Specialist · Fort Lauderdale · Member since 2025 · 17 posts · 7 votes
If you’re underwriting SFRs, multifamily, or reviewing deals at volume, you should be thinking about how AI and data tools can support your process.
You don’t need to be technical. You don’t need full automation. But if you’re still pulling rent comps manually, copying numbers into spreadsheets, and trying to underwrite dozens of deals a week you are wasting time.
Here’s where AI and simple systems can help:
Surface listings with below-market rents or pricing gaps
Automate comp pulls and underwriting templates
Flag risk factors and patterns that are easy to miss manually
Stay consistent across markets
Sharpen your market research
The goal isn’t to replace your judgment. It’s to free up your time so you can focus on what actually matters.
Start small. Build a system that works for how you think. And if you want any free advice, I’m happy to answer questions or talk through how I approach it.
If you’re underwriting SFRs, multifamily, or reviewing deals at volume, you should be thinking about how AI and data tools can support your process.
You don’t need to be technical. You don’t need full automation. But if you’re still pulling rent comps manually, copying numbers into spreadsheets, and trying to underwrite dozens of deals a week you are wasting time.
Here’s where AI and simple systems can help:
Surface listings with below-market rents or pricing gaps
Automate comp pulls and underwriting templates
Flag risk factors and patterns that are easy to miss manually
Stay consistent across markets
Sharpen your market research
The goal isn’t to replace your judgment. It’s to free up your time so you can focus on what actually matters.
Start small. Build a system that works for how you think. And if you want any free advice, I’m happy to answer questions or talk through how I approach it.
Hey @Brett Ponters, welcome to the BP Forum! How are you accomplishing what you mention in your post? What system have you built?
If you’re underwriting SFRs, multifamily, or reviewing deals at volume, you should be thinking about how AI and data tools can support your process.
You don’t need to be technical. You don’t need full automation. But if you’re still pulling rent comps manually, copying numbers into spreadsheets, and trying to underwrite dozens of deals a week you are wasting time.
Here’s where AI and simple systems can help:
Surface listings with below-market rents or pricing gaps
Automate comp pulls and underwriting templates
Flag risk factors and patterns that are easy to miss manually
Stay consistent across markets
Sharpen your market research
The goal isn’t to replace your judgment. It’s to free up your time so you can focus on what actually matters.
Start small. Build a system that works for how you think. And if you want any free advice, I’m happy to answer questions or talk through how I approach it.
Hey @Brett Ponters, welcome to the BP Forum! How are you accomplishing what you mention in your post? What system have you built?
For starters, I was sourcing majorly undervalued MF deals in the South Florida Market through regression (Predictive Models). I did this using the CSV file exported from my MLS. This allowed me to essentially predict a properties rent using different parameters or variables (Sqft, bedrooms, etc). Then filter by cap rate and cashflow and how well it would preform as a house hack, etc.
I've also built multiple of other tools like one I'm working on right now an AI Chatbot that has access to different real estate databases through MCP's (Model Context Protocol) and is pretty much an investment super assistant.
This is just the tip on how machine learning and data WILL supercharge real estate.
Please reach out again if you have any questions or want to learn more! Cause there is a lot more...
For starters, I was sourcing majorly undervalued MF deals in the South Florida Market through regression (Predictive Models). I did this using the CSV file exported from my MLS. This allowed me to essentially predict a properties rent using different parameters or variables (Sqft, bedrooms, etc). Then filter by cap rate and cashflow and how well it would preform as a house hack, etc.
I've also built multiple of other tools like one I'm working on right now an AI Chatbot that has access to different real estate databases through MCP's (Model Context Protocol) and is pretty much an investment super assistant.
This is just the tip on how machine learning and data WILL supercharge real estate.
Please reach out again if you have any questions or want to learn more! Cause there is a lot more...
@Brett Ponters So, you're serving up potential value add-MF properties (or whatever the user selects for the filter criteria) to prospective buyers/investors to reduce the amount of time they have to devote to finding them on their own?
@Jaycee Greene Essentially, it pretty much would underwrite 1000 properties in about 10 seconds and allow me to filter out all the bad and only see the few hidden gems at a time
@Jaycee Greene Essentially, it pretty much would underwrite 1000 properties in about 10 seconds and allow me to filter out all the bad and only see the few hidden gems at a time
@Brett Ponters I get that...and then what? Does it draft an offer to the seller and secure financing? ;-)
Super cool. There is so much you can do with the amount of data AI can collect, process and analyze. There's no doubt a program could be built to do literally everything automatically like clockwork