We are just delighted to have Tom Siebel with us at the Citizens JMP Technology Conference. C3.ai is hosting their Transform User Event, starting tomorrow. Where is it? So I said it's our user group, International User Group Conference in Boca Raton. It started Wednesday morning at, I think, 8:00 A.M. East East Coast time. And we will have our largest partners and customers speaking there about the well, I mean, our product managers will prepare the product roadmap. There'll be, I think, five or 600 customers and partners there. And then our customers—think Shell, think Dow, think Cargill, think United States Air Force—will be talking about what they, their experiences of deploying the C3 AI solutions, the economic benefits, what the benefit they've realized and what they'd like to see from us going forward. So if you're interested in, like, firsthand seeing it from the real people, the extent to which they were receiving economic benefit from what we're doing and the extent to which they're being successful with these projects, I encourage you, you just go into our website and register and it will be live cast. My point on that is we're grateful that you made the time to come spend time with us even though you've got all these people waiting for you in Florida. So thank you. Next time. All right. The other thing that Tom pointed out to me, on our callback, which I then bought, is this is the tiniest book. This book is only 100 pages long and it's called What Is ChatGPT Doing and Why Does It Work? I'm on page 2, okay? And I've already learned this is all I do, okay? So, like, this is and it is the clearest, best explanation of so for example, can anyone explain what temperature is in an LLM? Not you, Ahmed. Anyone who doesn't work at C3, right? So by the time you get to page 2, you will understand how it is that these models are adjusted to be more creative or less creative. And it is so simple. So anyways, this was Tom's recommendation. You can get it on Amazon. It costs nothing. And highly recommend. Okay, Tom, thank you for coming. We'll start out with my standard question, which this year is actually really great because you guys just reported your results, right? How's business? Business is good. Yeah. F or some years now we've been predicting that there would be an enterprise AI market. While there was much speculation about the addressable size of that market over the last decade, whatever the speculation was, it turned out to be quite a bit larger than that. I looked up the market cap of public AI companies this morning on my way in on Google Bard of all things. I think the combined market cap of public AI companies is somewhere between $7-$9 trillion. It appears that there might be a market here. We spent the last 15 years getting ready for this. We spent, over a decade and $2 billion building a platform that enables a software platform that allows us to design, develop, provision, operate large-scale enterprise AI applications. On top of that, we've built more than 40 turnkey enterprise AI applications. So as we enter March of 2024, the market seems to be coming our way. And a lot of people want to deploy enterprise AI applications. And if there is, I think, one company in the world that offers a family of enterprise applications that address the value chains of financial services, defense, intelligence, oil and gas, manufacturing, what have you, and that would be C3 AI. So business looks promising. We've made it through our pricing transition from subscription-based pricing to consumption-based pricing. We experienced the downturn in growth rates that we predicted, okay? And now we are experiencing the upturn in growth rates that we also predicted. F or those of you who still, you know, know how to do regression models, you'll find that, you know, the correlation between our growth rate and the stock price approach is one. And so as we return to rapid growth, the stock price seems to be, well correlated with that. Yeah. When you accelerate, stocks tend to go up. So talk to us a little bit, you know, what is the demand like? What are the conversations that you're having, like, in the federal government? What's it like in enterprises here in the U.S.? And then what's it like internationally? There's no Secretary of a Service, no government leader, no CEO in the world who would not take a meeting about Enterprise AI today. Not one, okay? And so the doors are wide open and they're trying to figure out what it is, how it works, the way that we have that at the product price today where it's, you know, we will take a value, you know, a supply chain, a demand chain, a production line, and we will, we'll optimize that using we'll bring that into production with an Enterprise AI application in full production use in six months for $500,000, $500,000. I mean, this person doesn't need budget, okay? It doesn't issue an RFP. This person just signs it for $500,000. It's live in six months. And then, if they like it, they keep it. W e're finding the interest in what we do is very high. The number of customers with which we're doing business has increased dramatically, I think 85% increase in customer engagement year-over-year, if I'm not mistaken. Okay. And, you know, business is good. Yeah. I think we have 4,145 customer engagements today, up 85% year-over-year. The market for what we're doing is on fire. Yeah. And most of the companies that we talk to don't actually talk about customer engagement and measure it the way you do. So explain to us how do you define it? Well, it's difficult for us to identify Department of Defense, for example, as a customer, okay? For example, I have, you know, three different projects in the Missile Defense Agency. And those are unique budgets, unique projects, okay? And those are three customer engagements. I have multiple engagements in the United States Air Force. And those are unique customer, separate budget, separate problem, okay? Separate division of the Air Force. And, so those would be that would be a customer engagement. In an organization like Koch Industries, we're installed at, you know, Flint Hills Resources. It's clearly quite different than Georgia-Pacific. It's just quite different than Molex. And those would be different customer engagements at Koch. All right. Great. So, for people who don't know, so this business in 2022 grew basically 40%, then 2023 decelerated to 6% and now is starting to re-accelerate again. What drove that and where can it go? Well, I think we're, so in Q2 of 2022, we're going to 42% exactly, okay? We announced a transition from subscription-based pricing, which meant our transactions were $10 million, $20 million, $30 million, $40 million, $50 million upfront to get started. This is how we operated as a public company as a private company. And so our customers financed the business. And we would do business at $39 million or EUR 39 million all day long, which is good work if you can get it and you don't have to ring any doorbells on Sand Hill Road, okay? As we transitioned to a public company, we transitioned to consumption-based pricing, which is just pay as you go. You know, ipso facto, we saw a decline in our growth rates from 42% year-over-year growth rates to 0%. Now as consumption pricing has kicked in, it's increased from, you know, 0% to 11% to 17% to 18%. We've seen dramatic growth in underlying infrastructure in AI in the past year or so. I think NVIDIA revenue was what, what, 260% or so year-over-year, GPU revenue up 400% year-over-year. What we're seeing happening with the cloud providers is quite dramatic. I think the enterprise value of public AI companies today is $7 trillion. And so this AI market turned out to be the real deal. We play in an important segment of it. The game that we're playing is to see if we can establish and maintain a market leadership position in enterprise AI, okay? This is not social media. This is not, you know, deepfakes. This is running core business processes, supply chain, demand chain, demand forecasting, fraud, manufacturing optimization, customer churn, customer satisfaction, et cetera. You know, that is a large and rapidly growing market. Now at Oracle, when we started that, we were nothing. We said we were going to establish and maintain a market leadership position in relational database. I think we did a pretty good job. At Siebel, a decade later, Siebel Systems, we set out to establish and maintain a market leadership position in CRM. We created that market and we sold the company to Oracle; we had 85% market share. I think our revenue at the time was order of magnitude $2 billion and Salesforce was order of magnitude $200 million. So, I mean, the company was doing pretty well. After that, you know, Marc did a pretty good job of building his business. Good for him. You know, we might not succeed. We might fail. We might end up number two or number three, okay? The number two or number three company in Enterprise AI, okay, is not worth $3 billion. Currently you're guiding it around a little over $300 million in revenue, right? For 2024. For 2024. Yeah, I think that's right. You'll know better than I. Just order of magnitude, you're talking about it's still a really small business in the greatest scheme of things, right? It's minuscule. Yeah. How big can it get? I think this can be one of the largest, most successful companies in the information technology business. I do. I think this is this is the real deal. We have great products. We have great customers. Listen to the dial into the users group meeting Wednesday or or Thursday or have one of your people do it and see what the customers say. I mean, customers will stand up and say there's a customer who will stand up. Shell will stand up and say they have stood up and said they're getting $2 billion in economic benefit a year from using our products. People, how many people will sit up at an SAP conference, an Oracle conference, a Siebel conference, a Salesforce conference, an IBM conference, okay, and said they're getting $2 billion in economic benefit a year from their products? That would be zero. And so this is. I encourage you to dial in and see what they have to say. Yeah. And, you took the business from losing money to basically getting to break even. And then this last quarter, I think operating loss or the operating cash flow was negative $39 million. So what was the. You're talking about break even in cash flow? Because I don't think we've made it break even in profitability yet, Pat. I think that that happens next year. And so we we will run at Siebel. I ran a consistently cash positive, profitable business for a long time. I am a cash positive, okay, profitable business guy. This is what I do, okay? I do really understand that. I get it, okay? And we were running a cash positive, profitable business back in the dot-com era when when that was completely out of vogue, okay? So we're, so our goal is to run a consistently cash positive, okay, non-GAAP profitable business, okay? That is that's the business plan. We will do that. And I have some experience and track record doing it. This This is it's not that hard, guys. I mean, if you have a structurally profitable business, which we do, what do I mean by structurally profitable? If your cost of sales and your cost of selling is lower than your revenue, you have a structurally profitable business, right? We could turn this into profitability tomorrow. All I got to do is lay off some people and cut some, you know, cut some marketing and R&D costs. And it's non-GAAP profitable and cash positive tomorrow. Is that in the best interest of the shareholders of C3? No way, no how, okay? But, you know, so this business of running a profitable business, I mean, it's not that hard. I mean, I didn't get to go to the Harvard Business School, but I imagine if they had a class on that, it would be something like, you know, figure out how much revenue I would come in and spend less than that. Got it, okay? We really do understand that. And this is what we will do. But you decided to reinvest is the point. We are reinvesting. I am investing in generative AI. When you made that decision and why you did it? I made that decision, I think, about four months ago. And this, you know, when we got into this generative AI market, which emerged really, you know, as we got into 2023 and, you know, every time we look at it, it's bigger than we thought. It's, I have no idea how big this is. It's just breathtaking. And the, you know, we've come up with a unique, highly differentiated solution. We're continuing to be really, you know, impressed by the creativity to which people are applying this technology. But, you know, we are investing in generative AI. We're establishing brand. We're establishing brand leadership. We are building product. We're establishing market share. And, you know, if you, you know, I gave the leading indicators in terms of what we're seeing in terms of web traffic, lead traffic, what have you, and they're extraordinarily positive. But I'm, you know, we have, I think, $750 million in the bank. So we really I mean, we're not, I can assure you, for those people who come to my desk and want to spend money, the default answer is no. We start with no, okay? And then we move from there. So we're very, I think, discriminating how we spend money. But we're a well-capitalized business and we're investing it prudently into this to establish a market share, a step established market share in generative AI. Okay. One more for me and then we'll open it up to the audience. I totally didn't include this on the list of questions. Sorry. What do you make of Elon Musk's lawsuit? Did you get a chance to look at that where he's suing OpenAI and he's basically saying, hey, look, this is. Sounds to me like he's dead right. I mean, when those guys had the meeting, hold on, they had the meeting at Madera, okay? In what was it? 2015 with Brockman and, with Greg Brockman and, and, what's his name? Altman. And these guys decided that it was unfair that, oh, that, that, Google had all the human capital and all the Google stack was proprietary. And the deal was that they were going to build the deal. Back then, they were going after AGI, which I would argue LLMs are not. But, okay, that was the goal to go after artificial general intelligence. You know what all that you know what that is, okay? And the and and and and, Elon said, listen, I'll I'll write a check up to whatever you guys go raise the money and whatever you don't get, I'll chew it up to $1 billion. I mean, he did it, okay? And the deal was everything we're doing is going to be open source, okay? And everything we're going to do is going to be free. That was the deal. For the benefit of humanity. Yeah. For the benefit of all, that was the bargain. So I think he's got a legitimate gripe. Now, whether anything, you know, whether there is a rule of justice in the United States, I'm not quite sure and how that might work out in the court system, I don't know. But I mean, if you play back the tapes on this, that was the bargain and that's definitely not what they're doing. It is not for the benefit of mankind. It is not open source and it's not available to everybody. That was the deal. So he's got a legitimate gripe, but he did pay for it. Questions from the audience. If you please, say identify yourself, please. Dave Pazuransky. I'm with the San Francisco Zen Center Endowment. So. San Francisco, which endowment? Zen Center Endowment. Okay. Fast forward 3-5 years and imagine you are saying to your C-suite staff, "Oh crap, I didn't see that coming." What might you be talking about? Well, I tell you what, I think the constraint will be in 3-5 years. I think it will be power, okay? Okay. We believe today, I mean, right now we have all these guys at, you know, my friend Jensen, okay, and the people, okay, and Andy Jassy and others kind of laying the infrastructure for what we do, okay, with all these the cloud infrastructure and all these GPUs, okay? I think the constraint is not going to be availability of GPUs and people as they believe today. I think it will be availability of power, okay? PG&E for details. So if we want to build a data center, okay, in Redwood City, PG&E will not provide us power, okay? And as you go south in South Silicon Valley, you also cannot get power, okay? So I think power becomes the, you know, at first it was change management, then it was GPUs that appeared to be the constraint. Well, first it was software. We got beyond all that. I think the constraint will be availability of power. And that's critical. Here's a great data point I heard on that from another CEO who's here, which is that to get 1 lousy MW of power from the leading provider in Japan, you have to wait until Q2 2025. That would be TEPCO. Yeah. 1 MW. Yeah. Yeah. The most energy-efficient industrial nation on the planet. I mean, those guys are really good. Other questions? Hi. Hi. My name is Robbie. I'm with Investment Strategy Analysis. I have a question. Do you think we are in an AI bubble of sorts or is this just the beginning of a giant run? Either, you know, I don't know if we're in a bubble. We will be in an AI bubble at some point. You know, look at every if we look at every major, you know, technology change from transcontinental railroads, urban electrification, the Internet, okay, I mean, they all result in the market all, you know, kind of they overvalued initially these technology changes that which were very significant positive technology changes. And let's go look at the dot-com explosion. And many of you were there and I can assure you I was there, okay? And the and okay. So this thing blew up about 2000, okay? How big was the Internet in 2000? How big is the Internet now? Significantly bigger today. Like maybe three orders of magnitude bigger today. So however big we thought it might be then, I mean, we couldn't have imagined what it is today. So will the market correct itself at some will it over will it overvalue this? Yes. Will it correct at some point? Yes. This is what markets do. You know, this is why you guys make the big bucks is to time that correction. Good news is I don't have to worry about that. All I have to do is focus on, you know, making customers satisfied and and growing the business, growing the business, growing the business. You know, the market correction will it'll correct and then it'll it'll take care of itself. Good. Thankful I don't have your jobs. You guys have hard jobs. Other questions? When there's no, that was somebody just yawning in the back. We're looking at you guys. Looks like we're off the hook, Pat. You know, so what are we focused on at C3? We're focused on technology leadership. We're focused on thought leadership, okay? And as we move into 2025, 2024, we're going to be questioning 2024, 2025, 2026. We're focused on growth, growth, growth. We're focused on market share, okay? Okay. In the way these markets work, somebody is going to establish a market leadership position. If not us, who? Okay. And so we're focused on, you know, accelerating this market and establishing market leading position. Question. Austin, Citizens JMP, question is the 15 years you've been developing this technology, can you break down for us what in those 15 years is giving you a competitive edge? Are there any other players that are coming to this space? You talk about the expanding market, but you still have to be vigilant in making sure that you are tracking with that expanding. Great, great question, Austin. I would say the investment we made beginning in the first decade was the most important one. So I mean, understand when we started, AWS had just gotten started. There was no Azure. There was no Google Cloud, right? Nobody talked about enterprise AI. Nobody talked about enterprise AI, you know, and people kind of remember Marvin Minsky talking about it in Princeton in 1951, but that's all they knew. Okay. Now the, you know, I think the investment we made that differentiates us was the 10-15 year investment we made in the C3.ai platform, the software stack that just massively differentiates us from everybody else in the market. So what Watson, what our bots, actually what IBM argued they built with Watson, which was a complete fraud, we built it, okay? What GE attempted to build with Predix, we built it, okay? And so whether we're deploying what's really counterintuitive about this, whether I'm deploying predictive maintenance at the scale of the United States Air Force, customer churn in Bank of America, whether I'm doing stochastic optimization of demand chain and supply chain at Cargill, 90% of the percent of the code in all the predictive maintenance for offshore oil rigs, hydrocarbon loss accounting, it's Shell. It's 90%, 7% of the code is identical across all those deployments. So the C3.ai platform is a core differentiator that distinguishes us from any other attempt to stay under this market. All right. I'll ask the last one in the last 30 seconds. Biggest near-term opportunity for C3 in the federal government? Biggest near-term opportunity in the federal government. We have an application, called CBM Plus, from the Rapid Sustainment Office where we are the standard for predictive maintenance in the Department of the Air Force. So one of the assets that we work with is an aircraft. And the United States Air Force has 5,000 aircraft. At any given day, about half of those will deploy and half are down for unscheduled maintenance. Well, you can use AI to predict system failure and subsystem failure before it happens. So auxiliary power unit, flap actuator, igniter in the afterburner of a B-1 bomber, whatever it might be. If you can predict it, you can identify the failure 50-100 flight hours before it happens. You can dispatch the personnel and the material to converge with the aircraft, fix it that night in Munich, it flies away, and net net, we get 25% increase in aircraft availability. Biggest short-term opportunity is to move this from the Air Force to the Navy. The Navy has more planes than the Air Force to the United States Army, to the Marines. Okay. So that's the biggest defense opportunity. The biggest opportunity in the short run is actually state and local government. I never anticipated this. This is turning into a really. We went over. So the short version on the state and local government. There are four applications that we're dealing with. One is, we brought AI to the assessment problem, property assessment. Why is property assessment important at the county level? Because this is the only source of their revenue. So we decreased the time to do an assessment of a commercial or a real estate structure by like a factor of 10. T he other error, the other area that's really turning huge is this is not an AI application, by the way, but the pendulum has swung. And even right here in River City in San Francisco, law enforcement is coming back into vogue. So we have a C3 AI law enforcement app that we're deploying at law enforcement agencies all across the United States that is, really gaining a lot of traction. Thank goodness. Well, thank you so much. It was great having you here. We really appreciate it. Thank you.