This is like a citywide “control tower” that uses maps and AI to show where problems are happening or likely to happen—traffic crashes, unsafe intersections, risky neighborhoods—so public agencies can fix them faster and plan better.
Helps public-sector and transportation agencies turn messy location data (traffic, incidents, sensors, 911, demographic data) into clear, map-based intelligence for improving public safety, mobility, and infrastructure planning, reducing manual analysis and slow decision cycles.
Domain-specific geospatial datasets and models tuned for public-sector mobility and safety use cases, plus integration into agency workflows and reporting requirements (e.g., transportation planning, capital projects, grant reporting).
Hybrid
Vector Search
Medium (Integration logic)
Geospatial data volume and update frequency (large, constantly changing map and sensor data), which can stress storage, query performance, and AI inference costs at city or state scale.
Early Majority
Focuses on public-sector safety, mobility, and planning workflows rather than being a general-purpose GIS; likely offers opinionated dashboards, KPIs, and AI analytics tailored to DOTs, MPOs, and city agencies rather than just raw mapping tools.