WinPure and Senzing Announce a Strategic Partnership to Enhance Data Quality Management and Make Entity Resolution Accessible to All Businesses.

WinPure, a leading provider of data cleansing and matching software, is pleased to announce a strategic partnership with Senzing, a pioneer in entity resolution technology. This partnership brings together WinPure’s expertise in data quality management with Senzing’s advanced entity resolution capabilities, enabling organizations to unlock the full potential of their data and make more informed decisions.

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Traditionally, entity resolution has been an expensive endeavour, confined to the domain expertise of specially trained developers and data analysts. Small-to-medium sized companies with limited budgets would find it particularly difficult to make sense of their siloed data, or to get holistic customer views, all of which is only possible when an entity resolution process is put in place.
In this first-of-its-kind partnership, WinPure and Senzing aim to make entity resolution affordable, accessible – and most importantly – available for businesses of all sizes.

“We are thrilled to partner with Senzing to bring industry-leading entity resolution capabilities to our customers,” said David Leivesley, CEO of WinPure. “By combining Senzing’s AI entity resolution technology with WinPure’s data quality management solutions, we are empowering organizations to achieve greater accuracy, efficiency, and insights from their data”.

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Jeff Jonas, Founder & CEO of Senzing said, “The Senzing team and I could not be prouder of this new partnership with WinPure, which has been a top brand for data matching for over two decades. Their mission to empower business users to perform their own data matching is a natural fit with the entity resolution AI we deliver. The market is going to love WinPure’s Clean & Match version 10 with Senzing inside.”

With this ground-breaking partnership, both organizations aim to make their respective ambitions come true – democratizing access to entity resolution and simplifying tedious data quality management processes.