 Welcome back, everyone, to SuperCloud 6, AI Innovators. I'm John Furrier here in Palo Alto, along with Dave Vellante all day, bringing all the top players in the AI, generative AI industry from infrastructure, software, application development, all building out the next gen AI at large scale. Our Ancona CEO, co-founder of Chara is here, CUBE alumni, great to see you. Welcome back to our AI Innovators and congratulations. You guys are doing a lot of innovative things. In particular, the world spun directly as we had predicted in the last time you were in the CUBE. So thanks for coming on. Well, thanks so much for having me. It's great to see you again, John. So excited to be here and talk a little bit more about what we're seeing in the generative AI space. You know, I love the term luck. I believe that luck is playing, it plays out big factor. Luck is preparation meets opportunity. You guys really at the right place at the right time with the right team. Obviously, the last time you chatted on the CUBE, we're talking about cost optimization and all that good stuff. Now everything's generative AI and now that is the number one conversation right now on how much am I going to spend? Is the juice worth the squeeze? That's the question. Everyone knows they want generative AI but the question is how do they get that? So what are you guys thinking? How are you seeing this spending challenge or opportunity with generative AI? How are you guys seeing this play out? Of course, it's probably impacting your business but what do you see happening? No, absolutely. Well, one of the key things that we're seeing in the space right now is that folks are starting to realize the benefits of generative AI really from a cost perspective and from a revenue perspective and just things like what we've seen with Klarna replacing a good chunk of their customer success costs with something that's much lower cost in a production generative AI model is I think the tip of the iceberg but what customers are starting to realize is that the science, the best practices they're only about a year old and the hardware space is constantly changing. Look, you've got the H100, H200, V100 all coming out in the span of the next few months. Who knows what the next generation state of the art model is going to require and who knows what the actual cost to serve these models once they get product market fit and reach production is going to look like. And I think that that uncertainty is something that's universal across the customers that we talk to when they're looking to do their one year, three year plus commitments to their cloud provider and figure out how much of this capacity from a GPU standpoint or from a high end, you know, ASIC standpoint like in Ferentia or TPU should I plan to actually be spending on as we experiment, go through POCs and ideally get to a place where we can scale something up that's making real production top line or bottom line impact. I want to get into your business. I know you guys are doing extremely well. Not sure you can talk about revenue numbers but I know you've got a series B financing going on right now. You guys are again, right on the growth curve. What are some of the business metrics that's impacting your revenue in terms of customer adoption? What are people looking to spend on? I'll see how they procure compute and GPUs are changing and the platforms are changing. Jensen says it says software world now. I mean, Kamata is going over almost zero cost for compute and GPUs in the future. That's the premise where software now is the value. So what's driving your business? Give us a feel for some of the revenue. What's in your pitch deck? I should ask you. Absolutely. Well, look, I think we've been really fortunate to come out with the right product at the right time. As you said, so what our chair does is we're completely free cost optimization platform. We have customers who saved millions of dollars a year with us on AWS and now Azure. I don't pay us a single penny and we love that. That's customer obsession. And where we make our money is in providing a first of its kind new insurance offering for cloud commitments, which is as simple as saying is if you commit to three years to run this GPU machine with AWS and you only end up using two of it, we'll pay for the one. We're on the hook there. And so what we've seen in our space as we've gone to market and really in our first year going to market, we basically 10X our revenue is that customers are hungry for something like this because of the risk inherent in committing to anything in a space that moves as quickly as generative AI. The chips move quickly, the services you're committing to and software stacks as you mentioned, move quickly and customers want to move fast at a great cost, but not lock themselves into something that might not be the right solution for them one year, let alone one month down the line. What's your vision for as the first of all, by the way, that's absolutely accurate. You're seeing two things happen that's coming out of this super cloud event. One is the organic growth of developer appetite for building on top of infrastructure for GenAI. And two, enterprises bringing their corporate data to the table, which by the way, it's not that easy to just integrate that into a bottoms up. You need to get them both together. You're seeing enterprises trying to go as fast as they can while the infrastructure is changing so fast. In other words, it's evolving which means it's changing constantly. So there's a lot of risk on making a decision that could foreclose the future. Absolutely, and I think that it's a multi-tiered problem because the generative AI, the fancy stuff with the GPUs, to really make that useful in the context of your business, you've got to get your data strategy right. Heck, in some cases you've got to even get your data to the cloud in the first place. So you can use those platforms like Amazon EMR or Databricks or Snowflake to start extracting value out of those data sets that are proprietary to your business and really are the moat to the generative AI that you build that powers your business on a top line or bottom line basis. So I think there's risks at every piece of the stack that needs to be built to support gen AI and CIOs are starting to really realize this as are their counterparts on the finance side, which is where a product like ours that's really blending that insurance aspect with deep technical and cost optimization knowledge can really make an impact in the customers we work with. It's an interesting dilemma because if you don't move fast enough with AI, you could be left behind. If you move too fast, you could make a suboptimal decision on infrastructure. So timing is everything on this wave. I mean, it literally is. If you miss, miss fire, you can be driftwood. On the other side, if you're too late, you missed the wave. So interesting dynamic. How do you guys see this playing out from a use case perspective? Because obviously your success is based on the fact that this demand for gen AI infrastructure and two, they don't want to pave something they're not going to share they're going to use. So what are they doing? What are your customers doing with Gen AI? How are they approaching it? Are they more on the app dev side? Are they looking for a hedge against costs on infrastructure? What do you see there? What's the power dynamics for your success? Absolutely. Well, now we're tracking billions of dollars of annualized cloud spend against hundreds and hundreds of customers that work with us ranging from some of the largest enterprises to fast moving generative AI startups and everyone in between. And I'd say that the kind of most common thing I've seen is then people are experimenting with generative AI but the very earliest minority are really putting it out into product or into internal processes and getting really large ROI from it. We're kind of in that earliest of adopters phase where folks are going from, hey, this new technology exists. Where can I apply it to a POC has been run? We've seen a really great ROI and now we're scaling it across our customer base or across our internal teams in a very specific way. Obviously we saw the reporting from Klarna which was kind of an example down on the internal side but look at folks like- Explain that example real quick. Explain that example real quick. Absolutely. So Klarna reported in their earnings that they were able to replace a significant fraction of the volume going to their human-based support team with responses from a generative AI based model. And I think across the customers that we're looking at particularly large enterprises that's been a really great beach head along with software development and code generation for this generative AI to make real dollars and cents ROI impact. Now compared to the organizations that we work with who actually do generative AI to drive top line revenue as part of a growth driver for their business the usage that we're seeing from the internal example is actually much smaller. And the customers who are really leading the pack here from a spend perspective are the ones who've gone through the training figured out what model works for them think of like an Adobe with a firefly. Hey, this thing really works makes the workflows better or Microsoft with a co-pilot. And now they're starting to contract real revenue against it. And with that revenue and usage growth their inference spend starts to scale with the number of customers they have. And what I'm looking at in our customer base as an indicator for if someone has really made that kind of product market fit transition with generative AI is are they really projecting forward that their inference spend is going to surpass their training spend and there aren't these spend on these models. And I'd say a very small proportion of our customers are there today but over the course of 2024 I think a larger number of customers will probably get into that early majority of customers starting to really get to that point from a spend perspective. So you're seeing in your customer base both cost optimization and revenue growth. Correct, the cost optimization is obviously coming from different places where the revenue is growing but the broad strokes is that budgets are growing not as much as they did say in 2021 or 2022 but a lot of that is going towards these generative AI initiatives and the dollars that are coming back from cost saving on your traditional kind of web serving workloads or database workloads those are getting reinvested back into these gen AI efforts. So I think that's been the common thread of the last quarter, quarter and a half. Okay, so let me play the role of a customer then I'm going to play the role of a VC because I know you're doing a funding round so I'll ask you a few questions on that with a funding side but first I'm a customer pretending I'm a customer love what you're saying I'm in my number one concern is I want to make sure that the money I'm saving and or the money I'm gaining which is net benefit has to be more than my cost. So do I come to you and lock that in? How do you help me? Do you come in with a like a TCO calculator? I mean, cause I want to make, I want to make sure I'm not overspending to get that savings. Take me through that use case. So it's one of the really unique things that we as our chair provide as part of our free platform is a full scenario modeling tool where you can go in, pick any stack of services from AWS from any of their marketplace vendors and figure out in, you know, some scenarios what the cost of that including things like your commitments like our eyes and savings plans or things like our insured versions of our eyes and savings plans what things like an enterprise discount or credits layered on top figures into as a total cost of ownership. And you can do this before you even run the Terraform template or click through the console and spin up that instance and customers love that because they're able to understand and go to their management with some of these very expensive, first box of the project type skews to spin up that might have 24 GPUs attached and really get that clarity in terms of what's going to hit the AWS bill at the end of the day who's going to own it and then what can we do to reduce the cost and the risk of running this workload be it buying a three year commitment if you're sure you're going to use the H100 for the next three years or buying an insured version from us that gives you the flexibility in case the technology changes. And so I think that's been one of the key things that we've seen with our customers as a huge requirement now that the barrier to entry of any new project is 10 X what it was before this generated AI boom. What's great about your company is you're actually on the growth curve doing a series B financing. You're on the upslope. Good funding round for companies like yourself. So I'm sure you're got a lot of action going on. So I'm the VC, what's in it for me? What's the investment thesis? What are you promising? What are you looking at? That's going to be the key driver revenue growth customer acquisition. What are the key metrics? What's the key highlights of your fundraising deck? Well, all of the above, I think one of the key things that we're seeing is that as this model has been validated within the customers that we've worked with in North America, internationally customers are knocking on the door as our partners. Beyond that, larger and larger customers are starting to knock on the door including some large Fortune 500s who are starting to understand, hey, if I'm insuring my biggest line item which is my employees health insurance, my second biggest line item is cloud. Shouldn't I be insuring that as well? And obviously we're looking to add more products both from what we insure as well as new SaaS products and new products for our partners to go to market with them more effectively. And we're already working with some of the largest and most important MSPs and global partners of AWS. And I think we want to do more of that over time. So all of that is in the service of growing the business and taking this vision of commitments for cloud insurance really to the broadest market possible. And that's really everyone using the cloud today. Well, last minute we have left. I'll give you the floor, share, quick plug for what you're looking to hire. So you're doing the fundraising rounds. So good luck with that. Thanks for that sharing that pitch there. What are you looking to hire? What's the stats? Put a plug in for your vision. You know, absolutely. Well, we're hiring for amazing engineers who know the cloud well. We're hiring for great sales people who've come from the cloud or the broader channel ecosystem. And we're also going to be hiring for executives on the finance side as we grow that side of our operations. So, you know, we're looking for amazing people wherever we can find them. And I think one of the key things that I'd love to talk to customers about as we get into this year is figuring out how to budget for generative value. We're looking for more customers who are interested in this idea of insurance for GPUs for their cloud commitments. And we're very excited to have more conversations as the space develops. And as we see kind of the technologies and the trend shift. It's its own financial economy right now, this GPUs is, you know, you definitely got to be in some good action going on. Thanks for coming on. I appreciate it. And thanks for the, the contributions part of our SuperCloud 6 and participating in our AI innovators. Absolutely. Thanks for having me, John. It's good to see you again. Take care. Okay, that's SuperCloud 6. We'll be right back with more all day here in Palo Alto. I'm John Furrier, your host of theCUBE with Dave Vellante and our team. We'll be back with more coverage after this short break.