Work / LandmAIn (founder)
LandmAIn: AI land intelligence for data center and energy site selection
An AI-powered land intelligence platform for data center, industrial, solar and storage site selection, with a dated, inspectable source behind every finding.
- 5
- representative sites screened on one evidence model
- 4
- public reports: briefing, atlas, profiles, deck
- 1
- interactive five-screen corridor explorer
The problem
AI data centers need land, power, fiber and permits in the same place, and the evidence for each lives in different systems: utility maps, county records, transportation data and policy documents. Early-stage investors and developers spend weeks assembling it, and comparisons between sites are rarely like for like.
What I built
I founded LandmAIn in 2026 to turn that scattered evidence into a disciplined, repeatable workflow for data center, industrial, solar and storage sites. It runs from regional search and shortlisting to parcel-level investigation (terrain, slope and infrastructure distances) to a reviewable site brief.
- One evidence model. Each opportunity is scored against the same criteria: transmission and substation proximity, highway access, fiber evidence, land characteristics and policy context.
- An evidence layer. Every finding ties to a dated, inspectable source, and items that still need utility or jurisdiction confirmation are flagged.
- Clear next steps. Map signals become specific diligence questions: utility capacity, carrier service, entitlement, water, buildable acreage and site control.
- Delivery formats people use. An interactive corridor explorer, a GIS map atlas, standardized opportunity profiles and an executive briefing deck.
The public demonstration runs as a fast static site on Cloudflare. LandmAIn also publishes market research on Colorado power and land-use policy, including Xcel Energy’s large-load tariff proceeding and Front Range data center permitting.
What it shows
LandmAIn is the kind of AI work I like best: a narrow, high-value question; messy public data; and an output that makes its evidence boundary explicit instead of overselling certainty. It also draws on my background as a US Army geospatial intelligence analyst and in GIS marketing. The same approach applies to research tools for marketing, healthcare and operations teams.
Explore LandmAIn or read about AI engineering services.