Blocks of images with human faces and data visualisations used to represent synthetic data by Hazy

Synthetic data.
Real results.

Hazy is the synthetic data platform of choice for financial institutions that want to conduct sophisticated data analysis without compromising safety or speed.

We’re
Hiring!

Hazy enables financial services businesses to use data without restriction.

Synthetic data allows you to:

Share data safely

Partner with third parties to safely create more business value by sharing the insights in your data without any private personal information.

Preserve the signal

Hazy synthetic data uses deep learning to understand the behavioural patterns in static and transaction data, so you retain the value not the risk.

Generate business insight

Break down silos and barriers to innovation. Empower your data teams to focus on their job and extract the value from complex structured datasets.

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Get competitive advantage

100× faster vendor evaluation

Hazy synthetic data cuts time for Nationwide Building Society to evaluate innovation partners from six months to three days.

Innovate faster

Rapid innovation is the key to competitive advantage. Synthetic data enables rapid validation of internal projects and external vendors without long governance processes.

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40× faster data provisioning

Hazy helps global automotive company provision safe, representative credit risk data at lightning speed for multiple use cases.

Unlock insight

Data is trapped in departmental, subsidiary, security and geographical silos. Aggregate your data in more accessible, safer environments to run more holistic data analysis.

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New product revenue stream

Accenture used Hazy's synthetic data to build and test a new Fostering Better Finance application for their banking client.

Monetise data

Major revenue streams are blocked by regulation. Safely sell insights, not identities. Create new revenue streams by sharing the value of your data.

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Using synthetic data is the key to really accelerating so much in technology. I believe that we are on the cusp of a completely different way of thinking about data. Using the synthetic equivalent allows us to be much much more open with the data in sharing with partners and amongst different teams within Nationwide. After all there is nothing more private for our members than data which has never existed in real life. As we tune the generation of the synthetic data we can create the data at scale that we have never experienced, and yet it reflects reality; truly amazing.

Robert Lee

Nationwide Building Society