Enable cross boundary data analytics

Hazy’s synthetic data generation lets you create business insight across company, legal and compliance boundaries — without moving or exposing your data.

Synthetic data

A new paradigm in information transfer

Hazy uses advanced generative models to distill the signal in your data before condensing it back into safe synthetic data.

Synthetic data generation and transfer illustration

1. Train

Hazy uses generative models to understand and extract the signal in your data.

2. Distill

These models can then be moved safely across company, legal and compliance boundaries.

3. Condense

Before then being used to generate statistically equivalent synthetic data.

4. Use

That's drop-in compatible with your existing analytics code and workflows.

Use cases

For cross boundary data analytics

This allows you to gain and share insight across company, legal and compliance boundaries, without moving or exposing your data.

Cloud Analytics

For: Cloud Analytics

Run analytics workloads in the cloud without exposing your data.

  • Harness cloud compute
  • Use cloud ML pipelines
External Analytics

For: External Analytics

Access specialist external data analysts and externally hosted tools and services.

  • Access the best specialists
  • Use external tools and services
Data Innovation

For: Data Innovation

Evaluate algorithms, projects and vendors without data governance headaches.

  • Increase speed of innovation
  • Without risking live data
Data Monetisation

For: Data Monetisation

Sell insights and leverage the value in your data without exposing sensitive information.

  • Safely monetise your data
  • Create new revenue streams
Data sourcing

For: Data sourcing

Access, aggregate and integrate synthetic data from internal and external sources.

  • Access sensitive data
  • Drop-in compatible

In enterprise financial services

Hazy focuses purely on enabling enterprise analytics and specialises in the financial services data domain.

Enterprise class capability

Enterprise class capability

An enterprise class software platform and a track record of successfully enabling real world enterprise data analytics.

Enterprise class capability
Financial services data

Financial services data

Advanced generative models that can preserve the relationships in transactional time-series data and real-world customer CIS models.

Financial services data
Formal privacy guarantees

Formal privacy guarantees

Formal differential privacy guarantees that ensure individual-level privacy and can be configured to optimise fundamental privacy vs utility trade-offs.

Formal privacy guarantees
Case study
"Often one of our biggest challenges as we develop innovative analytics solutions is accessing customer data."
Patrick Hegarty

Patrick Hegarty

Global Centre for Innovation

Hazy helped the Accenture Dock team deliver a major data analytics project for a large financial services customer. Accenture were aiming to provide an advanced analytics capability. However, their ability to do so was blocked by data access constraints.

Hazy generated a synthetic version of their customer’s data that preserved the core signal required for the analytics project. This unblocked Accenture’s ability to analyse the data and deliver key business insight to their financial services customer.


“Hazy has the potential to transform the way everyone interacts with Microsoft’s cloud technology and unlock huge value for our customers.”


“By 2022, 40% of data used to train AI models will be synthetically generated.”


“At Nationwide, we’re using Hazy to unlock our data for testing and data science in a way that signicantly reduces data leakage risk.”

Hazy’s customers

Next step

Find out more

Find out more aboout Hazy's use cases in enterprise data analytics and how to contact sales.