At the ASUS AI Tech 2026 event, the company has announced they will be moving up the “AI food chain” by shifting itself from a purely standalone hardware vendor to a “complete AI factory” platform, and they will be working alongside NVIDIA and a long list of partners including AMD, Intel, Samsung, IBM, and Schneider Electric to help businesses actually operate AI at production scale, not just run it.
The idea here is that ASUS now covers the whole AI infrastructure stack, everything from computing and networking to storage, deployment software, and governance, all tied together into one continuous platform. Utilizing NVIDIA DSX Sim Blueprint alongside partners like Schneider Electric, AVEVA, and IBM, ASUS lets organizations simulate and validate their entire AI factory setup as a digital twin before anything gets physically installed, catching bottlenecks and configuration issues ahead of time rather than after deployment.
Once things are actually running, that oversight continues through ASUS’s management tools and its broader AI Software Stack, which handles things like resource management, billing, and connecting enterprise governance directly to AI agents so companies can keep tabs on increasingly autonomous systems.
On the hardware side, ASUS rolled out a pretty wide range of gear depending on what companies need. For massive AI factories, there’s the AI POD XA VR721-E3 built on NVIDIA’s Vera Rubin NVL72 platform, which ASUS says delivers 10 times the performance per watt compared to the previous generation. For agentic AI workloads, the XA P2N-E2 pairs dual NVIDIA Vera CPUs with GPU support for reasoning and orchestration tasks. On the edge and visual computing side, the ESC8000-E12P brings RTX PRO Blackwell GPUs into the mix, while the compact PE3000N targets robotics and industrial automation. ASUS also rounded things out with new storage systems built to handle the data demands of modern AI pipelines.
Beyond the hardware itself, ASUS showcased some real-world use cases too, including Foxlink’s work on autonomous robotics and Aleria’s focus on sovereign AI deployments that keep data control localized. Looking forward, ASUS says the goal is to help companies shift from just buying AI infrastructure to actually embedding intelligence across their operations, with an eye toward cutting costs, reducing waste, and shortening the time it takes to see real returns on their AI investments.
