Technology startup has launched the first data protection and privacy management and control solution born of the enormous growth of privacy regulation globally.

Specifically designed to meet the stringent requirements of the EU General Data Protection Regulation (GDPR), as well as those of other privacy regulations, the suite of solutions provides continuously updated visibility into the data flows within an organization, enabling privacy and security stakeholders to locate all personal data—be it known or unknown, structured or unstructured, in motion or at rest. GDPR sets the guidelines for how global organizations store, process, and share personal data collected from organizations established in the EU in order to protect data subject rights.

The solution maps the organization’s personal data flow to business processes, outlining how information is being shared within the network and with partners and international organizations. It is also able to auto-classify (i.e. identify and categorize data by type with no user intervention). 

“Our mission is to provide organizations with an efficient, simple, and inexpensive means of tracking personal data -- not just for GDPR, but for all compliance and security purposes,” said CEO and co-founder Zak Rubinstein. “[O]ur solution helps companies show privacy regulators that they are taking reasonable steps to protect personal data, and much more. It essentially provides significant support for compliance with all privacy rights involving data access, rectification, erasure, processing restrictions, third-party sharing, notification and data portability.” is available as hardware or for installation on a virtual appliance and works by combining several cutting-edge and proprietary technologies and techniques, including:

Network tapping: Leverages network taps to analyze traffic in a seamless and non-intrusive manner; automatically and perpetually discovers which repositories, assets and applications are holding, processing or sharing personal data.

Data mapping: Creates neural networks of personal data flow and business processes, outlining which network elements are communicating personal data with each other, how and why.

Natural language processing: Differentiates between personal data and sensitive personal data.

Artificial intelligence algorithms: The system self-learns to identify other assets that are storing, processing or sharing personal data based on an automatically generated profile.