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CRE operators, AI builders & research teams—let’s connect.
I spent 30 years in industrial commercial real estate. Started with a desk, a phone & 200 dials a day.
Now I’m turning that experience into datasets and evaluations grounded in how deals actually work: site selection, underwriting, industrial facilities & cold chain logistics.
Looking for collaborators who know the problems AI still struggles to solve.
What would you test against 30 years in the trenches?
DM me. Let’s build. 🐝
The hive is filling up. 🐝
Want a model that actually speaks CRE?
DM me. Let's cook. 🐂
#ColdChainOS
Ask a general AI to underwrite a last-mile hub.
It doesn't know zoning, dock counts, or curb access.
Operators do.
#ColdChainOS
Last mile.
The most complex mile in the real economy.
Every package. Every door. Every day.
#ColdChainOS
Define the task.
Curate the data.
Test the painful exceptions.
That's how you build a CRE model you can trust.
#ColdChainOS
5 major proteins riding the cold chain 🧊
🥩 Beef
🐔 Poultry
🐖 Pork
🐟 Seafood
🥚 Eggs
Farm → processor → cold storage → truck → your plate.
When the power stops, the clock starts.
Who’s underwriting that risk?
#ColdChainOS
How we build, step 1:
Start with the questions operators actually ask.
Not the ones that are easy to scrape. #coldchain
Power out at a cold storage site.
Three questions:
How long is the backup good for?
Who gets the call?
What gets thrown out?
Blackout hits. Now what’s your cold chain?
How long can you hold temperature?
Does backup power carry the full load?
Who gets the alert?
Who makes the call?
The inventory is real. The clock is running.
Underwrite the outage before it happens.
ColdchainOS ❄️⚡



