Real estate is our founding vertical. We've built specific integrations, schema alignment, and data depth for MLS platforms, listing portals, brokerages, and agent tools. RESO-aware APIs, listing-ready neighbourhood data, and energy disclosure layers built for the Canadian real estate industry.
Neighbourly · Real EstateReal 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.
A raw listing record — address, bedrooms, bathrooms, price — tells buyers almost nothing about the place the property sits in. The neighbourhood character. The permit history. The energy cost. The walkability. The schools. This is the information that drives real purchase decisions, and it's the information that U.S. listing platforms have been surfacing for a decade while Canadian platforms lag behind.
Neighbourly is the API that closes that gap. Connect any Canadian listing address and get back a full property context layer: RESO-aligned neighbourhood data with boundaries and character tags, building permit history with type and status, energy efficiency scores and annual utility cost estimates in Ontario, census-derived neighbourhood demographics, walkability and transit scores, and nearby points of interest.
The integration is a single API call per listing address. The output maps directly onto listing page components. And the data is maintained from live municipal, provincial, and federal sources — so it stays current without your team managing any of it.
The specific, production-grade capabilities behind real estate on Neighbourly — not features on a slide, but data and tooling you can ship on.
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.
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.
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.
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.
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.
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.
Return every listing inside the current map view against verified neighbourhood boundaries.
Programmatic, SEO-ready location pages with demographics, schools and market context.
Attach neighbourhood, demographics, permits, schools and energy to any listing in one call.
Fuzzy name and geo search across agent and office profiles.
See every Neighbourly data layer assembled onto a single property page — boundaries, demographics, schools, permits, energy and more, all from one address.
One key and one schema replace the multi-vendor stitching that usually stands between an idea and a working neighbourhood or listing page.
Every listing, guide and map view draws from the same boundary hierarchy and demographics, so context never contradicts itself between templates.
Programmatic, slug-based location pages built on real boundaries and demographics let you cover markets you could never author by hand.
Pre-computed geometry and pre-joined hierarchy keep responses fast for map panning and search, even as viewport queries scale.
Use the data yourself, have us build the whole thing, or bring in our team for strategy and analysis — whatever fits how you work.
Wire standardized real estate data straight into your product or workflow — REST and GraphQL, one key, Canada-wide.
Explore the API →No engineering team? We design and build the real estate tool, dashboard or platform on our data — you bring the idea, we ship it.
Start a build →Strategy, enrichment, analytics and measurement from our team, so your real estate data turns into decisions and results.
See our services →Hosted in Canadian data centres, end to end.
Privacy-first by default, with provincial compliance built in.
Every layer shares a spine, so data joins cleanly.
Live, maintained data — never stale snapshots.
Common questions about this data and how to use it.
With RESO-aligned neighbourhood data, energy disclosures, permit history, and demographics for MLS platforms, brokerages, and listing portals. One call attaches neighbourhood, demographics, permit history, schools and energy to any listing, with no runtime reconciliation.
Yes. Fields follow RESO conventions, so the data maps cleanly into listing schemas and IDX feeds.
In most cases, yes — it is delivered through standard APIs and can flow into existing listing templates without UI changes.
Address and neighbourhood layers cover all of Canada; permit layers roll out by region, and energy data is available in Ontario.
Neighbourly connects to your MLS/CREA listing feed and resolves each listing to an address, then attaches the data we own — boundaries, demographics, schools, building permits and energy. We connect to listing data rather than store it; agent and office lookups run through a live partner integration, and all of it is queryable by coordinate, address or map viewport.
Yes. Viewport search returns listings inside a map view against verified boundaries, with property-attribute filtering, ready for a search UI.
Yes. Curated neighbourhood content, demographics and boundaries let you build programmatic, SEO-ready location pages with clean, slug-based URLs.
Yes. The Schools layer resolves catchment boundaries for any address, and FSA-level demographics attach to every listing and neighbourhood.
The listing connector, Location Boundaries, Demographics, Schools and Building Permits are the core layers, with Energy available as an add-on.
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.
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.
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.
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.
Contact us for API access and a coverage report for your markets.
Tell us about your platform, your listing feed, and the data you want to surface. We'll show you what's possible.