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spk02: Good day, and thank you for standing by. Welcome to the C3AI second quarter fiscal year 24 conference call. At this time, all participants are in listen-only mode. After the speaker's presentations, there will be a question and answer session. To ask a question during the session, you need to press star 11 on your telephone. Please be advised that today's call is being recorded. I will now turn the conference over to your host, Mr. Amit Barry. Please begin.
spk01: Good afternoon. And welcome to C3AI's earnings call for the second quarter of fiscal year 2024, which ended on October 31st, 2023. My name is Amit Berri, and I lead investor relations at C3AI. With me on the call today is Tom Siebel, Chairman and Chief Executive Officer, and Juho Parkin, and Chief Financial Officer. After the market closed today, we issued a press release with details regarding our second quarter results, as well as a supplemental to our results. both of which can be accessed through the investor relations section of our website at ir.c3.ai. This call is being webcast and a replay will be available on our IR website following the conclusion of the call. During today's call, we will make statements related to our business that may be considered forward-looking under federal securities law. These statements reflect our views only as of today and should not be considered representative of our views as of any subsequent date. We disclaim any obligation to update any forward-looking statement or outlook. These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations. For a further discussion of the material risk and other important factors that could affect our actual results, please refer to our filings with the SEC. All figures will be discussed on a non-GAAP basis unless otherwise noted. Also during the course of today's call, we will refer to certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in our precedent. Finally, at times in our prepared remarks, in response to your questions, we may discuss metrics that are incremental to our useful presentation to give greater insight into the dynamics of our business or our quarterly results. Please be advised that we may or may not continue to provide this additional detail in the future. And with that, let me turn the call over to Tom.
spk04: Thank you, Amit. Good afternoon, everyone, and thank you for joining our call today. Results. Bottom line, we continue to accelerate our revenue growth and our customer engagement count and continue to gain traction with C3 generative AI and our enterprise AI applications in the second quarter. Total revenue for the second quarter was $73.2 million, an increase of 17% compared to $62.4 million one year ago. and accelerating from an 11% increase in the first quarter. The total number of customer engagements was 404, an increase of 81% compared to 223 last quarter. North American revenue of $61.2 million increased 28% year-over-year, while EMEA revenue of $10.6 million decreased 11% year-over-year. federal revenue increased 100% year-over-year. Subscription revenue for the quarter was $66.4 million, constituting 91% of total revenue and increasing 12% from a year ago. Gap gross profit for the quarter was $41.1 million, representing a 56% gross margin. Our non-GAAP gross profit for the quarter was $50.4 million, representing a 69% non-GAAP gross margin. Our GAAP net loss per share was $0.59, and non-GAAP net loss per share was $0.13. We ended the quarter with $762.3 million in cash, cash equivalents, and investments. C3's AI's partner ecosystem continues to drive significant growth. In Q2, the company closed 40 agreements through our partner network, including AWS, Booz Allen, Baker Hughes, Google Cloud, and Microsoft. The qualified opportunity pipeline with partners has increased by 75% in the past year. We signed new and expanded agreements with new core corporation, Roche, Con Edison, Hewlett Packard Enterprise, GSK, formerly SmithKline, the United States Navy, the Administration for Children and Families, the Division of Health and Human Services, Indorama, and First Bank, amongst others. Over the past several months, C3AI has helped Nucor, the largest steel producer in the United States, to better optimize caster production schedules, specifically to improve production levels and reduce cost levels in the steel casting process. C3AI is now helping Nucor scale this across several additional mills. In Q2, C3AI also kicked off two new additional use cases at Nucor, tackling process optimization and demand forecasting, and we also completed a C3 generative AI pilot targeting operational health and safety. GSK, formerly GlaxoSmithKline, is now using C3 AI supply chain suite to increase efficiency in its supply chain, using AI to optimize yield and improve demand forecasting processes. Con Edison, a C3 customers since 2017 continues to expand its use of the C3 AI applications, most recently by adding C3 generative AI. Con Ed is using C3 generative AI to help workers quickly find answers to questions and analyses related to smart meters, service levels, and infrastructure data. In the second quarter, Con Edison completed two pilots of C3 generative AI, which have now converted to production. We also continue to expand our footprint in state and local governments with particular interest in C3 AI law enforcement from San Mateo County, California, and C3 AI residential property appraisal from Stark County, Ohio and Charlotte County, Florida. Our federal business continues to show significant strength with bookings up 187% year over year. We closed new and expanded deals with the United States Navy, the Intelligence Community, Joint Staff J-8, the Defense Logistics Agency, and the Administration for Children and Families. We've talked many times about our success, our successes in helping to monetize or to modernize, sorry, the Department of Defense, and we're proud now to say that our products are helping civilian government agencies as well. This quarter, we began work with the Administration for Children and Families, a division of the U.S. Department of Health and Human Services. The agreement with C3AI was part of their first order under a $90 million blanket purchase agreement. This part of ACF's work involves helping unaccompanied children who cross the US border find temporary shelter and permanent homes. Our platform will be used in complex modeling and predictive analytics at ACF to help them keep track of the number of unaccompanied children in the agency's care, staffing needs, and determine how long these children are with their case managers, amongst other tasks. C3AI continues to leverage its extensive commercial supply chain experience in the federal government. It is now applying this experience to the defense sector with the C3AI contested logistics application for Transcom and for DLA. During the quarter, C3AI converted two Defense Logistics Agency pilots into follow-on projects for the Department of Defense. The first project delivers a common operating picture of the supply chain for DoD and enables leaders at multiple echelons to see in near real time their global Class 9 supply posture. The application unifies disparate supply data and provides the Defense Logistics agency the ability to identify supply chain inefficiencies, forecast parts consumption and part shortage, and conduct impact assessments and put into place mitigation plans. The second project supports DLA's energy directory, leveraging C3AI's commercial expertise in the oil and gas sector. The C3AI contested logistics application modernized modernizes and streamlines global fuel distribution for the Department of Defense. Users can see global fuel inventories, anticipate fuel consumption, identify supply network risks, and create distribution and transportation plans to prevent disruption and assure supply. These applications promise to significantly impact the efficiency of the Department of Defense logistic enterprise and improve readiness. Our partnership with AWS deepened with an expanded strategic collaboration agreement in the quarter. Okay. And the availability of our new no-code self-service generative AI applications, C3 generative AI, now available on the AWS marketplace. I think we announced that last week. This new application allows customers, users, of all technical levels to begin using generative AI within minutes of signing up. And this application CT generative AI is now available to you on the AWS marketplace under a 14 day free trial. And so I encourage you to take a look at it for those of you who are interested. Under the expanded collaboration agreement with AWS, we're focusing on offering advanced generative AI solutions combined with what they're doing in Bedrock and other initiatives for enterprises and for AI applications for customers in multiple verticals, including manufacturing, power and utilities, consumer packaged goods, state and local government, and the federal government. C3 AI... And AWS's joint qualified pipeline has more than doubled year over year with heightened interest in the C3 generative AI suite. In Q2, C3 has been recognized multiple times for its innovation in the AI space. We've been named to the Fortune 50 AI innovators list, and the list kind of goes on and on. So I'm not going to belabor that. We get recognized all the time. Pilot growth, this is important. In Q2, we closed 62 agreements, including 36 pilots and trials. Our new pilot count is up 270% from a year ago. Notably, 20 of these were generative AI pilots, 150% increase from Q1. With the lower entry price points of our pilots, we are more easily able to land new accounts. With our pilots, we're engaging customers across a diverse set of industries in this quarter, Our pilots came from manufacturing, federal, defense, aerospace, pharmaceuticals, and other industries. Now, we did see sales headwinds in the quarter. While the interest in AI applications, and especially generative AI, is growing substantially, we're also seeing, in many cases, lengthening decision cycles. Virtually every company in the last three to six months has created a new AI governance function as part of its decision-making process. These AI governance functions assess and approve those AI applications that will be allowed to be installed in the enterprise. This has candidly added a step to the decision process in AI. You might have heard it here first, but you will be hearing this from every AI vendor in the next few quarters. Take it to the bank. It has simply added a step to the process. And it is lengthening the normal sales cycle. So it's kind of, so, and so this had a, you know, this provided a sales headwind in the quarter. Okay. And while the increased scrutiny lengthens the sales process, we believe this is a healthy process to ensure that companies are adopting safe and appropriate AI solutions. So we're all for it. Okay. And, you know, did it, you know, move revenue, you know, a little bit, you know, a click below the center of the range. Yeah, it did. Okay. But you know, get over it. The world's a better place. People are making, you know, very careful, well-informed decisions. They have their best people on it and we will all be happier for this in the long run. Okay. So it did, you know, that dynamic did provide an unexpected headwind to our Q2 sales revenue performance. In addition, our sales execution in Europe was candidly unacceptable. And since then, we've been through our planning meetings and we've taken appropriate organizational steps to immediately improve sales execution in Europe. Now, let's take a look at if this is the big story, this is the top line. And really what this whole story has been about for the last six or seven quarters has been from the transition from subscription-based pricing to consumption-based pricing. And before we switched to consumption-based pricing, you'll recall the company was growing at quite a rapid growth rate, like I think seven quarters ago, order of 38% year-over-year growth rate. So we were definitely in the top quarter. And we announced the transition to consumption-based pricing that we believed would be and has become the standard in the industry. The consumption-based pricing is based upon per virtual CPU or virtual GPU hour, similar to the pricing at Snowflake, Google Cloud, AWS, Microsoft Azure, et cetera. Prior to this, we were doing large enterprise subscription deals of $1 million, $5 million, $20 million, $50 million. And it was a good business. That being said, the downside of that model was lumpiness in bookings, lengthy sales cycles, and low levels of revenue predictability. We believe the transition from a primarily subscription-based pricing model to an assumption-based pricing model, brought us into line with what we believe are today the industry standard cloud pricing standards, making it easier and less costly for new customers to acquire solutions and then increase their spending as their usage and adoption increase. We anticipated and announced when we made that transition that it would have a short to medium negative effect on revenue growth a long-term drag on RPO as the sales price was significantly reduced and the contracts often lacked a time-certained multi-period commitment. We believed when we made the announcement that the conception-based pricing model would increase the number of customers and increase the total amount of system consumption, resulting in a return to increased revenue growth, increased customer growth, decreased average selling price, and decreased RPO over time. Now, while we are still in the process of working completely through this transition to the new pricing model, the preliminary empirical results that we are seeing, evidence by year-over-year growth rates, appear to be proving out exactly as expected and exactly as we predicted. Since the transition, revenue growth initially decreased, then it flattened, And now it is increasing as the consumption-based pricing model takes effect. Average selling price has decreased. RPO has decreased. Customer engagement has increased substantially. If we look back over the last, say, one, two, three, four quarters, four quarters ago, our revenue growth was negative 4% and then 0%. The last quarter was 11%. Now it's 17%. Bookings growth, 71% year over year. I'm sorry, bookings growth, 100% year over year. Okay, new contracts growth, 148% year over year. Okay, pilot growth, 50%, quarter over quarter, 170% year over year. So this is basically the beginning, the middle, and the end of this story. Okay, we announced six, seven quarters ago a transition to, to our consumption-based pricing. We predicted that revenue would decline and then flatten and then increase, and we are now seeing these increases that we predicted. So now let's talk about generative AI. Generative AI simply changes everything, okay? I believe that it more than doubles the size of our addressable market overnight. We've all seen the predictions, you know, from Bloomberg that predicts this is a hundred, you know, know in excess of a trillion 1.3 trillion dollar market by 2032. uh goldman sachs predicted that this could increase corporate profits by 30 in the next decade and that generative ai alone could raise the global gdp by seven percent people this is a big deal okay it is difficult to overestimate the levels of interest that we're seeing in the category of generative ai now by combining our multi-billion dollar say 14-year investment in the c3 ai platform with the recent developments in life language models and retrieval augmented generation c3 ai is unique in the market and that we are able to to solve the disqualifying hobgoblins that are preventing the adoption of generative AI, okay, in government, in defense, intelligence, in the private sector. What are those hobgoblins, okay? Those are the facts that, you know, the answers that come out of these large light watch models are stochastic. They're random. They're not traceable. We have this hallucination problem, which is extraordinarily problematic, okay? We have research. None of our data access controls, be it DOD or Bank of America, are enforced. We have these problems with LLM cause data exfiltration, LLM cause cyber threats and IP liability. Okay. In addition, all the solutions that are out there, almost all those solutions, I would say with the, with the exception of AWS bedrock tend to be specific. And I don't think anybody wants to be LLM hook their wagon onto any given LLM today with all the innovation that's going on in the market. And to be dependent on any LLM provider that could, you know, make some announcement on Friday and be gone on Monday. See OpenAI for details. So, you know, this LLM agnostic is there. So the bottom line is our solution in the market addresses every one of those hobgoblins that prevent the installation of generative AI in the enterprise. And so this is really unique. And it took 14 years and $2 billion of software engineering for us to be ready for this. This is why we could solve it. So while the rest of the world is playing catch up, okay, how about multimodal? I mean, we completely nail multimodal. We've been doing it for 14 years. Multimodal, what does this mean? Rather than all these LLM solutions basically handle text. We handle text, we handle telemetry, we handle images, we handle signals. There is, we handle enterprise data, we have the structured data, we have unstructured data. So we are unique in the market and the result is quite exciting. So while the rest of the world is playing catch up and we have scores of, you know, of startups, you know, with, you know, three guys, four girls and two cats in an apartment in San Francisco being, getting, you know, Billion dollar fault funding and you know, multi billion dollar market valuation see pitch book for details. Okay, we have You know, I don't know how many customers really have an order of 1000 employees and I don't know how many countries and we're delivering these solutions today. Okay, okay. And so while the rest of the world is playing catch up, we're working closely with our customers and new customers to install high-value generative AI solutions that rapidly realize value to their organizations. Okay, we believe that our strategic decision to invest in generative AI could address our addressable market opportunity. Our suite of 28, now I think 29, generative AI products wins on reliability, flexibility, adaptability, accuracy, and security. Okay, all of the same qualities that are inherent in our enterprise AI platform. Our vision to expand our customer base is working. Okay. The idea, and this is very much idea about the work that we're doing on the AWS marketplace is to go from eight customers to 80 customers to 8,000 customers to 80,000 customers. Okay. So, so what we're dealing with now is kind of a new game with massive market leverage and we are the first to market. Okay. And we, so I think we have the, opportunity here through our innovation, through our applications that will proliferate across the business. C3 Generative AI has enabled us to land high caliber new customers and expand agreements with the current customers. The surge of interest led to our C3 Generative AI qualified pipeline increasing of new opportunities, increasing 55% sequentially quarter over quarter in the second quarter. representing the most rapid acceleration of all our product offerings. We expect this momentum to grow as we continue to innovate and build increasingly exciting products. Our November announcement of the self-service C3 generative AI on AWS Marketplace plays a big part in this story, potentially expanding our addressable customer pool and our user base exponentially. This new application allows users of all technical levels to enroll in the application and begin productively using generative AI in minutes. Okay, again, this product is available today on the AWS marketplace should you have interest. As I introduced last quarter, we made a well-considered decision to seize the immediate and candidly staggering market opportunity that we see in generative AI. As such, we are making and increasing a sizable and timely investment in application development, model engineering, lead generation, branding, and market awareness to seize market share in generative AI as rapidly as possible. This will put short-term downward pressure on free cash flow and profitability. Closing thoughts. The generative AI opportunity is staggering. We believe that it is in the best interest of our shareholders to further accelerate our investment in generative AI, deepening our investments in lead generation, branding, market awareness, and customer success. Given our substantial cash balance, we believe it is a strategic imperative to invest further in the generative AI opportunity at this time. Separately, now with the release of our platform version of our 8.3 product line, which is really quite remarkable in terms of the benefits that it brings to our customers and the increase in performance that it brings to our customers, we have decided to further invest in our customer base to accelerate their upgrade from version 7 to version 8.3, which we believe will further increase our customer satisfaction levels that are already quite high. That being said, we continue to expect positive cash flow in Q4, and while we're not giving fiscal year 25 guidance yet, we continue to expect positive cash flow for full year, fiscal year 25. C3 AI remains focused. We are one of the few AI software peer plays that has established relationships, a tried, tested, and proven technology platform, and the reputational equity to capitalize on this generative AI market opportunity. Now, I'll turn the call over to Juho Parkinen, our Chief Financial Officer, to talk more about our financial performance and provide guidance for the remainder of the fiscal year. Juho.
spk03: Thank you, Tom. I will now provide a recap of our Q2 financial results and some additional color on our consumption-based revenue model which we introduced five quarters ago. Then I'll discuss factors that will drive our financials in the back half of the year. All figures are non-GAAP and as otherwise noted. Total revenue for the second quarter increased 17.3% year-over-year to $73.2 million. Subscription revenue increased to 11.7% year-over-year to $66.4 million and represented 90.7% of total revenue. Professional services revenue was $6.8 million and represented 9.3% of total revenue. Gross profit for the second quarter was $50.4 million and gross margin was 68.8%. As a reminder, we continue to expect short-term pressure on our gross margins due to a higher mix of pilots which carry a greater cost of revenue during the pilot phase of the customer lifecycle. Operating loss for the quarter was negative $25 million compared to our guidance range of negative $27 to negative $40 million. The improvement in operating loss versus guidance was driven by timing and amounts of degenerative AI-related investments we made to capture market share, as well as our team's ongoing focus on disciplined expense management. At the end of Q2, our accounts receivable was $143.2 million, including unbilled receivables of $104.8 million. the general health of our accounts receivable remains strong. Now turning to RPO and bookings. Reflecting our transition to consumption-based contracts, we reported second quarter gap RPO of $303.6 million, which is down 27.3% from last year, and current gap RPO of $170.2 million, which is up 3.5% from last year. We continue to see positive trends in the diversity of our pilot bookings with 10 industry segments represented in Q2 pilots as compared to eight in Q1. Free cash flow for the quarter was negative 55.1 million. We continue to be very well capitalized and close the quarter with 762.3 million in cash, cash equivalents and marketable securities. Now I'll provide an update on our consumption business model for the second quarter. During the quarter, we started 36 pilots, a 50% increase from last quarter. We are pleased to report that the actual vCPU consumption data that we're seeing from pilot activity has validated the assumptions we made when we transitioned to the consumption-based pricing model five quarters ago. Our pilot conversion rates are trending upwards or getting close to our target of 70%. At quarter end, we had cumulatively signed 109 pilots, of which 103 are still active. This means they're still in their original three to six month term, extended for one to two months, converted to consumption or a licensed contract, or are currently being negotiated for a production license. Finally, our customer engagement count for the quarter was 404, an 81% increase from 223 a year ago. Turning to guidance. As Tom mentioned, we expect Q revenue Q3 revenues range from $74 million to $78 million, and non-GAAP loss from operations to range from negative $40 million to negative $46 million. We remain committed to delivering positive cash flow in Q4 FY24 and for the full year of fiscal year 25, and non-GAAP profitability in the second half of fiscal 25. For the full fiscal year 24, we are maintaining our previous revenue guidance in the range of $295 million to $320 million. We are increasing our non-GAAP loss from operations guidance to a range of negative $115 million to negative $135 million. I'd like to turn the call over to the operator to begin the Q&A session.
spk02: Our first question comes from the line of Timothy Horan of Oppenheimer. Your line is open.
spk05: Thanks a lot, guys. Really appreciate the time. Can you give us a sense of what you're seeing with GAI in terms of productivity improvements and what is the major bottleneck that you think customers need to overcome to really start implementing services? Thanks.
spk04: I'm sorry. The question related to Gen AI?
spk05: Yes, specifically on Gen AI. What type of productivity improvements do you think customers can see on specific applications and what is the major bottleneck for them adopting GAI things?
spk04: The major bottleneck as it relates to generative AI relates to the problems that are inherent in these large language models and they're very real. I mean, as you know, if you use ChatGPT or Google BARD, both of which are like excellent products, but the answers tend to be stochastic. Okay, so Every time you ask a question, you get an answer. If it doesn't know the answer, it hallucinates. The data access controls are not enforced, so the CEO and the person on the factory floor get access to the same information. Carnegie Mellon and others are now identifying huge cybersecurity risks that are associated with these large language models to corporations and government entities. We have IP liability problems that people are concerned about because these large language models are trained on and have access to all the data into the Internet. This is weather, stock prices, what have you. And somebody has the copyright to all those data, be it the weather company or Bloomberg, and they want to get money. So, you know, the, you know, the quintessentials of the world are going to build big businesses litigating these issues in the next 10 years. We have, so there's very real issues. The other issues, it relates to almost all the solutions that are being offered are LLM specific. and you know in say december of 2023 to hook your wagon onto any any specific llm is kind of crazy because next week somebody's in a leap rocket by a factor of ten so you need to be able to switch you need to be online agnostic so i think those are really the hobgoblins cyber security hallucination information security that are basically making it so many organizations will not allow the any generative AI application to be installed. What's unique about the C3 AI solution is that we can talk about this some other time, or you can look it up on the internet. But by combining with the 14 years of work that we did with the C3 AI platform, we've addressed all those problems, cybersecurity, data security, hallucination, what have you. So I think that's the hot topic. Now, that's what slows things down. And people need to be need to be satisfied with those issues resolved, and if they're not resolved, not being installed at any reasonable organization like General Motors or JPMorgan Chase or you name it. Now, as it relates to productivity increases, holy moly, they're going to be staggering, whether you're a lawyer, whether you're a realtor, whether you're a physician, or whether you're running a paper machine, or whether you're operating the infantry, or the space command. I mean, if you do not have or are not being supercharged by generative AR, your competition will be. And if they are and you're not, they win, you lose hard stock.
spk05: So specifically for your customers, what do you think the bottleneck is for adoption? It sounds like you have all these problems pretty much resolved for them. What do you think they require at this point to really start adopting?
spk04: Well, you know, we just, you know, our sales cycles are pretty fast. Our sales cycles for tentative AI has been as close as 24 hours. And basically our offering is, okay, we'll bring the application live. Okay. In one or two months, if you like it for, I don't know, a quarter million dollars or something. And if you like it, keep it. So this has to do with people evaluating bond portfolios, people running paper machines, people running steel mills, uh, uh, the intelligence community, missile defense agency, others. So we just, you know, we, we, we, many of them are existing C3 customers, although increasingly we will be serving, you know, nine out of 10 will not be existing C3 customers. But, you know, we, we, we have to address the concerns that identified. We seem to be able to address those. After that, we just bring the application live. We get it live in 48 weeks and if they like it, keep it. And so it's a, It's a pretty short sales cycle for us, and you're seeing a very substantial increase in the pilots that we're deploying. You can expect, we're expecting a pilot to production conversion rate of, you know, it looks like about 70%. And so it does look like a big opportunity. Thank you.
spk02: Thank you. Again, ladies and gentlemen, if you'd like to ask a question, please press star 11 on your telephone. Again, to ask a question, please press star 1-1. One moment for our next question. Our next question comes from the line of Mike Sikos of Needham. Your line is open.
spk09: Hey, thanks for taking the questions here, guys. I wanted to ask first about the subscription gross margins, and this probably goes back to Juho's prepared remarks, but it was good to see gross margins actually increase sequentially despite the increased pilot count. And I know that you guys are calling out the short-term pressure just based on the growing mix of pilots. And so can you help us think about, like, what was it that actually went better for you guys? Because I think we were expecting a little bit more degradation in the subscription gross margins versus how you guys, how the quarter actually came through.
spk03: Thanks, Mike. This is Juho. So yeah, in the big picture, as we announced five quarters ago, as we're seeing, we are expecting the gross margin degradation for the subscription to continue. Now, in this particular quarter, we were very pleased to see some improvement on a sequential basis, but I think we would expect flattening to down again on the next quarter as the target count increases and is going to put pressure before the consumption amounts start picking up and offsetting that.
spk09: Got it. Thank you. And if I just shift down to OPEX for a second as well, I guess a two-quarter here. I know that you guys are increasing the anticipated operating losses here. Last quarter, we had cited increased investment in, like, branding and lead gen and awareness, right? So can you help us think through where you guys are doubling down? And then the second piece there, there was obviously that article that came out in Bloomberg. I think it was in mid to late November citing headcount costs. headcount cutting, I'm sorry. So can you just comment on the validity of the Bloomberg article, just because I think people are trying to see if you did make those headcount cuts, how much are we doubling down on these investments, or if that article proved to be false?
spk04: Hey, Mac, it's Tom. Doubling down, we're doubling down on data scientists, we're doubling down on You know, largely language model engineers were doubling down. A lot of it is going into engineering, but also candidly in lead generation. I mean, there is an opportunity now as we move to these marketplaces to be dealing transactions in hundreds to thousands to tens of thousands of units rather than scores. And that, I can assure you, is the plan that we have. As it relates to, I'm not familiar with Bloomberg article that you talked about. It sounds like somebody, uh, mentioned something that we did some layoffs in the quarter. Mike, we do performance related layoffs every quarter. Okay. And the, you know, so we, I think last quarter we had 42,000 job applicants. Uh, we, how many people did we hire you hope or order of a hundred or order of a hundred. And these people, yes, they went to MIT. Yes, they worked at Bank of America. Yes, they went to Chicago GSB, and they command an F-18 squadron. And so we're constantly upgrading our human capital, and we move underperformers out regularly. So if somebody said that in a Bloomberg article, I don't know what they said. What I told you is the truth.
spk09: Got it. Thank you. I'll turn it over to my colleagues, but thank you for the call there.
spk02: Thank you. One moment, please. Our next question comes from the line of Kingsley Crane of Canaccord Genuity. Your line is open.
spk08: Hi. Thanks for taking the question. I wanted to touch on the pilot program. You mentioned that you'd move to a lower entry price point for pilots. Could you give us a sense of the magnitude of that change? And then has the minimum fee post-pilot also changed? I'm curious what kind of upsell you're seeing upon conversion, if any.
spk04: Hey, Kingsley, it's Tom. I think the standard pilot that we have with Genevieve and the enterprise is like $230,000. But that being said, you can get the AWS... generative AI for AWS, which basically handles documents like every other LLM. It handles text. It's not really multimodal, but that's free for 14 days. So that would be pretty available. Is there a question that he asked that I didn't answer?
spk03: No, that's right, I think.
spk08: Okay. Okay, yes. Thank you. That's helpful. And I just want to touch on OpEx as well. So I think it makes sense that you want to invest more in both LLM Engineers and Legion, and it looks like that's particularly hitting harder in Q4 of this year. But as we think about fiscal 25, it seems like some of the nature of those investments would naturally continue as you scale on this large opportunity. Is it about timing in this year, or are you expecting those to continue next year?
spk04: Well, Kingsley, I expect them to continue next year. But if you look at the guidance that we gave you in terms of about six quarters ago, what we see is the consumption over the first 12 quarters in terms of CPU seconds per new customer. We just did an analysis of, I don't know, about 30 customers over 12 customers, and Those data that we predicted, I think six or seven quarters ago and provided you, it's uncanny in how accurate it is. It's basically plus or minus 10%. And so if you look as these things kick in, in quarter five, six, seven, and eight, the consumption numbers get pretty big. So you can expect that we don't really need to cut back on the investments to get to the point of, cash positive and non-GAAP profitable. So the top line kind of takes care of that.
spk08: Makes perfect sense. Thanks, Tom.
spk02: Thank you. One moment, please. Our next question comes from the line of Sanjit Singh of Morgan Stanley. Your line is open.
spk07: Great. Thank you. This is Dion for Sanjit. Tom, maybe something with you. I mean, with a couple quarters of the consumption model now under your belt, clearly you're seeing a lot of sort of quantity of deals and pilots. Is there any way that you can frame or give us a sense of the quality of those customers that went with the consumption model early on? Like, is there any sort of scale in terms of spending or growth profile that they're hitting now that you can kind of shed us some light and give us the quality piece where you've given us, I think, a lot on kind of the quantity piece of the yields. And then for you all, maybe, could you just give us some color on the subscription revenue versus the services revenue this quarter, and then also maybe the partner impact and sort of what that looks like on a go-forward basis? Thank you.
spk04: Hi, Sanjay. Regarding quality, I think there's only two ways to look at pilot quality. It's going to be what's the conversion rate and what are they going to consume. Based upon our best guess at this time, based on looking at every pilot we have out there, going to look at what actually has converted and what we think we will convert. We think our guesstimate that we gave you six or seven quarters ago, 70%, is about right. So there's one indication of quality. The other indication of quality is how many CPU seconds are they consuming? Okay. Over as you go from quarter zero to quarter 12 and it's tracking right in line. I mean, it varies a little bit from one quarter to another, but it's basically right in line with what we told you is the quality is pretty high. Now that being said, as we move now to mass markets and start dealing with hundreds of thousands of people, um just either kind of ordering this online and playing with it you're going to expect that conversion rate from that level of pilot to be i would say i mean the quality there will be much lower okay and and i think we need to measure quality by conversion rate and concession levels a lot of those people will try it for five minutes and drop off and that's just the way that it is with three stuff um now the rest of the question i think goes to you yeah right so uh
spk03: Your second part about subscription versus services, so we were 9.3% professional services this period, which is a little bit lighter than our expected long-term model of 10% to 20% on professional services. We continue to expect that we will be at that range on a go-forward basis. And then I think you were asking about how we feel about the partners in a go-forward basis, and partners are hugely important for us, and we continue to believe that they're the key part of our go-to-market approach going forward.
spk02: Excellent.
spk07: Thanks.
spk02: Thank you. It looks like we have time for one last question. Our last question will be from Pat Walraven of J&P Security. Your line is open.
spk06: Hey, everyone. Thanks for the question. This is Owen Hobbs. I'm with Pat. I guess first one for Tom. What would you say are the top one or two federal use cases for generative AI that you're seeing with those five new federal generative AI deals this quarter?
spk04: Our largest federal use case, as you know, is predicted maintenance of the United States Air Force. This was chosen by the chief of staff and the, and we now are doing that, but this is the Panda system, which is the only, uh, AI system of record that we're aware of in all of DOD. So this is the system record for the air force for predictive maintenance for all assets. So far we have loaded the data, I believe from 22 weapons systems at 15, F 16, F 18, F 35, KC one 35, F 22, et cetera. into a unified federated image. This is 100 terabytes of data. Some of it is your maintenance data, sorting data, inventory data, flight data, flight history, telemetry. And one aircraft, like a B-50, each B-1 bomber has 42,000 sensors on it, emitting telemetry. And I'm not sure what heard cycles, but pretty fast. So this is a stack of data. I will be there on Monday. uh that is like next monday i will be in washington dc okay showing this to our customers with a generative ai front end so think about this as a mosaic browser front end where a general officer can ask any question about any this is a hundred terabyte production system this is this is one of the largest um production enterprise AI applications in existence. And that person will be able to ask on Monday, be able to ask any question that you could ask of the weapons system. For example, what aircraft are operative at Travis Air Force Base now? What is my cost of operating the B-1 bomber program in the last year? As it relates to F-35, where are my largest part shortages? And rather than going through some, you know, Cold War era menu-based, you know, SAP or even Siebel Life. I don't want to take shots at SAP. You know, enterprise information system user interface that looks like your Bloomberg terminal. Okay, which is, I have one on my desk. It's unusable. Okay, the, you know, it'll just be a mosaic browser. You can ask any questions. and get the answer related to any one of these weapons systems in the United States Air Force against their production data. And we will show it on Monday, on Tuesday, on Wednesday. And I am telling you, we expect some light bulbs to flash.
spk06: Great. Thank you. And if I could sneak one last one in for you, Ho. Can you please explain the dynamics between the increase in accounts receivable from last quarter to this quarter, despite revenues kind of staying flattish?
spk03: Well, accounts receivable is timing of invoicing. So obviously when we drop an invoice, it shows up in the accounts receivable. So it's just timing of invoicing.
spk04: Great.
spk03: Thank you, guys.
spk02: Thank you.
spk04: Ladies and gentlemen, I think we're at end of program. We appreciate your time and your attention and thank you very much. And we look forward to, uh, Talking with you next quarter, stand by. It does appear to be game on in the AI industry at global scale, and I can assure you we are very much in the game. So thank you all, and we're signing off.
spk02: Thank you. Ladies and gentlemen, this does conclude today's conference. Thank you all for participating, and have a good night. You may now disconnect.
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