C3.ai, Inc. (AI) Earnings Call Transcript & Summary

Tom, good to have you here.

Thank you.

To connect in person. Just you kind of had kind of really good solid results yesterday. Maybe we start a little bit like on a quick summary of that one and then kind of be going to kind of deeper into see free more from a kind of industry perspective, but like to get everyone on the page like what were the highlights for you from yesterday's results.

Well, what's kind of the big picture. I guess we're about roughly 1/3 of $1 billion business. We're a computer software company. We're growing at a -- the idea was to build a platform and a set of applications that would allow organizations to apply elastic cloud computing, big data, Internet of Things and predictive analytics to build enterprise applications. So we've built a family of 42 enterprise applications that provide predictive analytics for the oil and gas industry, the utility industry, health care, manufacturing, aerospace, defense, intelligence. And we started in January of 2009. Today, we employ about 900 people and operate in any number of cities around the world. And in this space of building turnkey enterprise AI applications, I think we might be the largest company in the world.

Yes, yes, yes. And then if you think about the -- like everyone is asking about macro, like where do you see customers and customer's priorities around like what you're offering? How high is that on their kind of mindset at the moment?

Well, if we look at enterprise application software. So I was there when we started that industry. Okay. And what we did is we took relational database systems. We built tools on top of relation with database systems so we can build forms and reports. And then we've built ERP and manufacturing and supply chain in CRM, and that is roughly $0.5 trillion business today and it turned to be a pretty good idea. That would be Oracle, PeopleSoft, SAP, Siebel, what have you. Now we use those applications. Without those applications, it would be impossible to operate enterprises. And we use those applications to report both for managerial purposes and regulatory purposes. With perfect 2020 hindsight, what happened 30 days ago or 180 days ago? What inventory levels were, what customer churn was, okay, what cash levels were? What was -- what was a failure rate of devices. Okay. Now enter this idea of predictive analytics, okay, that promises to be a $600 billion software market in a few years. I mean all that is, I mean, it's really simple. But when we take this large installed base of SAP, Oracle, PeopleSoft, Salesforce and what have you, and we make these applications predictive, which is what we do. Okay. In addition to telling Boeing, okay, how many parts they have in their supply chain from [ Bremerton ] Washington or South Carolina, all the way to Shenzhen and a Boeing 777 has got a million parts. And then you got [indiscernible] 767, 757, 747, 737, 707, et cetera. So there's a lot out of parts and a lot of bins and you need to report what they all are very, very accurately. Because rather than a report, so this is for roughly last time I checked, a $60 billion aircraft manufacturer or we can tell them what their customer churn was or we can tell them what the failure rate of their equipment was. Now when we make these applications predictive, we can tell Boeing, Dave Calhoun, exactly how many parts he needs in each bin in the next 6 months to meet this demand function, which, oh, by the way, Boeing is not doing a very good job of and that's why they're not shipping airplanes, okay? Or we can tell them rather than simply tell them what their -- where their breakdowns and the supply chain were, we can predict breakdowns in the supply chain so we can mitigate, get the right part to the right place, the right timing, rent in or South Carolina wherever it is and deliver the product, OTIF, on time in full to Southwest Airlines or me or whoever it might be, okay? Rather than to report to him what the -- what his customer churn was, okay, in the last period. We can tell them which customers are going to leave in the next year, so you can do something the same. So this is what happens when we make these companies, where we make these applications. It's predictive. And I will argue that this is in 5 years, there is no Board of Directors that is going to tolerate a CEO standing up and tell them where the supply chain broke down. Okay? None. Okay. Or what our customer churn was. I'm sorry, that's not going to be -- that CEO will be gone. So it's a -- it's not a 100% replacement market for enterprise applications, but it addresses all of the problems that we addressed in the enterprise application software and we're making them predictive. And that's what we do at C3 AI.

Yes, yes, yes. Okay. Perfect. And then when I first looked at your kind of forward like, okay, is this like an AI platform. Or you talked about all the applications that you have there, like when you started out the business, how did you think about it? Was that like -- was the idea to build the platform business? Or was the idea to have like help customers with kind of solutions?

Great question. The first application, we started in January of 2009, and the idea was to build an application. Okay. And the application is what you could think of today is like ESG on steroids. So we wanted -- this was like the ultimate clean tech play. We run and take an organization the size of a General Motors, a Dow Chemical, United States Army and be able to characterize their energy and carbon footprint in real time and report on it in any number of formats. In order to do that, we had to build a platform. So we spent $1 billion in 10 years, $1 billion. This is not like some Sequoia dollars or government dollars. It's like real money. Okay. This is not Sand Hill Road dollars. This is real money. Okay. And building a software platform that basically allows us to build any kind of predictive analytics application for any industry. First, we apply it to energy, okay? And then we apply it to oil and gas. And then we apply it to aerospace, financial services, health. So we do have a platform when people do license the platform from us. But on top of that, we have 42 turnkey applications that address the value chains of oil and gas utilities, manufacturing, banking, what have you. Now we've seen something. So in the last 10 years, our primary competitor was some combination of the hyperscalers, Cloudera, Pivotal, the Apache Open Source stacks, data tricks, robo blocks, and all this kind of crip craft that's out there where people wanted to some CIO was going to take 20,000 programmers in Bangalore and try to build this themselves with some of these huge science experiments. Yes, I think my friend, Jamie Dimon, is hitting $1 billion right now trying to do this. Well, I mean, no way know how he's going to fail, everybody fails. And now we had a kind of a secular change in this market in the last month when all of the hyperscalers, Google, Thomas Kurian, okay, AWS, Adam Selipsky, okay? And Azure Scott Guthrie came out and said, our customers are telling us loud and clear. They don't want tools anymore. They don't want toolkits. They want turnkey applications. Well, you want turnkey applications that address supply chain, demand chain, okay, supply chain optimization, customer churn, okay? Predictive maintenance that run on the Google Cloud, AWS, Azure, Oracle or Bare Metal or on the Edge or in video box, this is exactly one doorbell in the world that you can ring on, that you can ring. And that's right down the road in Red Root City. And it says right above its the C3 AI. That's what we do.

And you talked about the -- how many, 46...

42.

42 so...

42 today.

Like how do you see that evolving over time? Like do we -- is there like a critical amount? Is there like diminishing returns at some point? Like how do you think about that number?

Well, you have a supply chain. You have supply network risk. You have demand change, you have customer churn. You have fraud detection. Now that's pretty much applied to all industries. Supply chain, you get into the DoD, they call it logistics. Okay. Fraud, they call it fraud, okay? But these applications apply to telecommunications. They apply to pharmaceutical, it chemical, oil and gas. And so it becomes a pretty big matrix of probably 300 turnkey applications before we're done. At Siebel, I think when we built Siebel Systems, I think we had almost 300 different applications that we brought to market, different variance of CRM for call center, field service, customer service, Internet self-service, sales automation for all the industry segments. And so it was...

The matrix.

It's about 300 products in the matrix.

Yes, yes. And then the -- if you think about that building it out like where are the [indiscernible] fitting in there? Like on the one hand, like I'm an old SAP guy like to -- so if you want to go deeper into certain verticals and kind of understand the process better and kind of work on that, you kind of need it as I just part of that. Like are you working with them, like how did that...

Well, we are. In Washington, D.C, we're working with Raytheon. We announced this morning a strategic partnership with Booz Allen. We do work with PwC. We do work with Accenture. So we kind of work with everybody.

Yes, yes. And what's their -- how are they building all their practices around you? Is it like...

Well, in the case of rate, Booz-Allen. Booz Allen is building kind of a very large in fact to serve the needs of the defense and intelligence community. I expect that PwC and Accenture, will be doing the same thing.

Yes, yes, yes. Okay. Perfect. Then the -- we talked about the -- you're building an application like the [indiscernible] where that happened, was that we kind of went from a kind of -- that we maintain a different pricing model, like consumption? Like can you talk about kind of that realization of lag, maybe actually the world's moving consumption and I need to change that -- like talk about that journey a little bit.

Well, historically, we sold on a subscription-based model where we would have 3-, 4-, 5-year commitments. So our average transaction value might be given $420 million. So for that to be true, we had to be doing our deals were $5 million, $10 million, $20 million, $50 million, $100 million at a time. Now that's good work, if we get it. Okay. And -- okay and it makes the financing business without having to ring any doorbells on Sand Hill Road and now particularly enjoy ringing doorbells on Sand Hill Road. So that enables us to build a very, very viable business without walking around hat in hand, begging for money all the time. And now -- but then as our products became more mature, and we had a partner ecosystem and a developer community and much richer documentation, online training and whatnot that enabled us to transition to a consumption-based pricing model. And in the cloud in the 21st century, I mean, a consumption-based pricing model just is the standard. It's the standard of GCP, AWS, Azure, Snowflake, you name it. And so we made that transition beginning last quarter where rather than selling multiyear subscriptions, we just allow people to buy the product and kind of pay as you go. Let's say, $0.55 per CPU or without having a gut-wrenching conversation about the $50 million or $75 million or $100 million upfront licensing agreement. That makes it a lot easier to do business. We can do business within any given quarter with, say, in order of magnitude more customers. And if you look at the revenue that we'll get from any given customer over, say, 10, 12 quarters, it's actually revenue neutral without having to go through to kind of...

Cycle?

What is an unnatural act today in cloud computing. No question. The cloud computing standard is there's consumption-based pricing. So it's really gone well.

It's like -- I mean, like because you have been in the industry, and I've admired you like for so many years, like the -- if you think about the evolution towards that consumption model, like when you back then, obviously, with Siebel it was like seat-based, et cetera, like if you think about that...

And like Oracle is perpetual, right?

Yes, yes. Exactly. Yes. It was all -- that was perpetual as well. Like if you think about that consumption model lake, do you think there's like certain parts of the industry? Or is that like something that the whole software industry probably have been...

I think it goes -- I mean it's pretty much going to be the standard in all industry segments, okay? Now that being said, if somebody was decided they really want to go big, like Shell or United States Air Force or somebody like who wants to go all in, they're going to drive up in their Mercedes and send them the guys and like, they're going to want some sort of enterprise license agreement. It will be on whatever terms they want, and it will be for a sufficient amount of money that a reasonable person will agree to their terms. And so then that just happens. That's the black swan. You can't model it but you know it's going to work it happens.

Yes, yes, yes. You take it. I mean like on that note, like you had like what's a baker use is like one of the big guys for you? Like their commitment towards you, but also like changing themselves as a company has been amazing. If you look at the dollar amount there.

The commitment to me was order of $0.5 billion. So that was a reasonably large software transition.

That is very large. Yes, yes. Like I mean -- and where do you see -- like I remember when the deal happened, it was like a big wake-up moment for a lot of the other guys like, "Oh, this is like a equipment or like equipment company that just kind of spend that much on...

Definitely, it repositioned them in the oil services market. I mean their oil and gas services market. Their competitors are Schlumberger and Halliburton. And as it relates to digital, there you look like dinosaurs compared to Baker Hughes.

Yes, yes, yes. And did you notice like pickup like in terms of other segments that you have, like are you kind of focusing on lighthouse customers that kind of could be that next Baker Hughes for a different industry? Or like was that just unique at the time?

Yes, honest answer, Raimo, it wasn't very sophisticated. It was really coin-operated. When a CEO walked into the door with a management team, a mandate, a check and the CEO is in the aerospace business, we're in the aerospace business. Okay? If we happen to be running a large European utility, we're in the utility business. Having in the world that Shell, we're in the oil and gas business. Or Lorenzo Simonelli walks in from Baker Hughes with roughly $0.5 billion offer, we're in the oil and gas business. And so now in the long run, there is no industry that's not going to -- no Board that's not going to mandate their CEO see around corners and identify problems in the supply chain before they happen, not [indiscernible] to the board, but why you can't ship cars because war broke out in Southeast Asia. I mean sorry not excuse, we got to ship cars.

Yes, Yes. No, fair enough. The last few minutes, I wanted to talk a little bit about the like one of the focus areas for this conference was that people realize, I need to think about more returns and think about more about my growth profile and how I'm growing, how profitable I'm growing. Talk a little bit about your own mindset in terms of like growth, profitable growth, where are you on that life.

Internal business. Yes. Okay. Well, we went public in December of 2020. We raised about $1 billion. And the purpose of that was -- and back in December of 2020, all of the analysts from all of the banks all went to the [indiscernible] School of Management, okay? And I would come in and explain that you're not spending up enough money, time. You're not spending enough money. You're not investing in a market, you're not investing in the market. And honestly, Raimo, between you and I, almost all of them graduated from business school after 2008, okay? And they've never seen anything but market that went up every day. Okay. So we didn't pay a lot of attention to that. That being said, when we went public, the purpose for which we raised the money was to build market share and to invest in technology, and that's what we did. Okay. Now clearly, the pendulum has swung, okay? And the markets are demanding the companies like us have a path towards profitability. Now we operate at an 80% gross profit margin. So come on, you know the software business. We're operating at 80% gross margin. How hard is it to run a profitable business? I mean I can be profitable this quarter. Okay. I only have one cost. It's human capital. So I do a big layoff and I'm probably cash positive and profitable that -- would that be in the best interest of our shareholders? No freaking way, okay? We'd be trading off future growth to make some analysts or one shareholder happy, okay? Now -- but if you look at what we're doing, last year, I spent 29% on marketing and branding, who spends 29% of revenue on marketing? That would be nobody, okay? 46% on R&D, who spends 46% on our data, Salesforce? Does Oracle? Does SAP? No way, no how. We're not even close. Okay, we spent 23% on sales. Okay, that's reasonable. We said 15% on F&A, maybe it's a little high, okay? But so our model is very simply we take -- we're operating at a gross margin of 80%. We keep marketing down to 11%. Sales will go up to about 25%. R&D will kind of come naturally down to scale to about 23% of revenue, which is a big number for R&D, F&A down to 12%. I haven't done the fast math, but the net of that should be we make about $1 profit, okay, in the fourth quarter of '24 and then we grow it from there. And so I see this as basically a 20% operating margin business. It will be throwing off cash. I think as this consumption model kicks in, in the next few quarters and about the same time and I don't know whether this happens in 4 quarters, even tell me, okay? When the Fed decides to take a foot off the brake, I mean, you're going to look at a company that's going to be a leader, if not the leader in enterprise AI software again, growing at north of a 30% compound annual growth rate, operating at a cash positive profitable business with a ton of cash in the bank. And so I think that's probably a product that equity markets will find it quite attractive when equity markets kind of recover from the current state of kind of chronic depression.

Yes, yes, yes. I mean like from you like you've seen this gain of game before, and you saw -- we had it at Siebel and at Oracle before. Like if you think about the noise coming from the financial markets, in terms of like, oh, now, you need to grow. Now you need to be like the guy that needs to kind of show me profitability, et cetera. Like for you as someone that needs to think more longer term, like what's your North Star in terms of like that balance between growth and margins?

I don't know how to tell you this, Raimo, but I'll still be here when that analyst has gone, okay? I've seen them all come and go and I'll still be here. And so our North Star is run a cash positive, but yes, at Siebel, we ran a cash positive profitable business from the day we shipped a product, okay? And we had 80% market share in CRM. We created the CRM market, right? 80% market share globally. When I sold the company to Oracle, I think our revenue at the time was roughly $2 billion. Marc Benioff, a guy who I hired at Oracle, okay, out of USC, studied business administration, okay, and have never seen a computer in his life. Their sales was about -- were about -- it's true, okay. Their sales was just $180 million, we're given about $2 billion. But -- so same story. I am committed to run at a cash positive profitable business, okay? We're committed to running a rapid growth business, and our goal is establish and maintain a market leadership position in this market. The market leader is going to have about 50% market share. Number two, we'll have 15% market share. Number 3, we'll have 10% market share. And then in expansive markets like a few years ago, there's another 20 companies out there once the market -- the music stops, all those guys kind of go out of business. So I think a lot of these guys are about to be gone. But that's our North Star. We're going to be a leader in the field, will be a great place to work, have satisfied customers, establish and maintain market share in Asia, in Europe, in North America, in South America, in manufacturing, aerospace, banking, telecommunications. And that's the game.

It's kind of funny, like the -- how do you think about these investment levels? Because I just interviewed the salesforce guy and they're like, "Oh, we could get sales of marketing below 35% and I was like, dude, you're only growing 10%. Like how does that work? Like -- so if you think about the like -- putting the foot down more on sales versus not putting the foot down like, is there a healthy level in terms of growth? Because the other thing is also, if you grow, if you overinvest and the wheels are coming off all the time, you lose the culture in the organization, et cetera. Like is there like -- I'm asking you because you've been around for longer than most of the other guys that are meeting there. Like is there a level that you think is like a healthy level?

I think that we will be investing about 40% in sales and marketing, okay? I'm confident we can be -- we can grow it. We can do that while growing the top line okay, north of 30%. And in a steady state, be drawing off, okay, 20% operating margins. So that is exactly where we're going with the model. We've done it before. We know how to do it. It's not rocket science. When -- if you have 80% gross margin business, I mean it's not that hard to make money.

Yes, yes, yes. Tom, that's actually a great closing statement. Hey, good to meet you in person again. Thank you.

Thank you, Raimo.

Thank you. Thank you.