Choosing where to live
is a research problem
nobody hands you.
There is a whole industry helping you evaluate the house, and almost nobody helping you evaluate the place around it. The public record is out there, in a dozen formats across a dozen agencies, and no buyer has the weekends to assemble it. So we did.
Built from experience.
It started in 2018, out of a house search. Every platform we could find was organised around what was inside a property: bedrooms, bathrooms, square footage. The things that actually decided whether we would be happy there were all outside it, and none of them were on the listing.
A working prototype was recognized at an AWS-sponsored hackathon as a standout MVP. After user interviews, a full technology rebuild, and months of late nights, version 1.0 launched in October 2024 covering Calgary. Vancouver followed shortly after, Edmonton joined in 2025, and Toronto came online in 2026.
Today it is a decision companion rather than a database with a search box: it asks what matters to you, ranks the city against that, and shows you the reasoning and the trade-offs rather than a verdict.
What we hold to.
Four rules, in this order. They are why the product behaves the way it does, and occasionally why it refuses to do something you asked for.
- 01
Data before opinion
Every figure traces to a public source and every method is published. Where we model something, we say we modelled it. Where a number cannot answer your question, we say that too.
- 02
Explanation before score
A number with no account of itself is a black box wearing a lab coat. Every score arrives with what it measures, how it was derived, and what it leaves out.
- 03
Trade-offs before "best"
Nothing here declares a winner. Every recommendation names what it asks you to give up, because whether that price is worth paying is a question about your life, not about the data.
- 04
Your priorities before ours
A generic ranking is a ranking of somebody else. You set what matters and the city is ranked against that. Our own weightings, where we publish them, are labelled as judgments so you can disagree.
Assessed values from municipal records in Calgary, Vancouver, Edmonton, and Toronto, except Toronto, where per-parcel assessments are licensed and values are modelled from census data instead.
Incident-level statistics from Calgary Police Service, Vancouver Police Department, Edmonton Police Service, and Toronto Police Service.
Each scored across 34 dimensions and ranked against city-wide averages.
Where our data comes from.
We ingest, normalize, and cross-reference data from official public sources across Canada.
See it in action.
Start with your own move. It is free, and there is a 7-day Professional trial with no credit card when you want the deeper analyses.