All right. Good morning, everyone. I'm Brendan Lynch. I cover REITs here at Barclays. Very happy to be with the Equinix team, Arquelle Shaw and Ryan Burke. Arquelle, you have been the President of the Americas for just over about a year now. Maybe you could tell us a little bit about your responsibilities and maybe about your prior responsibilities as SVP of Sales in the Americas.
Sure. Thank you, and it's a pleasure to be here today, and thank you for having us. In my capacity as the President, I am responsible for our growth strategy in the Americas, and the Americas for us is everything from Canada all the way down to Chile and Argentina. I have responsibility for corporate development, I have responsibility for our business development, and then also the growth that comes from those investments that we're making. Prior to that, I ran sales for the Americas as SVP of Sales, so I did that for about six years. I think that brought a unique lens to where I see things from as a President now.
Great. I think you've kind of led the change in the go-to-market strategy in your prior role at the firm. Maybe you could talk a little bit about the changes that you wanted to see and how you executed on it.
Yeah. I came into the company. We've been such an incredible story of growth over our 28+ years, and when I came in about seven years ago, it'll actually be officially seven years at the end of this month, we were doing exceptionally well, and we needed more. We had been approaching the enterprise space very effectively. We were starting to see, and there was a journey to the cloud. There was starting to be a conversation around repatriation, potentially. We also wanted to significantly increase revenue growth. What I went about doing when I came in, is putting together probably a more structured approach against the segments that we had. Rather than treating every customer equally, we have small and medium-sized customers and large customers.
We had verticalization that was important in terms of stronger. We play very well in the financial services, for example, so making sure that we had the right focus around that. It was really bringing a consistent focus around how we managed the go-to-market strategy against the different customers that we had, so we could really differentiate. One of the things that we saw was the fact that we had so many Fortune 500, Fortune 100, Fortune 1000 customers, but we had a small bit of their business. So really understanding the role. I think seven years ago, people thought of data centers as a box and didn't know very much about what happened in that box, and we have such a different value proposition in terms of an ecosystem that lives in that.
Working with our customers around the digital transformation that they were going through, and aligning our sales organization so they could effectively go after that opportunity in the market, and it proved to be quite good in terms of the growth rate that we saw coming off of that and bookings growth.
I think the whole world is getting an education in data centers over the past couple of years.
Yes, definitely.
In terms of the go-to-market strategy, certainly the data center market has evolved over the last two to three years. How should we think about your positioning the sales force and your go-to-market strategy now, and is it continuing to evolve as we see AI enterprise and AI inferencing demand start to ramp?
Yeah, absolutely. We have a new CRO. He's not new anymore. I think he can officially be called tenured. He's been here over a year. Shane Paladin, and he has introduced, again, a go-to-market strategy that's evolved with what's happening in the marketplace, which is important for any sales organization to do. What we're seeing is the differentiation in terms of where the opportunity is and the different ways in terms of how customers are served. We have almost 11,000 customers, which is really different from any other data center operator. Those customers are not all served the same way, and we have very small, and we have very large customers, and everything in between.
Being able to effectively serve those customers in a way that allows us to move as quickly as is necessary to capture the opportunity, but to do it in a way that is meaningful for that segment is important. For example, in the small size business, we use many more partners, and we have a robust channel organization. Whereas you go upmarket and you start to look at some of the very large enterprises that we have, and they have very dedicated, bigger teams that support them on a global basis, and then everything in between. So that's how we align.
Great. Maybe we can talk about enterprise demand and how customers' capacity requirements are evolving as AI adoption accelerates, and what you're seeing on the ground now.
Yeah. Well, it's definitely evolving, and what I would say is we've seen this over the last few years just in terms of the increased size of capacity that they need. The workloads that they're placing with us in our data centers and across the industry are drawing more power. They require greater density. We're seeing that shift. Whereas a 250 kVA deal was a large deal for us, a megawatt is kind of the going thing now. That's a big shift that's occurred over a number of years. What we're also seeing is AI has really taken off. Enterprise is a little bit slower in that, and I think there's reasons for that. The enterprises are the businesses that have to make the investment in infrastructure and all of the changes that AI might be driving.
I think that up until last year, I was just sharing this in one of the meetings we were in, if you talk to an AI company or you talk to a hyperscaler, they were all in on what was happening with AI. When you talk to enterprise customers, we ask the question of, "What's your AI strategy?" The majority in the room were contemplating it but had not embarked on developing a strategy. They were dealing with what we would call Shadow AI shops, where there were people using AI, but they still hadn't stepped into actually driving a strategy. This year when we met with that same group of customers, they all were heavily invested in building that strategy and implementing a strategy.
That's reflected in what we see customers doing with us and the work that they're doing trying to understand the growth patterns that they have.
Customers commonly think of Equinix as the go-to location for latency sensitive workloads. Maybe you could elaborate on what element of demand is coming from those latency sensitive workloads versus maybe some other types of AI workloads that might not be as latency sensitive.
Sure. I think, and Ryan, if you want to jump in here at any point. I think what we're seeing, first of all, is the latency sensitivity has always been a factor in workloads. AI is potentially driving a greater need for latency sensitivity. We're still looking at that because what we're seeing from what customers are telling us is not all AI workloads are the same, just like any other workload, they're all different as well. What we're finding is that the customers, it's probably important to do this, when we build a data center, it's typically within what we call a metro. It's a campus of data centers. We are very thoughtful about where we place the workloads in that data center, depending on the latency that's required.
In non-traditional, in before AI, you think about financial services, high-frequency traders, where the latency is so incredibly important. What you start to see with AI is the response time on more and more applications is really important. You're ordering an Uber, you can tell within seconds if you haven't gotten a response on your phone. AI is driving more and more of that need for instant response rates on that, and that's driving latency sensitivity associated with that. We also build our data centers in the sense that, again, as I said, it's almost like concentric circles where the high sensitivity around latency gets placed in a certain part, certain IBX, and where it's not necessary, we'll work with the customer to place those in different areas.
I think that's an interesting example, the Uber, because for a lot of people, it's hard to envision what the latency sensitive, why it's important when you can, in some ways, get low latency from across the country. I believe every time we order an Uber, there are 300 workloads that are involved with making sure that journey goes successfully and getting those all timed right and with super low latency is part of the reason that it works the way that it does.
Yeah. That's an incredibly good point because the complexity of what takes place to make that happen is something that most people don't know about.
Sure.
Yeah.
Sure. You recently introduced some new products, Fabric One and Inference Exchange. How do these enhance your current product suite?
Yeah. I think that they are two products that actually enhance the product suite by helping us move with the needs of AI. I think of it as Fabric One as the connection and the Inference Exchange as what's operating. When you mentioned that it takes 300 different activities to occur, that's what Inference Exchange helps us do. It helps us to actually make it simpler for the customer to use the data that they need in order to drive the business, so they don't have to think about that. And the connection, the Fabric One, it makes it easier for customers to connect. So we know where they need to connect to, how they need to connect, whether it needs to stay in one location because of sovereignty or the data can move to another location, all of that, but they don't need to think about it.
We do the work behind the scenes for them.
Great. On that point of sovereignty, I think that's a growing consideration in workload placements. How are you guys thinking about that internally at Equinix?
Yeah. It is a good one because I feel like we were built for sovereignty because we have always worked with that in terms of understanding that we are in countries, we are throughout the world as the largest data center, and we work in countries where sovereignty has always been important. We have the ability because we operate within the countries, we understand that there is data that needs to stay within the country, and then there is data that can leave the country. We are able to help facilitate that for our customers and acknowledge that there is some data that is going to stay, and we provide that to them. The data that needs to traverse and can leave, we help facilitate that for them as well with our interconnection. Is there anything you want to add to that one?
Just that today, given the rise of sovereignty needs, having sovereignty built into the network layer for us is a huge draw to customers. It is very different, much more automated and much less complex than having to deal with it on an app-by-app basis or a software basis. We are naturally sovereign, and that has been one of the many selling points to our customers today.
Great. You have had a relationship with NVIDIA for years. Maybe you could talk a bit about how some of these new products that you have rolled out, specifically Inference Exchange, which is also a partnership with NVIDIA, is different from past iterations of the relationship that you have had.
Yeah. I will take that one. We have had a longstanding relationship with NVIDIA. I think the way I would think about it is when we first started working with them, it was really about the infrastructure that customers needed, and so facilitating access to that infrastructure. As it has evolved and our customers are now looking at how do they use inference and how do you get inference to the customer, our relationship with NVIDIA has changed as well. Introducing this product was an important part of that journey in terms of working with NVIDIA and also Together AI to build out how we can actually facilitate the customer using the data, right? Not just you have got the infrastructure, but what do I actually do to get the data so I can now use it coming off of the different places that that data comes from?
We facilitate that, and that's how that has evolved with the relationship with NVIDIA. I assume it's going to continue to evolve that way as we think about how customers are using AI.
Good partner to have, that's for sure.
Yeah.
Maybe you can talk a little bit about your pricing strategy and if you anticipate that that would continue to evolve with different partnerships.
That's a big question. A broad question. Is there a particular part of that, just in terms of the particular product or in relation to everything?
I think with [inaudible] , if I am not mistaken, there was a suggestion that it is going to be more outcome-based pricing.
Yeah.
Maybe just if you could clarify what that means.
Well, I think part of that ties to simplicity for our customers. So when you simplify, instead of having to price out a multitude of components and navigate that from a pricing perspective, that can provide one price based on the outcome that the customer is looking for. We simplify it for the customer. And then for us, it also makes it more manageable for us in terms of expectations on what we are building. We anticipate that what is going to happen with interconnection is that it is going to continue to grow. It is one of our fastest-growing products at 9% this year. We feel that it becomes essential for customers using AI to retrieve their data from many different places, whether it is a model or it is compute, in order to get it to where the workload needs to be in order to utilize it.
That interconnection becomes greater in importance to the overall outcome they are using. Simplifying for customers and making it easier to deliver becomes the most important part.
Maybe to touch on that, the connection component, how is AI adoption driving increased demand for interconnection? I think there is a thesis out there that historically your customers would have had an interconnection with maybe some of the fiber providers and one or two of the hyperscalers, but now with OpenAI, Anthropic, et cetera, all in the mix, is that driving increased interconnection density?
Yes, very much so. In the past, when data lived kind of in one place, maybe two places, your interconnections, you would see, were typically point to point. With AI, it is driving a greater need to retrieve data and move data to many different places. Data doesn't live in one place anymore, right? It can live in a cloud. The model might be in one place, your compute might be in another place, and then you need to ultimately get the data over to an end user. That is far more complicated than it used to be and requires more interconnections than were required in the past, and they need to operate more flexibly as well. We are seeing that this is driving two things. One, a significant increase, which I think is why we are seeing that growth in our interconnection product.
Increase in interconnection and the flexibility of that interconnection. It is also creating a lens on networking that maybe hadn't been in the industry for quite a long time. Two years ago, three years ago, you would be in a room talking to people about networking, and you don't even go to university to learn about networking anymore. Now with AI, it has had a kind of a rebirth in terms of the critical element of running a platform is that networking that you create. Yeah, we see it as being an absolutely important element of driving AI, or utilizing AI and driving a platform that helps a customer to use that AI.
Maybe you could talk specifically about Equinix's competitive advantages and interconnection relative to some of the other options that might be available in the market.
Yeah. Besides the products that we have and the reliability that we have, we have over 522,000 interconnections globally. We also have the largest number of data centers globally as well. Is it 282 at this point? I think we are at. It changes, growth. That gives us a level of density that is unparalleled. There are other companies that absolutely have interconnections, but we have this density of interconnections that is unparalleled. When you combine that is good, but what really differentiates us is the fact that they are connected to ecosystems. We have been building ecosystems for almost 30 years. It takes a long time to build a really viable, rich, dense ecosystem.
That is what we have done, and that is where we have focused in our major metros, in terms of making sure that we have attracted the right customers, whether it is clouds or network service providers, the customers who actually live there, the right neoclouds. Making those connections is critically important, and it creates a magnetism, and customers come to us and say, "I want to be in that ecosystem because half of my supply chain lives there," or, "I have got an important customer base that is there." We have shown and proven that it creates this magnetism that draws more business in that is very important. I think the two are important, not one or the other alone. That interconnectivity to that ecosystem is what is most critical.
One of the elements that is kind of newer to your ecosystem is the xScale offering. How should we think about the value proposition of your xScale assets relative to maybe some of the single-tenant assets that might be available through other developers?
Yeah. We do not build gigawatt data centers to perform training. That is not what we do, and that is not what our xScale product is. But what we do know is that the clouds want to be close to where those ecosystems live. Those ecosystems sit in large, densely populated communities. So you are not going to build a gigawatt data center in a large, densely populated community, but you want to get closer to it. That is what xScale's purpose is to bring those clouds closer in so that they can connect into those ecosystems and the customers that are there, and so that our customers have a way to connect into the clouds.
I believe you have about half of the Hampton campus still available. You have also got the Minooka site. Maybe you could talk about those two assets or two locations and perhaps where else in the Americas you are considering expanding xScale next.
Well, those are the two right now that we are looking at. They are on track. We are excited about them. I do not know if there is a whole lot else that we have shared publicly other than that they are on track and progressing well on plan.
That is good xScale growth through 2028- 2029 for those investment-grade hyperscale customers. Excellent. Maybe I will open it up to the room if there is any questions here. Happy to relay them. Or I can keep going. Maybe on the topic of development, how is Equinix adapting facilities and your design to meet the operating standards of some of these higher power density workloads that you are seeing through AI?
Yeah, I would be glad to do that. We do this, and we have probably our real estate guy in the room as well who does this every day as part of his job and livelihood. We are always thinking about this, and I think let me back up for a moment and talk a little bit about the metros that we exist in, these campuses that we build. We have assets that have been there for many years, and then we have new assets we are continually growing. As we think about what we are building and we think about what is needed in those metros, we are constantly assessing existing workloads, the new workloads that are coming in. We have a degree of churn that happens in those metros as well, and where we are placing customers to best meet their needs.
When we think about what we are building to with AI workloads, it is absolutely creating a need for us to build at a larger scale with higher density. When we think about, for example, I think it is DA12 that we have announced that we are building, we are going to be delivering, I think about 67 MW, and it is going to have a density of about 18 kVA per cabinet. That is denser than we have ever gone, and we are very comfortable with that, but that is what is required. We will continue to think about that as we think about our designs, how we are evolving that to address the needs of AI, and how we can do that. I think what is also really important, this has come up in lots of other conversations we have had today, how do we do that in a responsible way as well?
Because we have environmental impacts that we have to be conscious of in terms of how we cool things, the amount of water that we use, et cetera. Keeping a lens on that while also making sure that what we are building accommodates the needs of what AI is driving. Sometimes I get the question of, "Well, what is that going to look like, and do you have a lens on that?" I do not think that we are building to say this is what AI is going to demand. I do not think anybody can say that right now. I think it is too unknown. But I think we are comfortable with the fact that we have a history of evolving how we build, how we are thoughtful and we are responsibly looking at what is happening and changing and how we change our builds to accommodate that for our customers.
I think we feel well-positioned for what AI is going to bring forward and what we are going to have to build to support the AI in the future over the next, say, five years.
I think it is an interesting dynamic for Equinix in that you are basically planning on doubling the size of the company over the next five years, which would be all the most modern assets. Even as AI requirements evolve, your starting point of where you might need to alter a facility is much more progressive than having to retrofit an asset from 20+ years ago. Even some of your assets from 20+ years ago are the most valuable ones in the portfolio because of the ecosystem density that you discussed earlier.
Exactly. I think it's an important differentiator for us, and it's also important in terms of how that ties into how we think about those metros and how we continue to build them. Also, the conversations that we have with our customers are probably different. They're not coming to us saying, "I just need space and power." They're coming to us and they're talking about, "This is what we're doing in our business. This is the next initiative that we might be rolling out." We're having much more business-led conversations with our customers in terms of what they're trying to accomplish, and then working with them on how we design where they end up being placed and what they're going to utilize.
How should we think about either the requirement or the option to retrofit older assets for liquid cooling and any other next generation AI type deployments?
In terms of retrofitting them, to your point, we have existing assets that we utilize with the cooling that we've had in place. When we think about new builds, we think about liquid cooling. We're less prone to retrofitting a building for liquid cooling, and we're anticipating where we need liquid cooling in the portfolio and building to that. I would say that's how we're handling it. We're not going back and retrofitting a bunch of buildings for liquid cooling.
We've got liquid cooling in 100+ properties right now, and Adaire, our CEO, likens it to
Like a NASCAR pit crew, in the sense that customer wants liquid cooling, they will pay for it. We can come in, put it into what they need in terms of the cage, they will use it, they will pay for it. They no longer need it, we can pull it out of that cage and deploy it elsewhere. So it is surprisingly nimble relative to what some people think the retrofit need might be. But it all goes back to the idea that when you take the new properties that we are building and the old properties that we have in place, we think what we have is a portfolio that is well set to serve enterprise need for the future.
Yeah.
There aren't many products or real estate types where what you built 25 years ago is still very relevant today, but that is very much the case for us.
Yeah
We are building to what we believe is core enterprise demand, just regular way, but also AI oriented.
Yeah, and I think what is also really important is building in that optionality in our new builds is really important because what we saw when we started looking, and the industry was looking at liquid cooling, is that I think there was an anticipation that customers, they are going to buy AI, and they are going to need liquid cooling. We did not see that uptick on AI in the enterprise space. And so you had AI companies that were very excited and growth was incredible. But over the last year, you didn't see or I would say three years, you saw a lot of customers looking at AI, the enterprise customer looking at AI from afar, but not actually leaning into it.
What we've seen over the last year is this acceleration in enterprises stepping into AI and needing to really grapple with what's our AI strategy and how are we using AI. When we originally, you would see a build happen with liquid cooling, and it would sit there with nobody, the customer would say, "That's really expensive too," right? Because it is more expensive. They'd say, "Okay, maybe I don't need liquid cooling." Now it's a requirement, so I think we've been really thoughtful in creating that optionality and flexibility in our builds so that we're not stuck with liquid cooling that we're not utilizing, and we've paid for the infrastructure to build it. Instead, it's there now and available as needed.
It's a journey for-
It is a journey
for your customer base.
Okay. One of the things that you mentioned was kind of building responsibly. Maybe you could talk a little bit about the impact of growing community opposition to development and how that is affecting your pipeline.
Yeah, absolutely. Community sentiment and backlash is a real thing. Let me back up a little bit. We've actually, as I mentioned probably 10 times up here, sorry, but we've been in the industry almost 30 years. Where we're located, we've been in those communities for 15 to 20 + years, 30 years in some cases. We have a reputation within the industry and within the communities that people can point at and say, "Oh, you've been a good operator. We understand who you are." That said, the issues, the growth in the data center industry is real and has happened. There have been bad actors in the industry. What the communities are pushing back on are, in some cases, very real issues.
Now, some of what they're pushing back on are things that they're hearing in social media or on the news, and not all of it is fact, and not all of it is real, but it certainly has picked up steam. Our position on it is that, first of all, we always listen to the community, and we get that they're concerned about rates, rate increases. They're concerned about what it's going to do to their community. Does it really bring jobs in? We're actually able to point at the fact that we've always paid for our usage. We've always invested, and we invest heavily in partnership with the power companies to build out the grid that's needed for us. We've done a lot with workplace development, workforce development, as well as community development.
Before we even acquire a piece of land or think about expanding, we will sit with the community leaders and talk to them about what we are thinking about doing because we need to have an understanding, agreement, right. That we can serve what their needs are and we can build what we need to build. Our sustainability projects are always like how we build a data center directly correlates to regulations that the communities have or what they are asking for. I think for us, we need to get that story out more. I just did a, probably four or five months ago now, but issued a document around our community principles, which we have been doing for almost 30 years, but we have not really had a need to talk about it. It has just been the values of how we are as a company. It is part of our principles as a company.
We have done some advertising on that and putting it out there and are trying to get that message out. I think it is from a. Is it holding up our development. I would say that our data centers are smaller than the big. We are not building big gigawatt data centers. We have worked extensively with communities that we are in right now where we do have specific builds happening. We see an ask of, "Work with us and help us to get that message out so that the elected officials that actually said yes and the community leaders will say, 'We want you to come out and meet with the community and do town halls with us,'" which we are happy to do. We just did an extensive one in Minooka that was really well-received, talking about what the project is and working with the community.
We do a lot of that, and I think that is very important. Therefore, we have not seen some of the delays or issues that have come up. But I think it is something that we are very sensitive to. It is a real thing going on, and I think continuing to get out what is fact and what is fiction is going to be important. I think also using fact about what specifically data centers have done is an important message for people to hear.
Sure. It is interesting just in the industry how we have gone from ribbon-cutting ceremonies at data centers a few years ago to pretty strong opposition, but to your point, a lot of it is based on misinformation and just having the right communication apparatus to spread the word.
Yeah. One of the things that a lot of people don't realize is what actually lives in an Equinix data center. When we start to talk to them about the fact that 911 runs through the data center, that the local hospital, and all of the things that a doctor might be looking at to transmit your X-rays to another doctor across town, the emergency services, the information that's going from an ambulance who's got a patient who's coding to the hospital, so that when they arrive at the hospital, the vital statistics are there, it all runs through a data center. When you start to talk about that, it brings to life what happens in an Equinix data center.
Great. Maybe when we think about development, you guys are clearly undertaking a very large development program now. How should we think about the outlook for development yields, given the rising costs and constraints on supply?
Sure. We think that we are a very responsible, thoughtful builder with our strategy. While you see costs going up, first of all, we think that the way that we build and how we build always has a lens to doing it so that we maintain strong returns on that investment. We also are seeing continued growth in customer demand and what's happening there. We feel that our build is keeping pace with, as demand accelerates and our builds accelerate, we feel that we're managing that well, and still have no problem in the returns that we expect from what we're building.
We think we'll continue to achieve the mid-20% cash yields that we have historically. That's driven by competitive advantages across everything involved with delivering and operating properties. At the core of it is just the individual mosaic at each data center. If you just pretended you had a bird's eye view of each data center, you're looking down on it and think about a bunch of colored tiles, and those colored tiles represent different workloads and customer types. It's really curating that ecosystem, curating that mosaic, that drives our ability to achieve the outsized yield. We'll continue to be very focused on that. Therein lies the lease-up period that we do have that takes two to three years to lease our properties up to Equinix level of stabilization. Equinix level of stabilization is at that higher mid-20% return.
Yeah. I might take a minute also to elaborate on the mosaic. When we build a data center, before we build, when we anticipate the size and scope of it, we think about who are the customers that are going to be in there. We think about it in terms of retail customers, so small and medium-sized deals, customers and large customers. We think about large footprint that goes in there. That all plays out in terms of the returns on that asset. We build accordingly, and then we sell accordingly. So you will never have an asset where we say 60% should be retail customers who have a higher yield, and all of a sudden we have two big customers come in and they want to buy out the data center. We will never do that because that would so dramatically change the returns on that asset.
That is a really important aspect of how we drive those returns, is how we fill that asset. That is all correlated then to market opportunity.
Maybe we will do one more topic here on guidance. When we think about your guidance through 2029, which is now for 9%-12% annual AFFO per share growth, how should we think about the contribution from the various components, be it cabinet volume growth, cabinet pricing, interconnection momentum, or anything else that you want to throw in the mix? How should we think about that kind of growth algorithm?
Why do not I take the first part, and then you can
Absolutely
add all the little details that you want to around that one.
Sure.
Okay. The growth is, we're very confident about what we're seeing. I think what we also are seeing is when we think about the growth that we've seen over even the last three to four years, which has been significant for our company. Then you see what's happened in the last year, just in terms of when I spoke about the enterprise maybe now coming into that AI period, and we start to see even greater growth happening. I think we're quite bullish on what we're seeing in terms of the future, and that's how we're thinking about what we're building, and how do we keep pace with that in a responsible way. Do you want to add in on your comment?
Yeah. Hopefully, what you're all hearing from us is just that there's broad strength across our business, whether it's customer type, whether it's workload type, whether it's each individual product and service. That's number one. Number two is we updated our long-term outlook, which is through 2029, after having just given one about a year and a half ago. What was our old high end is now our new low end, and that's because of a mix of demand strength, which frankly came on faster than the company anticipated, but also the team's execution as well. If you think about it just from a simplistic perspective, you can see our same-store pool sort of migrating from mid-single into high digit revenue growth. Then you can expect that capacity expansion will do the rest.
We're mindful that we're a very differentiated company within the data center space. We're core focused on core workloads, core metros, colocation. We have a good feel of supply and demand conditions in our core addressable market. We feel good about the execution over the next few years.
I think the last piece is we're very diversified across the customer base, so there's no single customer that houses it over about 2.5% of the portfolio, and that's significant. When you see shifts happening, and we've seen this over the years in the history of our company, when you see shifts happening, it does not have the impact on us that it might have on another company that's heavily invested in one customer type or one particular product.
Diversification is always important.
Yes.
Let's leave it there. Thank you very much, Arquelle and Ryan.
Thank you. Nice being here. Thank you.
Thank you. Take care.