AI Moves From Experiments to Governed, Production-Grade Systems
Enterprises are accelerating AI adoption but struggling to operationalize it securely across complex environments. Research cited by Unisys shows that only 36% of organizations feel ready to support large-scale AI workloads, underscoring a widening gap between ambition and operational reality. As models, data pipelines and agents proliferate, AI infrastructure governance and enterprise AI security become central concerns rather than afterthoughts. The latest wave of partnerships focuses on solving these foundations: connectivity, orchestration, policy control and automation across hybrid and multi-cloud AI orchestration landscapes. Instead of competing on access to models, providers are collaborating to deliver control layers that standardize how intelligence is deployed and monitored. Three recent partnerships – Unisys with Rafay Systems, LTM with SSP Group, and Persistent Systems with Kong – illustrate how enterprises are re-architecting AI infrastructure to meet regulatory, performance and cost pressures while maintaining agility.
Unisys and Rafay: Orchestrating Hybrid Cloud AI in Regulated Environments
Unisys and Rafay Systems are targeting one of the hardest problems in hybrid cloud AI deployment: running GPU-intensive and private AI workloads across public, private and edge environments under strict governance. Their partnership delivers a unified, intelligent AI software layer that spans agents, models and modular AI infrastructure as a SaaS offering. This approach simplifies lifecycle management, governance and financial control, enabling organizations to move AI from experimentation into production with consistent policies and visibility. Rafay’s platform provides hybrid cloud orchestration, including Kubernetes management and cost optimization, while embedding governed self-service into broader cloud operations. For regulated and sensitive use cases, integrated security and governance support AI workloads across on-premises, edge and cloud, helping enterprises adopt agentic frameworks and workflows with confidence. The result is multi-cloud AI orchestration that balances flexibility with compliance and standardized controls across diverse environments.
LTM and SSP Group: AI-Powered IT Infrastructure Support and Automation
LTM’s expanded partnership with SSP Group shows how AI is reshaping day-to-day IT infrastructure operations. Positioned as a “Business Creativity” partner, LTM will provide modernized, end-to-end IT infrastructure support and application maintenance, powered by its BlueVerse ecosystem. The focus is on reducing operational risk, simplifying complex infrastructure and applications, and using AI-led automation to enhance agility and customer experience. By infusing AI into support workflows, SSP aims to move toward an intelligent, streamlined IT estate that can scale with its global operations. Data-driven decision-making, faster innovation cycles and cost optimization through automation are central themes. While this collaboration is less about building new AI platforms and more about transforming existing IT, it reinforces the trend that hybrid cloud AI deployment requires not only governance and security but also smart, automated support structures that keep critical systems resilient and efficient.
Persistent Systems and Kong: API Governance as the Control Layer for GenAI
The partnership between Persistent Systems and Kong puts API governance GenAI at the center of enterprise AI strategy. As organizations move AI into production, the bottleneck is not access to models but how APIs, data pipelines, models and agents are connected and controlled. Persistent, as Kong’s global systems integration partner, is helping enterprises implement Kong’s unified API and AI connectivity platform as a scalable control layer across hybrid and multi-cloud environments. This includes modernizing legacy API estates, enforcing policy-driven safeguards such as PII protection and centralized access management, and providing end-to-end observability. Together with Persistent’s GenAI Hub, the joint offering supports GenAI and agentic workflows, including Model Context Protocol-based architectures, with built-in security and governance. This enables enterprises to move from isolated pilots to governed, production-grade AI systems where connectivity, compliance and reliability are engineered into the fabric of AI interactions.
Governance and Security Become the Cornerstones of Enterprise AI
Across these three partnerships, a clear pattern emerges: enterprises are prioritizing AI infrastructure governance and security over one-off use cases. Unisys and Rafay are tackling hybrid cloud AI deployment and resource-intensive workloads with governed orchestration and financial transparency. LTM and SSP Group focus on embedding AI into IT operations to manage risk, automate support and simplify complex environments. Persistent Systems and Kong, meanwhile, position APIs as the control plane for enterprise AI, enforcing policy-driven security and compliance across multi-cloud AI orchestration. Collectively, these moves show that scalable AI is no longer just about choosing models or clouds; it is about building a robust control layer that unifies orchestration, observability, access control and cost management. As AI adoption accelerates, enterprises that invest in secure, governed infrastructure will be better positioned to translate experimentation into sustainable business value.