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Delivering on the Promise of Synthetic Data

Replica Technologies

Our Data Synthesis Technology

Replica Analytics develops unique technologies for generating privacy protective synthetic data that maintains the statistical properties of real data. We enable fast and effective access to high utility data while meeting regulatory obligations.

Methods employed by Replica Analytics combine machine learning tools to generate synthetic data, and privacy assurance on synthetic data to ensure that the privacy risks are very small.

In addition, users can create data simulators and share them with other users on the platform. Our objective was to make data synthesis and the sharing of synthetic data as simple as possible for end-users. The software also has an API and development libraries in R and Python for use by data scientists and software engineers to rapidly create data synthesis pipelines and integrate data synthesis into existing pipelines.

Data Synthesis & Privacy Assurance

Replica Synthesis provides a highly automated and user-friendly capability to create synthetic data and to evaluate data utility and privacy. 

Key Features of Replica Synthesis

  • Synthetic Cohort Builder to query and integrate data from multiple data sources and generate synthetic variants of these cohorts.
  • Validation Server to re-run analytics code on the original data.
  • Produces a synthesis report which describes the data, methodology, the synthesis results, the utility results, and any limitations. 
  • Customizable synthesis parameters.
  • Can be deployed on the cloud or on-premises. Clients do not have to share their data to synthesize it.
  • Comprehensive REST API for integration with multiple and varied front ends.
  • The software is built for small and large datasets.
  • SDKs supporting multiple data science and software engineering end-users.
  • Flexible synthesis plan specifications to handle complex datasets.

Replica Synthesis Technology

  • Getting a real dataset from a client and using our machine learning tools and algorithms to generate a synthetic dataset for them
  • The process is largely automated – these synthetic datasets can be generated quickly and at scale
  • The outputs are the synthetic dataset with a report documenting the utility characteristics of the data
  • Utility assessment provides a comprehensive view of utility under multiple realistic conditions / workloads

Workflow designer UI allows for significant flexibility when building pipelines.

Privacy Assurance

Given the risks of not processing personal information properly under various legal regimes, privacy assurance gives you the compliance evidence needed.

Key features of privacy assurance technology include:

  • Uses validated metrics to evaluate multiple disclosure / privacy risks in the synthetic data.
  • Produces a detailed report describing the risk assurance methodology as well as the results of the risk assessment.

  • Employs state-of-the-art risk estimation models to evaluate data risk relative to the population.

  • The privacy assurance models also account for multiple types of privacy risks simultaneously.

Simulator Exchange

Generative models created during the synthesis process can be saved as data simulators using the Replica Synthesis simulator exchange, allowing the generation of synthetic data from these simulators. This way, data users can get access to realistic data without providing access to real data.

Key features of Simulator Exchange:

  • Generate synthetic data without direct access to data
  • Share the “Model” instead of sharing data
  • Get the same results as if you had the original data
  • As only models are shared with data users, the privacy risks are minimized, making it easier for data providers to make their data available

Why Replica Synthesis?

Built for Handling Complex Data 

Trustworthy Synthetic Data

Enabling AI Innovation through Rapid Data Access 

Flexible Deployment


Access our multi-tenant deployment of Replica Synthesis on the cloud


No need to send data externally
for synthesis.

Virtual Private Cloud

Deployed on a client's Virtual Private Cloud

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