Location data for real estate, built for search and display.
Power property search, listing pages and neighbourhood guides with structured, display-ready data — MLS/CREA listings, boundaries, demographics, schools and permits, all through one API.
Real estate products live and die on location context. Stitching listings to boundaries, demographics, schools and permit history from a dozen sources is slow, brittle and expensive to maintain.
What Neighbourly gives real estate teams.
The specific, production-grade capabilities behind real estate on Homicity — not features on a slide, but data and tooling you can ship on.
One-call listing hydration
Resolve a listing by MLS-format address or coordinate and receive the neighbourhood, boundary hierarchy, Forward Sortation Area demographics, catchment schools and permit history pre-joined onto the record. Because the geographic hierarchy is denormalized onto each result, there are no runtime spatial joins between listings and their context.
Verified viewport search
Query listings inside a bounding box against pre-computed Location Boundaries rather than raw radius math, so a search UI returns the properties a buyer would consider part of the neighbourhood on screen. Property-attribute filters run alongside the spatial query in a single request.
Programmatic neighbourhood pages
Combine the location-by-slug endpoint with Neighbourhood Data, Demographics and boundary geometry to generate clean, slug-based URLs for thousands of areas. Each page draws from the same graph, so market context, schools and demographics stay consistent across your entire site.
School catchment resolution
The Schools layer resolves the catchment a given address falls within, not just the nearest school, so a listing page can answer the question buyers actually ask. Catchment geometry is returned alongside school attributes for display or filtering.
Permit-driven property signals
Attach normalized Building Permits history to a listing or neighbourhood to surface renovation activity, additions and development nearby. This gives a listing page a signal of recent investment that raw listing feeds do not carry.
Agent and office graph search
Search agent and office profiles with fuzzy name matching and geographic filtering, returning structured profiles that link back to listings and boundaries. This supports find-an-agent tools and office directory pages without a second data source.
How Real Estate teams use Neighbourly.
Map & viewport search
Return every listing inside the current map view against verified neighbourhood boundaries.
Neighbourhood guide pages
Programmatic, SEO-ready location pages with demographics, schools and market context.
Listing enrichment
Attach neighbourhood, demographics, permits, schools and energy to any listing in one call.
Agent & office search
Fuzzy name and geo search across agent and office profiles.
Why real estate teams choose Homicity.
Ship location context in days
One key and one schema replace the multi-vendor stitching that usually stands between an idea and a working neighbourhood or listing page.
Consistency across every page
Every listing, guide and map view draws from the same boundary hierarchy and demographics, so context never contradicts itself between templates.
SEO surface area at scale
Programmatic, slug-based location pages built on real boundaries and demographics let you cover markets you could never author by hand.
Predictable performance under load
Pre-computed geometry and pre-joined hierarchy keep responses fast for map panning and search, even as viewport queries scale.
See an example listing
See every Neighbourly data layer assembled onto a single property page — boundaries, demographics, schools, permits, energy and more, all from one address.
Data layers for Real Estate
The Neighbourly layers most relevant to this industry — all under one API key, one schema, Canada-wide.
Three ways to put Neighbourly to work for real estate.
Use the data yourself, have us build the whole thing, or bring in our team for strategy and analysis — whatever fits how you work.
Canadian data residency
Hosted in Canadian data centres, end to end.
PIPEDA-compliant
Privacy-first by default, with provincial compliance built in.
One consistent schema
Every layer shares a spine, so data joins cleanly.
Always current
Live, maintained data — never stale snapshots.
Real Estate — common questions
What real estate data does Neighbourly provide?
MLS/CREA-format listings with 80+ attribute lookups, agent and office profiles, plus boundaries, demographics, schools, permits and energy — all queryable by coordinate, address or map viewport.
Can I build a property search on the Neighbourly API?
Yes. Viewport search returns listings inside a map view against verified boundaries, with property-attribute filtering, ready for a search UI.
Can I create neighbourhood guide pages for SEO?
Yes. Curated neighbourhood content, demographics and boundaries let you build programmatic, SEO-ready location pages with clean, slug-based URLs.
How do I enrich a listing with location data?
One call attaches neighbourhood, demographics, permit history, schools and energy to any listing through the Neighbourly graph — no runtime reconciliation.
Does it include school catchments and demographics for listings?
Yes. The Schools layer resolves catchment boundaries for any address, and FSA-level demographics attach to every listing and neighbourhood.
Which data layers matter most for real estate?
Real Estate listings, Location Boundaries, Demographics, Schools and Building Permits are the core layers, with Energy available as an add-on.
Can I filter listings and enrich them in the same request?
Yes. A viewport or address query can carry property-attribute filters and return the listing with its neighbourhood, demographic, school and permit context attached, so there is no second round trip to hydrate the result.
Do you offer both REST and GraphQL for a search UI?
Yes. The same data is available over REST and GraphQL under one API key, so you can use GraphQL to fetch exactly the listing fields a card needs and REST where a simple endpoint is easier.
If we would rather not build the front end, can Homicity help?
Yes. You can build directly on the Neighbourly API, commission a custom build, or use our data services to deliver enriched listing or neighbourhood datasets to your team.
How current is the listing and permit data?
Listings follow MLS/CREA format and are refreshed on an ongoing basis, and Building Permits are normalized across supported cities. We can walk through refresh cadence for your specific markets during onboarding.
Bring Neighbourly to your real estate product.
Tell us what you're building and we'll map the right data layers and plan to your use case.