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[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”] Signs Licensing Agreement for Its Property and Area Forecast APIs with Forescite, Inc.

Honely, a Boca Raton-based prop tech firm that uses proprietary AI/ML techniques to forecast the values of over 100 million properties, is pleased to announce that they have entered into a strategic relationship with Forescite, a leading New York City-based FinTech company revolutionizing the journey to a secure financial future with their AI/ML-powered mobile app, Investall. Forescite will now have the capability to help calculate a user’s net worth and equip them with statistics pertinent to the real estate market through a major licensing deal with a big data player in the Prop Tech space.

Forescite will be licensing Honely’s Property and Metro Level Forecast APIs which will allow them to give a true assessment of their users’ financial position.

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“This major partnership will be the first of many to come,” said Maxwell Schwarz, President of Honely. “We understand how impactful our statistics can be especially on a robust real time wealth management platform such as the Investall APP. The use case of our statistics can vary over a broad spectrum of industries, however the first one the public will be able to interact with is on Forescite’s Budgeting and wealth management platform.”

FORESCITE EXECUTIVE Bala Shagrithaya, Investall CEO commented, “After an exhaustive search of data from industry leaders such as Zillow, we’re thrilled to have found a partner in Honely, that far exceeds the complexity and reliability of data available on any property, which is important when trusting an algorithm that our users can rely on.”

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