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AI is only as powerful as the data foundation it learns from, and in the built environment that foundation is broken. Today, zoning bylaws, permitting rules, environmental overlays, and valuation inputs all live in disconnected silos, making it nearly impossible to generate reliable, scalable intelligence. At a time when construction and housing systems are under immense pressure, this fragmentation is one of the sector’s biggest bottlenecks.
This presentation explores how an Intelligence API for the built environment can transform messy, incompatible datasets into structured, machine readable intelligence. Attendees will learn how such an approach enables both humans and AI systems to make faster, more transparent, and more coordinated decisions, accelerating project feasibility analysis, reducing permitting friction, and creating the conditions for more scalable housing and infrastructure delivery.
Arash Shahi is an entrepreneur and innovator at the intersection of real estate, technology, and the built environment. He is the CEO and Co-Founder of LandLogic, where he leads efforts to transform fragmented property and land data into decision-ready intelligence. Named one of the Top 40 Under 40 in Canadian Construction, Arash also serves as Managing Partner of the AECO Venture Fund and CEO of AECO Innovation Lab, an incubator dedicated to modernizing the built environment through research and cross-sector collaboration. His work bridges policy, practice, and technology to advance responsible AI adoption across the sector.
AI is only as powerful as the data foundation it learns from, and in the built environment that foundation is broken. Today, zoning bylaws, permitting rules, environmental overlays, and valuation inputs all live in disconnected silos, making it nearly impossible to generate reliable, scalable intelligence. At a time when construction and housing systems are under immense pressure, this fragmentation is one of the sector’s biggest bottlenecks.
This presentation explores how an Intelligence API for the built environment can transform messy, incompatible datasets into structured, machine readable intelligence. Attendees will learn how such an approach enables both humans and AI systems to make faster, more transparent, and more coordinated decisions, accelerating project feasibility analysis, reducing permitting friction, and creating the conditions for more scalable housing and infrastructure delivery.
