- an indexing engine
- a real estate search engine delivered on mobile
- a recommendation system
- a Business Intelligence and analytics engine
- a targeted marketing platform
We use Artificial Intelligence to provide fast insights and drive agile, competitive decisions and actions for the real estate businesses and we help regular users find what they need faster by analysing their behaviour and preferences.
Housepedia searches and curates hundreds of thousands of property listings as soon as they appear on the market. We analyze data using Artificial Intelligence and push relevant properties to web and mobile devices.
With Housepedia you can find a home faster:
- compare property prices in your area
- search using a smart and easy to use map interface
- choose from thousands of curated listings
- from multiple online sources
- use a radar feature to get notified on offers around you in real time
- get personalized recommendations based on your preferences
- easily review your favourite listings
Architecture, challenges and solutions:
The main parts of this system are:
- mobile app
- the web API extends the Python Flask microframework and provides data
- the crawler’s main responsibility is to populate our database with valid property listings. It was written in Java, extending the crawler4j framework. The main challenge here has been cutting down on processing time and database calls spent determining whether a listing has already been processed.
- the NLP module’s main responsibility is to extract features from listing text. To this end we used the NLTK framework.
- recommendations are made by our proprietary system
- the business intelligence module is meant to provide market statistics, trend and predictions. This is currently a work in progress.