Announcing our Series A funding
We started Hazy in 2017 with the mission to set data free for businesses, without compromising individuals’ privacy. With this belief, we are thrilled to announce that we have raised $9m in Series A funding.
This round was led by Conviction VC and was joined by our existing VC investors including UCL Technology Fund and M12 (Microsoft). The round also includes several strategic investors including Wells Fargo, Nationwide Building Society, ACT Venture Partners, Terra VC and Neva SGR, the Intesa Sanpaolo bank venture capital company.
We’ve come a long way since 2017. Hazy is now the enterprise specialist in the synthetic data category with an incredible set of customers including Wells Fargo, Nationwide Building Society and Vodafone. Our product is specifically engineered to tackle the largest datasets out there, scale to complex enterprise environments and work hand in hand with existing enterprise technology.
There are several tail winds powering the synthetic data category right now. Generative AI has finally gone mainstream, the data access problem for enterprises has not gone away with tightening regulation and enterprises are increasingly looking to leverage sensitive data for technology transformation and innovation.
2023: the year for generative AI
There has been a lot of noise in the generative AI space in the last six months thanks to Open AI and the ripple effect of its technology across industries. But this is not just a flash in the pan, it is the culmination of years of investment and research within this space.
Some parts of the industry, like synthetic data, have already been around for some time and are being deployed in complex environments. Hazy was the first enterprise synthetic data provider and has been enabling enterprise firms to move faster and reduce compliance risk for six years.
There are many ways enterprises could adopt generative AI technologies, and now is the opportune moment to reap the benefits of this technology.
Five years on with GDPR
This year is also a momentous one in the privacy space: May 2023 marks five years since the inception of the GDPR. Despite being half a decade in, many enterprises, especially banks and telcos, are struggling to balance adhering to the regulation without slowing transformation.
The noose is also tightening for firms as the European Commission is set to significantly tighten its compliance requirements. Each national regulator must share an overview of its data-protection investigations six times a year and provide the Commission with an overview of all its large-scale cross-border investigations under GDPR.
This toughening stance on privacy is an existential threat for large regulated businesses. There is a stark ‘either/or’ trade off of which neither are desirable options: risk hefty fines and brand reputation damage, or slow digital transformation and lose to competitors.
But it doesn’t need to be an either or. Synthetic data can solve this challenge in many instances by producing a drop in replacement for real data, but with none of the PII of the original data which allows it to be free used and shared. According to Gartner, synthetic data will enable organisations to avoid 70% of privacy violation sanctions by 2025.
Speeding up AI adoption
Gartner has also predicted that by 2024, 60% of the data used for the development of AI and analytics projects will be synthetically generated. Our latest customer Vodafone is using synthetic data for just that - to train and test its machine learning models for customer value management. The synthetic dataset preserves the performance of the machine learning model, saving the team time, cost and in some cases even increasing the model performance.
An enterprise-grade platform
Since its inception, Hazy has been working with enterprise clients. Our product has been specifically developed to be deployed within our customers environments - be that on-prem or in the cloud - and our team has been built to drive enterprise success, from deployment to ongoing value creation.
This latest funding is being used to further bolster our platform’s capabilities. Some of the highlights of these are:
- Increased memory optimisation and secure cloud support
- Collaborative configuration and access control across teams
- Frictionless creation and delivery of synthetic data
- Assured quality of synth data generated via detailed built-in metrics
- Automated datatype detection and configuration
We can’t wait for this next phase of Hazy. If you’d like more information about how we’re working with customers such as Vodafone, Nationwide Building Society, Wells Fargo and BMW, get in touch.