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Qindom Cracks the Code for Real Estate Prediction with Quantum Machine Learning


Qindom, the Toronto-based Quantum Machine Learning (QML) start-up, is shifting conventional pricing practices in Real Estate business. Qindom’s proprietary AI technology inspired by quantum computing underpins the value of residential properties, addressing the pricing opacity between supply and demand. The team now announces the successful launch of their Real Estate Prediction and Decision Optimization Engine(hereafter, Engine), presenting prominent live results benchmarked against world-leading counterparts.
“We found the key to facilitate the trillion US dollars market. Our system carries out accurate predictions on individual home values in Canada and US, and has the potential to untie the knots existing in the home buying, selling and investing process,” said Yao Wang, Co-Founder of Qindom, a serial entrepreneur from Alibaba Group. “Our clients are experiencing an exciting 30% boost in performance compared to Zillow and Redfin, among other major players in this field.”
Real estate price prediction is largely subject to information asymmetry, moral hazard of agents, experience or “gut feeling”, open statistics, etc. To address the above-mentioned issues, Qindom provides an adaptive approach to predict individual real estate properties, which will inform optimized buying, selling, and investing strategies.
The Engine is fueled by a variety of data sources, unsupervised data representation learning, and frontier technologies including quantum computing and deep learning. More specifically, listing, text, image, geographic, and contextual information are preprocessed and fed into the Engine, where synergy is created among Quantum Ensembling, Deep Neural Networks and Optimization methods.
The Engine has been running in production with real-time data from the Greater Toronto Area (GTA) real estate market. The prediction accuracy reaches 96.35% within 10% error range of the sale price for houses and condominium apartments, which outperforms rivals on the market. Detailed project explanation and comparative results are referenced via https://link.medium.com/WNObM5AFGW.
The online service is provided to Qindom’s industry clients via their real estate mobile applications and updated on a daily basis. Real-time API is supported as a platform service. The system serves more than 100,000 active users. “Further development plan includes comprehensive prediction and deep analytics such as ROI estimation, property assessment, and investment decision support,” said Yao.
SOURCE Qindom Inc.
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