Use Claude to screen real estate deals and tenants
Investors used Claude and ChatGPT to pre-screen deals, compare comps, and check tenant and rent details before doing manual underwriting.
- What they did
- They handed Claude or ChatGPT deal packages, rent rolls, comps, and other gathered facts, then asked it to organize the numbers, find similar properties, estimate basic metrics, and summarize terms. One investor also used ChatGPT to dig into deal information, tenant details, and nearby rental rates before checking the numbers themselves.
- How it went
- People said it saved hours and made early screening much faster, often getting them most of the way to a rough yes-or-no. The downside was that the models could sound certain while being wrong, so the thread treated them as a filter, not the final underwriting step.
- Tips
- Use it with a spreadsheet or other checked data source, and verify every assumption yourself. Treat any answer that affects pricing, financing, or a purchase decision as a draft until you confirm it.
Try it yourself with Claude
Iโm reviewing [number] incoming real estate deals. For each one, read the deal sheet and any comps, rent roll, or market notes I paste in. Pull out the key facts, compare them against [my screening rules], and sort the deals into pass, maybe, or reject with a short reason. Also list any tenant or local rent questions I should verify next. Stop and ask for my approval before you do anything that would be irreversible, like sending the analysis to someone, deleting any input, or submitting a decision.
Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.
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