Home News AI startup Hazy announces $1.8 million in latest seed raise

AI startup Hazy announces $1.8 million in latest seed raise

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Artificial Intelligence startup Hazy announced $1.8 million in a latest seed funding round led by the UCL Technology Fund. The other investors in the round included Nationwide Building Society, Pentland, Amadeus Capital Partners, and AI Seed. The funds will support the London-based startup build a new range of products and expand its workforce. This brings Hazy’s total seed investment to $2.8 million following a $1 million funding from M12 and Notion in May, this year.

Established in 2017 by Harry Keen, Hazy offers cloud-based artificial intelligence solutions and has worked with several startups, international banks, and the UK government. The company claims that its artificial intelligence platform allows organizations to share data responsibly and securely through a workflow tool that automatically anonymizes the data.

Speaking on the new investment, Harry Keen, CEO of Hazy, said, “In recent months we have seen a seismic cultural shift around data. Consumers are acutely aware of the importance of data security and GDPR legislation means that businesses rightly now consider safe data-handling as mission-critical. Our technology ensures that huge, unwieldy data sets are GDPR-compliant. Recognising that most companies don’t have data experts, Hazy has been built to require zero technical integration or any technical expertise. We are proud to be working with organizations ranging from major banks and building societies, to small businesses and UK central government and we are excited to continue developing our solution as we launch our product more widely.”

David Grimm, Investment Director at Albion Capital, who manages the UCL Technology Fund stated, “Big data analytics offers unparalleled opportunities for start-ups and corporate giants alike, but also puts data security at the top of the agenda for the world’s regulators. Hazy’s solution is a game changer, enabling businesses to automatically anonymize complex datasets without the need for a lengthy technical integration with internal systems. We are excited to support the team through the next phase of growth.”

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