Patero and Orilla have announced a strategic partnership to develop a quantum-safe infrastructure platform designed for industrial AI deployments at the network edge.
The joint solution combines post-quantum cybersecurity technologies with edge-native AI infrastructure to secure industrial operations ranging from factories and ports to energy facilities and remote infrastructure networks. The companies said the platform is intended to address growing concerns around cybersecurity risks tied to the rapid expansion of AI-powered industrial systems.
Industrial operators are increasingly deploying AI across distributed operational environments to improve automation, analytics, and real-time decision-making. However, industry adoption has accelerated faster than the deployment of advanced security frameworks capable of protecting operational technology (OT), IoT systems, and industrial data pipelines.
The partnership comes amid growing global focus on quantum-resistant cybersecurity measures. Governments and defense agencies are urging organizations to begin transitioning toward post-quantum cryptography as advances in quantum computing threaten to weaken existing encryption standards over the coming decades.
According to the companies, the combined platform is designed to secure machine-to-machine communication, edge-to-cloud data pipelines, and remote operational workflows. The infrastructure also supports AI analytics, industrial automation systems, enterprise integration, and distributed operational environments.
Patero and Orilla said the platform introduces what they describe as a new category of “Quantum-Safe Industrial AI Infrastructure.” The solution is intended to protect long-lived industrial data against future “harvest now, decrypt later” cyberattacks, where encrypted data is collected today for decryption once quantum computing capabilities mature.
Key features include secure session-based quantum tunnels designed to replace traditional VPN architectures, crypto-agility aligned with evolving cybersecurity standards, and protection for distributed industrial systems operating across long lifecycle environments.
Peter Bentley said industrial infrastructure is becoming increasingly intelligent through AI integration, but warned that advanced connectivity also increases vulnerability without quantum-safe protection measures.
Lindi Sabloff said trust in infrastructure and operational data remains one of the largest barriers to broader industrial AI adoption. She added that integrating quantum-safe security into edge-native AI systems is intended to improve confidence in industrial automation deployments.
The companies noted that many industrial systems operate on infrastructure lifecycles ranging from 15 to 30 years, increasing the importance of long-term data protection strategies as quantum computing technologies continue to advance.
The joint platform is available immediately for pilot deployments, OEM partnerships, integration programs, and critical infrastructure applications targeting industrial and government sectors.
