SiliconANGLE: Neocloud Infrastructure and QumulusAI’s Compute Strategy

SiliconANGLE recently published an in-depth profile of QumulusAI and our approach to GPU-powered cloud infrastructure for artificial intelligence workloads. Written by Zeus Kerravala, principal analyst at ZK Research, the piece explores what sets neoclouds apart in today's AI infrastructure landscape and why enterprises are increasingly looking beyond traditional hyperscalers for their GPU compute needs.

The article digs into our full-stack ownership model—from power and data centers to GPU-accelerated cloud services—and how we're addressing the massive gap between AI compute supply and demand. CEO Michael Maniscalco shares our strategy of deploying smaller, modular compute clusters that can reach the market faster and more cost-effectively than gigawatt-scale data center campuses. While hyperscalers serve the OpenAIs of the world, there are millions of businesses that need flexible, affordable access to GPU infrastructure for model training, inference, and AI development. That's the opportunity we're going after.

Kerravala also highlights what makes our approach different: flexibility in architecture, transparent pricing, and a developer-friendly experience that abstracts away data center complexity. Whether you're a consulting firm scaling AI solutions for clients or a development team building the next generation of AI-powered applications, the goal is the same—getting reliable GPU compute into your hands quickly without the usual barriers. Read the complete article on SiliconANGLE for Maniscalco's full thoughts on the neocloud market, our partnership strategy, and where AI infrastructure is headed.