Penguin Solutions, Inc.

Welcome to the Penguin Solutions third quarter fiscal 2026 earnings call. 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, press star 1 again. I will now hand the conference over to Suzanne Schmidt with Investor Relations.

Thank you, operator. Good afternoon, and thank you for joining us on today's earnings conference call and webcast to discuss Penguin Solutions' third quarter fiscal 2026 results. On the call today are Kash Shaikh, Chief Executive Officer, and Nate Olmstead, Chief Financial Officer. You can find the accompanying slide presentation and press release for this call on the investor relations section of our website. We encourage you to go to the site throughout the quarter for the most current information on the company. I would also like to remind everyone to read the note on the use of forward-looking statements that is included in the press release and the earnings call presentation. Please note that during this conference call the company will make projections and forward-looking statements including but not limited to statements relating to statements about the company's growth trajectory, financial outlook, and preliminary expectations for future fiscal periods, business plans and strategy, product development and innovation, market demand and shifts, Supply chain conditions and cost assumptions, leadership transitions, strategic agreements, and existing and potential collaborations. forward-looking statements are based on current beliefs and assumptions and are not guarantees of future performance and are subject to risks and uncertainties including without limitation the risks and uncertainties reflected in the press release and the earnings call presentation filed today as well as in the company's most recent annual and quarterly reports the forward-looking statements are representative only as of the date they are made and accept as required by applicable law We will also discuss both GAAP and non-GAAP financial measures. Non-GAAP measures should not be considered in isolation from, as a substitute for, or superior to our GAAP results. We encourage you to consider all measures when analyzing our performance. A reconciliation of the gap to non-gap measures is included in today's press release and the accompanying slide presentation. And with that, let me now turn the call over to Kash Shaikh, CEO. Kash?

Good afternoon, and thank you for joining our third quarter fiscal 2026 earnings call. Penguin Solutions delivered an exceptional quarter with record results that reflect disciplined execution and strong customer traction for our AI factory platform strategy. At the company level, we delivered record net sales and significantly higher than anticipated EPS. Building on our excellent third quarter, we are again raising our full year outlook for both net sales and EPS. All of our business units performed well. Growth was outstanding in our AI-driven businesses. In Q3, our AI-driven businesses represented 74% of total company net sales and grew 104% year over year. These businesses consist of integrated memory and non-hyperscale AI infrastructure solutions. In these businesses, AI-driven demand continued to outpace net sales growth, contributing to a growing backlog. This gives us confidence that the AI opportunity is expanding as enterprises increasingly adopt agentic AI workloads powered by inference at scale. Our results this quarter demonstrate that Penguin's solution is evolving into a leading AI factory platform company. We believe we are still in the early stages of a significant long-term profitable growth opportunity. Before discussing about performance in more detail, I want to address our finance leadership transition. As announced on June 1st, Nate Olmstead will step down as Chief Financial Officer on July 8 to pursue an opportunity in a different industry. Nate has been an important partner during a meaningful period of transformation for Penguin Solutions. His leadership helped strengthen our financial and operational foundation, and I want to thank him for his contributions and wish him well. I'm also pleased that Aaron Johnson, our vice president of finance and accounting, will serve as interim CFO effective July 9th. Aaron brings more than 16 years of public company experience in the technology sector and deep understanding of our business. We have also initiated a search for a permanent CFO. This transition does not change our operating priorities. Financial Discipline, or Focus on Execution. Today, I'll cover four key topics before reviewing our third quarter performance. First, the market environment as AI moves into production scale inference and agentic AI. Second, how our AI factory platform is positioned to address this opportunity. the customer and partner momentum that validates our strategy, and fourth, how we are executing across product innovation, operations, and go-to-market. Since our April earnings call, the demand environment has strengthened as AI continues to transition from early prompt and response experimentation to production scale inference and agentic AI. A simple way to think about the shift is that early AI answered questions while agentic AI performs work. In the early phase of AI adoption, many workloads were transactional. A user asked a question, AI generated an answer, and the session ended. Agentic AI is different. Agents are persistent, context rich, and task oriented. They can operate continuously across workflows, applications, and data sources, moving AI from an advisor to an operator. For example, in software development, each engineer can now have multiple agents that write, test, review, document and monitor code. In business operations, agents can monitor customer activity, analyze supply chain risk, prepare follow-ups, and update workflows. As inference workload scale and agentic AI deployments accelerate, infrastructure requirements for production AI environments continue to expand across full AI data center technology stack. Demand is increasing not only for GPUs and accelerator attached high bandwidth memory or HPM, but also for general purpose compute, including CPU as well as memory storage and networking. Every GPU deployment depends on a surrounding layer of general purpose compute and memory to feed data, coordinate workflows, manage context and connect agents to enterprise applications. We believe this trend is strengthening demand for our memory solutions. These persistent context rich workloads require more memory capacity, faster access to context and better orchestration. As AI moves to inference at scale, The industry is increasingly recognizing that memory, not compute alone, is becoming one of the primary bottlenecks for a large context AI inference performance. We designed our memory AI appliances specifically to address this bottleneck and improve both inference performance and token economics. We believe that for enterprises, sovereign AI initiatives, and new cloud customers, AI factories are becoming essential for optimizing time to first token performance and token economics for inference. These developments reinforce the strategic premise behind Penguin Solutions. Production scale AI infrastructure requires a full stack AI factory platform approach. Our platform connects AI infrastructure, memory, operation software, and operational execution to help customers deploy and operate at scale. Our second topic today is how Penguin is becoming a leading AI factory platform company at the intersection of memory and AI infrastructure. Our platform combines five core elements with our partner ecosystem. First, clusterware AI, operating system software for AI factories. Second, memory AI and integrated memory solutions. Third, advanced computing systems under our compute AI brand. Fourth, what is an AI factory architectures and fifth, end-to-end design, build, deploy and managed services. We believe our platform differentiation comes from combining these proprietary products and services into an integrated offering. Customers increasingly need more than just AI hardware procurement. They need architecture that performs in production at scale. An accelerated deployment path and an operating model that helps them generate profitable revenue or deliver operational efficiencies. In production AI, time to production deployment is directly tied to time to revenue, and our platform is designed to compress both. Customers need the ROI and superior token economics that our Penguin AI factory platform can provide. Turning to our third topic, customer and partner momentum. With our land and expand go-to-market strategy, we continue to add new customer logos and deepen engagements with existing customers. In Q3 26, we added four new AI infrastructure customer logos. New logo acquisitions are important in part because they often lead to repeat business. For example, across four trailing quarters from Q3 25 to Q2 26, we added 13 new AI infrastructure logos and seven of those customers have already increased their business with us. New customer engagements can involve longer sales cycles. but they also support deeper customer relationships, repeat business, and more durable long-term growth. Deepgram is a strong example of the power of our partner model and technical differentiation. Penguin designed and deployed an optimized inference environment built with Dell infrastructure and NVIDIA Technology to support enterprise voice AI workloads. In Q3, we expanded our engagement with DeepGram to support additional production capacity as its business scales. And DeepGram also acquired our clusterware product and additional services. In Q3, we also expanded our previously disclosed engagement with a tier one financial institution. This expansion includes our compute express link or CXL powered memory AI KV cache server, clusterware AI software, and services with Dell providing AI compute. Deployments such as Hain in South Korea, which provides local new cloud CPU as a service continue to demonstrate our ability to support AI infrastructure requirements across a range of customer environments. So does our recent Q3 customer win with a leading quantitative trading firm. Another important proof point is Spectra, a new sovereign deployment. This supercomputer system was built and deployed through our collaboration with Sandia National Laboratories and Next Silicon. For Penguin, Spectre demonstrates our ability to design and deploy complex system in a demanding national security environment. In our memory business across trailing four quarters from Q3 25 to Q2 26, we added 16 new logos. and five of those customers subsequently increased their business with us. We also saw continued expansion with a generative AI customer that is purchasing our CXL memory expansion cards to support inference workload solutions. These relationships validate our land and expand strategy. Once a customer experiences the value, performance, and ROI of our AI Factory platform, we have an opportunity to deepen and scale our relationships. Finally, our partner ecosystem continued to recognize Penguin's capabilities. We were recently named an NVIDIA AI Factory Specialized Partner, a recognition of our expertise in designing, building and deploying and managing full stack and NVIDIA-based AI Factory Infrastructure. We will also recognize this quarter as the 2026 Dell Technologies Global Alliances Americas AI Partner of the Year. Finally, let me share some insights into our product operations and go-to-market execution. In our product portfolio, we continue to invest in the areas where we see potential for durable differentiation, including our memory AI products, our clusterware AI operating system software, and our origin AI reference architectures. Memory AI is focused on addressing the memory bottleneck that emerges as AI inference workloads become contextually larger, more concurrent, and more latency sensitive. Our CXL-based memory AI KV cache server is designed to keep large context inference closer to the workload, allowing large language models to respond faster without needing to reprocess entire data sets for every prompt. Memory AI KVCache can dramatically improve AI factory efficiency by enabling superior token economics for inference and agentic AI workloads, delivering, first, up to 2x higher inference performance, second, up to 8x lower time to force token latency, and third, expanded memory capacity beyond GPU-HBM by leveraging CXL memory that is approximately 4x to 5x more cost-effective than GPU-HBM. The Tier 1 financial services customer we added in Q2 purchased additional memory AI KVCAS servers in Q3 for their on-prem AI factory. which is initially focused on inference and agentic AI for code generation using open-weight LLMs. We see AI-assisted code generation as a common use case for inference-focused on-premise AI factories where the right architecture can deliver superior token economics. Our early investment in Celestial AI, a pioneer in photonic fabric technology, reflects our long-standing focus on memory architecture innovation. We continue to advance our memory AI photonic memory appliance, or PMA, through our continued partnership with Celestial AI team, now part of Marvell. This appliance is designed to extend memory capacity and bandwidth for large context AI inference environments. Together, our CXL memory expansion cards, CXL-based memory AI KVCache server appliance, and memory AI TMA appliance reinforce our innovation agenda and long-term vision for AI memory infrastructure. Cluster-ware AI addresses another critical need. managing and orchestrating complex AI infrastructure across heterogeneous environments. Clusterware AI is a hardware vendor-agnostic operating system for AI infrastructure in the data centers. It acts as a unified control plane across GPUs, CPUs, memory, and networking, allowing the infrastructure to operate as a single cluster while reducing manual configuration and supporting faster time to production. We recently introduced a new AI factory operations agent, which provides data center administrators with a conversational natural language interface for operational insights. This is the first in a planned family of agents. designed to simplify and automate cluster operations and increase administrator productivity with a human-in-the-loop approach. Origin AI brings these technologies into validated reference architectures that can reduce deployment complexity and risk. Faster deployment can mean faster time to revenue for our customers. We recently introduced Origin AI inference solutions. Together, these solutions are designed to leverage Penguin Solutions' 4 billion hours of GPU runtime experience. They also draw on more than 30 years of expertise delivering advanced memory and AI infrastructure solutions. As our deployments continue to scale across enterprise, sovereign AI and new cloud customers, our focus is on increasing repeatability. This includes architectures, software, services and operations. Over time, this can strengthen both customer outcomes and platform economics. Within Penguin, we are applying agentic AI across our own operations with a focus on measurable business outcomes that support our profitable growth plans. This includes AI-assisted software development, often referred to as wide coding, and AI-powered productivity tools designed to accelerate our product cycles, improve time to market, and make our supply chain more scalable and responsive. We are also managing supply chain, working capital and growth investments with discipline as we scale to meet AI driven demand. Turning to our third quarter performance, we delivered record quarterly net sales of 479 million, up 48% year over year and 40% sequentially. Non-GAAP operating income was a third quarter record at 64 million, up 67% from the year-ago quarter, demonstrating the strong operating leverage in our model as we scale. AI-driven demand continued to drive growth in integrated memory and in the non-hyperscale AI infrastructure business within Advanced Computing. Together, these two businesses represented 74% of total company net sales and grew 104% year over year. Advanced Computing net sales total 138 million, representing 29% of total company and growing 4% year over year. Demand and customer engagement of our AI infrastructure business within advanced computing remains very strong across enterprise, sovereign AI, and new cloud customers. Our non-hyperscale AI infrastructure business is scaling rapidly, with third quarter net sales up 81% year over year. In Q3, this non-hyperscale AI infrastructure business represented 58% of total advanced computing net sales versus 33% in the third quarter of last year. The shift to inference at scale with agentic AI aligns directly with Penguin's AI factory platform strategy. and the differentiated role we play at the intersection of memory and compute infrastructure. Our memory AI appliance continues to gain traction. It generated both revenue and new bookings this quarter. The pipeline also continues to strengthen across enterprise sovereign AI and new cloud customers. Memory business net sales were outstanding at $275 million, up more than 111% year-over-year, supported by both higher volume and pricing. Our strong results reflect a fundamental shift. Agentic AI is driving sustained, structured demand for memory, reinforcing our view that this AI-driven demand is more durable than a traditional cyclical memory upturn. We are anchoring our memory business on data center market, where demand is driven by agentic AI. We are growing our engagements across networking, hyperscale infrastructure, and enterprise computing customers for their data center products. We exited the third quarter with a very strong backlog. This reflects robust data center focused AI demand. This demand continues to outpace net sales growth, giving us a strong backlog entering the fourth quarter. Just as important, we are broadening that growth across a wider set of memory customers. This is creating a more durable customer base. This momentum reinforces the expanding reach of our data center focused memory solutions. It also highlights the strength of the opportunity ahead. Our CXL memory expansion cards continue to gain traction, generating both revenue and new bookings this quarter, while our customer pipeline continues to strengthen. Our LED business also performed well this quarter. with Q3 net sales totaling 66 million, up 7% year-over-year. Our strategic priorities remain centered on memory and AI infrastructure within advanced computing. At the same time, LED continues to be managed with discipline. It generates positive cash flow and continues to execute against its innovation roadmap. On June 1, we announced an improved financial outlook. At that time, we expected full-year fiscal 2026 net sales and diluted EPS to be at the high end of our previously issued ranges. Today, based on our third quarter results and supported by strong AI-driven demand, we are further increasing our fiscal 2026 outlook for both net sales and diluted EPS. Nate will provide more details in a moment. Looking ahead, we intend to continue balancing growth investments with operational discipline. Our priorities are clear. First, invest in differentiated software, AI memory, and compute infrastructure solutions. Second, execute with discipline and speed. Third, add new logos and deepen existing customer relationships. Fourth, grow our partner ecosystem and diversify our customer base. Together, these actions are designed to support more consistent and predictable profitable growth. In closing, AI is entering a production phase. This phase is reshaping both architecture and economics of data centers. As agentic AI makes inference more persistent and demanding, several capabilities are becoming more essential. These include memory, orchestration, full stack integration, and operational discipline. We believe we are strategically positioned at the intersection of memory and AI infrastructure to lead the next phase of AI, inference at scale powering agentic AI workloads. We are still in the early innings of a very large growth opportunity. Thank you to our employees, customers, and partners. Our teams are energized by the opportunity ahead. and we appreciate their continued focus on execution and customer delivery. With that, I will turn the call over to Nate for a closer look at our financial results and outlook.