Zettabyte and LiteOn have officially announced a new research and development collaboration aimed at evaluating a next-generation distributed edge AI inferencing platform known as the Ultra Edge Pod. This initiative marks an important step forward as both companies work to bring artificial intelligence processing closer to mobile users through infrastructure deployed directly at cell towers and nearby network locations.
To begin with, the initial rollout will focus on deploying a specialized Mobile Edge Compute (MEC) AI inferencing platform at cell towers, tower-adjacent facilities, and other network-proximate infrastructure. By doing so, the project aims to move AI inference workloads closer to end users, which will significantly reduce latency and improve real-time responsiveness.
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Moreover, MEC platforms can play a critical role in supporting countries that lack mature data center infrastructure. Instead of relying solely on centralized computing hubs, this approach enables nations to accelerate digital transformation and achieve AI readiness for both citizens and enterprises. As a result, edge deployments like this could open new possibilities for AI-driven services in regions where traditional infrastructure remains limited.
Under the collaboration, LiteOn will take responsibility for delivering the essential physical components needed for these distributed edge deployments. This includes power systems, cooling solutions, and overall infrastructure support. Meanwhile, Zettabyte will provide the advanced software layer that will manage GPU scheduling, orchestration, observability, and remote operations. Together, these contributions will allow MEC deployments to harness the combined computing power of multiple cell towers, creating a more unified and scalable edge AI environment.
In addition, the deployment is designed to demonstrate how tightly integrated infrastructure and software can enable reliable, cost-effective, and low-latency AI inference in highly distributed telecom environments. This is especially important because tower-based deployments face real-world limitations such as power availability, thermal constraints, and space restrictions.
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The planned Edge AI Deployment will also support low-latency, location-aware AI workloads operating closer to mobile users, radio access networks, and data sources. Furthermore, it will validate the feasibility of running GPU-based AI computing in power-and-space constrained telecommunication scenarios managed by tower companies and telecom providers.
“This deployment allows both teams to validate a practical and scalable model for edge AI deployment, emphasizing repeatability, resilience, and operational efficiency through a clear separation of infrastructure and software responsibilities,” says Kenneth Tai, chairman of Zettabyte.
“LiteOn’s experience in power systems, thermal management, and physical infrastructure positions the company to support emerging edge AI use cases through disciplined, deployment-driven collaboration,” says Jason Tsao, Associate Vice President and Head of Direct Current Microgrid at LITEON.
Overall, this collaboration highlights a major move toward scalable, low-cost edge AI infrastructure that could reshape how AI services are delivered in distributed telecom environments worldwide.
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