Alpha Compute Corp., a technology leader in AI GPU-as-a-service (GPUaaS) and AI Confidential Compute, announced that it has rebranded from AlphaTON Capital Corp. to Alpha Compute Corp., with its common shares trading under the new ticker symbol ALP on the Nasdaq Stock Market. The rebrand reflects the Company's accelerating strategic growth and market demand for scalable AI compute infrastructure, with privacy-preserving confidential computing at its core.

The name Alpha Compute signals the Company's intent to lead the global race to build the AI infrastructure of the future. As artificial intelligence reshapes how the world stores, processes, and monetises data, the demand for sovereign, privacy-first compute has become structural. Alpha Compute is purpose-built for this moment.

"This rebrand is not cosmetic, it is structural," said Brittany Kaiser, CEO of Alpha Compute Corp. "From the moment I wrote Targeted and first testified before Congress and Parliament about data rights, my mission has been to ensure that the future of technology is built on privacy by design, not just policy and promises. Alpha Compute is the culmination of that mission: a publicly traded infrastructure company providing the world's most sensitive AI workloads with compute they can trust. We are entering the fastest-growing industry in history, and we intend to lead it."

The global AI market, valued at approximately $390 billion in 2025, is projected to reach $3.5 trillion by 2033 (Grandview Research, 2025), growing at a compound annual growth rate of more than 30 per cent. Global AI spending is expected to surpass $2.52 trillion in 2026 alone, a 44 per cent increase year over year (Gartner Group, 2025). The AI chip market sales were $200 billion in 2025, with the NVIDIA Blackwell architecture, the same generation powering Alpha Compute's infrastructure, driving the majority of that growth. NVIDIA's own fiscal year 2026 revenues reached $215.9 billion, up 65 per cent year over year (source: Nvidia press release), underscoring the relentless demand for advanced GPU compute.

Over 70 per cent of Enterprise AI Workloads will Require AI Confidential Computing

Within this market, confidential computing represents one of the highest-growth and highest-value segments. Enterprises in healthcare, financial services, government, and defence represent over $2 trillion in combined annual IT spending (Gartner), and cannot rely on standard cloud infrastructure for their most sensitive AI workloads. Alpha Compute solves this problem with an infrastructure that is private by encrypted architecture, not by promise. 

The convergence trend represents a significant market signal. Operationally, the key factor is that confidential computing is transitioning from a standalone market to the embedded security layer within the broader Secure AI Cloud stack. By 2026, over 70 per cent of enterprise AI workloads will incorporate sensitive data, thereby accelerating the demand for secure AI infrastructure (Fortune Business Insights). Consequently, the addressable opportunity is more accurately defined as a segment of the cloud AI market, specifically where stringent security and data sovereignty mandates restrict workload migration.

Regulatory pressure has become a compelling catalyst. The escalating use of AI within enterprises is driving major concerns around data sovereignty, as current infrastructure designs struggle to provide the necessary guarantees for regulated or sensitive workloads. As reported by Computer Weekly, the confluence of the EU AI Act enforcement in 2026, the updated FedRAMP 20x requirements, and various national data residency laws is creating a mandatory, rather than merely opportunistic, procurement cycle.