Proptech startup raises funding for algorithm development

IpData, a proptech startup, has recently raised $1.6 million to continue working on its technology platform. IpData helps investors and property developers to predict whether its worth buying a specific piece of land for development in any city in Australia and 

The company, chaired by a former KPMG partner, Con Tragakis, says it has developed a fully automated property feasibility algorithm which uses machine learning to assess what the profit upside is likely to be for any proposed development, and spits out a sensible purchase price before a buyer goes ahead.

The ipData platform uses what the company calls a "land economics" artificial intelligence engine to determine the return on investment.

The algorithm factors in between 20 to 30 different sets of data including optimum building size, development style, distance from the beach or harbor, whether the land is near a main road, if it is on a tree-lined street and comparable house and land package prices. It also assessed how close the land was to public transport, along with many more attributes which ultimately determined value and future returns.

The chief executive, George Giannakodakis, said the number-crunching algorithm would work equally as well in a property downturn  and during more buoyant times because it fed in real-time data.

"We've developed big data learning sets," he said. "It sees patterns. We've been experimenting with a lot of data layers."

ipData is an Australian owned and based predictive analytics company that provides superior property and planning advice based on state of the art algorithms driven by artificial intelligence. Our aim is to better inform people’s decisions, help business grow and assist policy makers to shape our cities. The company includes a strong management team, high calibre data scientists and systems engineers with extensive modelling experience, advised by property and planning professionals with Australia wide residential property and development, urban planning and spatial data experience.

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