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Data & AI
Community Data Insights Program
Combines public collision history with community observation and AI-assisted analysis to produce grant-ready evidence.
This is CRSIF's core data engine — the program that turns scattered local observation into the risk bands, dashboards and briefs every other CRSIF initiative relies on.
From signal to evidence
Public collision history is combined with community and youth-program observation, then run through the Observe → Enrich → Analyze → Act → Measure model.
Human-reviewed, always
AI-assisted analysis surfaces patterns and confidence indicators, but every output is checked by a person before it reaches a partner.
Built to be used
Deliverables are grant-ready and decision-ready — one-page briefs, dashboards, and risk maps designed for non-technical audiences.
Key Points
- The prevention model behind every CRSIF program
- Aggregated, location-based reporting — never individual driver identification
- Outputs are designed for funding and council-ready decisions