Privacy Controls for Data Flow Data Flow

Integrate privacy controls into data flow. Combine active user consent and policies to filter data as data moves between systems.

With ConsentGridā„¢ Privacy Controls for Data Flow technology your organization can:

  • Eliminate development and maintenance costs for ad hoc privacy implementations,
  • Manage data exchange and data usage policies with reusable privacy components,
  • Remove or mask sensitive data based on policies and consent as data moves between systems,
  • Implement privacy-by-design principles by embedding automated privacy controls into data processes.

Secure and Private

Privacy controls for data flow technology uses components that are installed on the host data center or cloud provider. Sensitive data never leaves the host network.

Filter/Mask Data

ConsentGridā„¢ works as 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.

Data Agnostic

Privacy controls for data flow uses schemas to add a privacy layer to JSON, XML, and CSV documents.

Anonymize, pseudonymize

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


Build data exchange policies for third parties and privacy-aware views for internal uses of data by composing overlays that annotate or process data.

Integrate consent to data flow

Integrate user consent to data flow to only process records with valid consent. Use granular consent to remove parts of data during data exchange.

How does it work?

Privacy control for data flow technology uses components that are installed at the host organization network. These components provide APIs that can be called as data moves from one system to another, when result sets are computed, or before sharing data with third parties. Sensitive data never leaves the local network.

1 Use schemas to describe your business entities used in data processing and data exchange.

2 Define overlays to classify data, to represent privacy constraints on fields, and to mask/remove fields.

3 Define data flow policies by combining overlays.

4 Use ConsentGrid™ APIs to process data with privacy controls before exchanging data with a third-party, before loading data to a data warehouse, or after extracting data from a system for processing.

Contact us to learn more about privacy controls for data flow. We will show you how it works and integration options for your platform.