Protecting AI and Sensitive Data in Collaborative Environments
Encryptiq provides the patented architecture for secure data processing and Confidential AI execution inside trusted execution environments in multi-stakeholder data ecosystems.
Built for infrastructure providers and regulated ecosystems.
AI Infrastructure is moving faster than trust
Organizations are rapidly deploying new AI capabilities across their infrastructure. On-premise large language models, AI agents interacting with enterprise systems, cross-organization AI collaboration, and the use of sensitive industrial and health data are becoming part of everyday digital operations.
While these technologies unlock significant innovation potential, they also introduce new trust challenges. Critical risks remain unresolved.
AI workloads must run in environments where data, models, and execution integrity can be protected by design.
From Confidential Computing to Confidential AI
Confidential Computing provides the foundation for secure data processing through hardware-isolated execution environments.
However, as organizations deploy AI systems and collaborate across infrastructure and organizational boundaries, additional challenges emerge.
AI workloads involve models, sensitive data, and autonomous agents interacting across multiple environments. Secure execution requires more than hardware isolation alone.
It requires a process architecture that governs how confidential data, AI models, and execution environments interact securely.
This evolution from secure data processing to Confidential AI is shaping the next generation of AI infrastructure.
Encryptiq defines the process architecture that governs Confidential Computing and Confidential AI
Encryptiq patented the process architecture for governing Confidential AI and data workloads across infrastructure and organizational boundaries. The architecture enables secure data processing, protected AI model execution, and verifiable runtime integrity inside hardware-isolated environments in multi-stakeholder data ecosystems.
Key capabilities
Confidential data processing across multiple organizations
Protected AI model execution in hardware-isolated environments
Attestation-driven runtime access control
Encrypted AI workloads with operator isolation
Secure collaboration without exposing sensitive data
Key benefits
AI models run directly on protected data
Data owners retain full control over access and usage
Infrastructure operators cannot access confidential workloads
Compliance can be enforced at infrastructure level
Sovereign AI Infrastructure
Secure AI collaboration is becoming a foundational requirement for modern digital infrastructure. Confidential AI enables organizations to collaborate on sensitive data while maintaining sovereignty, security, and regulatory compliance.
Where this matters
Sovereign cloud platforms
National health data infrastructures
Industrial data ecosystems
Regulated financial AI systems
Critical infrastructure analytics
Compliance and sovereignty alignment
GDPR-aligned data protection
European AI Act governance requirements
Sovereign cloud initiatives
National digital sovereignty strategies
Award-Winning Recognition
The technology underlying Encryptiq was recognized by the European Cyber Security Organisation (ECSO) as one of Europe’s most promising cybersecurity innovations at the Cyber Investor Days Award 2020.
The architecture also received the OVHcloud Startup Program Award 2022 – Rising Star, recognizing the technology developed through Securitee, one of the earlier ventures building on this Confidential Computing architecture.
These recognitions highlighted the potential of the technology to enable secure data processing, confidential collaboration, and trusted infrastructure for sensitive workloads.
Strategic Value for
Cloud & Infrastructure Providers
Encryptiq’s process architecture introduces a governance layer for Confidential AI and secure data processing across modern infrastructure environments.
Designed architecture for
Sovereign cloud operators
AI infrastructure platforms
Confidential compute environments
Regulated data ecosystems
The architecture enables to offer
Secure AI workloads
Confidential analytics on sensitive data
Attestation-based trust guarantees
Compliant cross-organization data collaboration
Key application domains include
Sovereign cloud environments
Industrial data ecosystems
National health data infrastructures
Financial sector analytics
Critical infrastructure operations
By embedding governance directly into the execution layer, Encryptiq helps infrastructure platforms deliver trusted AI and data capabilities in environments where security, sovereignty, and compliance are critical.
For research, collaboration, and infrastructure discussions get in touch here!
About
Encryptiq
Encryptiq GmbH is a German cybersecurity company founded by Christian G. Junger in 2025.
In 2017, Christian and his former teams started developing the core architecture behind what would become a DPMA-granted patent in 2019. Built with exceptional teams across two prior ventures in Confidential Computing and one successful exit later, the technology matured through real-world deployment in some of the most demanding data environments in the world.
Encryptiq holds the patent rights behind the process architecture for secure data processing and Confidential AI execution across hardware-isolated compute environments in multi-stakeholder data ecosystems.
The framework enables protected AI models, secure AI agents, and encrypted analytics workloads to operate on sensitive data without exposing it. By combining Confidential Computing with attestation-driven access control and policy-bound execution, Encryptiq enables secure AI & data collaboration across sovereign cloud infrastructures, regulated industries, and critical infrastructure environments.
Encryptiq was founded to establish the license market for Confidential AI process infrastructure.