SharonAI Holdings Inc. (SHAZ) Earnings Call Transcript & Summary

Good day, everyone, and welcome to the SharonAI Second Quarter 2026 Conference Call. [Operator Instructions] Please note, this conference is being recorded. It is now my pleasure to hand the floor over to your host, Ross Barrows, Head of Capital Strategy and Investor Relations. Sir, the floor is yours.

Good afternoon, and welcome to our earnings call to discuss SharonAI's operating results for the quarter ended June 30, 2026. Joining me today is James Manning, SharonAI's Chief Executive Officer; and Tim Broadfoot, SharonAI's Chief Financial Officer. I'll now take a moment to read the safe harbor statement. During the course of this conference call, we may make certain forward-looking statements within the meaning of the federal securities laws, including statements regarding our expectations, plans, prospects, strategies, future operating results and financial performance. Although they may reflect our current expectations and are based on our current view of the industry and our business, they are not guarantees of future performance. These statements are subject to risks and uncertainties that could cause our actual results to materially -- be materially different from those expressed in these statements and speak only as of the date of this call. For more details on factors that could affect these expectations and cause these differences, please see our most recent Form 10-K and Form 10-Q and other SEC reports filed with the Securities and Exchange Commission and available on the SEC's website and in the Investor Relations section of our website. SharonAI undertakes no obligation to publicly update or revise any forward-looking statement, whether as a result of new information or future events. In addition, during this call, we may discuss certain non-GAAP financial measures. Reconciliations to the most directly comparable GAAP measures and related disclosures are available in today's earnings release and/or on our Investor Relations website. I'll now turn the call over to James.

Hello, everyone, and 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, and I'll talk about some additional capacity and our capital strategy moving forward. The central message from the quarter is that we have materially increased each of the 3 inputs required to scale this business, AI factory capacity, contracted customer demand and capital. Let me give you the headline numbers first, then I'll unpack them. As of today, we have 212 megawatts of total secured AI factory capacity across Australia and New Zealand, which is an upgrade of 80 megawatts from our last guidance of 132 megawatts. 120 megawatts are contracted through multiyear take-or-pay agreements, and I'll expand further on this updated capacity shortly. We expect to have more than 64,000 NVIDIA GPUs deployed by mid-2027. We've raised approximately $2.2 billion of capital since December '25, and we've executed roughly $8.8 billion of total contract value year-to-date. Three months ago, our portfolio was comprised of 100 megawatts capacity and $2.2 billion of TCV. So the contracted book has grown by roughly 4x 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 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 5-year take-or-pay agreement with a global technology company worth $950 million. A few days ago, we secured a 5-year take-or-pay agreement with the global AI platform with $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, and we've expanded our partnership with VAST Data to 600 petabytes of storage commitment, providing sufficient back-end infrastructure to support continued growth of up to 100,000 GPUs. On capital and governments, 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; and Andrew Penn has been appointed as the 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. And we serve enterprise, government, hyperscaler and AI natives. I'm often asked why are we well positioned? And I'd 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 Australia and New Zealand hosted sovereign infrastructure is particularly relevant to regulated and 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. And by co-locating with the improving data center infrastructure, we accelerate our deployment, reduce capital requirements and minimize the development risk associated with greenfield builds. Finally, while we're headquartered in Australia, our customers are global, and our contract wins this year emphasize just that point. I said last quarter that we solve for one thing and that's scarcity. And using that framework, which hasn't changed, I'd argue this quarter has validated it on all 4 fronts. From a GPU allocation, finally 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 our 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 secured capacity, which has now grown to 212 megawatts. 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. And 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 buildout. So let me spend a bit more time on NVIDIA and our relationship. This is a first-of-its-kind partnership, six years an initial 72 megawatts, 40,000 GV300s and $4.9 billion of minimum revenue or an average of $817 million of revenue per annum at implied base rates. But this partnership does 2 things. It expands our ability to provide compute access to the broader AI ecosystem, namely AI native and enterprise customers, and it reinforces supply certainty at scale through the NVIDIA Cloud Partner program. But 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 megawatts 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 derisk 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. But the pricing under this agreement is guaranteed as a 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 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 is 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 network 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 onwards, we recognize monthly revenue on reserve capacity for the full term. For take-or-pay contract, we have 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. And at the end of the term, depending on tenure, there might be several years less of useful economic life, so we can recontract or sell to the on-demand market. The question we get asked the most is whether the customers actually recontract. And I'd like to point out a few things. Data gravity or moving petabytes between clouds is a real switching cost, not moving compute and the 600 petabytes committed under the expanded VAST Data partnership is there for customers to grow into. Second, the platform itself. Because networking, storage and orchestration are tuned to each workload, switching means rebuilding and revalidating their stacks. Third, the time to compute because redeployed elsewhere means a multi-month hardware and deployment lead times all over again for the customer. And finally, the upgrade path. Because as an NVIDIA cloud partner, we have priority access to generational upgrades of future GPU allocation. We can save the customer from joining this sec for scarce supply. So who are our partners? We see our partner ecosystem as a unique differentiator. We orchestrate a best-in-class ecosystem around a single AI cloud platform, compute, data, networking, data centers, procurement and installation and hardware life cycle support. We don't need to own every layer. Instead, we combine leading technologies and infrastructure partners within a single SharonAI platform. That model is designed to support faster deployment and more capital-efficient growth. To name a few, NVIDIA is our primary supply of compute. NEXTDC is our primary supply of data center capacity. And recently, our agreement with VAST has notably strengthened our storage strategy, and we cannot forget Worldwide Technology, which is our exclusive APAC procurement, testing and implementation partner. It's also worth calling out that this partnership approach has had 2 big impacts. One is that this results in lower operational risk, greater market validation and credibility and two, that internal technical headcount does not need to scale as fast as some others as they internalize these capabilities. And now to capacity. And this is a piece of news I want to make sure it doesn't get lost today. Since our last capacity update, we have secured an additional 80 megawatts in Australia, taking our total secured AI factory capacity to 212 megawatts. To put that trajectory in context, we had 54 megawatts at the start of the year. We have, therefore, increased our secured capacity roughly 4x year-to-date while accelerating customer wins. Demand has consistently run ahead of what we can supply. So having 92 megawatts of secured available capacity heading into the back half of this year is exactly the strong position we wanted to be in. The pipeline isn't just a number, it's a commitment to deliver compute online. And so I'm pleased to confirm that we have successfully handed over B300 cluster to one of our customers this month as well. We are actively focused on our next deployment of both B300 and GB300 equipment into the balance of this quarter and in early quarter 4. If you look at how the contracted revenue book has built throughout the year, it's a fairly steep line. We started Q1 with Canva, GMI and ESDS with a $1.3 billion of total TCV. In May, we announced a global technology company with a major Asia Pac presence for a further $950 million. In June NVIDIA for $4.9 billion and in July, the global AI lab for $1.32 billion. And just a few days ago, we signed another agreement with a global AI platform for $373 million. That takes us to roughly $8.8 billion of total contracted value for the 120 megawatts of contracted capacity, which leaves us with 92 megawatts available to sell. Finally, it's worth turning to our capital strategy. And we secured approximately $2.2 billion of cash since December 2025. That includes the recent $1.6 billion strategic financing closed in the second quarter. The June financing was oversubscribed and led by a cohort of top-tier institutional funds, and we remain grateful to their ongoing support. Many of you will have joined the call today, and we appreciate your continued support and suggestions as we work to deliver our GPUs to customers. I'll now close with 4 points on our outlook. First, demand continues to materially outpace supply, and we secured 212 megawatts of capacity for deployment by the end of 2027, while our contracting visibility now extends out through to 2031. Second, we're well funded for our near-term build-out following the $1.6 billion financing and other capital raises to date. Third, we expect the first material revenue to commence in the fourth quarter of 2026 as large-scale B300 and GB300 deployments come online. And fourth, we are targeting more than 64,000 GPUs deployed by mid-2027 across our footprint in Australia and New Zealand. We've made significant progress in a short period of time, but the hard work is still ahead of us. Contracted revenue becomes recognized through execution, delivery and operating at the high standards our customers expect. That's what the next 12 months is about and I'm confident in our ability to deliver. Finally, on a personal note, I wanted to take this opportunity to thank Tim Broadfoot, our CFO, for his work in getting to Sharon where it is today. This will be Tim's last 10-Q, and we look forward to Anuj joining our team and leading the next call. Tim will continue consulting the company for a period, and we wish him all the best in the future. Operator, please open the line for some Q&A.

[Operator Instructions] Your first question for today is from Darren Aftahi with Lucid Capital Markets.

Congrats on all the progress. Just two, if I may. The additional capacity, the 80 megawatts you guys added this morning in the release, is that source coming from a same partner you're working with? Or is the new partner? Second question on the NVIDIA partnership, the 72 megawatts, any updates on releasing that? And with that question on the release, our conversations with customers, I assume, in the ballpark of where your latest contract was north of $4 GPU-hour?

Thanks, Darren. James. So new partner solution for the additional 80 megawatts, fairly confident around some early megawatts potentially as early as late this year, but definitely in Q1 next year. So good to unlock some capacity there and delivery through 2027 from that perspective. So look, the 80 megawatts is in Australia, and there's some strategic activities we're focused on around that capacity. And at this time, it's probably not appropriate to give you much more detail on it. But as we've been through the whole history to date, it's been about adding consistently megawatts across partners and delivering modules to get them online and get those programs working. With respect to your second question for the customer demand on the AICP program that we've been running for the 40,000 GPUs. I'd point you to the announcement just this week, we sold that capacity for record dollars per hour or price per megawatt hour, depending on both ways you're thinking about it for both B300 and GB300. And that's the demand profile we're seeing and the pricing mechanisms that we're having with our pricing discussions we're having with our current customers. So we are seeing quite a constrained market ultimately for access to GPUs. And with those constraints, we're being able to incrementally increase those price per hour that we're getting. Certainly other thing is I'd say based on the customer demand profiles we're seeing, we'd expect that strong pricing to continue throughout the year.

Your next question is from Brett Knoblauch with Cantor Fitzgerald.

Related to kind of the NVIDIA contract, I know it's quite unique there, and congrats on adding the additional capacity in Australia. What is your priority to resell the potential the backstop capacity from NVIDIA or to sell the remaining capacity or the remaining 92 megawatts that you have? Is there a preference for what would come first or what would NVIDIA want first? How should we think about that?

Great question. We've been -- we often talk about our sales cycle, Brett, and that's probably the way we think about this. So when I talk about the program that we've got currently going to resell the space in Melbourne, that's compute that's very well designed. We have a very clear path about how we're going to build that out, what the compute form is going to be when it's coming online, all the RFS dates are done. And so we know with that knowledge, we can start giving customers RFS states and contracts. So short term, we're very focused on the resale of that NVIDIA capacity because there's a lot of deals there for AI natives, and we're seeing a lot of demand in there. And the program really put us on the map globally for a lot of other customers that we didn't historically have relationships with. And so we've got some great relationships, which is giving us really good insight to then the other capacity that we've just announced. And so quite often, I've spoken about this on several calls, but key to us is when we get capacity online and we know we've got energy or white space, we then have to go through a design process to get the right form factor of compute to then be able to take that out to customers. So we're early in the journey on the additional megawatts, but we are already having those conversations with those customers. So one of the great things we're seeing out of the resale process on the AICP is we're talking to these AI natives and they're looking at what's the rest of your capacity? What are you saying to our sales? What are you seeing for '27? What are you going to have online for '28? And so we're getting a lot more further out insight as to what customer demand profiles are looking like. And they're all asking for it. They're like, can we guarantee if we get 5,000 GPUs out of the 40,000 on this, can you guarantee some 5,000 or 10,000 in your next bit of capacity that you're going to be building out. And so that's amazing from a forecasting perspective. It gives us a lot of confidence, but it also enables us to start to talk to those customers about specifically what they're looking for. Are you looking for a cluster with more storage next time? And so we can do a bit more planning. And so having released that additional capacity publicly and now being able to talk to customers about where we see that pipeline and what's publicly available as pipeline and then when we talk to them about what's not publicly available as pipeline, it's very helpful overall from an organizational perspective about planning overall capacity and how we're thinking about growing the business.

Awesome. Very helpful. On contract duration, if I look at all the contracts you've signed, maybe absent some of the really small ones, it's been five years, except for NVIDIA at six. Is there a target duration you're looking for when you do ultimately get into the reselling NVIDIA capacity? Like is it more one, two years? Is it shorter? Is there a target duration that we're thinking of?

Look, we're largely being driven by customers on that component and that conversation. I think every customer -- it's a bit of a balance between price and duration. Every customer would love to have the longest term they can is the general conversation we're having them. But the demand we're seeing is in the three to five year range. But they all want to lock up as much as they can. And so we're trying to find a balanced book where we take the limited resource of 40,000 GPUs and split it between a mix of three to five year contracts, but also depending on what we see that customer's forward demand profile or curve is, think about how we match those things across future demand as well. So, what we want to try and do is find those customers that we can expand, not just so once we've landed a customer, how do we expand the customer because it's a lot easier once you've got that customer on your books to expand those relationships.

Yes. That makes sense. And then maybe just one follow-up for me. If I kind of do some back of the math here on the storage with your partnership with VAST, it's about 100,000 GPUs, which is about similar to how much megawatts you've now secured from the 80. At what point would you look to expand that just ahead of additional capacity ramp in the future? Are you thinking about that yet? Or is that still a bit of a ways out?

Great question. I mean we always like to leave a few breadcrumbs in an announcement is the way we are thinking about it. I think those early indications of where we're thinking as we sign those deals like the one we did with VAST was a good indicator about where we were thinking the business is going and where we had -- where we thought that was -- where we thought we'd be announcing our megawatts as we came into this period. We're always in discussions with VAST been an amazing partner. And so we are looking at how we expand that storage. The other thing I'd just say more broadly on storage is we've seen huge customer demand and shifts in those storage dynamic. And that is as to how we design a facility, how we turn on a facility is changing those dynamics as well as we're realizing with customers, we need to be able to take more storage into a design beyond the standard 3 petabytes per 1,000 GPU sort of reference architecture, customers are looking for more storage. And so as we think about that, the recent $1.32 billion contract was 10 petabytes of storage for 1,000 GPUs. And that's a material upgrade from three. And that means you have to think about storage capacity, that additional loads, traditionally they're air-cooled loads and attaching to our GB environment. So there are mixes here that we have to start considering as we're seeing these shifts in storage.

[Operator Instructions] Your next question for today is from Michael Donovan with Compass Point.

This is [ Ian Generes ] calling in for Michael Donovan. Congrats on the continued progress and signings. My first question, I just wanted to ask your partnerships now include NVIDIA, Dell, VAST and a number of data center operators. Can you talk about how those relationships support the growth strategy from here, whether that's validating next-gen GPUs? And what kind of line of sight they give you into future demand?

Yes. So I think the demand cycle we're seeing from the -- we're seeing demand cycle from our partner network. Partners are obviously referring as business, and that's very helpful. When we start to talk to our supply side on demand, we're definitely hearing about supply constraints in market where customers are -- where customers -- their customers are experiencing demand. So what we're hearing through supply relationships with the Dells, with the supermicros, with the Lenovos is an overwhelming story of large demand. But then when we talk to our storage customer partners like us and so forth, we hear about what they're doing in storage and what other NeoClouds and other people in the space are doing. But really, by using this partner network, it's all about lowering our execution risk. And so everyone's got to have a relationship with an OEM. But when we have a relationship like a WWT and we have those relationships with the data center operators, it just lowers our overall net operating risk. And all of those -- we get a lot of customer referrals through those channels. So from that perspective, it's absolutely fantastic, that partner-led model. And working within the ecosystem, you get a lot of insights as to those changes in customer profiles and how we need to be thinking about them before they necessarily need to be implemented in our business as well because like we've just mentioned before, 10 petabytes per 1,000 GPUs, I'm sure that will -- VAST will tell someone else they need to start thinking about more storage per 1,000 customer for some of their other customers. And that may not necessarily be true for their customers today, but it is true for what we're experiencing. So that information throw through the network is very valuable over time, I think.

That's very helpful. And as a follow-up, as those conversations extend into the next generation, how are you observing pricing dynamics on Vera Rubin? Are customers engaging on Rubin commitments today for late '27, '28 deliveries? And how do you see pricing trending relative to GB300s, for example?