“Two exits. 100,000+ users. We know this industry.”
Real Estate Software Development — PropTech Built by a Team With Two Canadian Exits
We have built, scaled, and sold two real estate technology platforms in the Canadian market. MARL reached 100,000+ users before its acquisition. CrimeLens is live today — AI-powered neighbourhood intelligence serving Canadian agents and buyers. Real estate is not a service line we added. It is a sector we have operated in for over a decade.
Projects you can verify
What makes real estate & proptech software hard
Canadian MLS data is more complex than it looks
CREA DDF, RETS feeds, and regional board data each have their own licensing terms, update frequencies, and display rules. Teams unfamiliar with the Canadian market spend months navigating this before writing a line of product code.
Agents and buyers need completely different experiences
The mistake most PropTech products make is trying to serve both audiences from a single interface. Agents need CMA tools, pipeline management, and showing coordination. Buyers need discovery, comparison, and neighbourhood intelligence. These are different products.
Location data needs to be trustworthy
Real estate decisions are some of the largest financial decisions people make. If your neighbourhood data, crime analysis, or price estimates are inaccurate, you lose trust immediately and permanently. The data infrastructure has to be right.
How we solve real estate & proptech problems
MLS integration and property data pipelines
We build direct CREA DDF and RETS integrations with proper data normalization, caching, and the board-specific display rule compliance that protects your licence.
AI-powered neighbourhood intelligence
Real-time machine learning over crime data, school ratings, transit scores, and market trends — at the block level, not the neighbourhood level. The architecture that powers CrimeLens.
Native iOS and Android agent tools
Mobile apps built for how agents actually work: in the field, between showings, on a phone. Listing management, client communication, and market data — without the laptop.
Real estate CRM and pipeline management
Custom CRM systems built for the real estate transaction cycle — lead routing, conditional periods, commission tracking, and the document management that generic CRMs never handle correctly.
Property search and discovery platforms
Map-based search with advanced filtering, saved searches, listing alerts, and the performance optimization required to make large inventory databases feel fast.
Investment analytics and valuation tools
Automated valuation models, cap rate calculators, market trend analysis, and portfolio intelligence dashboards for investors and developers who need data, not guesses.
CrimeLens: AI neighbourhood intelligence, live in 12 Canadian cities
We built CrimeLens from the ground up — real-time ingestion from public crime feeds across 12 Canadian municipalities, a geospatial indexing layer with PostGIS, and an ML risk scoring model that outputs neighbourhood safety scores at the block level. Designed for real estate professionals making location-based recommendations and buyers evaluating neighbourhoods before purchase.
The stack we use for real estate & proptech
Questions about real estate & proptech software
How complex is Canadian MLS data integration compared to the US?
More fragmented. The US has RETS as a relatively standard protocol. Canada has CREA DDF nationally, but major boards like TREB, REBGV, and OREA each have their own feeds, licensing requirements, and display rules. We have navigated all of these and can save you months of trial and error.
What made MARL reach 100,000+ users in the Canadian market?
Separate agent and buyer experiences — rather than one generic interface — and a genuinely fast MLS data feed with real-time updates. Agents adopted it because it was built for how they actually work, not how product managers assumed they worked.
Can you build an AVM (automated valuation model) for Canadian properties?
Yes. We have experience building ML-based valuation models trained on Canadian transaction data. The key challenges are data quality (Canadian sale price data is less comprehensive than the US), regional variation, and recency weighting in a volatile market.
What licensing requirements apply to displaying MLS data?
CREA DDF has specific display rules: attribution requirements, data refresh minimums, prohibitions on certain types of aggregation, and restrictions on how sold data can be shown. We build data pipelines that comply with these requirements and can help you through the DDF licence application process.
How does CrimeLens get its crime data?
CrimeLens ingests from public open data portals maintained by municipal police services and cities across Canada. The data quality and update frequency varies significantly by municipality — building the normalization layer that makes inconsistent public data usable was the hardest part of the technical build.
Do you work with real estate brokerages directly, or only PropTech startups?
Both. We have built custom technology for brokerages that want proprietary tools — CRM, transaction management, agent portals — as a competitive advantage rather than a dependency on generic platforms.