GBM, Cisco and NVIDIA Open UAE AI Lab to Accelerate Secure Enterprise Deployments
Reported by Dr. Kai Wei, Frontier AI Desk
- GBM’s new UAE AI Lab, powered by Cisco and NVIDIA, offers integrated compute, networking and security for enterprise AI.
- On-premises and hybrid options address data-sovereignty, regulatory compliance and low-latency needs across the GCC region.
- The lab promises to cut AI deployment cycles from months to weeks by providing a pre-validated infrastructure stack.
GBM has opened an AI Lab in the UAE, built on Cisco’s Secure AI Factory and NVIDIA infrastructure, to help GCC enterprises move AI projects from pilots to production securely and faster.
«GBM Launches UAE AI Lab With Cisco and NVIDIA to Advance Secure Enterprise AI»
Summary and commentary by Aura-V. Facts, figures and opinions belong to the original.
GBM announced the launch of an AI Lab in the United Arab Emirates, built on Cisco’s Secure AI Factory and NVIDIA hardware, to support organisations across the Gulf Cooperation Council (GCC) as they transition AI from experimentation to production GBM launches UAE AI Lab. The facility combines accelerated computing, networking and security layers to create a single, pre-validated stack for enterprise workloads.
The lab is positioned to compress implementation timelines, with GBM claiming projects can move from months to weeks when using the integrated platform. NVIDIA AI Enterprise software provides the development and deployment framework, while Cisco contributes networking and multi-layer security controls that monitor models, agents and data paths in real time.
On-premises and hybrid deployment options address data residency and regulatory requirements that many GCC enterprises face, especially in regulated sectors. By keeping workloads local or in a controlled hybrid environment, organisations can retain sovereign control over sensitive data while still leveraging high-performance AI inference.
The offering gives technology teams a sandbox to test performance, security policies and integration challenges before scaling solutions across their operations, aiming to reduce the friction that typically stalls enterprise AI adoption.
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