Automate Prod Data Replication for Dev + Test.

Synthetic data doesn’t cut it, and using production data is dangerous. Discover a safer, more efficient way to handle your data.

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Use Cases

Most Popular Use Cases

Privacy Dynamics is powering a world where ethics, data insights, and personalized technology can all co-exist to support business growth and customer privacy.

Dev + Test Data

Keep the complexity and richness of your raw data, without all the risk. You can use production data to seed development, test, and preview environments without disclosing customer data and violating SOC-2.


Build metrics off anonymized data to simplify governance and RBAC. Don't restrict access to sensitive columns like postal code and birth date; use anonymized values instead.


Shift your compliance and regulatory procedures directly into the DevOps space. By addressing compliance early in the development cycle, you alleviate future burdens on your teams. Made for sectors handling healthcare, financial data, and sensitive customer information.


“It didn't make sense to build a data minimization solution ourselves when Privacy Dynamics would give us a more comprehensive solution on day 1.”

Alda Pontes

Head of Technology, House Rx

Works with Your Tools

Privacy Dynamics persists anonymized data back into your database, warehouse, or data lake, so you can use it just like the raw data.

Analyze. Anonymize. Utilize.


of the U.S. population can be uniquely identified by only their 5-digit zip code, gender, and date of birth.



known data breaches in 2021


per PII record = the average cost to businesses

Latest Blogs

Data Anonymization in AI

Data Anonymization in AI: A Path Towards Ethical Machine Learning

Data is the new oil, lubricating the engines of Artificial Intelligence (AI) and Machine Learning (ML), ceaselessly driving us towards an era of automated enlightenment. However, as we guzzle down this invaluable resource, there's a lingering side effect of ethical indigestion. Reality hits hard when we realize that amidst this data binge, we might be inadvertently serving up generous portions of personal or sensitive information on the platter of AI/ML training and applications.

Data Masking vs Data Tokenization: Differences And Which To Choose

Data Masking vs Data Tokenization: Differences And Which To Choose

The endless stories of data breaches that decorate the headlines testify to how vital robust data security frameworks are. Amidst an array of data protection mechanisms, Data Masking and Data Tokenization emerge as prominent players. These data security tools are not only pivotal in safeguarding sensitive information but also play a crucial role in ensuring compliance with evolving data privacy laws.