Astera Labs, Inc. Common Stock Citi’s 2026 Global TMT Conference

Welcome, both. Thank you. Thank you.

Yes, definitely fast and furious. You put it well. Thank you, Papa, first of all, and good to see all of you, some familiar faces, some new ones. Let's start with the AI question first. I believe that we are still early in the multi-year build-out of AI that we are seeing. I think more than my word, we should look at the CapEx expenditure from the hyperscalers, which is now expected to cross $1 trillion next year. That's a very good sign that not only are our hyperscalers investing a lot of dollars, but actually the pace of that investment is even increasing. In many ways, you can see that the tide is rising, and of course, all boats will rise with the tide.

At the same time, I'm also very excited really about the pace of innovation and change that is there in the AI industry. Every three months, every six months, there is something new that comes up. Talking about the IPO, when we went IPO, the unit of compute was basically eight GPUs in a HGX board, the eight Hopper GPUs. That's how ChatGPT moment happened. Now the unit of compute has become a rack. The reason for that is these models just keep getting bigger and bigger. IPO time, we were talking barely just getting into a trillion parameter models. Now we have crossed 10 trillion, and there is no sign of stopping. You look at the latest Astra model that came out was trained on more than 100,000 GPUs. Inference is driving a lot of new workloads, including longer context windows and so on.

Even for inference, now you need racks of compute. The rack has now become a unit of compute. The other trend that has come up more recently is supply. The demand for compute is so much that it is really outstripping the available supply. All of our customers are also looking to figure out how to get more out of the hardware that they have available. Fortunately for us, Astera was really founded back in late 2017. We started operations in 2018 on this premise to solve the challenges with AI connectivity, remove the bottlenecks for data, for networking, and for the memory bottlenecks. This is really what we have been doing.

Our vision is to provide connectivity infrastructure at the rack level, which includes all of the different components, whether that is switching, signal conditioning components, running over copper, running over optical, hardware, as well as software. We are well on our way to do that. That has been our journey since IPO. At the time of IPO, I recall that our revenues were about $60 million something, give or take. Last quarter, we were $392 million. We guided for $550 million at the midpoint for Q3. Similarly, our earnings per share were $0.10, and then last quarter was $0.80. We have come along quite a distance in there. In fact, I brought something to show you guys just to put this in perspective. Apologies for those on the webcast, but this is where we started. This was our Aries Retimers chip.

This is the Scorpio X that we have just recently introduced. This is the 320 lane Scorpio X. That gives you a little bit of perspective about the journey. Going back to the point I made about the tide is rising with AI, with the CapEx spend, we are growing a lot faster simply because we have managed to introduce new product families and capture a lot more content on a per XPU basis. In fact, when we started our content on a per XPU basis was sub $100, largely driven by the Aries retimer products that were attached to the Hopper GPU. Now we are already at close to $1,000 of content. If you look at the Aries family, the Taurus family, the Leo CXL family, and then of course, the most recently introduced Scorpio family.

Every generation of XPUs, we increase our content, especially with the Scorpio X. We are on track to get $1,000 or more content on a per XPU basis from the Scorpio X family alone. So we are very pleased with where we have come over the years. We will continue to work on new product families that gets us into multiple thousands of dollars of content on a per XPU basis. So really proud of the growth that we have seen, really proud of the team to have come up with so many different products and the strong trust that our customers are placing in us and inviting us to the table years in advance of an actual deployment and helping us define these products and bring them to market.

Yeah, certainly. So for those of you not familiar, we have two series of Scorpio devices. Both are purpose-built for AI applications. So before Scorpio, the PCIe switches were used for general purpose compute applications to connect storage and sometimes networking devices, et cetera. So when we decided to enter this space, we wanted to build something that was purposely done for AI, that understands the AI workloads and so on. So we started with the Scorpio P series, which is meant for scale-out connectivity, connecting GPUs to NICs, and to CPUs to connect these different clusters together, typically over Ethernet. That was a product that we introduced in October of 2024 at OCP, and then it very quickly became our fastest-growing product line. Just in three quarters last year, it was 15% of our total revenue. So definitely one of our fastest growing product lines.

That growth has continued. We have added another hyperscaler customer. We are into multiple customers that are now deploying Scorpio P into their AI infrastructure, just because of some of the unique things that we built into Scorpio P. Scorpio X, especially the 320 lane device we introduced just last May, and it has just got a tremendous amount of traction from our customers. So just to explain what Scorpio X is, it sits right in the center of our scale-up network. As I said earlier, it is connecting all the GPUs together so that it looks like one GPU. So from a software perspective, it is very easy to just address, let us say the 72 GPUs as just one big GPU. So a lot of that intelligence goes into this chip.