Getting Started
- How predictions workSide 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.
- 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?