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Casafari is the AI agent-native real estate data intelligence platform. The most complete property index in Europe: a deduplicated, cleaned property graph of residential and commercial property, for sale and for rent, in 16 countries.The most complete property index in Europe: a deduplicated, cleaned property graph.

How the graph is built

Use cases and worked examples · FAQ

How do I analyse how prices in an area have moved over time?

Resolve the place to a location id with ma_get_location_typeahead, fetch the series with ma_get_time_series_data, then calculate growth and volatility with ma_get_time_series_operations.

  1. ma_get_location_typeahead: pass the place name in English and pick the location_id you want. Check the breadcrumbs when names repeat.
  2. ma_get_time_series_data: request type_group apartment, business_type sale, data_point avg_price_psqm and date_interval month, with a date_range and the location ids. Each point holds one period's value.
  3. ma_get_time_series_operations: request the same segment with operations such as mean, delta_pct, cagr, std and cv.

Casafari's example question: How has the asking price per m² of flats in Valencia moved over the last three years? Over REST, POST /market-analytics-api/time-series returns the series.

See: Area Insights.

Where this is documented

All questions

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