SharonAI Holdings, Inc. Class A Common Stock 2026 Q2 Earnings Call

Hello everyone. Welcome to SharonAI's second quarter 2026 earnings call. I'm James Manning, CEO and co-founder of SharonAI. I'll begin with the highlights from the quarter and an overview of our market position.

I'll then cover some of our recent customer wins. I'll talk about some of the additional capacity and our capital strategy moving forward. The central message from the quarter is that we have materially increased each of the three inputs required to scale this business: AI factory capacity, contracted customer demand, and capital. Let me give you the headline numbers first. I'll unpack them. As of today, we have 212 MW of total secured AI factory capacity across Australia and New Zealand, which is an upgrade of 80 MW from our last guidance of 132 MW. 120 MW are contracted through multi-year take-or-pay agreements. I'll expand further on the updated capacity shortly. We expect to have more than 64,000 NVIDIA GPUs deployed by mid-2027.

We've raised approximately $2.2 billion USD of capital since December 2025. We've executed roughly $8.8 billion of total contract value year to date. Three months ago, our portfolio was comprised of 100 megawatts of capacity and $2.2 billion of TCV. The contracted book has grown by roughly four times, and our secured capacity has more than doubled since. That demonstrates both the strength of demand and our ability to expand our supply to meet it. On customers, the standout is a six-year strategic compute collaboration with NVIDIA, worth $4.9 billion in total contract value. Alongside that, we have signed a five-year take-or-pay agreement with a global AI lab worth $1.32 billion and a five-year take-or-pay agreement with a global technology company worth $950 million. A few days ago, we secured a five-year take-or-pay agreement with a global AI platform worth $373 million in TCV.

Notably, this is a B300 deployment with a record price of over $4 per GPU hour. On platform, we have a growing pipeline beyond our announced capacity. We've expanded our partnership with VAST Data to 600 petabytes of storage commitment, providing sufficient backend infrastructure support continued growth of up to 100,000 GPUs. On capital and governance, we completed a $1.6 billion oversubscribed financing round in June, which followed a $350 million convertible note in April. We've made three significant leadership appointments. Anuj Goel, formerly of Macquarie Group, joins as our CFO. Melissa Anastasiou joins as our chief legal officer. Andrew Penn has been appointed as a non-executive chairman of the board. Bringing in senior leadership of Andrew, Anuj, and Melissa's caliber strengthens our governance and ability to execute SharonAI, as SharonAI enters its next phase of growth.

I'm delighted to welcome the multiple new team members we have added across the organization, including technical, operations, and sales to the team. SharonAI is a leading Australian NeoCloud and trusted AI infrastructure partner. Sharon is purpose-built to power the next generation of artificial intelligence and high-performance computing. We do so through our partner-led ecosystem, enabling our customers to confidently build, train, and deploy AI that drives productivity, innovation, and growth for their customers and themselves. What that practically means is we design and operate AI infrastructure optimized for large-scale training, inference, and high-performance compute. We deliver GPU-as-a-service, AI platform layers, and high-performance storage as one integrated solution. We serve enterprise, government, hyperscaler, and AI natives. I'm often asked why are we well-positioned. I like to think of it this way. Our NVIDIA Cloud Partner status supports our prioritized access to NVIDIA's latest generation of GPUs.

Our networking storage and orchestration are purpose-built for AI and HPC workloads. Our Australian/New Zealand-hosted sovereign infrastructure is particularly relevant to regulated and data sensitive customers in the region. Our capital-efficient deployment model is built around partnering with leading data center operators to deploy their tier 3 and tier 4 facilities. By co-locating with the improved data center infrastructure, we accelerate our deployment, reduce capital requirements, and minimize the development risks associated with greenfield builds. Finally, while we're headquartered in Australia, our customers are global. Our contract wins this year emphasize just that point. I said last quarter that we solve for 1P and that's scarcity. Using that framework, which hasn't changed, I'd argue this quarter has validated it on all four fronts. From a GPU allocation, timely access to NVIDIA's GPUs remains one of the most critical constraints in this market.

Manufacturing constraints and demand from hyperscalers continue to limit the supply available to everyone, and emerging providers are facing long lead times. Our NVIDIA Cloud Partner status, and now a six-year collaboration with NVIDIA, puts us in a unique position to provide access to AI compute. Power. High-density GPU clusters need substantial, reliable power. However, ready data center sites with source power are becoming increasingly scarce due to grid constraints and long regulatory queues. Our multi-site data center relationships underpin our secure capacity, which has now grown to 212 MW. On the regulatory front, data residency and sovereignty requirements are becoming increasingly important across a number of markets. That trend supports our locally hosted model, and we extend our footprint this quarter with our first New Zealand facility. Finally, on capital and talent. Executing in this market takes significant capital and highly specialized HPC talent.

Our successful capital raisings to date address the first issue, and our senior hires, as I mentioned earlier, address the second, in addition to our ongoing technical team build-out. Let me spend a bit more time on NVIDIA and our relationship. This is a first-of-its-kind partnership, six years and initial 72 MW, 40,000 GB300s, and $4.9 billion of minimum revenue, or an average of $817 million of revenue per annum at the implied base rates. This partnership does two things. It expands our ability to provide compute access to the broader AI ecosystem, namely AI natives and enterprise customers. It reinforces supply certainty at scale through the NVIDIA Cloud Partner program. The other thing we've seen it do is reaffirm to our partners globally that Sharon is a regional leader in AI compute.

We are well positioned to expand our MW and GPU opportunities throughout the region with the support of all our partners and including NVIDIA. Next, I want to be clear about how this works commercially, because I think it's been misunderstood based on some of the commentary we've seen. Under the agreement, NVIDIA provides a six-year anchor commitment. That commitment helps de-risk the capital investment by providing NVIDIA guaranteed minimum revenue stream for the initial six-year period of the hardware deployed. This is viewed very favorably by debt providers who help fund the substantial capital investment in the GPUs and the associated infrastructure as they can bank the guaranteed revenues in their models. The pricing under this agreement is guaranteed as minimum only. That is, it provides a floor, not a ceiling.

We expect to secure customers for a significant portion of the GPU capacity at prices above the guaranteed minimum. In those cases, we retain 100% of the anchor price and then share the incremental revenue above it. Importantly, NVIDIA will share in this incremental revenue too, which creates a new strategic alignment with NVIDIA who are incentivized to support us to both deliver a premium GPU service and to source and secure higher rate paying customers to maximize the share of the incremental revenue. Importantly, if we perform successfully under the initial 40,000 GB300 allocation, we believe there may be an opportunity to expand the program over time. On the contracting model itself, not much has changed from what I described last quarter, but it's worth reiterating. Here's an example showing what a contract might look like. In month one, the customer contracts and prepays an amount.

That prepayment lets us submit the purchase orders for the specific GPUs and networking infrastructure in a way that reduces our upfront capital outlay. Over months one to four, we receive and install the hardware. The GPU and the other hardware is delivered within three to four months, and final payment lands on delivery, and installation and configuration takes two to four weeks. From month five onward, we recognize monthly revenue on reserved capacity for the full term. For a take-or-pay contract, we are paid irrespective of whether they use the compute 100% of the time or 40% of the time, which gives us real clarity on the expected revenues. At the end of the term, depending on tenure, there might be several years less useful economic life. We can recontract or sell to the on-demand market.