Property Data for Real Estate & PropTech

Build on the market itself
— not a copy of it

Most real estate platforms are built on MLS feeds that fragment history, lag transactions, and lose the property thread across relists. BrightCat is the dataset underneath — continuous, structured, and lifecycle-complete.

Property data for real estate platforms, proptech applications, and investment analytics — structured for direct integration via Snowflake and MCP.

If your product depends on property data, this is the foundation layer.

MLS feeds weren't designed for what you're building

If you're building a proptech product, a valuation model, an investment platform, or a brokerage tool — you're probably working with MLS data. And you've probably noticed the problems.

MLS numbers reset on every relist

A property that lists, expires, and relists gets a new MLS number each time. Your system sees three different properties. It's one. The price history, the days on market, the listing trajectory — all fragmented across disconnected records.

Sold data arrives late and disconnected

Transaction prices appear weeks after closing. By then, your valuation model is already stale. Worse, the sold record often references a different MLS number than the listing — breaking the link between what was asked and what was paid.

No lifecycle continuity

Most feeds show you what's active today — a snapshot. What listed last month and was pulled? What relisted at a lower price? What sold privately without appearing in the listing feed? If you can't track a property through its full lifecycle, you're working with fragments.

Board-by-board access is a nightmare

Canada has dozens of regional MLS boards, each with its own data format, API, access agreement, and update schedule. Building national coverage means negotiating with each one individually — or paying an aggregator who normalises away the detail you actually need.

Property data fields for real estate and PropTech platforms

Specific BrightCat fields and products relevant to this vertical. Every field listed below is queryable through Snowflake SQL, MCP natural language, or available in the weekly flat-file delivery.

Signal	Product	Field / Logic	What it tells you
Full listing lifecycle	Listings	All status transitions, 135+ columns	Build on complete market data, not MLS fragments
Sold transaction history	Sold	221 columns per sold event	Comparable analysis and price history reconstruction
Rental market data	Rentals	Unit-level asking rents, availability	Rental analytics and investment yield calculations
Commercial coverage	Commercial	297K+ properties, dual-listing flags	CRE market intelligence for multi-asset platforms
Persistent property ID	All products	Stable identifier across relists and agent changes	Property-level longitudinal analysis without MLS fragmentation
Home Price Index	Core	194K+ repeat-sale pairs	AVM inputs and market trend construction

Sample query

-- PropTech: property history across relisting cycles
SELECT property_id, address, city, province,
       listing_status, asking_price, days_on_market,
       pricechangeamt, cumpricechgpct, original_price,
       file_date
FROM BRIGHTCAT_LISTINGS.PRODUCT.listings_weekly
WHERE property_id = 'PROP-00472819'
ORDER BY file_date DESC
LIMIT 20;

Abstract example. Exact column names provided with access provisioning.

The full Canadian property market — structured for integration

One dataset. National coverage. Weekly updates. Every property tracked with a persistent identifier across its full lifecycle. Delivered directly into your Snowflake account or accessible by AI agents via MCP.

5.8M residential properties

Every province. Every listing status. Every price change. 135+ columns per property. Updated weekly since 2014.

899K+ sold transactions

Confirmed prices matched to listing history. verified repeat-sale pairs for property-level appreciation. Not estimates — outcomes.

297K commercial properties

Sale and lease activity tracked together. Thousands of dual-listed properties with transaction-outcome inference in real time.

Repeat-sale Home Price Index

Built from confirmed transaction pairs. Property-level appreciation, not smoothed regional averages.

Pre-mover intelligence

Observed listing signals, not modelled predictions. Identify households entering a move cycle the week the property lists.

Snowflake + MCP delivery

No file transfers. No ETL. Query live data inside your Snowflake account. Connect AI agents via MCP. Build on it, not around it.

Use cases for real estate and proptech teams

Automated Valuation Models

Build AVMs on confirmed transaction pairs, not comparable-sale estimates. verified repeat-sale pairs provide property-level price trajectory data. Connect listing lifecycle context to understand why prices moved, not just that they did.

Lead Generation & Timing

Identify homeowners entering a sale cycle the week they list — not after the deal closes. Power agent matching, mortgage offers, and home service campaigns at the moment of highest intent.

Market Intelligence Dashboards

Build real-time dashboards showing supply, pricing pressure, days on market, and inventory turnover at the postal code level. Weekly data means your dashboard shows this week's market, not last quarter's.

Investment Analysis

Identify investor-owned properties by cross-referencing sold and rental data. Track sale-to-rent conversions. Detect portfolio accumulation patterns at the neighbourhood level. Analyse cap rates using actual transaction and rental pricing.

Property Search & Discovery

Power property search products with lifecycle-aware data. Show buyers not just what's active today, but how long it's been on market, whether it's a relist, and how the price compares to the original ask. Context that listing-only feeds don't carry.

AI-Powered Property Agents

Build AI agents that query live Canadian property data via MCP. Natural language access to listings, transactions, rental data, and market signals — no preprocessing, no transformation layer. Your agent reasons over the actual market.

MLS feeds vs. BrightCat

Typical MLS data feeds

MLS numbers reset on every relist

No cross-cycle property tracking

Sold data arrives weeks late

Board-by-board access and formats

Current snapshot only — no history

Separate commercial and residential feeds

BrightCat

Persistent property identity across all cycles

Full lifecycle: list → relist → sell → rent

Weekly updates, national coverage

One unified dataset, all provinces

12 years of continuous weekly data

Residential + commercial + rental integrated

Common questions from real estate and proptech teams

What property data does BrightCat provide for real estate and proptech companies?

Six integrated Canadian property datasets: Listings (5.8M+ properties weekly), Sold (Canadian sold transaction events), Rentals (national coverage), Commercial (297K+ properties), Core (unified layer with HPI), and PreMovers (observed pre-mover signals). All delivered via Snowflake Marketplace Secure Data Share or MCP connector for AI agents.

How is BrightCat different from MLS data feeds?

MLS numbers reset on every relist, fragmenting property history. BrightCat uses a proprietary property identifier that preserves full property lifecycle across relists, agent changes, and brokerage transfers. This enables true days-on-market calculation, renovation detection, and repeat-sale analysis that MLS-based systems cannot provide.

Can proptech companies build products on BrightCat data?

Yes. BrightCat data is delivered via Snowflake Secure Data Share — you query it directly alongside your own data inside your existing Snowflake account. For AI-powered products, the MCP connector enables direct model access to live property data. No file transfers, no ETL, no stale extracts.

What does BrightCat data cost for proptech startups?

Sample data is available for every product via Snowflake Marketplace. Professional plans are custom-priced per product with annual terms. Enterprise bundles include multi-product access, custom enrichment layers, dedicated support, and SLA. Contact us for pricing.

Does BrightCat cover all of Canada?

Yes. BrightCat tracks residential properties across all ten Canadian provinces. Commercial coverage spans 297K+ properties nationally. Rental coverage is national across Canada. All updated weekly.

Build on the market itself
— not a copy of it

MLS feeds weren't designed for what you're building

Property data fields for real estate and PropTech platforms

Sample query

The full Canadian property market — structured for integration

Use cases for real estate and proptech teams

MLS feeds vs. BrightCat

BrightCat has an MCP connector

Common questions from real estate and proptech teams

Products used by real estate and proptech teams

Build on the full market — not a snapshot of it

Build on the market itself— not a copy of it

MLS feeds weren't designed for what you're building

Property data fields for real estate and PropTech platforms

Sample query

The full Canadian property market — structured for integration

Use cases for real estate and proptech teams

MLS feeds vs. BrightCat

BrightCat has an MCP connector

Common questions from real estate and proptech teams

Products used by real estate and proptech teams

Build on the full market — not a snapshot of it

Build on the market itself
— not a copy of it