QumulusAI, Inc.

Hello, everyone. Thank you for joining us and welcome to the Cumulus AI second quarter 2026 earnings call. At this time, all participants are in listen-only mode. After today's prepared remarks, we will host a question and answer session. If you would like to ask a question, please press star 1 to raise your hand. To withdraw your question, please press star 1 again. Today's call is being recorded. I will now hand the conference over to Zachary Graeve, Head of Investor Relations. Zachary, please go ahead.

Good afternoon and welcome to Cumulus AI's second quarter 2026 earnings call. I'm Zachary Graeve, Head of Investor Relations, and with me today I have Mike Maniscalco, our Chief Executive Officer, and Scott Krosnowski, our Chief Financial Officer. Thank you. I'd like to remind everyone that certain statements made on this call may constitute forward-looking statements. These statements include those about our strategy, capacity and deployment plans, customer agreements, and future performance. Please be advised that these forward-looking statements are covered under the safe harbor provisions of the Private Securities Litigation Reform Act of 1995 and that Cumulus AI avails itself of the protections of the safe harbor for these statements. forward-looking statements are based on management's current expectations and assumptions as of today and are subject to risks and uncertainties that could cause actual results to differ materially from those stated or implied those risks are described in our risk factor section of the registration statement on form s1 as amended file number three three three two nine two five one four filed with the Securities and Exchange Commission Those factors may be updated in our subsequent filings, so please read these reports and future filings that cumulusAI will make with the SEC. CumulusAI disclaims any obligation to update or revise any forward-looking statement except as required by law. Please note that we may refer to non-gap measures in today's call. Any non-gap measure will be paired with the most directly comparable gap measure, and reconciliations are included in today's release. Now with that, I'll turn the call over to Mike.

Thanks, Zachary, and thanks to all of you for joining us. This is our first call as a public company, so I'll start the way I did on the NASDAQ stage in July with an expression of gratitude for our customers, employees, shareholders, board members, and partners. A number of them committed to this company well before there was much evidence to go on. We're thankful for that and excited about the future, which is the reason the rest of this call will focus on executing on the opportunity ahead. Let me tell you how I got here. Thank you so much for joining us. If software was going to become this easy to build, then software wasn't the constraint anymore. Whatever sat underneath it was. And what sits underneath the AI tools are the models and the compute to power them. The heavy AI infrastructure, power, data centers, and GPUs were the enabler of every good thing I was watching happen. So less than eight months after I left the infrastructure space, I came back. And I came back through Atlanta. I was in town visiting Georgia Tech, my alma mater, where I met the Cumulus AI team. Cumulus AI's own story runs on a parallel track. Two companies, both founded in 2019. One built data center assets and power. The other built blockchain managed services. In December of 2022, they merged into what is now cumulusAI. And in April of last year, we acquired the CloudMinders, which brought GPU as a service as a foundation. Two halves of an answer put together. Thank you for watching. Last week, we announced a co-location agreement in Metro Atlanta, our home market, for up to initial 3.75 megawatts. That agreement also carries a right of first offer for up to 7 megawatts of additional capacity, which the provider may pursue at the same site and could bring the Atlanta location to 10.75 total megawatts. Now looking back, the guidance we issued in July 14th, 2026 contemplated 18 megawatts of HPC capacity by year end. The eight we had plus 10 more to develop. Atlanta is the first 3.75 of that 10. If you add the 39 megawatts under lease, that's roughly 57 megawatts in our combined footprint going into 2027. That's real opportunity ahead of us. Now to the quarter. On July 16th, we began trading on the NASDAQ global market under the ticker QMLS. We did it as a direct listing. Our registration statement was declared effective on July 14th, and we rang the opening bell of the NASDAQ market site on July 29th. On July 17th, the day after we began trading, we were approved as an NVIDIA cloud partner. Two things in the same week, and both are about access. One to the capital markets, the other to the supply chain that the capital buys from. Thank you for joining us. A 224% increase from Q1. It's worth highlighting that most of this was compute we had already sold coming online and revenue more than doubled year over year. Additionally, gross margin expanded to 66% from 55.1%. Scott will talk about that later in today's call. But those three numbers tell one story. AI compute we had already sold came online. and whenever compute comes online, that's when the economics of this business show up. On the commercial side, we signed 21 new direct customer contracts totaling $169.7 million in the second quarter. That brings our total signed contract value to $282.5 million across 40 contracts with a weighted average term of 2.2 years, shorter than what you'll see from the largest players, but that's deliberately so. I'll come back to why later. Thank you for joining us. because it's the real number I'd watch. It isn't revenue. It's signed multi-year demand sitting in front of a company that recognized 6.7 million in the quarter. The distance between those two figures is the entire operating challenge of the business. And it's our job to close it. The only way you close it is by putting compute on the floor at hyperspeed. The customer base has changed too. Direct customer relationships now account for more than 96% of our recurring revenue, up from less than 10% a year ago. We've completed the transition away from dependence on a single marketplace to direct multiyear agreements with customers themselves. With marketplaces used for what they're generally good at, tailored user experiences and filling short-term gaps between term customers as they roll on and off. And customer contracts are getting bigger. If you look at our recent announcements, the trend is clear. What we're signing now is materially larger than what we signed six months ago. As we secure more power, we expect that trend to continue. Now, I want to take a step back for a minute and talk about why we're built the way we are, because there's a lot of noise in this category. We are not a powered cell developer building sites to lease to the next hyperscaler. We are not brokering powered land to data center developments. And we're not brokering GPU clusters. We deploy and operate GPU clusters for our customers at scale. And we made a deliberate choice about how. The traditional way to build AI infrastructure goes like this. And I think this is important to understand. You do an initial data center design and seek data center development approval for about a year. Then you engineer it. And then you finance it. You spend 24 to 36 months in construction. You roll in the GPUs. You spend a few more months commissioning. And three to four years later, you've delivered a token generating cluster. Now, look at the pace that AI is moving. Then look at NVIDIA's chip roadmap. Neither of those paces line up with a four-year build. So we don't lead with four-year builds. We look for pockets of power, call it two to 50 megawatts, where the power shell already exists or can be ready for service soon, and we deploy quickly. Most of that is co-location, and it means we bring capacity online in months, not years. Now, that's hyperspeed. There is a trade in that, and I'll name it. It's gigawatt-scale campuses. Gigawatt scale monolithic builds are important for AI, but they aren't for everybody, and we're not chasing those at the moment. We are currently focused on customers who need capacity today, not those planning for 2030. That market is large and is underserved. What we get in exchange is speed, and in this market, speed is a core differentiator. But speed alone does not win. There are five things customers actually buy. We call it our FACTS framework. First, flexibility. Whether it's around location, vendors, or architectures, such as bare metal versus Kubernetes or Rocky versus InfiniBand, we provide customers that flexibility. Second is access. As I mentioned, our customers struggle to find capacity. So what we do, we provide access and capacity that's available when a customer needs it. And we do that with a fair and clear price that customers can grow into. That's our cost structure. Next is trust. We're building long-term partnerships. Through reliability and SLAs or isolation and data privacy, we're here to support our customers' needs. Lastly, it's speed. And all five matter, but one of them decides most deals right now. customers just aren't opening with price. They're opening with, when can I be running? What we see is an industry that's compute constrained top to bottom, from the largest providers down to the startups that can't get enough compute to keep pace with their customer demand. When supply can't keep pace with customer demand, speed stops being a feature. It becomes the decision. That's the near-term reason we go after small pockets of power. It is the fastest way to get a customer running. There's a second thing that comes from building this way. Because we typically deploy into pockets of existing power rather than financing for your builds, we don't need to lock in every megawatt into longer-term five-year contracts. Most of our contract value is multi-year, but part of the book comes up for renewal each year. and GPU prices have been rising, not falling, which means in a market like this, we'd rather have some capacity repricing than all of it locked to rates we set years ago. And that's deliberate. But we're also making a longer term bet on that same footprint. Today, distribution is a means to an end. Over time, we think it becomes the end itself. As workloads shift from training to inference, they get more particular about where they run. For example, budget starts to matter more. Latency begins to matter. Proximity to the end users starts to matter. So does the security and compliance posture of a specific location. So when customers start choosing in those terms, a network of sites in different places stops being an operational complexity and becomes a differentiated product. Now, we'll see how quickly that develops. In the meantime, the same footprint is doing exactly what we need it to do today, delivering supply at the highest speed. That's why we built this company, Inference First. Tokens are the output. And getting tokens to customers faster than anybody else in our business is winning today. Getting them to the right place is the business we're building towards tomorrow. Now, let me put it together. In the second quarter alone, we more than tripled our GPU fleet. We signed 21 new contracts. We gained access to the capital markets and a place inside Nvidia's partner ecosystem. Our go-to-market motion is working. We activate capacity, sign demand, and deliver the supply. Those are the three dials, and all three move this quarter. Thank you. Now I'll turn it over to Scott to walk you through our financial reports in more detail. Over to you, Scott.