John Hewitt
Analyst · Sidoti & Co
Thanks, Bill. Good afternoon, everyone. Bill just gave you my resume, so I won't read it back to you. Let me tell you why I took this job, and then I'll spend my time where it belongs on the business and the industry. At Vertiv, I had about the best vantage point in the industry to watch what AI compute is doing to the thermal limits of the data center. I saw every cooling technology in the market, what worked, what scaled and what hit walls. I joined the Accelsius Board four years ago because I concluded that two-phase direct-to-chip cooling would ultimately be the answer for the most demanding AI and high-performance workloads. I took this job because I believe that ultimately is arriving faster than most people expected. You maybe get one or two opportunities like this in a career, and I am excited to be here. One more thing before I move on. As Executive Chairman, Josh Claman remains actively engaged in this company. We have been great partners for the last four years, and I am excited to continue working with him in a different capacity. Four years ago, Accelsius was founded on a conviction that physics would drive the industry to liquid cooling and that two-phase would earn a two-phase portion of that market. At that time, we didn't think it would become so widely understood that two-phase will be required. The market didn't just make room for us. It's coming toward us, and that's made us aim higher. We are no longer planning like a scrappy start-up buying for single-digit market share over the next 10 years. We believe we can hold a much more significant share, and this calls about how we plan to do that by building our product thoughtfully alongside key ecosystem players, holding the attention of the companies that define the AI sector and focusing where the expected return is greatest. So what instills that conviction in us? We believe important things outside our control are breaking our way. Physics favors too phase. Every AI generation runs hotter, and the industry has discovered what servicing single phase actually costs. There's another force accelerating all this. Data center developments are experiencing significant pushback from communities being asked to host these facilities over water and power usage concerns. Two-phase changes the energy profile of a data center. In greenfield designs, it can lower cooling-driven energy use by 1/3. At a moment when $700 billion in planned 2026 data center CapEx is colliding with $130 billion in blocked and delayed projects, and New York has just enacted the first statewide moratorium. That isn't a nice to have. It's how the industry earns the right to keep building. We believe the question is no longer if, only when. We can't control when, but we do control how we execute and where we focus. Over the last few years, we've been pursuing two goals simultaneously. The first was building the foundation for a great company, one that could gain a meaningful share of the liquid cooling spend and one that can deliver a highly differentiated product reliably and at scale. The liquid cooling market is forecasted to exceed $30 billion in 2030, of which $9 billion is expected to be two-phase. For context, today, there are no mass scale two-phase direct-to-chip deployments in the United States. I'm proud of the work the team has done to lay the foundation, but the next year is critical, and we'll talk about that. The second was delivering at-scale revenue from a hard tech company inside of five years and not just any hard tech. This is an advanced technology one few companies have ever solved designed to protect GPUs, the asset whose demand far exceeds supply and easily among the most valuable line items on any AI company's balance sheet. For context, one B300 GPU runs over $50,000 and eight-way server built on them runs $400,000 to $500,000 and a loaded rack of those servers can run between $3.5 million and $4.5 million. When we benchmarked ourselves against successful hard tech companies in the cooling space, very few had any commercial revenue in year four. Against the relevant comparisons, we're tracking ahead of the pace. The problem was never the pace. It was the yardstick we measured against. We expected Accelsius to travel the normal tech adoption curve with smaller early adopter companies as our main revenue source for a few years. Then we learned something about the AI market. Adopting this technology requires GPU allocations, access to power and the scale to influence server designs, and those are precisely the things smaller companies can't get. This is exactly what we saw happen with the DarkNX deal Dave spoke about earlier. Our analysis and the feedback we are receiving indicates that the market structure is sidelining many of the customers who would normally take the first risk. As a result, in this market, there are very few early adopters. Here's why that's good news. The relationships we are now focusing on are the companies that dominate this market, companies worth hundreds of billions. And they haven't just noticed us. They're showing deep and promising interest, active proof of concepts with several key hyperscalers and impressing results that are driving next steps. And make note of this because I'll come back to it. For these companies, benchmarked data-backed proof of superior performance is what drives adoption. We just delivered a major proof point. Now these companies move slower than early adopters would have, but I want to be clear about why. We believe it's a product of how a good business makes major decisions. They have shareholders, countless customers and established procurement and build cycles. They evaluate in a mature way, deliberate studies between engineering teams, starting with single-loop cold plate level tests, then proof of concepts, then operating impact analysis and then a dedicated haul deployment. Ultimately, they're built into their IT procurement plan and into their data center road map. Some iterations run over multiple quarters, and we are in various stages of progress with many of them. So the trade we ended up with is this. Instead of seeking quick revenue from small companies that aren't likely to scale, we're focusing instead on the technology leaders, and we are deep in the evaluation cycles with some of the largest companies in this industry. Our earliest customers are also our largest possible customers. We believe that this isn't a phase, but the GPU allocation and power scarcity, among other factors, define AI infrastructure, and they aren't easing. When I stepped into this role last month, we did a detailed review of the Accelsius commercialization strategy and made major updates. Substantially all of our partnership and market adoption work now focuses on four customer segments: chip manufacturers, server OEMs, server ODMs and hyperscalers. Our goal is to have chip manufacturers reference our solution, OEMs and ODMs design for it and end customers incorporate those requirements into their IT and infrastructure designs. And when those players move, the market moves. Remember, almost all the data center footprint deployed or in process today uses either air or single-phase liquid cooling. Until two-phase adoption crosses the line, bookings and revenue are going to be lumpy and hard to predict. So as Dave said, we will not guide until we see that adoption. We believe bookings and revenue are lagging indicators in this market. The milestones we will report are the ones we view as the leading indicators. As I mentioned earlier, the next year is critical. We are actively engaged in advancing progress around major milestones and the four we are focused on now are as follows: one, chip maker engagement leading to reference designs. Inclusion in a silicon vendor's partner ecosystem would be the strongest validation this market offers. It would put us in front of every customer designing around that silicon. Two, server OEM and ODM relationships expanding into co-development initiatives. This would be the first step toward factory integration and server warranty coverage, key enablers to market adoption. Number three, moving beyond proof of concept to an executed statement of work with a leading hyperscaler, one that scopes the power usage effectiveness and operational impacts of two-phase in their data centers. That's the difference between being evaluated and being planned for. And four, continuing to deliver benchmark data and deployment with leading thermal labs, giving the industry's strongest thermal minds the proof needed to adopt. Hitting these four milestones is how we'll measure progress and how you'll know we're creating meaningful company value. Given the decision-making timeline within large organizations that I spoke about earlier, we don't anticipate having material updates every quarter. That said, each one of these milestones already has its own work stream underway, most with significant progress, and we look forward to updating you on further progress when warranted. And to that end, let me update you on one huge milestone just achieved. As I said earlier, for mature customers, data backed proof is everything, and we just completed a major study. In July, we published the most important technical validation in the company's history, and I want to walk you through it because the numbers deserve more than a headline. An independent third-party systems integrator took a commercially available Dell PowerEdge XE9680L and eight-way NVIDIA B200 server drawing roughly 10 kilowatts and benchmarked it with its factory-installed single-phase cooling. Then they retrofitted the same server with our new cool cold plates and ran it again. Same server, same GPUs, same simulated workloads, roughly 40,000 operating points. The only thing that changed was the cooling. The results, new cool ran the GPUs 9 to 14 degrees centigrade cooler at the system level, using roughly 1/3 of the coolant flow at the chip. At 50 degrees C facility water, the single-phase system pushed the B200 past its 84 degrees C throttle point, the temperature where the GPU slows itself down to survive. Ours held 9 degrees C of headroom below it, same server, same chips, different outcome. Now here's what we believe those degrees are worth. NVIDIA has pointed the entire industry toward warmer facility water as a key lever for AI factory efficiency and their current single-phase designs top out around 45 degrees C. Our headroom means the performance single phase delivers at 45C, we deliver it up to 54 degrees C and beyond. At those temperatures, chillers convert from a necessity into a contingency in most of the world for most of the year. That's the energy story that I opened with. This is how the industry earns the right to keep building. But for an operator, the energy savings isn't really about the utility bill. Every data center lives inside a fixed power envelope. Whatever the grid gives you, that's your budget, and every watt spent on cooling is a watt not spent on compute. Cut the cooling load and two things happen. You make the most of the power you were allocated and you redirect those savings into the only thing that generates revenue, which is more GPUs doing more work. Based on the Jacobs reference design, two-phase enables on average, 5% more GPUs inside the same power envelope. At the scale of a gigawatt campus, 5% more revenue-generating compute from the same grid connection is an enormous number. This is why I say the benchmark validates the strategy, not just the product. Remember what I told you to hold on to, the behemoths are evaluating us and the evaluations are going well. This test is what going well looks like. The companies that can adopt this technology have gigawatts to consider and PhD teams who will take a claim like ours apart line by line. This test was built for that audience, widely available hardware run by a third party at the warm water conditions their own road wraps require. We didn't hand them a marketing claim. We handed them a data set. The full white paper, warm water ready is on our site, and I'd encourage you to read it the way our customers are reading it. So back to that question of when. We can't answer it definitively, but I can give you two data points. First, the chips. IDTechEx after interviewing chip makers, cold plate suppliers and integrators across the value chain identified 1,500 to 2,000 watts per package as the point where single phase begins to struggle. The B300 shipping today is already at 1,400. Every generation on NVIDIA's public road map goes higher. Second, the racks. Beyond heat removal at the chip, single phase stays competitive only by pushing more and more water. As industry analysts have pointed out at extreme rack densities, the pipe sizing and physical volume required becomes constraints of their own. So whether the limit arrives through the chip's heat or the racks density, the limits exist and every generation moves us closer to them. That's the moment we're preparing for, and the four milestones I laid out are how we will measure progress. Accelsius is positioned to scale when that time comes, and our deployments to date tell the story of an evolving company. Our earliest shipments were demo systems, an in-rack CDU with a load sled or two, built to show nucleation, the boiling physics at the heart of two-phase and to build awareness. Then we matured to shipping thermal simulation racks, pack with load sleds that simulate real AI workloads, letting users test our cooling and prove the physics for themselves. Today's deployments are different. They're built around specific servers, specific chips, specific hyperscale computing solutions. Our customers are no longer testing whether two-phase works. They're testing how well it works with their equipment. I'm proud to be leading Accelsius through this moment. We believe that we have proven the technology. Now it is time for us to prove our reliability, then to scale it with maturity and commercial discipline. That's exactly what we're doing. I'm glad to be here, and I look forward to your questions. Bill, back to you.