GMI Cloud Supports the Next Era of AI Factories with NVIDIA Vera Rubin

GMI Cloud, an AI-native cloud infrastructure company purpose-built for production AI, announced its support for the next era of agentic AI factories following the momentum of NVIDIA Vera Rubin platform at GTC 2026 Taipei.

As AI workloads evolve from single-model prompts into multimodal, long-running, autonomous systems, enterprises and developers require infrastructure that can support real-time reasoning, secure orchestration, high-throughput inference, and continuous AI operations at scale.

GMI Cloud is building an inference-native cloud platform designed to help AI builders deploy, scale, and operate production AI workloads with performance, flexibility, and security across the full model-to-application lifecycle. As AI evolves from a conversational interface into an intelligent operating layer capable of reasoning, taking action, coordinating complex workflows, and continuously learning from multimodal context.

These next-generation AI workloads demand a new class of infrastructure designed to support real-time, high-performance intelligence at scale. Requirements include high-throughput, low-latency inference for interactive applications, seamless deployment of multimodal models across text, image, video, audio, and agentic workflows, and advanced capabilities for long-context reasoning, memory, and orchestration. Enterprise adoption further requires secure multi-tenant environments, dynamic scaling for continuously operating AI systems, and optimized infrastructure orchestration that reduces token costs while maximizing resource utilization and efficiency.

Also Read: CIO Influence Interview with Kyle Wickert, Field CTO at AlgoSec

This is why GMI Cloud selected NVIDIA for its best and only full-stack end-to-end AI factory platform designed specifically for large-scale inference, agentic workloads, and production AI deployment.

The GMI Cloud platform brings together:

• High-performance AI infrastructure for AI training, inference, and production deployment
• Prime Inference for optimized, low-latency model serving
• MaaS APIs that provide unified access to proprietary and open-source models
• Dedicated Endpoints for enterprise-grade production inference
• AI infrastructure orchestration and optimization layers for scalable AI operations
• Agentic workflow infrastructure for sandboxed, tool-using, autonomous AI systems
• Multimodal-native deployment environments for next-generation AI applications

“GMI Cloud enables builders to move from prototype to production faster while maintaining the performance and reliability required for real-world AI systems by combining optimized compute orchestration, production inference delivery, and developer-friendly APIs,” said Alex Yeh, CEO and Founder of GMI Cloud.

“As AI factories increasingly process proprietary data, regulated content, model context, and agent memory, security becomes a critical layer of the AI infrastructure stack,” said Yeh.

GMI Cloud is aligned with NVIDIA’s vision for secure, high-performance AI factories and is adopting NVIDIA Confidential Computing to support trusted execution environments for next-generation AI workloads that require security and privacy of both models and data.

As enterprises scale AI from internal pilots to production-grade systems, secure infrastructure will become essential to enabling broader AI adoption.

Aligning with the NVIDIA AI Factory Ecosystem

NVIDIA Vera Rubin marks a major milestone in the evolution of AI factory infrastructure, bringing together next-generation compute, networking, security, and rack-scale system design to support the demands of agentic AI.

“GMI Cloud continues to deepen its alignment with the NVIDIA ecosystem because of the excellent economics for providers and customers – highest compute/watt, lowest token cost, vast customer offtake, and longest useful life,” said Yeh.

“Together, we will help developers and enterprises deploy advanced AI workloads globally — from multimodal inference and model APIs to dedicated endpoints and agentic infrastructure.”