No need for a Data Scientist or Machine Learning Expertise! Creating Synthetic Data for Numerous Use Cases – from Software/API Testing to Sharing Real Data Internally and Externally without worrying about Privacy Breaches!
Current approaches make Synthetic Data creation much harder than it needs to be! Advances in Generative AI, especially Generative Adversarial Networks (GANs) have made it easier do it. We remove all the friction in generating Synthetic Data from Real Data while assuring that it has all the same characteristics and privacy is assured with the latest privacy assurance algorithms!
We noticed that the need for Synthetic Data spanned many use cases – Sharing Real Production Data internally and externally without worrying about Privacy Breaches; using Real Data but changing its characteristics so that statistical distributions for some columns be adjusted for software and API testing and safely using Real Data when it contains highly sensitive data like Credit Card Information, Personally Identifiable Information (PII) and Personal Health Information (PHI).
The founders were in just too many meetings with Private Industry and Public Sector agencies where the need for Synthetic Data came up as a much-needed capability in 2020’s. So we founded brewdata in 2022 to do something about it!
We further noticed that in order for Synthetic Data Generation to be adopted more broadly, the following requirements need to be met:
brewdata was conceived by three technology veterans who want to remove all the friction in Synthetic Data Creation. The tools should be usable by just anyone, not just those who have Machine Learning expertise or be Data Scientists.
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