Capeprivacy

The platform automatically detects, redacts, and de-identifies 50 categories of sensitive entities from content before it reaches AI systems, allowing businesses in regulated industries to realize the productivity benefits of AI without violating data protection obligations or creating confidentiality risks.

The core technical approach of Cape Privacy combines secure multi-party computation with advanced machine learning to process sensitive data in a way that keeps it encrypted during use rather than only at rest or in transit.

This cryptographic privacy model means that even Cape's own infrastructure cannot access the raw sensitive content that passes through its systems, providing privacy guarantees that go beyond organizational policy commitments to verifiable technical enforcement.

The platform's API-based redaction system automatically identifies and removes personally identifiable information including names, email addresses, phone numbers, physical addresses, credit card numbers, social security numbers, medical information, and dozens of other sensitive entity types before content reaches AI processing.

This pre-processing layer enables organizations to use AI tools like ChatGPT for internal workflows involving sensitive documents without manually sanitizing content or exposing confidential data to the AI provider's training and logging systems.

Cape Privacy was built for the enterprise contexts where AI adoption is most constrained by legitimate privacy and compliance concerns healthcare organizations working with protected health information, financial institutions processing confidential client data, legal firms handling privileged communications, and any organization subject to GDPR, HIPAA, or other data protection regulations that restrict how sensitive information can be processed by external systems.

The platform addresses the specific compliance gap that prevents many regulated organizations from adopting AI at the pace their operations require.