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Delivering on the Promise of Synthetic Data

Share and reuse sensitive data for internal and external use.

Get realistic data for software testing and vendor evaluations.

Augment small datasets for research and clinical trials.

Provide access to data simulators and track utilization by your data users.

Introducing Replica Synthesis 

Synthetic data generation with a strong focus on privacy

As a premier provider of Synthetic Data Generation technology, we understand contemporary concerns with data sharing and privacy. 

Using real, client-supplied datasets, Replica Analytics employs its machine-learning and deep learning technology to generate privacy-preserving and high utility synthetic data while retaining the patterns and statistical properties of the original data.

Our solutions will work with large datasets, small datasets, as well as tabular and longitudinal data.

Share your synthetic (non-identifiable) data more freely with minimal administrative and technical controls. And yes, get comprehensive documentation regarding the utility characteristics of the data, and a comprehensive privacy risk assessment.

Don’t stop half way when managing privacy risks

Given the risks of not processing personal information properly under various legal regimes, our privacy assurance technology gives you the compliance evidence needed to demonstrate very small privacy risks in your synthetic data.

We provide a unique solution to evaluate multiple disclosure risks in synthetic data. If you are generating or using synthetic data, your legal team will want assurances that this synthetic data is not personal information. Our privacy assurance solutions implement a complete risk assessment methodology.

Applications of Synthetic Data Generation

Share. Augment. Amplify.

Share Data with Trustworthy Privacy

Regulation, cost and other factors can at times impede the great many societal and organizational benefits of sharing data.

Replica Synthesis is the solution and the future of data sharing within and across borders. 

  • As there is no one-to-one mapping between real data and synthetic data, data generated by Replica Synthesis has a very small risk of identifying individuals
     
  • It is a safe way for organizations to share and reuse sensitive data internally and externally
     
  • Replica Synthesis significantly improves over current de-identification methods
     
  • Ours is the only complete privacy assurance model and process on the market today covering multiple disclosure risks simultaneously

Augment & Amplify Your Data

  • Virtual patients can be simulated to augment patients recruited in real clinical studies, and to rescue studies that are unable to recruit patients or that have high attrition
     
  • Replica Synthesis has built-in tools to amplify small datasets (e.g., for rare diseases and pediatric populations)
     
  • Biases in data are now a big problem – Replica Synthesis can correct for known biases and imbalances in data

Share. Augment. Amplify.

Share Data with Trustworthy Privacy

Regulation, cost and other factors can at times impede the great many societal and organizational benefits of sharing data.

Replica Synthesis is the solution and the future of data sharing within and across borders. 

  • As there is no one-to-one mapping between real data and synthetic data, data generated by Replica Synthesis has a very small risk of identifying individuals
     
  • It is a safe way for organizations to share and reuse sensitive data internally and externally
     
  • Replica Synthesis significantly improves over current de-identification methods
     
  • Ours is the only complete privacy assurance model and process on the market today covering multiple disclosure risks simultaneously

Augment & Amplify Your Data

  • Virtual patients can be simulated to augment patients recruited in real clinical studies, and to rescue studies that are unable to recruit patients or that have high attrition
     
  • Replica Synthesis has built-in tools to amplify small datasets (e.g., for rare diseases and pediatric populations)
     
  • Biases in data are now a big problem – Replica Synthesis can correct for known biases and imbalances in data

Easy to use. Accessible. Maintaining High Utility & Privacy.

Build a Workflow

Connect to data sources, define cohort and define synthesis parameters.

Synthesize Data

Synthesize cohort, generate utility assessments and produce report. 

Export Data

Export synthetic data and transfer to Jupyter notebook for analysis.

What Users are Saying

What Users are Saying

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