About
Built to make Canadian urban ecology decisions better.
Rangifer is a Canadian urban-ecology intelligence platform. It started from a question — what if every city's tree data was enriched, normalized, and accessible in one place? — and grew into infrastructure for consultants, planners, developers, and AI agents who need ecological data they can trust.
The data
2.49 million trees across six Canadian cities — Montreal, Toronto, Vancouver, Calgary, Edmonton, and Winnipeg — enriched with carbon sequestration, ecosystem-service valuations, native/invasive classification, and biodiversity metrics. Layered with heat islands, flood risk, air quality, equity, pollinators, and more.
The approach
The raw data is public. The value is in the enrichment, the normalization, the cross-city coverage, and the ability to turn a polygon into a citable assessment. Rangifer follows the questions wherever they lead — any environmental data that deepens understanding or enables better diagnosis is in scope.
Who it's for
Environmental consulting firms doing impact assessments. Municipal governments wanting cross-city canopy analytics. Real estate developers and insurers pricing environmental risk. Developers and AI agents querying ecological data programmatically via API or MCP.
How it's built
Rangifer is built by a solo founder working with AI agents — no traditional team, no venture funding, no premature abstraction. The stack is Rust + PostGIS for the API and database, Cloudflare Workers for billing and gateway infrastructure, Next.js for the frontend, and an MCP server for AI-agent access. Everything runs as cheaply as possible until revenue justifies scaling.