Privacy Governed Data FlowData Flow

Integrate privacy controls into data flow. Combine active user consent and preferences with policies to govern data in-flight.

ConsentGrid™ allows organizations to implement privacy-by-design principles by embedding automated privacy controls into business practices. With privacy governed data flow, organizations can remove or mask sensitive data as it moves between systems while keeping a record of data use. This builds an automated data map showing what type of data is stored where or shared with whom. With ConsentGrid™ privacy governed data flow, companies can smoothly integrate user preferences as well as organizational privacy policies into their data flow without interruption, respond to the changing regulatory expectations, and empower their users by letting them decide how their data is used.

Filter/Mask Data

ConsentGrid™ is a filter intercepting data flow between applications or organizations. It tracks the flow of personal data between data processing locations and uses consent and policies to filter or mask data in-flight.

Automated Data Mapping

ConsentGrid™ builds an automated data map at the data subject level. Organizations can respond to data subject requests (DSARs) quickly and accurately using ConsentGrid™ data maps.

Sanitize, anonymize

Mask, filter, or redact data fields using consent and organizational policies based on the situation at hand. Sanitize or anonymize data in-flight as it moves between systems or locations.

Manage Locations and Data Entities

Use JSON/XML schemas to describe business entities and assign privacy labels at entity or field level. ConsentGrid™ works with standard (such as FHIR for medical records) or custom schemas developed for business specific purposes.

Define physical or logical location where data is captured, stored or processed, so you can track and control data movement between locations.

Data Labeling

ConsentGrid™ uses a rule-based data labeling system to assign privacy labels to fields using structural information (schemas, field names), field content, or contextual information. Use JSON Pointers, XPaths, value sets, patterns to select and test fields, and apply privacy labels to data in-flight.

Data Filtering and Masking

Define filtering and masking rules to sanitize, anonymize, or pseudonymize sensitive data based on privacy labels of each data element.

Data Flow Pipelines

Define data pipelines between locations to filter and mask data using privacy policies, consent, and contextual information. Map, track, and control data as it moves between systems and organizations.


Privacy governed data flow is current in beta and available to a limited number of customers. Contact us for more information about our beta program.

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