A property data API for sixteen countries

Try it now

curl -X GET "https://api.houski.ca/properties?api_key=YOUR_API_KEY&city=calgary&country_abbreviation=ca&demographic_education_level_bachelors_degree_percent_gte=0.30&demographic_income_median_pre_tax_gte=100000&page=1&property_type_eq=House&province_abbreviation=ab&results_per_page=3&score_walkability_gte=6&select=address,latitude,longitude,bedroom_total,estimate_list_price,demographic_income_median_pre_tax,demographic_education_level_bachelors_degree_percent,score_walkability"

const houski_data = async (): Promise<PropertiesResponse> => {

    // You must copy the PropertiesResponse type declarations from the 
    // Houski API documentation to strongly type the response

    const url = new URL('https://api.houski.ca/properties');
    url.searchParams.set('api_key', 'YOUR_API_KEY');
    url.searchParams.set('city', 'calgary');
    url.searchParams.set('country_abbreviation', 'ca');
    url.searchParams.set('demographic_education_level_bachelors_degree_percent_gte', '0.30');
    url.searchParams.set('demographic_income_median_pre_tax_gte', '100000');
    url.searchParams.set('page', '1');
    url.searchParams.set('property_type_eq', 'House');
    url.searchParams.set('province_abbreviation', 'ab');
    url.searchParams.set('results_per_page', '3');
    url.searchParams.set('score_walkability_gte', '6');
    url.searchParams.set('select', 'address,latitude,longitude,bedroom_total,estimate_list_price,demographic_income_median_pre_tax,demographic_education_level_bachelors_degree_percent,score_walkability');

    const response = await fetch(url);
    const data = await response.json();

    return data;
}

(async () => {
let data: PropertiesResponse = await houski_data();

// Log the response
console.log(data);
})();

{
  "cache_hit": true,
  "cost_cents": 1.619999885559082,
  "data": [
    {
      "address": "239 Dalhurst Way NW",
      "bedroom_total": 4,
      "demographic_education_level_bachelors_degree_percent": 0.43396225571632385,
      "demographic_income_median_pre_tax": 142269,
      "estimate_list_price": 960243,
      "latitude": 51.110740661621094,
      "longitude": -114.1513900756836,
      "property_id": "100086f6bc064d3f",
      "score_walkability": 8
    },
    {
      "address": "188 Mount Aberdeen Close SE",
      "bedroom_total": 3,
      "demographic_education_level_bachelors_degree_percent": 0.3230147957801819,
      "demographic_income_median_pre_tax": 122978,
      "estimate_list_price": 454348,
      "latitude": 50.93125915527344,
      "longitude": -113.97802734375,
      "property_id": "1001894d82aeeb0c",
      "score_walkability": 8
    },
    {
      "address": "432 27 Avenue NW",
      "bedroom_total": 3,
      "demographic_education_level_bachelors_degree_percent": 0.5232558250427246,
      "demographic_income_median_pre_tax": 171205,
      "estimate_list_price": 1176562,
      "latitude": 51.07721710205078,
      "longitude": -114.06916046142578,
      "property_id": "10021e44aa219b00",
      "score_walkability": 7
    }
  ],
  "error": "",
  "pagination": {
    "current_page": 1,
    "has_next_page": true,
    "has_previous_page": false,
    "page_total": 53978
  },
  "price_quote": false,
  "result_total": 161933,
  "time_ms": 157,
  "ui_info": {
    "city": "Calgary",
    "city_id": "6ec95b53075d062c",
    "city_link": "ca/ab/calgary",
    "city_slug": "calgary",
    "country": "Canada",
    "country_abbreviation": "CA",
    "country_abbreviation_id": "9ace2b6431b7f1be",
    "country_abbreviation_link": "ca",
    "country_slug": "canada",
    "province": "Alberta",
    "province_abbreviation": "AB",
    "province_abbreviation_id": "aae1f05a0f89d2c7",
    "province_abbreviation_link": "ca/ab",
    "province_slug": "alberta"
  }
}

Check the data quality

Search any address in the sixteen countries we cover. The data you see is what the API returns. The same data can be used to power property listings, heat maps, area averages, and permit searches.

What you can build

• Score insurance risk across a portfolio with flood and wildfire exposure, materials, year built, roof type, and lot attributes for every address in the book
• Screen and triage lending and underwriting with assessment values, property taxes, listing history and model valuations, wherever a market publishes them
• Build comparable sales analysis with recorded sale prices from public records wherever they are published, and model estimates everywhere else
• Refresh portfolio valuations monthly across a mortgage book, real-estate fund, or insurance book without spinning up an internal valuation team
• Enrich an address book or customer database with 400+ standardised property fields (assessments, permits, listing history, risk scores, census figures, climate risk) for the addresses you already have in the sixteen countries we cover
• Optimise direct-mail and customer-database segmentation for home-services, insurance, energy, and renovation campaigns by filtering on permit history, assessment value, property taxes or building age
• Bulk export millions of rows to Snowflake, BigQuery, Databricks, Power BI, or a Python notebook for machine-learning training and one-off research datasets
• Build a property research agent on the Houski Model Context Protocol (MCP) server for Claude, Cursor, or your own large-language-model pipeline
• Detect change via permit history for due diligence, renovation tracking, insurance re-underwriting triggers, and construction analytics
• Map property concentrations and risk heatmaps for site selection, infrastructure planning, campaign targeting, and council briefings
• Brief municipal planners and policy teams with one uniform schema across every state, province and region we cover, ready for housing-affordability, climate-adaptation, and zoning analysis

Who uses Houski

Why Houski

• Nearly every property, every field: Where no record exists, a model estimates the value, and source fields on the main building facts say which values are recorded and which are estimated.
• Standardised across every country: Every state, province and region, every municipality, one schema. Field names, units, property type vocabulary, address formats, all normalised to a single definition you can query without translation tables.
• Clean data: Hundreds of public, government, and crowdsourced data sources, each in its own format. We deduplicate them, reconcile their conflicting field definitions, and map every record onto a single property entity. Years of data engineering so analyst teams stop hand-stitching exports.
• Independent: No ties to the real estate industry or government. We pull public, government, and crowdsourced data sources, so no real estate license is required to access the API.
• Rebuilt every night: New records reach the API in the next nightly build.
• Developer-first: A modern easy API with consistent filtering, sorting, and selection across every endpoint, plus an MCP server and full documentation
• Usage-based pricing: Pay for what you use, $99 USD monthly minimum. See pricing