Data, analytics, and AI decision support.
The initiative uses open data, public-sector datasets, geospatial analysis, and AI-assisted scenario modeling to support better transportation decisions.
Data Integration
Connect transportation, housing, workforce, and demographic datasets across agencies.
GIS Mapping
Visualize mobility access, transit coverage, and affordability burden geographically.
Predictive Analytics
Forecast which communities are trending toward affordability stress.
Scenario Simulation
Model investment alternatives and policy changes before they're adopted.
AI Policy Assistant
A conversational interface to interrogate complex transportation and affordability data.
Executive Dashboards
Decision-ready views for agency leaders and elected officials.
Data Governance Assessment
Evaluate readiness and define standards for cross-agency data sharing.
Cross-Agency Data Model
A reusable schema for transportation-led affordability analysis.
Benchmarking Reports
Comparative analysis across Virginia localities and peer states.
AI is not a replacement for transportation planners or public officials. It is a decision-support capability that helps leaders explore scenarios, compare alternatives, and identify trade-offs more efficiently.
All AI tooling is built on vendor-neutral, governed data foundations — designed for transparency, auditability, and public accountability.