Modern AI Underwriting for Land Deals
A demonstrator walks through a custom AI-powered land underwriting tool that pulls property data from multiple APIs and open-source sources in real time. The tool analyzes road frontage, comps, flood zones, soil permeability, and automatically subdivides parcels into lots with projected financials. The presenter argues this level of deal analysis — including skip tracing — is accessible and relatively easy to build.
Summary
The presenter gives a live walkthrough of a custom-built land underwriting tool triggered by dropping a pin in Google Maps on an Oklahoma property. By inputting coordinates, the tool automatically pulls data from multiple sources, including owner information, last deed of sale, road frontage, and comparable sales. In this case, 14 comps were found, giving the presenter insight into sell-through rates for 20-, 2-, and 80-acre lots in the area.
The tool also overlays infrastructure and environmental data, including a 10-inch water main, FEMA flood zones, electric lines, oil and gas infrastructure, and wetlands data — all sourced from free, open-source datasets. The presenter highlights a custom 'perk score' feature that evaluates soil permeability based on soil type to estimate whether a parcel would pass a percolation test, which is critical for septic system viability.
Using AI, the presenter traces the parcel boundary and asks the tool to automatically subdivide the land into the maximum number of lots given a minimum lot size of 30 acres. The tool generates a subdivision layout and then produces a financial projection: given a hypothetical purchase price of $600,000 and selling 11-acre lots, the tool estimates a potential net of $5 million — though the presenter acknowledges this figure is likely off and the realistic purchase price would be closer to $1.2 million.
Finally, the tool can generate a full due diligence report — including risk factors, data sourcing, and a breakdown suitable for sharing with a broker or surveyor. It also integrates skip tracing to surface the property owner's name and phone number, making outreach immediately actionable.
Key Insights
- The presenter claims the tool pulls owner info, last deed of sale, road frontage, and comparable sales automatically just from dropping a pin in Google Maps and inputting coordinates — requiring no manual data lookup.
- The presenter built a custom 'perk score' that evaluates soil permeability by soil type to predict whether a parcel would pass a percolation test, which he describes as a unique feature of his tool.
- The AI subdivision feature automatically cuts a traced parcel into the maximum number of lots given a user-defined minimum lot size, generating a visual layout without manual planning input.
- The presenter acknowledges the AI financial projection — estimating a $5 million net on a $600,000 purchase — is likely significantly off, and that the realistic acquisition price for that deal would be closer to $1.2 million.
- The tool can export a full deal report including risk factors, data sourcing citations, and skip-traced owner contact information, making it usable as a deliverable for brokers or surveyors.
Topics
Transcript
[0:01] All right, guys. Quick walk through. I don't think people are realizing how crazy it is all these APIs and access what kind of enrichment you can do. So, let me give you guys an example. Like, you could be just going around. This is in Oklahoma uh in uh Google Maps. And you can come over here and just grab a pin. And then, uh I created a tool here where I can load whatever in, and it's going to pull from a few different sources, but I'm just going to do it by coordinates. plug that in and pull that up really quick. [0:32] And it's actually gone ahead and pulled that in. It's looked for road…
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