Infortrend Technology, Inc., a provider of enterprise storage and AI infrastructure solutions, has announced the launch of its new KS 3000U edge AI server, targeting mid-sized enterprises and distributed locations looking to run AI inference closer to where data is generated.

As organizations increasingly push AI workloads away from centralized cloud environments, the move toward edge-based processing is gaining momentum due to concerns around latency, rising cloud costs, and data security.

Industry analysts point to a significant shift underway. By 2030, nearly half of all enterprise AI inference workloads are expected to be processed locally at the edge.

This transition presents challenges for organizations with limited on-site IT expertise, where deploying and managing complex AI infrastructure can be difficult. Infortrend positions the KS 3000U as a turnkey platform designed to simplify this process while delivering enterprise-grade availability.

The KS 3000U integrates compute, storage, operating system, and application management into a single system, allowing organizations to deploy containerized AI applications with minimal setup.

The platform can be deployed in under 30 minutes and supports a two-node cluster configuration that enables automatic failover, making it suitable for remote or lightly staffed locations that require continuous availability without dedicated IT teams.

Performance is another core focus of the new platform. Powered by AMD EPYC 8004 Series processors, the KS 3000U supports up to two GPUs, including NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition, along with low-latency NVMe SSDs.

This configuration enables real-time, on-site AI inference, reducing dependence on cloud connectivity while keeping sensitive data local and lowering bandwidth costs.

Designed for environments beyond traditional data centers, the KS 3000U features a compact 2U chassis with a short-depth form factor. It is available in standard and low-noise models, enabling deployment in edge racks or people-occupied spaces.

The platform is aimed at use cases such as real-time video analytics in retail, automated inspection and predictive maintenance in manufacturing, and AI-assisted diagnostics and remote patient monitoring in healthcare, reflecting the growing demand for edge AI across industries.