Cape Privacy is the data privacy solution for collaborative data science and machine learning.
Easily integrate data privacy into your workflows
Request data access for your project, select the advanced privacy and security policy and get to work in minutes.
Collaborative data privacy
Cape Policy and Cape Projects offer a collaborative workflow that guides cross functional contributors to work together on projects and policies. This upfront work saves weeks of meetings to get to a policy decision and accelerates data science projects.
Project-specific policy for your data science
Apply the most advanced privacy techniques for your data projects. Writing policy to set privacy and security measures for your projects effectively balances the need for data privacy and data value. Projects empower users to see, manage and define how data is accessed and under what protections.
Audit and monitor your data science
Cape allows you to set project-specific monitoring and auditing configurations to ensure you have the logs you need. Review the policy for a project, propose policy changes and approve the active policy with a few clicks. Activity monitoring is easily done from your favorite environment.
Integrates into your data workflows
Who uses Cape Privacy?
Data Scientists & Engineers
Safe and trusted data science development
Data Protection Officers
Collaborative oversight with a single privacy lens
Information Security Analysts
Collaborative workflow policy for GDPR and CCPA
- Design, deploy and enforce distributed data privacy and security policies
- Enable self-serve access to data through advanced privacy techniques and privacy-preserving machine learning
- Apply data governance in policy for increased security and compliance
- Manage trust with context and structure around the data sensitivity, user identity and model deployment
How it’s used in the real world
Bring together your data science and compliance experts to create faster workflows, better insights and maintain customer and organizational trust.
Creating fine-grained access control rights for unique cloud services protects against threats and accelerates cloud migration.
Collaborative machine learning allows financial institutions to partner with other organizations and work together on model development.
Creating collaborative policy design and machine learning with security and privacy guarantees enables cross-organizational machine learning using PHI, health and clinical trial data.
Applying privacy-preserving techniques to things like location, or other personal information, allows the sharing of data without fear of abusive repercussions or surveillance.
Learn from customer data while building customer trust
Cape has developed The Trust Management Maturity Model (TM3) as a framework for cross-functional collaboration that allows you to spend less time developing policy and more time deploying them. Utilizing Collaborative Privacy and Trust Policy Design provides a context-aware policy development process to ensure machine learning deployments are compliant and secure.
Collaborative Privacy and Trust Policy Design is the foundation of the TM3. It provides a context-aware policy development process to ensure machine learning deployments are compliant and secure.
We make data privacy accessible
We’re helping to grow an open community that will change the worlds of Data Privacy and Data Science, and we want you to be part of it.
Technology should protect our privacy by default
Our mission is to help data solve important problems without compromising privacy.