Arista Networks, Inc.

Welcome to the first quarter 2026 ERISA Network's Financial Results Earnings Conference Call. During the call, all participants will be in the listen-only mode. After the presentation, we will conduct a question-and-answer session. Instructions will be provided at that time. If you need to reach an operator at any time during the conference, please press the star key followed by zero. As a reminder, this conference is being recorded. and will be available for replay from the Investor Relations section on the Arista website following this call. Mr. Rudolf Araujo, Arista's Head of Investor Advocacy, you may begin.

Thank you, Regina. Good afternoon, everyone, and thank you for joining us. With me in today's call are Jayshree Ulal, Arista Network's Chairperson and Chief Executive Officer, and Chantel Bright, Arista's Chief Financial Officer. This afternoon, Rista Networks issued a press release announcing its fiscal first quarter results for the period ending March 31, 2026. If you want a copy of this release, you can find it on our website. During the course of this conference call, Arista Networks Management will make forward-looking statements, including those relating to our financial outlook for the second quarter of the 2026 fiscal year, longer-term business model, and financial outlooks for 2026 and beyond, our total addressable market and strategy for addressing these market opportunities, including AI, inventory management, lead times, and product innovation, which are subject to the risks and uncertainties that we discuss in detail in our documents filed with the SEC. specifically the most recent Form 10Q and Form 10K, and which could cause actual results to differ materially from those anticipated by these statements. These forward-looking statements apply as of today, and you should not rely on them as representing our views in the future. We undertake no obligation to update these statements after this call. This analysis of our Q1 results and our guidance for Q2 2026 is based on non-GAAP and includes stock-based competition expense, intangible asset amortization, gains, losses, and strategic investments, and income tax effect of these non-GAAP exclusions, including the recognition of direct access tax benefits associated with stock-based awards. A full reconciliation of our selected GAAP to non-GAAP results is provided in our earnings release. With that, I would turn the call over to Jayshree.

Thank you, Rudy, and welcome everyone to our first quarter 2026 earnings call. Arisca has experienced significant velocity in all our sectors in Q1 and are now commanding the number one market share in high-speed switching in the greater than 10 gigabit Ethernet category. With that, we have overtaken many incumbent vendors according to major market analysts for 2025. Our cloud and AI networking strategy for diverse AI accelerators continues to gain traction. Unlike typical workloads, AI workflow patterns can be long-lived elephant flows or short-lived and simply not predictable. This implies careful attention to performance, where a flow can cause burstiness for a long duration of milliseconds. The intensity of a flow can determine the line rate throughput. The shifting traffic patterns to massive flows synchronized to all-in-all or all-reduce or bursts of collective communication are all important for AI training and inference applications. I would like to take a moment to review our three AI fabric use cases. In scale-up mode, we have familiar technologies such as NVLink and PCIe that have enabled vertical scaling of single compute modes or racks. The advent of eSun, Ethernet for scale-up networking specifications, allows for increasing or decreasing computing power in a flexible manner with Ethernet to automatically adapt to workflow demands. Scale-up will be a new entry for Rista in 2027 and beyond, where we will be working closely with our customers to build AI racks with very fast interconnects for co-packaged copper, CPC, or open co-packaged optics, CTO, as well as supporting collectives and memory acceleration. Scale-out or horizontal scaling involves adding more machines to a least fine fabric, moving workloads across multiple servers or nodes, or even connecting other elements like storage or CPUs. As you scale up or out with massive data sets, bottlenecks can be resolved with collectives and protocol acceleration at L2, L3, cluster load balancing, all at wire rate. The system must deliver consistent performance without degradation as more nodes participate. Arista is a shining example here, with greater than 100 cumulative customers to date in 800 gigabit Ethernet deployments, and we expect the addition of 1.6 terabytes in 2027 at production scale. Scale across drives across the cloud in AI, as the AI accelerators in a location may need to be distributed to achieve the appropriate bandwidth capacity with the optimal power. As workloads become more complex and more distributed, the bisectional bandwidth must scale smoothly to avoid bottlenecks and preserve performance. This demands sophisticated traffic engineering, deep routing, encryption properties, and integrated optics based on Arista EOS staff and using Arista's flagship 7800 R3 or R4 series. The 7800 has established itself in this category as the premier scale across choice. You can see with Arista's accelerated networking strategy and these three types of AI fabrics, these are critical to deployment of diverse accelerators and frontier models. Traditional static network topologies with hotspot jitter that slows down job completion time or increases time to first token for inference are all not the way to go. Arista's EtherLink portfolio addresses both the synchronous flows for massive training and the low latency for concurrent swarms of real-time inference in this era of trillions of tokens, terabits of performance, and terawatts of power. In 2024, you may recall, we discussed four Ethernet-based AI training deployments, and of course, since then, we've expanded and exploded to countless others. This fourth customer from the group has officially moved from InfiniBand to Ethernet at production scale over the last two years. The high-speed Ethernet AI vSpine with flexible air or liquid-cooled infrastructure overcomes the physical constraints of power and space for AI workloads. It results in a low-latency distributed AI supercomputer fabric across global regions. What is clear to me and us is our networking prowess with data, control, and management, and multi-planar orchestration is not only central to our AI switching performance, but also important for high-speed optics transmission. At the recent Optical Cyber Conference, Arista unveiled its Extended Plugable Optics, XPO form factor, designed specifically for optics innovations at high speed. Now endorsed by greater than 100 vendors, salient features include record-breaking throughput, delivering 12.8 terabits per pluggable module, unprecedented rack density, achieving 204.8 terabits per OCP rack unit, integrated cold plate capable of cooling up to 400 watts power per module, and the universality and flexibility across a range of pluggable optics, copper, as well as linear halftime or retimed interfaces. A special kudos to Andy Beckleshine, Arista's chief architect, for driving from OSFP 10 years ago to this next-generation XPO, bringing structural improvements in power, footprint, and cost reductions. Our enterprise business experienced strong results in Q1 2026, both in data center and campus. Our VeloCloud acquisition is also integrating well into our branch and campus strategy, bringing more distributed enterprise use cases and a new channel motion with managed service providers, MSPs. To share some recent wins, let us hear now from Todd Nightingale and Ken Duda, our co-presidents, to delineate our Arista 2.0 centers of data strategy. Over to you.