Yahoo Finance

This has to be a wild day for you. You started as a a commodities trader. I mean, take us through what this whole process, road show, this day has been like for you.

Well, a little bit different than being on a trade floor. Um, and a little bit different than, uh, when I was building these computers when I was a kid back at when I was eight years old. So road show process, testing the waters, it is a relentless process of meetings, right? It is eight, 12 meetings a day with maybe 15 minutes in between, and you're running out the door, jumping in a suburban, getting to your next meeting, throwing your ID card on the table and like getting up the elevator and doing the same thing again. It's been, uh, it's been a fantastic process and the investment banks who are running this, Goldman Sachs, JP Morgan, Morgan Stanley, they kept commenting that this has been the most overwhelming amount of investor interest that they've ever seen. And you know, it it's made a lot of sense to us because this is a brand new business that no one has ever been able to see before in the public markets within the already high velocity space of AI. So it's been really exciting.

In doing my research for this company, uh, Brandon, I take us through a little bit about the model. Now you've raised $14.5 billion in debt and equity across 12 financings.

Yep.

That's a lot of debt. How does that work? And then what if the economy slows down? What if we don't need all this AI? What happens to this debt on your books?

Yeah. So this has been my primary role and we were the first to bring to market this concept of taking revenue, backing it with infrastructure and then collateralizing all this together. It's a fancy way of saying that we match our client demands with our revenue profile and then establish these debt facilities to help support the growth of the business. So we work with the world's leading AI labs and enterprise adopters of AI, and they tell us what they need in the market and then we go build it. And when we build it for them, they're asking us to deliver infrastructure for three years, four years, five years in these fixed term agreements for them that have like the same price of compute throughout that term because they need to be able to access that compute for many, many years.

Gil Loria, uh, over at DA Davidson said, this is you are buying depreciating assets in, I guess Nvidia chips. Does that should investors be concerned about that?

We use a six-year depreciation schedule, which is industry standard. And the way you think about a depreciation schedule, that is useful life of the infrastructure, right? We actually see infrastructure on our platform being used for more than six years right now. I think we have some compute from like 2018, 2019 where clients are still saying, I need that for my LLM or my AI application because at the end of the day, it's not just one GPU that rules everything or one model that's the best for everything. It's this matrix of different sizes of workloads versus different sizes of infrastructure, and our clients are just filling in that matrix volumetrically. You don't need a NBL 72 GB 200, which is this amazing cutting edge piece of infrastructure that powers some of our thought leaders in this space within our client base for running an eight gig model from 10 years from five years ago in the LLM space.

Has AI infrastructure already been overbuilt?

Not that we see. And this discussion of AI bubble, we we don't understand it.

I think it was Alibaba chairman this week was saying that.

Yeah. And and like this is a recurring theme, right? This isn't the first time we've talked about an AI bubble. And each time the market says, AI bubble, all of a sudden there's this massive product growth that comes, people get quiet for a little bit, and then they're like, well, we should start talking about this bubble thing again. It starts popping back up into the market, but our position is clients come into us and they are saying, core weave, we recognize you're the best at delivering this infrastructure in the in the space. We need more. And we need a lot more. And that scale of growth is just continuing to accelerate for us. That's why we're going public is to support our clients and their growth requirements for infrastructure that we bring to market for them.

About a billion dollars, you're raising $1.5 billion here. Um, about a billion of that will go to servicing your debt. Um, how much of a burden is it that you have to pay out that type of interest on all of the deals you have done?

Yeah, yeah. So use of proceeds on this transaction, right? First and foremost, it is to go grow the business. Um, that's research, sales, development. It is just capital for the business to keep moving forward. Part of the proceeds is for some debt facilities. These are a part of many debt facilities that we run, but keeping in mind, all these facilities are directly linked to contractual revenue for us. That is supporting our growth and it's effectively underwritten by these multi-year commitments that clients make to us because they need this infrastructure for long durations of time.

Got a question from our anchor, Brad Smith. Brad, take it away. Got a question for Brandon.

Hey Brandon, thanks so much for taking the time here with us. You know, I just wonder from the core weave executive and leadership team, how you were looking across this this era right now of volatility in the markets and why now was the time for core weave to go public, knowing that that's something that a lot of businesses are trying to evaluate, especially when they're making their market entry.

It market timing is incredibly difficult, but this was the right time for us to move forward. And our move into the public markets is dictated by our client demand. They need to be able to access more infrastructure and grow at the pace of AI software adoption.

Certainly. And then just as a follow-on to that, you talked about the total addressable market growing to $399 billion by 2028 here. Uh, the percentage of that market that you anticipate that core weave will be able to generate some type of run rate around, what does that look like as you kind of look out into the future?

So when we look at that market, we interpret it as something that's growing at 40% year over year, and core weave is a market share grower within that, within that sector. Um, our product is servicing AI workloads. So that's training, inference, fine-tuning, everything that sits in there. We are the critical piece to connecting the artificial intelligence products that the world's thought leaders are bringing to market to the consumers of those products.

All right, we're taking a look at the offering price that was up there on the screen, $40 a share, but the indicative price, it sounds like is somewhere closer to $46.5 a share in your debut today. We're going to be continuing to track that closely. Brian and Brandon, thanks so much for taking the time from the Nasdaq.

Thank you.