AI Transit-Oriented Development
The Problem
“TOD deal teams lose weeks to fragmented data—while the best transit sites get taken”
Organizations face these key challenges:
Analysts spend days merging GIS, zoning, transit, comps, and financials into brittle spreadsheets
Deal screening is inconsistent: different teams reach different conclusions from the same inputs
Entitlement and zoning constraints are missed until late, blowing up timelines and budgets
Opportunities are found too late because market/tranist signals aren’t monitored continuously
Impact When Solved
Real-World Use Cases
AI for Finding High-Potential Real Estate Investments
It’s like giving every real-estate investor their own tireless analyst that quietly scans thousands of properties and markets in the background, then taps you on the shoulder when it finds deals that match your strategy and are likely underpriced or high-potential.
Transforming Commercial Real Estate Through Artificial Intelligence
This is about using AI as a super-analyst and super-assistant for commercial real estate: it scans market data, building information, and financials much faster than people can, then suggests better deals, pricing, layouts, and operations decisions for offices, retail, and industrial properties.