GeoStats is a TAGS product — designed, built and owned in-house. Visit geostats.ai · See all TAGS products.
We built GeoStats, our own geo-intelligence and urban analytics platform, which layers population, income, mobility and real-estate data onto a single interactive map — covering an entire metropolitan region — with an AI insight engine that turns raw data into location-specific recommendations.
Planners, developers and investors now query an entire city's worth of data from one interface, replacing weeks of manual cross-referencing.
Urban planners, real-estate developers and investors working across a major metropolitan region had to manually cross-reference four distinct datasets — each maintained by a different authority, in a different format, on a different system — before they could make a single location decision.
That cross-referencing took weeks per analysis. Insights were stale by the time the work was done, and there was no way to query across all four dimensions simultaneously.
Population, income, mobility and real-estate transaction data layered onto interactive maps with full drill-down capability — from metropolitan region to individual neighborhood.
An AI engine translates the raw data layers into location-specific recommendations for planning decisions, investment analysis and development feasibility — going beyond visualization to actionable insight.
Comprehensive data coverage across an entire metropolitan region — every district, zone and neighborhood represented in the platform without gaps.
A map-first interface where planners and investors explore data spatially — filtering by metric, comparing zones and generating reports directly from the map view.
Population · Income · Mobility · Real Estate
All four data dimensions queryable simultaneously from a single map interface.
Replacing Manual Cross-Referencing
Weeks of data assembly replaced by on-demand, AI-powered location intelligence.
Coverage
Every district and neighborhood in the metropolitan region represented — no gaps, no partial data.