Urban Insight Group applies AI, spatial analytics, and digital twin thinking to urban planning — helping cities and technology companies navigate development policy, governance, and the built environment challenges created by rapid technological change.
Spatial modeling, regression analysis, and demographic mapping that reveal what conventional analysis misses.
Development agreement analysis, community benefit negotiation, and public-private partnership strategy.
AI governance, digital twin simulation, algorithmic impact assessment, and smart city strategy for planning agencies.
Last-mile delivery analysis, transit corridor planning, and autonomous vehicle infrastructure policy.
Nvidia's Omniverse Blueprint lets cities build physically accurate digital replicas at urban scale. For planners, the implications go far beyond better 3D models.
New data from 42 North American transit agencies reveals persistent gaps in service quality between low-income neighborhoods and wealthier areas — and points to practical remedies.
Upzoning for duplexes, triplexes, and courtyard housing is not radical — it is a return to the building types that made American neighborhoods walkable for generations.
Development agreement analysis for San Jose’s largest mixed-use proposal — 15,000 homes, 7.3M sq ft of office space, and a public benefit framework worth over $200M.
Spatial lag regression and LISA cluster analysis to identify undervalued residential zones in Santa Cruz County — a replicable framework for California housing markets.
Research on how algorithmic decision-support tools reshape urban planning — from zoning automation to autonomous systems that challenge the scope of governance itself.
Whether it's a development agreement for a campus-scale project, a spatial model that reveals hidden market patterns, or a policy framework for AI in urban systems — we bring analytical rigor and planning expertise to the table.