Use AI to speed up multifamily deal research

A multifamily broker uses AI to gather comps, draft property writeups, and flag missing details before outreach and early diligence.

Done with Custom agent· Intermediate

What they did
The broker used a custom or unnamed agent as a research helper before they contacted owners and while they were still checking a deal. They had it collect market context, sort rent and sales comparables, draft first-pass property summaries, and search for details that were spread across different sources. They treated the output as a starting point and kept the actual judgment work for themselves.
How it went
The main benefit was faster preparation for deal review and marketing materials. They said the approach was not reliable enough for valuation or other subtle brokerage work, and it should not handle pricing calls or relationship management.
Tips
This works best if you already understand the market and can spot weak or misleading outputs. Use it for synthesis and early research, then verify anything that affects price, strategy, or the client relationship.

Try it yourself with Manus

I’m reviewing a multifamily property at [address] in [market]. Gather recent sales and rent comparables, summarize the key trends in [submarket], and draft a short property overview that includes the unit mix and any obvious gaps in the information. For every figure, show the source you used. Then list the missing items I should confirm with the owner. Pause and ask for my approval before you do anything that would send, submit, or share information externally.

Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.

Read the original on reddit.com ↗

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