In this episode, we speak with Alex Bouzari, chairman, CEO, and co-founder of Data Direct Networks, or DDN, a company specializing in large-scale data infrastructure for artificial intelligence and high performance computing. DDN has supported over 500,000 GPUs and has enabled tens of exabytes of data across enterprise AI, analytics, and research workloads. Its technology underpins critical operations for organizations such as Nvidia, NASA, PayPal, and many others. Alex co-founded DDN in 1998 alongside Paul Block to address the data bottlenecks in emerging supercomputing environments. Today, the company's technology underpins data operations for more than 85 Fortune 500 companies across sectors including financial services, automotive, and healthcare. I'm your host, R.J. Lumba. We hope you enjoy the show. If you like the episode, click to follow.
R.J. Lumba is the executive chairman of Market Insight Media and the managing partner of GrowthCap. He is the host of Great Entrepreneurs, a podcast for driven entrepreneurs and business owners. Our podcast covers all topics related to the entrepreneurial journey from ideation to execution to optimization and to reaping the rewards of a well-run business. In the minutes ahead, we'll share with you unique insights and tactics from some of today's most accomplished and inspiring entrepreneurs.
Alex, thank you so much for taking the time to chat with us today.
It's a real pleasure, R.J. Looking forward to it.
So I think what's really interesting is that DDN has been around since the late 90s and it's been growing and been an active technology innovator in this whole kind of ecosystem hardware software and it seems like maybe in more recent years it's really come to the forefront. Maybe I'm wrong. You can give me a little bit more about the evolution of the company, but today it's intertwined, it seems, with the AI revolution and it's becoming front and center. You recently brought in capital earlier this year from Blackstone 300 million. Your partnership with Nvidia is a deep and broad partnership. So maybe to start off for the benefit of our audience, tell us a little bit about that journey that DDN has been on from the early days up to today.
Sure, absolutely. So we started out pretty much like Nvidia did in high performance computing. So we were solving these massive data challenges that government agencies and enterprises had in extracting value out of data. So they were using these large supercomputers and they did not have the data processing capability that would keep up with the supercomputers. So we developed technology that solved that problem very quickly. I think we became the market share leader for those types of use cases. At some point we were powering 60 out of the 100 fastest supercomputers in the world. And then about 8 years ago Nvidia was looking at standing up a reference architecture to demonstrate the capabilities of their GPUs in solving AI. And that's how our journey pivoted and expanded from high performance computing into AI. And by the way, eight years later, Nvidia still uses DDN exclusively as the third party technology internally to power their own clouds and infrastructures. So I think it was a natural evolution because as you get to solve complex problems for high performance computing and supercomputers, well AI exhibits many of the same attributes. It's very very large amounts of data as you can imagine. I mean we're seeing it for the models that are getting built by OpenAI, ChatGPT, by xAI, Grok, and so on and so forth. So it's very large amounts of data that have to be processed in real time. So these are very complex problems that organizations who come from high performance computing can solve easily. So that's been our journey. I think it's been an evolution from solving one type of very complex problems to solving similar problems in a market which is much larger and is growing much faster.
And you have a data intelligence platform and I think the way you've been communicating where you fit is in the stack as well as above the stack. Can you help explain what that means? So in the stack, yeah, where's DDN?
Yeah. So think of it as we are to data what Nvidia is to compute. So Nvidia has developed GPUs which sit in data centers and greatly accelerate the processing of data in order to gain insight. So they do that in the stack which is in the data center but they also do it above the stack. So above the stack refers to those use cases and those enterprises which have software stacks that they're using in essence to gain the insight which will give them a competitive edge or will give them a better set of services and products for the consumers or the organizations that they serve. So likewise we have developed a data intelligence platform which sits alongside Nvidia's GPUs and makes Nvidia's GPUs perform far more efficiently in a smaller footprint in the data center and with lower power consumption. So that's the in the stack enablement because if you ask anybody today what are the biggest challenges in AI they will tell you it's three things: I don't have enough GPUs, I don't have enough data center space, and I don't have enough power. So DDN is addressing those challenges by one making the GPUs run much faster much more efficiently so you need fewer GPUs, we do so in a smaller footprint in the data center, so you need less space in the data center, and we do it with significantly lower power consumption. So we lower that barrier. So that's in the stack. Then above the stack it's making the models run faster for instance. So you know xAI is one of our customers. We're powering more than 100,000 GPUs in that data center. The ability to bring in data and we're talking about more than a trillion elements in the data model is huge huge huge numbers and just very quickly have that model learn in order to deliver value to consumers is very important so that's the value above the stack and for AI initiatives to be successful for enterprises for governments for consumers well you have to lower the cost and you have to accelerate the outcome so that it's as real time as possible and that's what DDN does in a sense.
And as I understand a lot of today's largest corporations are using DDN. I think the status that I heard is seven out of the 10 largest financial institutions DDN is employed and does that mean it is across all of their functions or where they're using Nvidia? How would you kind explain the prevalence of DDN throughout the financial industry?
So typically the reason why financial services has been an early adopter of AI is that well as you can imagine financial services organizations have very complex models. They run those models with market data in real time in order to extract better insight and make better recommendations in terms of you know what their investors should be investing in. So the models are very complex and the edge that financial institutions have is the ability to deliver better insight faster with more data. So that's why you see many financial institutions and those are hedge funds, high frequency traders, banks and so on are embracing AI, are investing heavily into Nvidia GPUs and as a result are using DDN because DDN helps accelerate insight to data which translates into better returns for their investors. So that's pretty much where we sit. It's the business enablement and the financial enablement of AI as opposed to I would say the simpler problem which is efficiency gains. I mean you see people talking about AI well you know I have a customer service organization and now I'm going to fire half of the people on my team and I'm going to implement AI. That's not what we do. What we do is create business value and financial value for organizations so that through AI they can be more successful as opposed to just taking jobs away and replacing people with technology.
Would love to understand a little bit about your management team and maybe your co-founder too and how you all came together.
Sure. So Paul Block and I started the company back in the late 90s. We've known each other for a very very long time. We went to college together. That's where we met and we became best friends and then you know we started working together. I think we're very complimentary in our skill sets and our capabilities. But at the end of the day look it's all about the team. I think we've put together a top-notch world-class team on the engineering side, product side, go to market, finance, infrastructure and I think the ability of any organization and especially in AI to outperform and deliver better value to customers is the quality of the team and how well the team works together across all functional areas. So I mean the philosophy at DDN is it's all about customer delight. We wrap ourselves around our customer and every function in the company needs to work towards delighting customers. That's the only thing that matters to us. Delight the customers day in day out. Deliver more value to customers than anybody else will and they will continue to buy from you because you're delivering better business outcomes and better financial outcomes than anybody else. So that's how the team is structured. We have added lots of people in the management team as the company has grown especially over the last several years. I mean the company has grown significantly. We're now approaching the billion dollar mark in terms of the financial profile of the company. And so it's key to continue to expand, enhance, and add capabilities to our team across all functional areas.
And related to this expansion, as referenced earlier, you brought in significant capital and it seemed as though that was like the first big influx of capital. Perhaps you didn't need external funding previously.
Absolutely. I mean, we've always run the company with a focus on the bottom line, running it profitably. Again, I think if you really focus on customer delight and you deliver more value to customers than others, then automatically you will be able to run the company in a financially positive mode. So, that's what we were focused on for many many years. I mean DDN has been profitable for a long long time more than a decade from the early years. But last year as AI started expanding we started getting approached by more and more organizations financial organizations strategic organizations saying hey we want to be part of your journey and our question always would be what value do you think you can deliver other than capital because capital is not something that we need. The company is generating enough capital to sustain its growth rate and Blackstone came to us with a very interesting approach. They said look the way we do things we invest in industry pivots. We identify industries where something fundamental is going to change. We research that industry very very well and we place strategic bets. We do not spread our dollars across lots of companies. And so we've looked at AI and we feel that in AI there are two areas where there will be significant opportunities for growth and therefore for financial rewards. One of them is the whole data center and cloud side and they said we've selected CoreWeave and CoreWeave just had a very successful IPO. I mean the stock is on fire, the company is doing extremely well and they said the other area is data. So I think they saw it as data intelligence and they said we can help you expand and accelerate our growth and get you ready for the next phases of your journey. So that's how we engaged with Blackstone and the relationship has been phenomenal. I mean they have actually done what they said they would do as opposed to making promises and not delivering. They've actually over-delivered in being very wise strategic advisors and because of the network of organizations they're involved in. They've been very helpful in opening doors for us and putting us in front of the right people so that we can deliver this value add message to a larger set of customers.
