Coyote Software and control.IT have made a joint strategic investment in PRODA, a London-based PropTech business utilising artificial intelligence (AI) technology to solve core data processing challenges.
The investment will see the integration of PRODA on Coyote and control.IT’s respective platforms, with customers of both businesses able to benefit from access to PRODA’s pioneering AI technology.
PRODA harnesses the power of AI to unlock the true value of data by enabling users to capture, consolidate and standardise data, with a focus on rent roll data. The technology, which is targeted at asset managers, real estate lenders and investment brokers, as well PropTech platforms handling rent roll data, aims to automate previously manual and error-prone processes. The business was launched in 2017 by property professionals, Peter Bredthauer and Charles Williams, who between them have a combined 15+ years’ experience in commercial real estate across investments and asset management.
Oli Farago, Co-founder and CEO at Coyote, says: “By working closely together, it has become clear that Coyote and PRODA share the belief that for the property industry to reap the benefits of digitalisation and AI, collaboration and the way in which the industry records and utilises data are key. We are delighted to be working with the ambitious team at PRODA whilst also broadening the services available to our clients.”
Klaus Weinert, Founder and Executive Director at control.IT, adds: “This investment in PRODA builds on our ambition to collaborate with pioneering companies that are revolutionising the way in which the property industry interacts with technology and operates for the better, increasing efficiency and productivity.”
Peter Bredthauer, Co-founder and CEO at PRODA, says: “By standardising unstructured data, we believe PRODA will facilitate advancement across the PropTech industry, presenting opportunities for technology platforms to expand their hubs for asset data, and also for property companies to enhance their ability to analyse rent roll data.”
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