
Average cap rate
7.92%Starbucks - Michigan shows a Net Operating Income label with no value, so it is excluded rather than treated as zero.
| Deal | Price | NOI | Cap | Seen on | Receipt |
|---|---|---|---|---|---|
Office - Missouri Triple Net | $10,450,000 | $737,752 | 7.06% | properties page 2, card 2 | |
Industrial - Minnesota Absolute NNN | $8,190,000 | $640,000 | 7.81% | properties page 1, card 18properties page 2, card 3properties page 3, card 9 | |
Gas Station - Texas Absolute NNN | $7,500,000 | $609,000 | 8.12% | properties page 1, card 2 | |
Medical Office - Texas Absolute NNN | $6,900,000 | $568,736 | 8.24% | properties page 1, card 3 | |
Medical Sciences - WI Absolute NNN | $5,400,000 | $373,000 | 6.91% | properties page 1, card 19properties page 2, card 1properties page 3, card 10 | |
Industrial - Ohio Absolute NNN | $5,300,000 | $425,000 | 8.02% | properties page 1, card 16properties page 2, card 6properties page 3, card 7 | |
Retail - Wisconsin Triple Net | $4,349,000 | $312,139 | 7.18% | properties page 1, card 8 | |
Industrial - South Dakota Absolute NNN | $4,100,000 | $295,436 | 7.21% | properties page 1, card 6properties page 2, card 13properties page 3, card 11 | |
Retail Plaza - Indiana Triple Net | $3,865,000 | $302,148 | 7.82% | properties page 1, card 9 | |
Retail - Indiana Triple Net | $3,825,000 | $282,870 | 7.40% | properties page 1, card 7 | |
Medical Office - Arizona Absolute NNN | $3,387,000 | $270,896 | 8.00% | properties page 1, card 1 | |
Medical Clinic - Texas Absolute NNN | $3,270,000 | $280,000 | 8.56% | properties page 1, card 10properties page 2, card 10properties page 3, card 3 | |
Industrial - Ohio Absolute NNN | $3,250,000 | $253,836 | 7.81% | properties page 1, card 12properties page 2, card 12properties page 3, card 1 | |
Medical Clinic - Tennessee Absolute NNN | $3,175,000 | $256,080 | 8.07% | properties page 1, card 14properties page 2, card 8properties page 3, card 5 | |
Gas Station - Ohio Absolute NNN | $3,150,000 | $252,660 | 8.02% | properties page 1, card 5 | |
Industrial - Iowa Absolute NNN | $2,900,000 | $235,580 | 8.12% | properties page 1, card 17properties page 2, card 5properties page 3, card 8 | |
Industrial - Pennsylvania Absolute NNN | $2,200,000 | $177,010 | 8.05% | properties page 1, card 15properties page 2, card 7properties page 3, card 6 | |
Medical Clinic - Indiana Absolute NNN | $2,110,000 | $168,516 | 7.99% | properties page 1, card 13properties page 2, card 9properties page 3, card 4 | |
Industrial - Oklahoma Absolute NNN | $2,000,000 | $200,000 | 10.00% | properties page 1, card 11properties page 2, card 11properties page 3, card 2 | |
Retail - Louisiana Double Net | $1,155,000 | $92,400 | 8.00% | properties page 2, card 4 |
What we would check first if a dashboard showed a wrong number. It already ran.
Ten tests ran against this data before the page was written, and every one of them flagged something. 5 did so hard enough that a warehouse should hold the row back rather than publish it. Each keeps the name it will carry as a dbt test, next to what it means for whoever reads the dashboard.
A flag is not a verdict. Any of these rows may be a data entry gap or a perfectly valid business exception. The point is that the system isolates it for a human to decide, before it reaches a financial model, instead of averaging it in silently.
The three public deal pages present 43 cards, but only 21 of them are different deals. A count that trusts the page as presented reports 43 deals and $172.9M of volume, against $89.1M once each record is counted once.
- Industrial - South Dakotaappears 3 times: page 1, page 2, page 3
- Medical Sciences - WIappears 3 times: page 1, page 2, page 3
- Industrial - Minnesotaappears 3 times: page 1, page 2, page 3
- Industrial - Iowaappears 3 times: page 1, page 2, page 3
- Industrial - Ohioappears 3 times: page 1, page 2, page 3
- Industrial - Pennsylvaniaappears 3 times: page 1, page 2, page 3
- Medical Clinic - Tennesseeappears 3 times: page 1, page 2, page 3
- Medical Clinic - Indianaappears 3 times: page 1, page 2, page 3
- Industrial - Ohioappears 3 times: page 1, page 2, page 3
- Industrial - Oklahomaappears 3 times: page 1, page 2, page 3
- Medical Clinic - Texasappears 3 times: page 1, page 2, page 3
21 deals, $89.13M, a 7.79% blended cap rate.
Every chart below is drawn from the same 21 rows, counted once each, so nothing here can disagree with anything above it. That property is the entire point of a warehouse: one set of numbers, defined once.
Deal volume by asset family
Grouped on the words in the deal name, because four of the twenty one deals carry no asset class on the record. Grouping on the classification alone would drop $20.9M without saying so.
Deal volume by state
Fourteen states, none of them Florida. Wisconsin only counts once here because the same state is written two ways across the cards.
Cap rate on every deal that publishes an NOI
The shaded band is the six to nine percent range the rest of the book trades in. One deal sits outside it at exactly 10.00%, which may be an opportunistic buy or a keying error. One deal is absent from this chart entirely because its NOI is blank.
The Monday brief.
The dashboard is where people go when they already have a question. The brief is what arrives before they have one. Same numbers, same lineage, written in five lines by the same models that feed the charts, with the exceptions surfaced rather than buried.
This one is generated from the public pages, so it talks about the public book. On your own systems it talks about pipeline, credit, and the deals that moved last week.
- 01The public book stands at 21 distinct deals and $89.13M, at a 7.79% blended cap rate.
- 02Industrial is the largest family at 31.3% of volume across 7 deals, just ahead of medical at 27.2%.
- 03One deal prices at exactly 10.00% on a round $200,000 NOI. Both the yield and the roundness say check the rent roll before this row feeds anything.
- 04Starbucks - Michigan shows a purchase price with no NOI, so it sits outside every yield number on this page rather than quietly counting as zero.
- 05A listing marked Live sits among the closed deals, and one asset is Arizona on the card and Nevada in its address. Two records, one owner each, ten minutes.
From your systems to a number anyone in the firm can defend.
Built in two week slices, each with a fixed scope and something working at the end of it, whether we start from your existing warehouse or from scratch. Everything lands in your accounts under your credentials: the code, the warehouse, the models, the documentation. Nothing runs on our infrastructure and nothing is hostage to us being available.
Ingestion and the warehouse
- If a warehouse already exists, this slice audits and instruments it rather than replacing it: same tests, same lineage, on what you already run
- HubSpot, Monday.com, Microsoft 365 and QuickBooks landing in BigQuery on a schedule
- Raw layer kept immutable, so any number can be replayed as of any date
- One owner, one place, instead of a report per tool
Models and the test suite
- dbt models for deals, pipeline, investors and lending, documented in plain language
- The checks on this page, running on every build, blocking a bad load
- Definitions agreed once, so two teams stop reporting two truths
Dashboards per division
- One board per division, built on the same models, not on seven exports
- Every tile traceable back to its rows, the way the tiles above are
- Acquisitions, credit, asset management and marketing each see their own
Back into the tools, and alerts
- Reverse ETL writing the modelled fields back into HubSpot and Monday.com
- The Monday brief in the inboxes that need it
- Alerts when a check fires, before the number reaches a meeting
What we sell is the orchestration and the proof harness around it: the machine that keeps the numbers honest while it is being built, and a firm that owns the whole thing at the end. This page is a sample of the harness, produced in one morning from public pages alone.