Hazy

About Hazy

Hazy is a synthetic data generation company that enables businesses to work with data that is faster and safer to use. Founded in 2017 by Harry Keen and Luke Robinson, the London-based firm originated as a spin-out from University College London (UCL). The founders identified the difficulty organizations faced in sharing and extracting value from data while respecting privacy and regulatory constraints. Initially focused on anonymization, the company pivoted to synthetic data, recognizing its greater potential. Hazy's platform uses generative artificial intelligence to create new, entirely artificial data that retains the statistical properties and correlations of the original source data. This process ensures the synthetic data is semantically identical and can serve as a drop-in replacement for real data in use cases like AI/ML model development and software testing, but without containing any of the original, sensitive information, thereby eliminating privacy risks. The software extracts statistical patterns without the underlying data ever leaving its protected environment. The business model is based on licensed annual software, with pricing scaled by usage. Hazy's technology can be deployed on-premises or in the cloud. The company targets regulated industries such as financial services, telecommunications, healthcare, and government, with clients including Nationwide Building Society, Wells Fargo, Vodafone, Accenture, and BMW. A significant milestone was winning the $1 million Microsoft Innovate AI prize in 2018, which included investment from Microsoft's venture arm, M12. Hazy has raised a total of over $11 million, including a $9 million Series A round in March 2023, with investors like Conviction VC, Wells Fargo, and Nationwide. In November 2024, SAS announced the acquisition of Hazy's principal software assets to integrate the technology into its SAS Viya platform and a new product, SAS Data Maker. Keywords: synthetic data generation, generative AI, data privacy, enterprise data, data security, privacy-enhancing technologies, AI model training, data anonymization, financial services, data masking, machine learning data, regulatory compliance, secure data sharing, data analytics, GDPR, AI data security, cloud analytics, data innovation, big data, UCL spin-out