Conference Transcript - BZAI 2026-06-11

Speaker 4

Okay. Blaze is a really interesting company. It's very exciting. And I see it as part of my job is to make sure a lot of people know about it. And so really appreciate you being here. It also means we should probably start at the beginning. Let's start about with the founding story for Deniker, how they got here, when you joined and where we're at today.

Speaker 2

Okay. Thanks, Gail. Thank you very much for having me. And hi, everybody. So I like to say that if you've ever used an Apple Macintosh in your life, chances are that the GPU, the Centrino chip, was designed by Dineker and his co-founders. And they started Blaze 12, 14 years ago with a view to designing a new type of GPU. And what's different is that that GPU is programmable. Programmability is hugely important. But number two, it's actually optimized for edge type of use cases. And why edge is important? There's low power, low latency, high efficiency. Those are the important things. The programmability part is super important. And another anecdote that one of the founders, co-founders says is, you know, if you go back 20 plus years, there were 45 GPU companies. Today, three exist or survive. Let's put it that way. NVIDIA, AMD or ATI that AMD acquired and Intel. And what's common with those three that was not common with the remaining ones that they were programmable. And I think it's true to say that Blaze, of all the startups and people who are playing in this space, we're that programmable chip. What we deliver is an AI platform which is underpinned with three pillars. And pillar number one is the edge and far edge. So if you have a drone or a box on a lamppost, that's inference happening where the data is being created. And that's where the efficiency and low power are important. Pillar number two is where we've married our chip, which is called the GSP, Graph Streaming Processor, with a GPU. So we like to say we're not here to replace NVIDIA. we're here to complement a GPU. And what that second pillar does is allows the right silicon to be used for the right workload. So today, if you're trying to use a GPU-based solution for the far edge, it's like using a sledgehammer to crack a nut. And so that middle pillar for us is super important because it allows us now to offer our AI services platform, which is the third pillar and the customers for that are tier two data centers you'll have read about our partnership with nokia and with datacom which is one of the first data centers that we're working with and that third pillar is hugely important because it allows those data centers now to generate a new revenue stream because the software layer that sits on top of the platform is exposed through API's so if you want something to do with facial recognition or security or whether it's in retail setting or smart city settings the API's allow the customer to benefit from from AI workloads and the advantage for blaze is we get to participate in the data center infrastructure revenue stream by providing servers powered by blaze as well as an ongoing recurring revenue stream from the monetization of the

Speaker 4

API's that's a great introduction let's let's go piece by piece here but let's Let's start with what application, when you can put your chip in a camera or on a drone or at the edge, what applications are your partners selling and your customers buying?

Speaker 2

So we don't actually go onto a camera. In fact, one of our chips can probably handle four to five high-definition streets. But if you take retail setting or smart city setting, So one of the customers that we've announced, a company called TCC, it's a subsidiary of the PIF, Saudi PIF, and their application is monitoring highways, number plate recognition, fines, and all of that. And it's a huge project. And they need a box that sits on a rooftop, on a lamppost. And what's really, really amazing is that last September, we went through a test with them, and our box was running the AI algorithms that they were interested in on a rooftop, and the temperature inside the box was 75 degrees Celsius, and the workloads were running. A GPU-based one stopped working at 50-something. So that's one set of use cases. Winmate, Taiwanese company, we announced something with them recently. They develop ruggedized boxes. And so our cards will go into those boxes for industrial use. But they also do drones. So when you're looking at a drone, and we have other drone applications as well, they're being used more in a defensive capability, which is, can my drones be flying around and look and see and identify incoming threats? So the card sits on the drone, and the drone is self-sufficient. All any algorithms that need to be run, whether it's navigation or whether it's identification or something, all happen on the drone itself.

Speaker 4

So it's video image processing, and then the uses are, you talked about smart city defense retail any place where cameras are placed and you can't have a human in a call center or a monitoring center right watch all the videos you need to monitor it and right now a lot of times they're sending all the signal back to a data center correct instead of doing some of the processing at the edge which is far more efficient yeah exactly and

Speaker 2

the adoption of AI at the edge has been hindered because of the cost of sending it backwards and forwards. And it's not just video processing. One of the beauties of the design of the chip is that it can run multiple algorithms on the chip at the same time, whether they are related to each other or not. So, for example, in a factory sort of setting, you could have sensing type of data coming in alongside your video, and that can be processed.

Speaker 4

But then when we talk about putting it side-by-side with GPUs in a data center, are we still just processing video, or are we processing other streams?

Speaker 2

No, now you are, so the roadmap for APIs includes, you know, text, document processing, video, anything else that people want to be able to utilize AI for where it's a combination of workloads running on our hardware versus workloads running on GPU. As far as the customer now is concerned, unless you're working with a very large company where they have a systems integrator and they're going to put all parts together, The majority of our customers now just want a solution. So the applications that are going to run on the hybrid thing are across the board. And the good thing is we have all seen and are continuing to see all these 600, 700 billion parameter models coming down to 7080, coming down to 78. And when you get to that level, then, and the accuracy is not compromised, you know, to the extent that it becomes meaningful. At that level, all of those models can run very well on the Blaze chip. And then if you have slightly larger models that are required, they will run happily on the GPU.

Speaker 4

So what's the microeconomics of it for a customer? Instead of buying a rack of just GPUs, now they're buying a rack with GPUs and GSPs in them. And what are the types of efficiency savings they're seeing?

Speaker 2

So we did, I'll mention Yotta is a company that we got a contract with last year. It's one of the data centers in India. And their end customer is the Indian highways. And if you look at, if anybody's seen an Indian number plate, I mean, it's all sorts of cursive. I didn't even know that you could make your own, you know, handwriting up, right? So that's a huge challenge to identify when you're doing Tollbooth. And they were running on NVIDIA-based GPUs. We were able to demonstrate to them that if they ran those workloads on a Blaze server, it happened to be a super micro server powered by 24 Blaze cards, that we could run that at 2 to 4x less total cost of ownership to them. It's not just the cost of the server to start with, but it's the cost of running it, which is significantly lower.

Speaker 4

So 50% to 75% cost reduction.

Speaker 2

That's right. And then when we move to, it's all workload dependent. one of the penalties that a GPU pays that if you have a batch of one then in order for it to go through is a lot of on and off memory and with Blaze that doesn't happen at all those workloads all run together so the advantage there is we don't need HBM memory to make ours run So it's all LDDR, right? And the combination of that is where the efficiency comes from. So now when you put it into a system, which, you know, we've got our own pilot tests that we've done right now, which, you know, you'll hear about a lot more publicly as we start to announce the deployment of these hybrid. Depending on the workload, you are getting a significant reduction. Our customer here is the Tier 2 data center. And with AsiaPAC, where we're pretty active right now, I think these are publicly talked about reductions in ROI from, let's say, five years down to four years down to three years from their perspective.

Speaker 4

Got it. So that's very powerful microeconomics that you can go to the market with. how do you let's talk about you've talked about partners what is your overall approach about go to market how much of that do you want to go through channel do you have any direct sales

Speaker 2

people will there be a change in that going forward so yes we do have direct sales people and yes we have an ecosystem that we're selling through I think the Nokia partnership for us is a game changer because they already have relationships with tier two, they have relationships with data centers, and they provide connectivity. And the combination of Blaze and Nokia together, we're able to bring an AI solution to those data centers. So we will no doubt leverage their sales force. We work with ecosystem of ISVs, the independent software vendors. We have developed some of our own applications, but we can't you know, it's just too expensive for us to do that for every use case. So we go and seek out experts that have already got an application built, and that ecosystem enables us to, if we win something then we bring the right ecosystem partner along if another ecosystem partner has an opportunity that you know can benefit then they bring us along so this is how we see the go-to-market you know it's a mixture of direct plus the partnerships got it so we went one way in terms

Speaker 4

of channel partners let's go the other way in terms of where we source where do we make our chips, who do we partner with?

Speaker 2

That's a great question because it's very important for defense. You know, you're talking about your 250th anniversary and the innovation. Well, this chip is taped out by the Samsung foundry in Austin, Texas. So, which means that when we put it in a defense application or our partners put it into a defense application, then the Made in America box is all ticked.

Speaker 4

Got it. And so that's helpful both for being able to sell to the U.S. Armed Forces, but also, let's say, somebody in the Gulf Coast.

Speaker 2

Yes. And any, so we, you know, some of the conversations that are going on in other parts, you know, not just Gulf, the U.S., but also in Europe. All of that is important.

Speaker 4

Who do we get the memory from?

Speaker 2

That's an interesting question. I know part of my job is to go talk to Samsung and Micron to see if I can secure the supply. I don't know the answer to that.

Speaker 4

I vote Micron or if Samsung can make those here as well. That's helpful. Before I open it up to questions, let's just go through some financial numbers so everybody gets a sense of where we're at. What's our current guidance for this year? What guidance have we given past that? What's our overall perspective on backlog?

Speaker 2

right now? So one of the questions I omitted to answer was my own story, and I'll come to yours in a minute, the question in a minute. So I've been with Blaze about seven years, and I love technology. I love getting involved with B2B salespeople, and I love to get, you know, how does software work and all that. And I feel it's really important for a CFO, because if you are putting numbers out, then I need to have a level of comfort that actually there is something to support them. So most of my day, I know as a public company CFO, the role is changing and it does change. I have different stakeholders to look after. But fundamentally, the message that I have to give them is based on the relationships internally. So our guidance for last year was a range which we tightened. We exceeded that by an amount. So I think we closed at about 39 million or so. And we had a range for 2026, which we tightened to $130 million. It is back-end loaded, and the reason for that is that some of the contracts and so on that we've got require us to go secure our chips, secure our cards, secure some servers, and a lot of my effort has been put to making sure that that's in place. And as some of the proofs of concept are getting into production, hopefully the two things come together that we are able to fulfill the promise that we made.

Speaker 4

And so if we get 130 done this year, how much of your existing deals will remain in backlog? How far into 2027 are you starting the year?

Speaker 2

So again, we have not projected anything for 2027. But the premise of your question is, look, when we're talking about data center type applications, it's kind of land and expand. So once you've created a solution for one, then it'll go into others. When we're talking about some of the edge type of applications, you look at the Yotta one, you look at the one in the GCC region, you look at some of the drones. We expect those to continue to grow, you know, not just within that one customer, but with other customers. I'm thinking very, very hard about introducing concepts like backlog and bookings, because we will have a software element, recurring element to our mix, you know, as we go through the rest of this year.

Speaker 4

How about pipeline? How would we quantify the pipeline?

Speaker 2

So pipeline, we talked about the pipeline maybe a couple of quarters ago. Pipeline is still a very important number for us, but internally. And what we want to focus on is revenue, contracts, purchase orders, backlog, and bookings. The pipeline, we're very deliberate about what goes into the pipeline. There is a process. We have to have gone through a proof of concept. It's not just, you know, I think this is going to happen and therefore that's a good customer for us. The use case has to be identified. In many cases, we focus on where we already have the workloads and the applications designed as opposed to going down rabbit holes with others.

Speaker 4

It's a good time for me to see if there's any questions from the audience.

Speaker 1

Sure. Maybe can you talk about how you see your revenue mix moving forward between hardware, software, some of the answers?

Speaker 2

Right. So 2025 and 2026, majority is hardware. 2026 will be more of the system level hardware that we've got. I expect edge boxes and just our cards also to feature in that. What I'm going to see with some of those deployments, for example, with the Yotta deployment in India, there was already a software component of that delivery, and that helped with our margins and so on on that. As we start to deploy AI services and participate in this recurring revenue model, I expect my margins to improve significantly as we go through 2017 to 2018 because the portion of software will continue to grow. Hardware will still remain an important part because we're still going to be providing a hybrid server, so GPU, GSP. The good thing is our relationship with NeoTensor is, and that's proving to be an amazing relationship. We've identified a white-labeled server manufacturer, so that helps my margins, but it also means that I'll still continue to be in the hardware business as part of the mix.

Speaker 3

I'm curious, if you were referring to on the revenue-wide industry, what that looks like today, and maybe where it's happening to work out.

Speaker 2

Right. So in my first pillar of the near and far edge, I would say it's smart city, and I would include highways and that type of thing, and I would call it defense, you know, drone type of applications. the as we move into the data center world then it kind of depends what their verticals you know what their customers are demanding the apis that we have today things like facial recognition and so on so those would be the use cases that we'd find as we go along the the roadmap is pretty rich. At some point, we'll talk more about the kind of use cases those APIs will allow the end customer to go into which vertical. We've done a lot of work with retail in South America, and at some point, one retailer versus another retailer is much the same type of application. But those are the kind of verticals that we are working with today.

Speaker 1

Maybe your new CRO, Stephen, has been in the seat now a few months. What's he seeing? Maybe what changes does he find out making?

Speaker 2

So we're actually very lucky to have Stephen. So he comes from, I think, a Cisco background, which means that where the company is going with the AI services platform is smack bang in a sweet spot of his understanding of the ecosystem. For us, the far edge will remain an important component, but really the growth is going to be in this AI services providing solutions. And that's exactly where Stephen comes from.

Speaker 4

Let me wrap up with one kind of forward-looking one. But before, let me ask you, where in the world is Dineker right now?

Speaker 2

Dineker is, he's just come back from Asia, so I think he's resting.

Speaker 4

I think last time we had earnings, he was just coming back from Saudi, where he was on a roof, measuring something that was 75 degrees. Which, by the way, is that 150, 200 Fahrenheit? That's a lot.

Speaker 2

It is. You know, the funny thing about that story is we were not expecting that. So they said, we need to do a test. And we said, fine. And we're going to do it outdoors. We said, fine, we thought it would be in some shade. But they said, let's take it up the roof and let's set it running. And then they went off to lunch and came back and the thing was still running. He was also at the Computex.

Speaker 4

In Taiwan.

Speaker 2

Taiwan, where we jointly presented with Winmate. I think that's another partnership that I'm really excited about because it just opens up, you know, opportunity for us. You know, the Nokia partnership, you know, those are really important for us.

Speaker 4

I'll go next year. But so let me just, I know that there's another generation of product coming within a couple of years. What's that generation going to be capable of? What kind of opportunities would that open?

Speaker 2

So one of the things that is allows us, I didn't realize, I came from a telecoms background and a bit of media. And I didn't realize how big a deal it is when you tape out a chip and it lights up first time. We're on our third chip. We had two test chips and one production, right? And they lit up within the first hour. It goes to show that the skill set that you have in the company, I'll name drop. Santiago came from, he's an ex-Apple guy, an ex-AMD guy, maybe he's also got NVIDIA in his blood somewhere. He's the one who started Apple's iPhone 1 to 5 chip business. So the pedigree that you have in the company is very deep. And the founders, the design that they've come up with is one which is common to every chip. So we can make it bigger, smaller, have more features and so on, But the design of how the chip works is common. So the next generation chip, we're not talking about what size and things it's going to be. But it is going to help run whatever size of models are going to be in the next two to three years. It's going to help our hybrid strategy extremely powerfully. It just means there will be more Blaze component, if you like, in the hybrid versus GPU.

Speaker 4

That's great. That's great. I think that's a good time for us to wrap up. I'll just point out that I see a lot of irony in the fact that Cerebris, which has less real revenue than you do, is trading at tens of billions, and we are where we are. So it's my job to make sure that changes.

Speaker 2

And it's our job to just keep on executing, right? And, you know, we have a good team. We have a great team right now that, particularly on the go-to market with, and Stephen's brought some people in that just have expertise in this area. And all our job is to just go execute on the contracts that we've got and make sure that the new ones that come in don't divert us into new types of development. You know, we'll use the ecosystem for that.

Speaker 4

Makes sense. Thank you very much.

Speaker 2

Thank you so much for having me.

Speaker 4

Thank you, everybody.