side street

Getting Started

Side Street uses a machine learning model trained on hundreds of thousands of historical Canadian real estate data points. It analyzes property features, location, market conditions, and comparable sales to generate a predicted sale price and confidence score for each listing. Predictions are updated regularly as new data becomes available.
Rather than giving you a blanket city-wide prediction, Side Street provides transparency at the smallest possible level — down to the neighbourhood or district. Our models operate at this granular sub-city level, which means the confidence label you see (ranging from low to high) reflects the actual data density and market consistency of that specific area. A lower confidence label simply means less historical data is available in that neighbourhood, not that the prediction is unreliable. 

How predictions work

What cities are covered

How is the AI score calculated

What does the price range mean?

Why does the predicted price differ from the asking price?

How do I use the ROI Calculator?

How can we help you?

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