Privacy Dynamics, a startup that simplifies ethical and responsible use of data, launched today a SaaS application that can anonymize thousands of records per second with the click of a button. Privacy Dynamics saves data and analytics teams valuable time while also ensuring organizations pull compliant, accurate information from a central data warehouse.
Privacy Dynamics has raised $4 million in seed funding to improve their product offering, expand the team, and accelerate growth within the modern data stack ecosystem. Privacy Dynamics’ seed financing is led by Root Ventures, with participation from Crosscut, Slack, Geometry Ventures, Hypergrowth Partners, and several angel investors from companies such as Auth0, Flatiron Health, and Looker.
As organizations of all sizes become increasingly data-driven, over 130 jurisdictions worldwide have subsequently passed data privacy laws to regulate how companies collect and store personally identifiable information (PII). Previously, data and analytics teams anonymizing data would build manual transformations in SQL, which was time-consuming and required a level of legal expertise that few employees possess. Privacy Dynamics allows data scientists and non-technical users—including marketers, analysts, sales reps, and finance workers—to quickly access compliant data on-demand for business intelligence, analytics, machine learning, and data publishing.
“Too often, we hear from engineers that data is unavailable due to well-intentioned security policies designed to prevent a data breach. The problem is that these policies also prevent them from doing their jobs.” said CEO and Founder Graham Thompson. “We believe that Privacy Dynamics will transform how companies manage access to data, and we’re excited to see what our users can accomplish with centralized access to high quality, privacy-safe data.”
Privacy Dynamics’ approach to anonymization is based on fundamentals derived from differential privacy and k-anonymity. The company uses a combination of proven privacy techniques to calculate how each cell in a dataset is contributing to re-identification risk, then performs the minimum transformation required to prevent re-identification. This level of precision reduces data distortion by 90% compared to industry standards. Privacy Dynamics’ treatment of data satisfies several regulatory requirements including HIPAA, GDPR, CCPA. Privacy Dynamics is SOC-2 compliant and the application does not store customer data.
Privacy Dynamics was designed and built to integrate closely with the modern data stack. The plug-and-play framework means the application can be swiftly implemented for new accounts. Out of the box, Privacy Dynamics supports the major data warehouse providers including Snowflake, BigQuery, Azure, and Redshift.
“Privacy Dynamics provides best-in-class privacy by default; it can be easily integrated into an organization’s existing data stack, removing the friction caused by data privacy.” said Lee Edwards, Partner at Root Ventures. “Machine learning engineers can create training data on-demand, business intelligence teams can power dashboards without disclosing sensitive customer information, and data can be shared with external partners in near real-time, safely and securely.”