As organizations expand their use of sensitive data for AI, analytics, modeling, and collaboration, they face a growing challenge: understanding how to protect and govern that data throughout the workflow, not simply determining whether a use case is compliant.

Karlsgate provides technology that can automate many of these protections, including de-identification, re-identification risk remediation, protected data matching and integration, data minimization, and governance policy execution. However, these capabilities address problems that can be difficult for prospective users to recognize or translate into their own data workflows.

The opportunity is to create an accessible, interactive tool that helps organizations describe a proposed data use case, identify the associated privacy and governance risks, and understand what protections and workflow design would be appropriate. The recommendations would be grounded in Karlsgate’s capabilities and architectural principles, allowing users to see how complex governance requirements can be operationalized rather than managed through disconnected policies and manual processes.

For Karlsgate, this creates a new way to educate the market and demonstrate the practical application of its technology. For students, it provides the opportunity to work directly with Karlsgate to understand real-world privacy-enhancing technology and translate those capabilities into a functional tool combining data governance, cybersecurity, AI, user experience, and software development. 

Success would be the development of a functional prototype that Karlsgate could realistically continue refining into a public-facing tool.

Key measures of success would include: