A street address looks like the simplest piece of data in real estate. A number, a street, a city, a postal code. But ask a real question about that address — which school does it feed into, what’s been built on this block, what does the home cost to run, what neighbourhood is it actually in — and the answer is scattered across dozens of sources that were never designed to talk to each other.
Neighbourly exists to close that gap. We connect any Canadian address to the full context of the place it sits in, through one API.
The problem: Canadian place data is fragmented by design
Canada’s location data isn’t missing. It’s dispersed. Boundaries come from one level of government, building permits from hundreds of municipalities, school catchments from boards, demographics from the census, business records from provincial registries. Each source has its own format, its own update cycle and its own idea of what an address looks like.
For anyone building a listing platform, underwriting a policy, approving a mortgage or choosing a retail site, that fragmentation becomes work: data wrangling, spatial joins, address matching that fails on rural routes and French-English variants, and a pipeline that breaks every time a source changes.
What Neighbourly does
Neighbourly standardizes Canadian addresses, resolves them to their geography, and returns an enriched record in a single call. One consistent schema. One auth token. Query by coordinate, by address or by bounding box, Canada-wide.
The foundation is the address itself. Neighbourly has normalized more than 13 million Canadian addresses, breaking each into clean components and linking it to its place in a six-level geographic hierarchy: country, province, county, upper-tier municipality, lower-tier municipality and neighbourhood.
Ten layers, one record
- Addresses and geocoding — validation, lookup, forward and reverse geocoding, postal codes.
- Boundaries — country, province, county and municipal boundaries.
- Neighbourhoods — neighbourhood-level context, so “where is this?” has a human answer.
- Real estate — listing data for real estate platforms and PropTech teams.
- Building permits — permit activity at and around an address, normalized into one schema across the cities we cover.
- Demographics — census-aligned profiles for every Forward Sortation Area.
- Schools — schools and catchments, so families can see which schools an address feeds into.
- Business — geocoded business data and points of interest for trade-area and site analysis.
- Environment — trails, Crown land, lakes and wildlife management units, alongside environmental data.
- Energy — verified consumption, efficiency scoring and cost benchmarks.
Energy: verified, not modelled
Our newest layer answers a question almost no Canadian listing does: what does this home cost to run? Neighbourly’s energy data comes from Green Button partnerships and direct utility integrations — actual consumption, not modelled estimates. Each record carries an efficiency rating, a monthly cost estimate and a benchmark against comparable addresses.
It’s built consent-first, in line with provincial privacy law, and outputs are aggregated and non-identifying. Coverage is provincial today.
Who it’s for
Location context matters anywhere a decision depends on where something is:
- Real estate, MLSs and boards — richer listings that answer buyers’ questions before they ask.
- Insurance and underwriting — an address-level view of the place, not just the policy.
- Banking and lending — including green mortgage products that need verified energy data.
- Franchises and retail — site selection grounded in who and what is nearby.
- PropTech and data teams — one integration instead of a dozen pipelines.
- Government, municipalities, telecom and utilities — planning and analysis on clean, consistent geography.
Built for AI, too
More questions about places now start with an AI assistant. Neighbourly offers MCP access for AI tools, so assistants can work with structured Canadian place data instead of guessing.
More than an API
Some teams want an API key; others want a partner. Alongside the platform, we work with teams on data strategy, data quality and enrichment, customer intelligence, market and location analytics, activation, measurement and custom solutions.
The bottom line
Every address sits inside a place. Neighbourly makes that place readable — one address, one call, the full context. Over the coming weeks we’ll share what we’re learning about Canadian location data here and on Instagram.
Start with any address: try the free geocoding lookup, read the free white paper, or explore every data layer. A 20-minute walkthrough is usually enough to know if there’s a fit.
Frequently asked questions
What is Neighbourly?
Neighbourly is a Canadian location intelligence platform. Its API connects any Canadian address to its geographic and neighbourhood context — boundaries, permits, schools, demographics, businesses, environment and energy — and returns it as one enriched record with a consistent schema and a single auth token.
Does Neighbourly cover all of Canada?
Neighbourly’s datasets are Canada-wide, with more than 13 million addresses normalized. Some layers vary by source: building permits are normalized for the cities currently covered, and energy data has provincial coverage today. Each data-layer page on neighbourly.io lists its current coverage.
How do I query the Neighbourly API?
You can query by coordinate, by street address or by bounding box. Every response uses the same schema across layers, so a single integration returns boundaries, neighbourhood, permits, points of interest and energy for an address without separate spatial joins or address matching.
Where does Neighbourly’s energy data come from?
The energy layer uses verified utility data from Green Button partnerships and direct utility integrations rather than modelled estimates. It’s built on explicit homeowner consent and provincial privacy law, and its outputs are aggregated and non-identifying.
Can I try Neighbourly for free?
Yes. The free geocoding lookup on neighbourly.io lets you test any Canadian address, and the free white paper explains the platform and its data in more depth.