Q3 2024 C3.ai Inc Earnings Call
Operator: Good day, and thank you for standing by. Welcome to the C3 AI's third quarter fiscal year 2024 conference call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during the session, you will need to press star 11 on your telephone.
Good day and thank you for standing by welcome to the C. Three a ice third quarter fiscal year 'twenty 'twenty four conference call. At this time all participants are in a listen only mode. After the speaker's presentation, there will be a question.
And answer session to ask a question. During this session you will need to press star one one on your telephone. Please be advised that today's conference is being recorded I would now like to hand, the conference over to your speaker today admit Barry. Please go ahead.
Operator: Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker today, Amit Berry. Please go ahead.
Amit Berry: Good afternoon, and welcome to C3 AI's earnings call for the third quarter of fiscal year 2024, which ended on January 31, 2024. My name is Amit Berry, and I lead investor relations at C3 AI. With me on the call today is Tom Siebel, Chairman and Chief Executive Officer, Juho Parkkinen, Chief Financial Officer, and Hitesh Lath, Chief Accounting Officer. After the market closed today, we issued a press release with details regarding our third quarter results, as well as a supplement 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 laws. These statements reflect our views only as of today and should not be considered representative of our views as of any subsequent date.
Barry: Good afternoon, and welcome to <unk> earnings call for the third quarter of fiscal year 2024, which ended on January 30.
Barry: 31st 2024, my name is I'm, a dairy and I lead Investor Relations at T. G I.
Barry: With me on the call today is Tom Siebel, Chairman and Chief Executive Officer.
Barry: Hope Arcana, Chief Financial Officer, and Chief Accounting Officer.
Barry: After the market closed today, we issued a press release with details regarding our third quarter results as well as a supplemental to watch results both of which can be accessed through the investor Relations section of our website at IR <unk> AI.
Barry: Today's call is being webcast and a replay will be available on our IR website. Following the conclusion of the call.
Barry: During today's call, we will make statements related to our business that may be considered forward looking under federal Securities laws. These statements reflect our views only as of today and should not be considered representative of our views as of any subsequent date.
Amit Berry: We disclaim any obligation to update any forward-looking statements 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 on material risks 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 today's call, we will refer to certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in our press release.
Barry: We disclaim any obligation to update any forward looking statements or outlook.
Barry: These statements are subject to a variety of risks and uncertainties that could cause actual results to differ material materially from expectations.
Barry: For a further discussion on material risks and other important factors that could affect our actual results. Please refer to our filings with the SEC.
Barry: All figures discussed on a non-GAAP basis, unless otherwise noted.
Barry: Also during today's call, we will refer to certain non-GAAP financial measures a reconciliation of GAAP to non-GAAP measures is included in our press release.
Amit Berry: Finally, occasionally in our prepared remarks, in response to your questions, we may discuss metrics that are incremental to our usual 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, I will turn the call over to Tom. Thank you, Amit.
Barry: Finally at a time in our prepared remarks in response to your questions. We may discuss metrics that are incremental to our usual presentation to give greater insight into the dynamics of our business or our quarterly results.
Barry: 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.
Thomas M. Siebel: Thank you Amit.
Thomas M. Siebel: Good afternoon, everyone, and thank you for joining our call. C3 Iot had a great third quarter. Total revenue of $78.4 million grew 18% year-over-year, exceeding the high end of our guidance rate. The total number of customer engagements was 445, an increase of 80% compared to 247 a year ago. Subscription revenue was $70.4 million, which constituted 90% of total revenue and increased 23% from a year ago. Non-Gap Gross Profit was 54.7 million, representing a 70% gross margin; our gap operating loss was $82.5 million.
Good afternoon, everyone and thank you for joining our call today.
Thomas M. Siebel: She had.
Thomas M. Siebel: We had a great third quarter.
Thomas M. Siebel: Total revenue of.
Speaker Change: $78 4 million grew 18% year over year exceeding the high end of our guidance range.
Speaker Change: The total number of customer engagements was 445.
Speaker Change: Greece of 80% compared to 247 a year ago.
Speaker Change: Such ships subscription revenue was 74 million constituting 90% of total revenue and increasing 23% from a year ago.
Speaker Change: non-GAAP gross profit was.
Speaker Change: $54 7 million, representing a 70% gross margin our GAAP operating loss was $82 5 million.
Thomas M. Siebel: Our non-GAAP operating loss was 25.8, better than our guidance for a loss of 40 to 46, which is a non-GAAP net loss per share. 13. We ended the quarter with $723.3 million in cash, cash equivalents, and investments. All these numbers exceeded our guidance and exceeded analysts. This is the 13th consecutive quarter as a public company in which we have met or exceeded our revenue guidance range. None of this should have come as a surprise.
Speaker Change: Our non-GAAP operating loss was $25 8 million better than our guidance for a loss of <unk>.
Speaker Change: $40 million to $46 million or non-GAAP.
Speaker Change: Our non-GAAP net loss per share was <unk> 13 cents.
Speaker Change:
Speaker Change: We ended the quarter with $723 $3 million in cash cash equivalents and investments.
Speaker Change: All of these numbers exceeded our guidance and exceeded analysts' consensus.
Speaker Change: This is the 13th consecutive quarter as a public company and which we have met or exceeded our revenue guidance range.
Speaker Change: None of this should have come as a surprise.
Thomas M. Siebel: The enterprise AI market is on fire. We have been predicting for some years that the market for enterprise AI will be quite large, but those predictions were subject to much speculation in the analyst community and media.
Speaker Change: The enterprise AI market is on fire.
Speaker Change: We have been predicting for some years because the market for enterprise AI would be quite large.
Speaker Change: Those predictions were separated much speculation in the analyst community and media.
Thomas M. Siebel: As of February 2024, I believe it's broadly resolved that the enterprise AI market opportunity is substantially larger than anyone predicted, constituting a secular change in the composition and growth rate of enterprise software writ large. Cloud infrastructure is scaling rapidly. NVIDIA grew 265% year over year.
Speaker Change: February 2024, I believe it's broadly resolved that the enterprise market opportunity is substantially larger than anyone predicted constituting a secular change in the composition and growth rate.
Speaker Change: Enterprise software writ large.
Speaker Change: Cloud infrastructure is scaling rapidly Nvidia grew 265% year over year Invidious datacenter.
Thomas M. Siebel: DataCenter GPU sales grew by 409% year-over-year. Now, some believe that this capacity is being built to use LLMs to write Christmas cards in the style of Charles Dickens, okay, and write college application essays to Yale. But that's simply not the case.
Speaker Change: Data Center GPU sales grew by 409% year over year now some believe that this capacity is built is being built to use algorithms to write Christmas cards from the style of Charles Dickens, Okay, and Wright College application essays to Yale, but thats simply not the case this capacity is being built.
Thomas M. Siebel: This capacity is being built to run enterprise AI applications, such as Stochastic Optimization of the Supply Chain, Supply Network Risk, Predictive Maintenance, Demand Forecasting, Fraud Detection, Perception Optimization, Customer Engagement, Predictive Medicine, Precision Medicine, and Government Services. And that is what we do at C3 AI. So as we power into 2024 and 2025, the world is very much coming our way.
Speaker Change: To run enterprise AI applications stochastic optimization of the supply chain supply network risk predictive maintenance demand forecasting fraud detection perception optimization customer engagement predict.
Speaker Change: Predictive medicine precision medicine and government services.
Speaker Change: And that is what we do at <unk>.
Speaker Change: So as we power into 2024 and 2025 the world is very much coming our way.
Thomas M. Siebel: C3 AI has been preparing for this enterprise AI market explosion for 15 years. We started in 2009 at the infancy of AWS. This is before Azure and before Google Cloud even existed. [inaudible] We carefully designed, developed, and tested a reference AI software platform architecture, now known as the C3 AI platform. We then used that platform to design, develop, and bring to market over 45 production enterprise AI applications that address the value chains of manufacturing, financial services, agribusiness, chemicals, lumber, paper products, utilities, oil and gas, state and local government, and defense. The market for enterprise AI is growing rapidly. Virtually all commercial, military, and government organizations are focused today on leveraging AI to improve their operations, optimize their processes, and transform their business. Our Qual Now, this is led by C3 Generative AI. I go to market with partners, he's driving a strong pilot edition, and it's still in the earliest inning.
Speaker Change: <unk> has been preparing for this enterprise AI market explosion for 15 years, we started in 2009 at the infancy of AWS. This is before <unk> and before Google cloud even existed.
Speaker Change: Yeah.
Speaker Change: We carefully designed developed and tested a reference AI software.
Speaker Change: Platform architecture now known as the <unk> platform. We then use that platform to design develop and bring to market over 45 production enterprise AI applications that address the value chains that manufacturing financial services agribusiness chemicals lumber paper products utilities oil and.
Speaker Change: Gas state and local government defense and intelligence.
Speaker Change: Okay.
Speaker Change: The market for enterprise market interest in enterprise AI is staggering.
Speaker Change: Virtually all commercial military and government organizations are focused today on leveraging AI to improve their operations optimizing their processes and transform their businesses.
Speaker Change: Our qualified opportunity pipeline has increased by 73% from a year ago. Now. This is led by G. III generative AI opportunities our go to market with partners is driving strong pilot additions.
Speaker Change: And it's still in the earliest innings in.
Thomas M. Siebel: In the third quarter, we closed 62% more bookings with our partner network than we did in Q2. 337% more bookings than a year ago. Bottom line, the market demand for enterprise AI products is overwhelming. Hi
Speaker Change: In the third quarter, we closed 62% more bookings with our partner network than we did in Q2.
Speaker Change: 337% more bookings than a year ago bottomline the market demand for enterprise AI products is overwhelming.
Thomas M. Siebel: In the commercial sector, in Q3, we signed new agreements with Boston Scientific, Pantaleon, Booz Allen, Southwire, Carpenter Technology, Florida Crystals, Santa Ana Agriculture, Service to Rio Guatemala, Abbey V, T-Mobile, Bloom Energy, Ball Corporation, DLA Piper, Carlyle Companies, and Holcim, among others. Holcim, a European leader in sustainable building solutions, embarked upon a production pilot with C3 AI Following a successful six month pilot, Wholesome entered into a four year subscription agreement with C3 AI to scale the reliability application across its 100, in excess of 100 cement plants. Wholesome's Predictive Maintenance Program monitors a large number of assets and will generate significant yearly economic value in reduced maintenance costs and production. Holcim is also implementing C3 generative AI to enrich the reliability application and to assist with complex machinery troubleshooting. Another example: D.L.A.
Speaker Change: Customers.
Speaker Change: In the commercial sector and Q3, we signed new agreements with Boston Scientific Panther, Leon Booz Allen, South wire Carpenter technology, Florida crystals, Santa Ana Agriculture <unk>.
Speaker Change: Service to rehab, Guatemala, ABV T mobile Bloom energy.
Speaker Change: Ball Corporation, DLA Piper Carlisle companies and wholesome among others wholesome a European leader in sustainable building solutions embarked upon a production pilot with <unk> AI beginning in May 2023 to configure and deploy the <unk> reliability suite following.
Speaker Change: A successful six month pilot wholesome entered into a four year.
Speaker Change: Scripture agreement with C. Three AI to scale the reliability application across its 100.
Speaker Change: Excess of 100 cement plants.
Speaker Change: Wholesale predictive maintenance program monitor is a large number of assets and will generate significant yearly economic value in reduced maintenance costs and production increases wholesome is also implementing C. III generative AI to enrich the reliability application and to assist with.
Speaker Change: Next machinery troubleshoot it.
Speaker Change: Another example, DLA Piper.
Thomas M. Siebel: Piper, a global law firm pioneering technology innovation in the legal sector, worked with C3 AI to create a first-of-kind generative AI application to streamline the analysis of complex legal agreements. In just three months, DLA Piper applied C3 generative AI to reduce the attorney time it takes to create over 200-point due diligence analyses of limited partner agreements, and it reduced the effort by 80%. As a result of this application, DLA Piper is realizing new operational efficiencies and freeing up their attorney's time to focus on delivering increased value to their clients. State and local government had a huge quarter, generating 29% of our bookings. Lighthouse agreements with San Mateo County, Daly City, and Riverside County, California are spearheading growing awareness for our state and local government's suite of applications, and we're now closing deals nationally.
Speaker Change: Global law firm pioneering technology innovation in the legal sector worked with <unk> to create a first of kind generate AI application to streamline the analysis of complex legal agreements and just three months DLA Piper applied generative AI to reduce.
Speaker Change: The time it takes to create over 200 point due diligence analyses of limited partner agreements and it reduced the effort by 80% as a result of this application DLA pipers, realizing new operational efficiencies and freeing up their attorneys time to focus on delivering.
Speaker Change: Increased value to their clients.
Speaker Change: State and local government had a huge quarter generating 29% of our bookings lighthouse agreements with San Mateo County, Daly City, and Riverside County, California are spearheading growing awareness for our state and local governments suite of applications and we are now closing deals nationally we see a huge.
Thomas M. Siebel: We see a huge potential to expand our footprint to the counties, cities, and municipalities across the United States. San Mateo County Sheriff's Office and the Daly City Police Department both signed multi-agency expansion contracts for the C3 Iot law enforcement application as a county-wide crime investigation platform to combat organized retail vehicle and cargo theft, this contract, involves a combined 15 local, Police Departments, and 16 agencies deploying the application in coordination, including Burlingame, Daly City, the City of San Mateo, San Bruno, Atherson, Redwood City, South San Francisco, Menlo Park, Foster City, Belmont, Pacifica, East Palo Alto, Colma, Broadmoor, Brisbane, and others. These deployments promise to significantly decrease the investigative timelines to solve crimes and empower multi-agency collaboration to help prevent crime. These engagements were funded through the Organized Retail Threats Grant from the California Board of State Engagements. The Board of State and Community Correction.
Speaker Change: Potential to expand our footprint.
Speaker Change: Counties cities and municipalities across the United States.
Speaker Change: San Mateo County, Sheriffs office, and the Daly City Police Department, both sides multi agency expansion contracts for the seed you a law enforcement application.
Speaker Change: Howdy wide crime investigation platform to combat organized retail vehicle and cargo theft.
Speaker Change: This contract.
Speaker Change: Involves a combined 15 local.
Speaker Change: Police departments in 16 agencies deploying the application.
Speaker Change: In quad and coordination, including Burlingame Daly City, the city of San Mateo San.
Speaker Change: San Bruno <unk>, and Redwood City, South of San Francisco, Menlo Park Foster City, Belmont Pacific East, Palo Alto coma broad more Brisbane and others.
Speaker Change: These deployments promise to significantly decrease the investigated timelines to solve crimes and empower multi agency collaboration to help prevent crime.
Speaker Change: These these endgame engagement sort of funded through the organized retail threats grant from the California Board.
Speaker Change: Third stake.
Speaker Change: The board of state and community corrections.
Thomas M. Siebel: And by the way, of all the submissions to this board, San Mateo County's submission ranked number one in priority as the best submission in the state, with C3 Iot law enforcement being the top investment in their initiatives to combat retail theft in the state of California. We also executed an agreement, actually multiple agreements, okay, with San Mateo County to deploy C3 AI property appraisal, C3 AI law enforcement, and C3 AI generative and generative AI applications, going to monetize the appraisal of over 230,000 parcels each year, constituting more than $300 billion in assessed property value. And to do this more accurately, more equitably, more expeditiously, and more defensively.
Speaker Change: And by the way of all the submissions to the to this board San Mateo County submission ranked number one okay.
Speaker Change: And priority.
Speaker Change: As the best submission in the state, Okay, with <unk> law enforcement being the top investment and their initiatives to combat retail theft in the state of California.
Speaker Change: We also executed an agreement actually multiple agreements, okay with San Mateo County to deploy C. Three AI property appraisal C. Three a loss in law enforcement and <unk> AI generative and Ctrip generative AI applications, the assessor or is that a county clerks recorders.
Speaker Change: And elections office license <unk> residential property appraisal and C III commercial property appraisal too.
Speaker Change: Kind of monetize the appraisal of over 230000 parcels each year constituting more than $300 billion in <unk>.
Speaker Change: Property value and to do this more accurately more accurately heavily more expeditiously and more defensively.
Thomas M. Siebel: Our U.S. federal business continues to show significant strength. Third quarter revenue was up... over 100% year-over-year, and bookings were up 85%. We signed new and expansion agreements with the Missile Defense Agency, the Department of Defense, the United States Air Force, JROC, and the U.S. Marine Corps. We have a really substantial growth opportunity in the federal government, and we're laying the groundwork to seize it. We're getting strong traction with partners in this federal space, not the least of which is AWS. We deployed our federal solutions on the AWS marketplace for the U.S. intelligence community in June of last year, and we're basically on speed dial collaborating with AWS federal executives every day in the defense and intelligence community.
Speaker Change: Our U S. Federal business continues to show significant strength third quarter revenue was up over 100% year over year and bookings were up 85%.
Speaker Change: We signed new and expansion agreements with the missile Defense agency at the Department of Defense, The United States Air Force and the U S intelligence community, including seven new generative AI agreements at the missile Defense agency in the United States Air Force.
Speaker Change: Hey, Rob and the U S Marine Corps.
Speaker Change: We have a.
Speaker Change: Really substantial growth opportunity in federal and we're laying the groundwork to season, we're getting strong traction with partners in the federal space not the least of which is AWS. We've deployed our federal solutions on the AWS marketplace for the U S intelligence community in June of last year, and we're basically out of speeds.
Speaker Change: While collaborating with fed with AWS federal executives, great everyday in the defense and intelligence communities.
Thomas M. Siebel: Additionally, and importantly, we entered into an enhanced partnership agreement with Paradigm. This is a high-end professional services organization in the federal sector, and we did this to increase our capacity for deploying appropriately cleared data scientists and application engineers into our classified government installations. We've aligned with Paradigm in our commitment to support the defense intelligence communities in their critical missions related to national security.
Speaker Change: Additionally, and importantly, we entered into an enhanced partnership agreement with paradigm. This is.
Speaker Change: This is a high end professional services.
Speaker Change: Organization in the federal sector, and we did this to increase our capacity for deploy.
Speaker Change: Really kind of cleared data scientists and application engineers into our classified government installations, we've aligned with paradigm and our commitment to support the defense and intelligence communities in their critical missions related to National security under the New agreement paradigm will significantly grew.
Thomas M. Siebel: Under the new agreement, Paradigm will significantly grow its number of dedicated C3 AI staff to accelerate joint selling and accelerate the delivery of these secure, classified, and powerful AI applications, predicting, and you know, providing predictive insights into these federal agencies. In addition, Paradigm will jointly mark up the C3 generative AI for defense application and the C3 AI law enforcement application. I want to highlight the continued diversification in our business and our go-to-market app. Our business continues to diversify across industries. In the last quarter Q3, our bookings distribution by industry was 29% State and Local Government, 25% Federal Defense and Aerospace, 16% Manufacturing, 11% Agribusiness, 8% Chemical, 7% Professional Services, 2% Energy and Utilities, 1% Food Processing and Consumer Packaged Goods, and 1% Oil and Gas. Now, let's take a minute, and this is important, so please pay attention, and look at the evolution of our And I want to talk in particular about the transition to consumption-based prices.
Speaker Change: Grow its number of dedicated <unk> staff to accelerate joint selling and to accelerate the delivery of these <unk>.
Speaker Change: <unk> classified powerful AI applications predicting.
Speaker Change: Brian predictive insights into these federal agencies.
Speaker Change: In addition paradigm will jointly market the C. Three generative AI for defense applications, and the <unk> II law enforcement applications.
Speaker Change: I want to highlight.
Speaker Change: The continued diversification in our.
Speaker Change: Yeah in our go to market efforts, our business continues to diversify across industries.
Speaker Change: In the last quarter of Q3, our bookings distribution by industry was 20.
Speaker Change: 29% state and local government, 25% federal defense, and aerospace, 16% manufacturing, 11% agribusiness, 8% chemical 7% professional services, 2% energy and services utilities, 1% food processing and consumer packaged.
Speaker Change: Good Andrew.
Speaker Change: 1% oil and gas.
Speaker Change: Now, let's take a minute and this is important so please pay attention and look at the evolution of our go to market model and I want to particularly talk about the transition to consumption based pricing.
Thomas M. Siebel: You'll recall that six quarters ago, we changed our go-to-market model from leading with a subscription-based pricing model to leading with a consumption-based pricing model. The general idea being that rather than people licensing $10, $20, $30, $40, $50 million up front, they would simply do a project, a pilot project for, say, half a million dollars for six months, and we'll bring the predictive maintenance application, the supply chain optimization, the demand forecasting application, whatever it may be, into full production in six months. And then the customer will offer half a million dollars, which is... insignificant. And if the customer likes it, they can keep it, and they pay, depending upon the volumes, generally 40 to 55 cents per vCPU hour to run the application, bring it live, if they like it. That was the idea.
Speaker Change: Youll recall that six quarters ago, we changed our go to market model.
Speaker Change: From a leading with a subscription based pricing model to leading with a consumption based pricing model. The general idea being that rather than people licensing 10, 2030, 40 $50 million upfront. They would simply do a project a pilot project for say half a million dollars for six months and will bring.
Speaker Change: That predictive maintenance application in the supply chain optimization and demand forecasting application whatever it may be in full production in six months and then on the customer all over half a million which is.
Speaker Change: Insignificant and if the customer likes it they could keep it and they pay depending upon the volumes generally.
Speaker Change: 40 to 55 stores had superb BCP you are to run the application bring it live if you like it keep it that was the idea.
Thomas M. Siebel: And this has clearly and substantially lowered the price barrier for companies to engage with us. And we've seen this now in the, you know, the size of the number of deals that we close each quarter, the size of the, you know, the transactions that we're doing. It's been very effective. So this model has been and continues to be very successful in driving engagement. And our contract volume has grown as we expected. At that time, we provided expectations of vCPU consumption ramps, pricing, and pilot conversion rates, and now we've compared this to the empirical data that we've realized over the past four quarters, and it turns out those initial assumptions have improved to be quite accurate. Our estimates on vCPU usage and how that ramps, say over 4, 5, 6, 7, 8 quarters, they're pretty darn accurate. I would say that, plus or minus 10%, it's about right on.
Speaker Change: And this clearly added substantially lowered the price barrier for companies to engage with us and we've seen this now.
Speaker Change: Besides the number of deals that we close each quarter the size of it.
Speaker Change: The transaction that we're doing it's been very effective. So this model has been and continues to be very successfully driving engagement.
Speaker Change: And our contract volume has grown as we expected.
Speaker Change: And at that time, we provided expectations of VC.
Speaker Change: The CPU consumption ramps pricing and pilot conversion rates.
Speaker Change: And now we've compared this to the empirical data that we've realized over the past four quarters and it turns out those initial assumptions have been proved to be quite accurate.
Speaker Change: Our estimates on the P C.
Speaker Change: CPU usage and how that ramps how that ramp say over a four or five years to 678 quarters, they're pretty darn accurate and I would say that.
Speaker Change: Plus or minus 10%.
Speaker Change: It's about right on okay.
Thomas M. Siebel: We assumed a pilot conversion rate of 70%, and what we're seeing, that appears to be right. Okay, we're also pleased to share that the pricing on the converted pilot is pretty much in line with our expectations. Now when we began the transition, we assumed that virtually all pilots actually would convert to month-to-month, pay-as-you-go, consumption-based pricing. Counterintuitively, it hasn't quite worked out that way
Speaker Change: Okay, we assumed a pilot conversion rate of 70%.
Speaker Change: What we're seeing that appears to be right. Okay.
Speaker Change: We're also pleased to share that the pricing on the converting part and then converted pilots is pretty much in line with our expectations.
Speaker Change: Now when we began the transition and we assume that virtually almost all pilots actually would convert to month to month pay as you go consumption based pricing.
Speaker Change: Counterintuitively it hasn't quite worked out that way in the empirical data show that the majority of our customers are choosing the sign multiyear subscription crowd contracts rather than after the trial. They have the option at the energy using beside multiyear subscription contracts rather than month to month payout.
Thomas M. Siebel: And empirical data show that the majority of our customers are choosing to sign multi-year subscription contracts rather than, you know, after the trial, they have the option, okay, and they're choosing to sign multi-year subscription contracts rather than month-to-month pay-as-you-go. And so why are they doing that? After pilot completion, many customers are electing to deploy multiple applications across multiple business units, and they're electing for a multi-year subscription, committed subscription pricing model as it offers them a more predictable cost model at large scale. Now, note also, it's not quite this simple for those of you that are working on models, because that subscription agreement also involves the consumption rights runtime component. So this is not going to be easy to model, people, for those who are working on their spreadsheets. Okay?
Speaker Change: Yup.
Speaker Change: And so why are they doing that.
Speaker Change: After pilot completion, many customers are electing to deploy multiple applications across multiple business units and they are electing for a multiyear subscription committed subscription pricing model as it offers them.
Speaker Change: More predictable cost model at large scale.
Speaker Change: No no at all so it's not quite the simple for those or that Youre working on models because that subscription agreement also involves the consumption rates run time components. So this is not going to be easy to model people for those who are working on your spreadsheet. Okay now the good news.
Thomas M. Siebel: Now, the good news is that our customers are making significant commitments to C3 AI, and our multi-year subscription agreements are a positive indicator of the depth of their commitments. Also, our data shows that over the term of the contract, the revenue from the subscription agreements is generally equal to the revenue from our consumption agreements. So whatever the customer chooses is fine to us because it's revenue-neutral over, say, 10 to 12 quarters. Bottom line, our go-to-market transition is working, as evident from the growth of our opportunity pipeline, the increase in our customer engagement, and increased revenue. Now, let's take a minute and talk about generative AI because this is a very significant market development. The opportunity ahead of us in generative AI is enormous.
Speaker Change: Is that our customers are making significant commitments to <unk> and our multiyear subscription agreements are a positive indicator of the depth of their commitment.
Speaker Change: Also our data shows that over the chairman of the contract the revenue from the subscription agreements is generally equal to the revenue for my consumption agreements.
Speaker Change: Wherever the customer chooses us find us because it's revenue neutral over say 10 to 12 courts Bottomline. Our go to market transition is working as evident from the growth of our opportunity pipeline the increase in our customer engagements and increased revenue.
Speaker Change: Now, let's take a minute and talk about generative AI because this is a.
Speaker Change: This is a very significant market development the opportunity ahead of us in generative AI is enormous.
Speaker Change: C III.
Thomas M. Siebel: AI has been at the vanguard of enterprise AI innovation now for 15 years. We've spent 15 years building enterprise AI applications for manufacturing, supply chain, demand chain, finance, defense, intelligence, smart grid, oil and gas, etc. In all fairness, we largely established the enterprise AI category. Now, with the advent of gender AI, I mean, this is fundamentally changing the nature of the market.
Speaker Change: AI has been at the Vanguard of Enterprise AI innovation now for 15 years. We spent 15 years building seat enterprise AI applications for manufacturing supply chain demand Jayne Finance defense intelligence, smart get oil and gas et cetera.
Speaker Change: We largely established the enterprise category.
Speaker Change: Now with the advent of generative AI I mean is this fundamentally changing.
Speaker Change: The nature of the market is changing the nature of the human computer interface is unlocking new use cases, and it's breaking and it's creating kind of breakthrough opportunities for non obvious applications in new industries.
Thomas M. Siebel: It's changing the nature of the human-computer interface. It's unlocking new use cases, and it's breaking, and it's creating opportunities for non-obvious applications in new industries and enterprises that we might, that we would not have expected, and we're just in the earliest days of it. Gardner Gardner's group predicts that by 2026, over 80% of enterprises will be using generative AI, including the deployment of generative AI-enabled applications in their production environments. This is up from basically zero in 2022.
Speaker Change: And enterprises that we might that we would not have expected and we're just in the earliest days of this Gartner predicts Gardner group predicts that by 2026 over 80% of enterprise will be using generate AI, including the deployment of generative AI enabled applications in.
Speaker Change: Their production environments. This is up from basically zero in 2022.
Thomas M. Siebel: For Gardner, organizations, this is a quote, that do not consistently manage AI risks are exponentially inclined to experience adverse outcomes such as security failures, Financial and Reputational Loss, and Social Harm. We are leveraging our first market advantage in scalable, trusted enterprise AI to bring secure, Germanistic, and hallucination-free.
Speaker Change: Third Gardner organizations. This is a quote that do not consistently manage AI or AI risks expert rationally inclined to experience adverse outcome such as security failures.
Speaker Change: Excellent reputation Ross loss and social harm.
Speaker Change: Hey.
Speaker Change: We are leveraging our first to market advantage in scalable trusted enterprise AI to bring secure.
Speaker Change: Chairman I stick.
Thomas M. Siebel: [inaudible] domain-specific generative AI solutions and generative AI-augmented applications to market. And we're seeing a groundswell of interest in all of our generative AI and our remarkable uptake of the C3 generative AI suite. Our generative AI customer activity has ramped sharply since we introduced this product to market four quarters ago. We're now applying AI, generative AI, in areas where we wouldn't have expected operator assistance in a major manufacturing facility, customer assistance at a global financial services company, and field technical support at a major multinational manufacturing company. DLA Piper is using generative data to significantly reduce the labor associated with limited partner agreement due diligence. Another leading law firm is using the corpus of S1s that are contained in scc.gov to train a large language model to reduce attorney labor in generating first drafts of S1s for IPO candidates.
Speaker Change: Elucidation free.
Speaker Change: Traceable.
Speaker Change: <unk> specific January with AI solutions and generative.
Speaker Change: Ill mannered applications to market and we're seeing a groundswell of interest in all of our generative AI offerings.
Speaker Change: Okay, and a remarkable uptick of the <unk> III degenerative AI suite.
Speaker Change: Our generative AI customer activity has ramped sharply since we introduced this product to market four quarters ago.
Speaker Change: We're now applying AI generative AI kind.
Speaker Change: Kind of areas, where we wouldn't have expected the operator assistance and a major manufacturing facility customer assistance at a global financial services company and field technical support and a major multinational manufacturing group.
Speaker Change: DLA Piper is using generative that significantly reduce the labor associated with limited a partner agreement due diligence another leading law firm.
Speaker Change: The corporates have S ones that are contained in <unk> SEC dot Gov to train a large language model to reduce the attorney labor, Okay, and generating first drafts of ask one for IPO candidates I mean imagine your train alerts large model on the corporate <unk> SEC Gov.
Thomas M. Siebel: I mean, imagine you train a large learning model on the corpus of S1s in scc.gov. And then you want to come up with your first draft of your S1 if and when the IPO market opens again. Okay, you put in the name, address, the finances, the key risk factors, hit the carriage return button, and you know, ipso facto, you know, the first draft of the S1 is there.
Speaker Change: And then you wanted to come up with your first draft of your ask one if and when the IPO market opens again, okay and you put it in the name address them for answers the key risk factors hit the carriage return episode facto.
Speaker Change: First draft of the S. One is there and then we have saved God knows how many weeks of legal associates.
Thomas M. Siebel: And we've saved, you know, God knows how many person weeks of legal associates where now they can just edit and get it done. So it's really, this is, this is pretty neat. Speaker Hughes is using C3 generative AI on top of Workday and ServiceNow to provide its global employees with broad and immediate answers to all employee questions about, you know, employee questions, policies, benefits, compensation, etc. Riverside County in California is using C3 generative AI to assist its staff in answering questions about citizens, questions about taxation, zoning, building codes, etc. We continue to be really impressed by the broad range of applications to which the generative AI technologies apply. In Q3, we closed 17 generative AI applications, pilots across a broad range of industries, including federal, defense, aerospace, ag, forestry, food processing, manufacturing, state, local government, chemicals, life science, and others, and these generative AI pilots span Europe. Latin America and North America.
Speaker Change: Now they can just get it done so it's really this is this is pretty neat.
Speaker Change: Baker Hughes is using Cte generative AI on top of Workday and service now to provide its global employees broaden immediate answers to all employee questions about employee questions policies benefits compensation what have you.
Speaker Change: Riverside County in California is using C. III generative AI to assist their staff and answering questions about citizens questions about taxation zoning building codes et cetera.
Speaker Change: We continue to be really impressed by the broad range of applications to which the degenerative AI technology is applicable.
Speaker Change: In Q3, we closed 17.
Speaker Change: Generative AI application of pilots across a broad range of industries, including Federal Defense Aerospace AG Forestry food processing manufacturing state local government chemicals life science and others.
Speaker Change: These generative I pilot spans Europe.
Speaker Change: Latin America, North America U.
Thomas M. Siebel: You, there are no bounds. We continue to drive innovation in the generative AI market with our highly differentiated C3 generative AI. (Inaudible) Our newest innovations include omnimodal data support. You've heard about multimodal. Well, multimodal doesn't cut it. Multimodal includes text and images.
Speaker Change: R&R bounds to this we continue to drive.
Speaker Change: Innovation in the January to the air market with our highly differentiated C. Three generative AI.
Speaker Change: Solution.
Speaker Change: Our newest innovations include omni modal data support you've heard about multimodal multimodal doesn't cut it multimodal includes text and images that doesn't get you very far you need to include you need enterprise data ERP CRM OSI Pi data telemetry images text photos.
Thomas M. Siebel: That doesn't get you very far. You need enterprise data, ERP, CRM, OSI-Pi data, telemetry, images, text, photos, voice. So, you know, in order for this dog to hunt, okay, it needs to, you know, multimodal doesn't get you anywhere.
Speaker Change: Voice so.
Speaker Change: In order for this for this dog to hunt, okay. It needs to.
Speaker Change: Multimodal.
Thomas M. Siebel: You need omnimodal data support, which is what we support in the C3 AI product today. We have advanced parsing and embedding capabilities to increase reasoning on tables and images within documents. Okay, we have the planning and execution of complex multi-step workflows, we support multilingual support, and the automatic invocation of advanced math tooling. Okay, we do this in a manner that is virtually hallucination-free.
Speaker Change: Get you anywhere you need omni modal data support which is what we support in the C. Three AI product today.
Speaker Change: We have advanced parsing embedding capabilities with increased reasoning on tables and images within documents again, we have the planning and execution of complex multi step workflows with smart multilingual support.
Speaker Change: And the automatic invocation of advanced math tooling, Okay. We do this in a manner that is virtually hallucination free okay, Anish allo I'm agnostic.
Thomas M. Siebel: Okay, and it's LLM agnostic. I'll show you. Our solution here is really quite unique, and it's getting a lot of traction, and we are installed today in some of the most secure installations on the planet Earth. Earlier this year, I actually asked when we announced on last quarter's conference call that we made a well-considered decision to accelerate our investments in generative AI to seize market share in this large and rapidly growing market. As a result of that investment last quarter, our webpage views were up 57% year-over-year in Q3, our organic search traffic was up 68%, and our unique visitors to our website were up an eye-popping 230% So this decision is already accelerating our business, already accelerating our product innovation, and it's driving definitely broader market awareness of what we do in enterprise AI and in generative AI. That being said, we continue to expect that we will operate a positive free cashflow business in Q4 of this year and in the next. Now, while we're not giving fiscal year 25 guidance yet, we will continue to expect positive free cash flow for the full year of fiscal year 25.
Anish: So it's.
Speaker Change: Yeah.
Speaker Change: Our solution here is really quite unique and it's getting a lot of traction and we are installed today.
Speaker Change: Some of the most secure.
Speaker Change: Installations on the planet Earth.
Speaker Change: Earlier this year lastly, as we announced in last quarter's conference call. We made a well considered decision to accelerate our investments in generative.
Speaker Change: Hi to seize market share in this large and rapidly growing market opportunity as a result of that investment last quarter, our way our webpage views are up.
Speaker Change: 57% year over year.
Speaker Change: In Q3, our organic search traffic is up 68% and our unique visitors to our website are up an eye popping 230%.
Speaker Change: So this decision is already accelerating our business already accelerating.
Speaker Change: Our product innovation, and it's driving definitely broader market awareness of what we do in enterprise AI and Ingenerate attack that being said, we continue to expect that we will operate a positive free cash flow business. Okay. In Q4 of <unk> in the next quarter.
Speaker Change: Now, while we're not giving fiscal year 'twenty guidance, yet we will continue to expect.
Speaker Change: Positive free cash we continue to expect positive free cash flow for the full year of fiscal year 'twenty five.
Thomas M. Siebel: Talk a minute about our International Users Group Conference C3 Transformed. We'll be holding our fifth annual International Users Group Conference C3 Transformed in Boca Raton next week, March 5th through 7th. Over 500 customers and partners are registered to attend, including leaders from almost every industry sector. General sessions on March 5th and 6th will be substance-packed, including C3 AI product roadmaps, C3 AI customer success stories, best practices in enterprise AI from C3 AI customers and partners, AI innovation in defense and intelligence, and discussions from experts about the past and future of generative AI. Transformed General Sessions will be simulcast to qualified investors and analysts, and those of you who are interested can register online beginning this Friday and tune in in real time to participate in any of those general sessions that you would like. And I think you'll find them pretty substantive stuff.
Speaker Change: Todd talk a minute about our international users Group Conference C. III transform we will be holding our fifth annual International users Group Conference Ctrip transform a broker on next week March 57th over 500 customers and partners are registered to attend including leaders from almost every industry sector.
Speaker Change: General sessions on March 5th and six will be substance packed, including Ctrip AI product Roadmaps C. III AI customer success stories best practices enterprise AI from <unk> customers and partners.
Speaker Change: <unk> in defense and intelligence and discussions from experts about the past and the future of generative AI and I'm very pleased to announce that the <unk> three <unk>.
Speaker Change: Transform general sessions will be simulcast to qualified investors and analysts and those of you are interested can register online beginning this Friday and <unk>.
Speaker Change: Julian in real time to participate in any of those to those general sessions that you would like and I think youll find them.
Speaker Change: These are not cheesy sales pitches folks. This is this is this is pretty substantive stuff and for those of you who are either interested in CRE or interested in AI in general I think youll find it.
Thomas M. Siebel: And for those of you who are either interested in C3 or interested in AI in general, I think you'll find it. We hope you'll join us, and you're welcome. In conclusion, business is good, prospects look bright, and C3 AI has returned to accelerating growth. Talk about guidance.
Speaker Change: Yes.
Speaker Change:
Speaker Change: We hope you'll join us and you're welcome to you.
Speaker Change: In conclusion business has good prospects look bright.
Speaker Change: And <unk> has returned to accelerating growth talk about guidance. So given current market conditions, we are increasing revenue guidance for Q4, okay and for fiscal year.
Thomas M. Siebel: So given current market conditions, we are increasing revenue guidance for Q4, okay, and for fiscal year. This fiscal year, 2024, for Q4, we're anticipating revenue in the range of $82 to $86 million. And for the year, we're anticipating revenue in the range of $306 to $310 million. Our non-GAAP loss from operations is expected to be in the range of $43.5 to $51.5 million for the quarter, and our non-GAAP loss from operations for the year is expected to be in the range of $115 to $123 million. Now, I will turn the call over to my colleagues Juho Parkkinen, the Chief Financial Officer, and Hitesh Lath, the Chief Accounting Officer, for additional detail. Juho.
Speaker Change: This fiscal year 2024.
Speaker Change: For Q4, we are anticipating revenue in the range of $82 million to $86 million and for the year. We are anticipating revenue in the range of $306 million to $310 million.
Speaker Change: Our non-GAAP loss from operations is expected to be in the range of $43 $5 51, 5 million for the quarter and a loss from a non-GAAP loss from operations for the year is expected to be in the range of $115 million to $123 million now let me turn the.
Speaker Change: Call over to my colleagues Yuko Youll Parkman, and the Chief Financial Officer, and had cash lap the chief accounting officer for <unk>.
Speaker Change: Additional detail you hope thank you Tom.
Juho Parkkinen: Thank you, Tom. I will now provide a recap of our Q3 financial results and some additional color on pilot activities. Then I'll discuss factors that will drive our financials in Q4 and in FY25. All figures are non-GAAP, unless otherwise noted.
Speaker Change: I will now provide a recap of our Q3 financial results.
Speaker Change: Some additional color on pilot activity, then I will discuss factors that would drive our financials in Q4, FY 'twenty five or.
Speaker Change: All figures are non-GAAP.
Juho Parkkinen: Total revenue for the third quarter increased 17.6% year-over-year to $78.4 million. Subscription revenue increased 23.4% year-over-year to $70.4 million and represented 89.8% of total revenue. Professional services revenue was $8.0 million and represented 10.2% of total revenue. Gross profit for the third quarter was $54.7 million, and gross margin was $69.7 million.
Speaker Change: Otherwise noted.
Speaker Change: Total revenue for the third quarter increased 17, 6% year over year to $78 4 million subscription revenue increased 23, 4% year over year to $70 4 million and represented 89, 8% of total revenue professional services revenue was eight 8 million and represented 10, 2% of total revenue.
Speaker Change: It grew.
Speaker Change: Gross profit for the third quarter was $54 7 million and gross margin was 69, 7%.
Juho Parkkinen: 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. Also, as we discussed last quarter, we expect short-term pressure on our operating margin due to the investments we're making in generative AI and upgrading customers to our platform version. Operating loss for the quarter was negative 25.8 million compared to our guidance range of negative 40 million to negative 46.
Speaker Change: As a reminder, we continue to expect short term pressure on our gross margins due to higher mix of pilots, which carry a greater cost of revenue during the pilot phase of the customer lifecycle.
Speaker Change: Also as we discussed last quarter, we expect short term pressure on operating margin due to the investments, we're making in generative AI on upgrading customers to our platform version eight three.
Speaker Change: Operating loss for the quarter was negative $25 8 million compared to our guidance range of negative $40 million to negative 46 million.
Juho Parkkinen: The improvement in operating loss versus guidance was driven by our team's ongoing focus on disciplined expense management, as well as the timing of additional investments we're making to capture market share. At the end of Q3, our accounts receivable balance was $173.5 million, including unbilled receivables of $102.6 million. The total allowance for bad debt remains low at $400,000, and we have no concerns regarding collection.
Speaker Change: The improvement in operating loss versus guidance was driven by our team's ongoing focus on disciplined expense management as well as the timing of additional investments, we're making to capture market share.
Speaker Change: At the end of Q3, our accounts receivable balance was $173 5 million, including Unbilled receivables of $102 6 million.
Speaker Change: Total allowance for bad debt remains low at 400000, and we have no concerns regarding collections. The general health of our accounts receivable remained strong.
Juho Parkkinen: The general health of our accounts receivable remains strong. Six quarters ago, we announced the transition from subscription-based pricing to consumption-based pricing, a standard in the industry. We anticipated and announced that this transition would have a short-to-medium-term negative effect upon revenue growth and RPO, as the average sales price was significantly reduced, and the contracts often lacked the time-certain multi-period permit. However, as the transition progressed, we expected to return to revenue growth as customer engagements accelerate and customers expanded their consumption. Reflecting our transition to a more consumption-based contract, we reported third-quarter GAAP RPO of $286.9 million, which is down 28.8% from last year, and current GAAP RPO of $172 million, which is down 2.4% from last year. Free cash flow for the quarter was negative 45.1 million. We continue to be very well capitalized and close the quarter with 723.3 million in cash, cash equivalents, and marketables.
Speaker Change: Six quarters ago, we announced the transition from subscription based pricing to consumption based pricing standard in the industry, we anticipated and announced that this transition would have a short to medium term negative effect on revenue growth in <unk>.
Speaker Change: The average sales price was significantly reduced in the contracts often lack the time certain multi appeared commitment.
Speaker Change: The transition progressed, we expect it to return to revenue growth of customer engagement accelerate and customers expand their consumption, reflecting our transition to a more consumption based contracts, we reported third quarter GAAP ARPA of $286 9 million, which is down 28, 8% progressed year on current GAAP <unk>.
Speaker Change: 172.
Speaker Change: Which is down two 4% progressed here.
Speaker Change: Free cash flow for the quarter was negative $45 1 million, we continue to be very well capitalized and closed the quarter with $723 3 million in cash cash equivalents in marketable securities.
Juho Parkkinen: Now I'll provide some additional metrics for the third quarter. During the quarter, we started 29 pilots, a 71% increase from last year, and down 19.4% from last quarter due to timing of the sales. Ten industries were represented in our pilot starts. At quarter end, we had cumulatively signed 138 pilots, of which 132 are still active. This means they're still in their original three to six month term, extended for some duration, converted to consumption or a license contract, or currently being negotiated for a production license. Our customer engagement count for the quarter was 445, an 80.2% increase from 247 a year ago.
Speaker Change: Now I'll provide some additional metrics for the third quarter during the quarter. We started 29 targets of 71% increase from last year.
Speaker Change: And down 19, 4% from last quarter due to the timing of the sales activity.
Speaker Change: Certain industries were represented in our pilot starts at quarter end. We had cumulative you signed 138 pilots of which 132 are still active. This means they are still in the original three to six month term extended for some duration converted to consumption or a license contract or currently being negotiated for a production license.
Speaker Change: Our customer engagement count for the quarter was 445, and 82% increase from 247 a year ago.
Juho Parkkinen: As the last item on our call today, I wanted to inform you that after three wonderful years at C3 AI, I will be stepping down as the company's CFO and assuming a role as VP of Finance. I have been at C3 AI for three amazing years and two of its CFOs. I'm grateful to Tom and the board of directors for the opportunity. It has been a privilege to work beside Tom and the entire executive team in this role. As you all are aware, C3 AI is a unique hyper-performance technology company 100% in the office, incredibly hard-working, and fast-paced.
Speaker Change: And the last item on our call today I wanted to inform you that after three wonderful years, let's say three years.
Speaker Change: I will be stepping down as the Companys CFO and assuming our role as VP of finance.
Speaker Change: I have been at <unk> for three amazing years, and two of its CFO I'm grateful to Tom and the board of directors for the opportunity.
Speaker Change: It has been a privilege to work with Tom and the entire executive team in this role.
Speaker Change: As you all are aware C. III is a unique hyper performance technology company.
Speaker Change: Hundred percent in the office incredibly hardworking fast paced.
Juho Parkkinen: You have to be on 150% all the time. And for me personally, I need to take a break and step aside for a bit and spend more time with my family. I am pleased to inform you that my colleague Hitesh Lath is assuming the role of CFO. I hired Hitesh about three months ago as our Chief Accounting Officer. Hitesh comes to us from Ernst & Young, where he was a partner for over 8 years and brings a total of 24 years spent serving large, multinational technology clients. I've known Hitesh for over a decade, and in fact, when I was at Ernst & Young, I worked for him on some engagements.
Speaker Change: Have to be on 150% all the time and for me personally I need to take a break and step aside for a bit and spend more time with my family.
Speaker Change: I am pleased to inform you that.
Speaker Change: Got my colleague to Tesla is assuming the role as CFO I hired Peter asked about three months ago, as our Chief Accounting Officer.
Speaker Change: <unk> comes to us from Ernst <unk> Young where he was a partner for over eight years and brings the total experience of 24 years spent serving large multinational technology clients.
Speaker Change: I have known who test for over a decade and in fact, when I was at Ernst and young I work for him at some of the engagements from.
Juho Parkkinen: From day one, Hitesh jumped right in and was heavily involved in preparing the financials for this quarter, and I'm very excited to hand the finance team into Hitesh's capable hands and expect him to continue the progress we have made and take the team to new heights. I will remain a C3 AI employee, advising Hitesh and Tom and assisting the team as necessary to make sure our operations are smooth and our financial reports continue to be pristine. Hitesh, would you like to say something?
Speaker Change: From day, one it has jumped right in and it was heavily involved in preparing to financials for this quarter and I'm very excited and the finance team through your test is capable hearings and expect him to continue the progress we have made and take the team to new Heights.
Speaker Change: I will remain a C. Three employee advisory comparison, Tom and assisting the team thats necessary to make sure. Our operations are smooth on our financial reports continue to be pristine detached would you like to say something.
Hitesh Lath: Thank you, Juho. I have been here at C3 AI for about three years, and I'm very excited to take it. These are great times for AI and for C3 Iot. And I look forward to working with Tom and the rest of the executive team and being a part of it. With that, I'd like to hand it over to the operator. Thank you. As a reminder, to ask a question, you will need to press star 11 on your telephone.
Speaker Change: Thank you Yuval.
Speaker Change: I have been here at <unk> for about three months.
Thomas M. Siebel: And I'm very excited to take on this role.
Thomas M. Siebel: These are great times for AI.
Thomas M. Siebel: And for CPI.
Thomas M. Siebel: And I look forward to working with Tom and rest of the executive team and be a part of the growth story.
Speaker Change: With that I'd like to hand, it over to the operator for Q&A.
Speaker Change: Thank you as a reminder to ask a question you will need to press star one on your telephone.
Operator: Please stand by while we compile the Q&A roster. And our first question comes from Timothy Horan of Oppenheimer. Thanks, guys.
Speaker Change: These standby, while we compile the Q&A roster.
Speaker Change: And our first question comes from Timothy Horan of Oppenheimer.
Thomas M. Siebel: Could you give us a little bit more metrics on the productivity improvements your customers are seeing or success stories? And, you know, where is generative AI adding the most value to AI as you see it now? If you or one of your associates, dial in next week to our users group conference because our customers are going to say what the productivity increases they're getting are. I mean, Shell has stood up and said they're getting $2 billion in economic benefits.
Timothy Kelly Horan: Alright, thanks, guys.
Timothy Kelly Horan: Could you give us a little bit more metrics on the productivity improvements you're customers are saying or success stories and.
Timothy Kelly Horan: Whereas generative AI, adding the most value to AI as you see it now.
Timothy Kelly Horan: Okay.
Timothy Kelly Horan: Timothy Hi, its Tom Thanks for the question.
Thomas M. Siebel: I would do this.
Thomas M. Siebel: Do you have time, either you or have one a year of associates dial in next week to our users group conference because customers are going to say with the productivity increases that are getting are Michel has stood up and said theyre getting.
Timothy Kelly Horan: $2 billion in economic benefit the United States Air Force, who will be presenting at this at this has stood up and said that theyre getting a 25% increase in aircraft availability increase in aircraft availability from our predictive maintenance applications deployed as a standard in the Air Force.
Thomas M. Siebel: The United States Air Force, who will be presenting at this, has stood up and said that they're getting a 25% increase in aircraft availability, an increase in aircraft availability from our predictive manage application that's deployed as a standard in the Air Force. So, I mean, that's a 25% increase in capability in the U.S. Air Force. There's a lot of capability. You know, those are two examples.
Timothy Kelly Horan: So I mean, that's 25% increase in capability United States Air Force is a lot of capability. So.
Timothy Kelly Horan: Those are two examples.
Timothy Kelly Horan: Generative AI Kimberly, there's just no telling where this goes.
Thomas M. Siebel: Genitive AI, there's just no telling where this goes. Whether it's sitting on top of Workday, sitting on top of ServiceNow, sitting on top of SAP, sitting on top of Salesforce, writing contracts for lawyers, the work we're doing at DLA Piper. One of the applications you're going to see, like, you know, for those of you that tuned in to our user group conference, they'll talk about the RSO application. This is the application, which is one of the largest AI applications on earth, deployed by the United States Air Force. And you know, now we're putting this together, and this is, we've used the data from 22 weapons systems in the Unified Federated Image, F-15, F-16, F-18, F-35, KC-135, etc. And including the telemetry from many of these devices, and a B-1 bomber has 42,000 sensors emitting telemetry at something like 8 hertz cycles, so there's a lot of data
Timothy Kelly Horan: Whether it's sitting on top of workday sitting on top of the service now sitting on top of these sitting on top of Salesforce driving contracts for lawyers.
Timothy Kelly Horan: The work, we're doing with DLA Piper.
Timothy Kelly Horan: What are the applications are going to see like for those of you that tune in to our user group conference call to talk about the RSO application. This is the.
Timothy Kelly Horan: The application was one of the largest AI applications on Earth Dysport reported the United States Air Force band now we're putting in this this is refused the data from 'twenty two weapon systems into a unified Federated image F. 15 F 16 F 18, F 35, KC 135 et cetera, and it could.
Timothy Kelly Horan: The telemetry for many of these devices.
Timothy Kelly Horan: B one bomber has 42000 sensors emitting telemetry, it's something like 800 cycles, So theres a lot of data.
Thomas M. Siebel: I think it's an order of 100 terabytes of data. And like any application of this nature, it has a highly technical interface. When we put generative AI on top of it, it has a Mosaic browser user interface. The Mosaic browser, you guys know that it's basically the Google browser. Okay, Google copied it, okay, and Mosaic came out of the University of Illinois, I think in 1993. And so now you simply anybody in the Air Force with the proper authority can ask any question about any weapon system or any weapon system and immediately get the answer. For example, what are my readiness levels for F-35 squadrons in Central Europe?
Timothy Kelly Horan: It's order of 100 terabytes of data and like any application of this nature. It is a highly technical interface why don't we put generative AI on top of it. It has a mosaic browser user interface is both mosaic browser you guys know that is the basically the Google browser Google copied it.
Timothy Kelly Horan: Okay.
Timothy Kelly Horan: Mosaic browser came out of University of Illinois, I think in 1993, and so now you're simply anybody in their floors with the proper authority can ask any question about any weapons system or any weapon systems and immediately get the answer what am I read it ups levels were up 35 squadron and Central Europe.
Thomas M. Siebel: What's my cost of running the B-1B program for each of the last five years? Okay, what are my biggest parts issues associated with the F-35 project? Whatever it may be. So it really is, as it relates to the, you know, as we deploy these enterprise AI applications in mass across organizations, it provides a user interface, it makes the change management project process much simpler. So these are examples in both those areas.
Timothy Kelly Horan: My cost of running the <unk> B program in each of the last five years, Okay. What about Vegas parts issues associated with the F 35 project whatever it may be so it really is though as it relates to the as we deploy these enterprise AI.
Timothy Kelly Horan: AI applications in mass across organizations. It rise a user interface. It makes the change management project and process much simpler. So these are examples in both those areas and you know I don't know how this big how big this generative. It I think is but it's bigger than a bad box I can tell you that.
Thomas M. Siebel: You know, I don't know how big this generative AI thing is, but it's bigger than a bed box. I can tell you that. Thank you. Thank you.
Speaker Change: Thank you.
Operator: One moment for our next question. And our next question comes from Sanjit Singh of Morgan Stanley. Thank you for taking the questions and sorry Juho to see you go. Best of luck spending time with the family.
Speaker Change: Thank you one moment for our next question.
Speaker Change: And our next question comes from Sanjay <unk> of Morgan Stanley.
Sanjay: Thank you for taking my question and sorry, if you heard or seen.
Sanjay: And best of luck.
Speaker Change: Spending time with my family.
Thomas M. Siebel: Tom, I wanted to ask a little bit about retrieval augmentation generation. It seems like that's an AI access pattern that's getting really, really popular across enterprises and across AI companies. And so there are a lot of companies sort of pursuing this opportunity, and what I wanted to hear a little bit about how C3 is sort of differentiated in terms of providing this capability to enterprises, and that sort of differentiates RAG from C3 versus some of the other players that are trying to make this a reality for customers. Sanjit, Enterprise AI in general or specifically generative AI?
Sanjay: Tom I wanted to ask a little bit.
Speaker Change: The fuselage Vincent generation it seems like Boston.
Sanjay: AI access pattern.
Sanjay: Really really popular across enterprise cost.
Sanjay: AI companies.
Sanjay: Okay.
Sanjay: A lot of problems with it.
Sanjay: This opportunity.
Sanjay: Good to hear a little bit about how.
Sanjay: It's sort of differentiated in terms of.
Sanjay: Reviving this capability.
Sanjay: That sort of differentiates rod from Q3 versus now.
Sanjay: Some of the other players.
Speaker Change: Hi, Joe.
Joe: I think thats a reality for customers.
Speaker Change: Sanjay enterprise AI in general or specifically generative AI.
Thomas M. Siebel: Generative AI, but I'm specifically talking about retrieval-augmented generation, like RAG being, it seems like one of these use cases that's catching fire with enterprises, and I just wanted to see how C3 is allowing customers to pursue RAG use cases. Okay, well, RAG usually, what we're referring to is a technology that allows the answer to be traceable. Okay, that allows you to, so when you ask the question, it tells you where the answer comes from. And most large language models will not do that. Okay, the C3 generative, by combining 15 years worth of platform architecture with the large language model, we're able to solve the generative AI equation in a highly differentiated manner. The C3 generative model, when we supply generative, all the answers are deterministic, not, not random. That means every time you ask the same question, you get the same answer. Go on to BARD, or go on to JET GPT; it doesn't work that way.
Speaker Change: Okay.
Speaker Change: I'm going to bring about the retrieval of merchant generation.
Speaker Change: <unk>.
Speaker Change: It seems like you think that that's catching fire with enterprises.
Speaker Change: I just wanted to see like how steeply.
Speaker Change: Allowing customers to pursue Rockies.
Speaker Change: Oh, Okay, well rag, usually what we're referring to is there technology that allows us to answer to be traceable. Okay that allows you to do so when you asked the question. It tells you where the answer comes from and most large like what's your models will not do that okay. The C. III generative by combining 15 years' worth of platform architect.
Speaker Change: With the large language model, we're able to solve that generate value equation in a in a highly differentiated manner. Okay.
Speaker Change: III generative AI when we support generate all the answers are deterministic not not random that means every time you asked the same question you get the same answer go onto Bard or go out of jet Gpt's doesn't work that way every time, we ask the same if two people asked the same question you get different answers okay.
Thomas M. Siebel: Every time you ask the same question, if two people ask the same question, you get different answers. Okay? Secondly, everything that we do is traceable, okay? And this is where we use RAG, you know, retrieval augmented generation technology, so we know exactly where the answer came from. Okay, and most large logic angles will not do that, okay? Because we have the temperatures turned down to zero. Okay, we don't hallucinate.
Speaker Change: Hendley everything that we do is traceable, okay and this is where we use a rag retrieval augmented generation technology. So we know exactly where the answer came from again, most large large angles. So let's do that okay. Because we have the temperatures turn down to zero. Okay. We don't we don't know.
Thomas M. Siebel: If it doesn't know the answer, it doesn't tell you where the answer is. Most of these other solutions are unimodal. You know that, okay? They can put anything you want as long as you put in text. That's not useful. Now they're thinking about multimodal. Multimodal, if you ask Andrew Ng, means, you know, text plus images. That's not that useful either.
Speaker Change: Elucidate.
Speaker Change: It doesn't know the answer it doesn't tell you where the answer is.
Speaker Change: Most of these other solutions are unit modal you know that okay.
Speaker Change: But anything you want as long as you put in text that's not usual now they're thinking about multimodal multimodal. If you ask Andrew Ang remains.
Speaker Change: <unk> plus imagers, that's not that useful either if we're gonna do generative AI for example on the airport application it needs to be omni modal text images graphics enterprise data telemetry voice.
Thomas M. Siebel: If we're gonna do generative AI, for example, on the airport application, it needs to be omnimodal. Text, images, graphics, enterprise data, telemetry, voice, signals, what have you. And so we're omnimodal. Almost all of these other LLM solutions, whether they come from OpenAI or Anthropic or Google or wherever they might be, they are LLM specific.
Speaker Change: Signals, so what have you and so we're omni modal.
Speaker Change: We.
Speaker Change: Almost all of these other <unk> solutions, whether they come from open AI, our ore anthropic or or Google or wherever they might be they are.
Thomas M. Siebel: Our answer is we're LLM agnostic. So you can change out the large language model every week as these guys out-innovate each other. One of the big hobgoblins associated with large language models is data exfiltration. This is what is stopping these applications from being installed everywhere. See Samsung for details. There's a lot of research, particularly coming out of Carnegie Mellon, that shows the cyber attack vectors that are opened by these large language models.
Speaker Change: Specific our answer is yes.
Speaker Change: Gnostic she didn't change out the large languished a battle every week as these guys out innovate each other okay. One of the big Hobgoblin associated with large language models is data extra filtration. This is what this is what is stopping these applications from being installed everywhere see Samsung for Dhl's Theres, a lot of research, particularly coming out of <unk>.
Speaker Change: Anniversary the Carnegie Mellon, Okay that are showing the cyber attack vectors that are opened by these large language models and then you know the story about Samsung with the kind of massive data ex filtration of their intellectual property under the public internet, okay, because the way that our system is structured we have the LLS has no.
Thomas M. Siebel: And then you know the story about Samsung with the kind of massive data exfiltration of their intellectual property onto the public internet. Okay, because the way that our system is structured, the LLM has no access to the data. Therefore, it can't exfiltrate, and it's not a vector for cyber crime.
Speaker Change: Access to the data therefore, it can't actual trade and it's not a vector for cyber okay. It also because it doesn't have access to the data at.
Thomas M. Siebel: Okay, it also because it doesn't have access to the data, it doesn't have the opportunity to hallucinate. Okay. Another reason why these LLMs are not being installed has to do with IP liability. The IP liability associated with these large language models that are trained on the public internet is unbounded.
Speaker Change: It doesn't have the opportunity to hallucinate. Okay. Another reason why these <unk> are not being installed has to do with IP liability. The IP liability associated with these large language models that are traded in the public internet or.
Thomas M. Siebel: Okay, unbounded liability is a problem for Bank of America. Unbounded liability is a problem at Cargill. It's a problem at any responsible organization, you know, even Morgan Stanley. Okay. And the way that our system works, only your data is available to the large language model.
Speaker Change: Unbounded, Okay unbounded liability is a problem for bank of America unbounded liabilities a problem at cargo.
Speaker Change: Problem at any responsible organization, even Morgan Stanley Okay and.
Speaker Change: Sure.
Speaker Change: The way that the way that our system works only your data are available with the largest English model. So there is no IP liability for album and finally, our solutions our LLP.
Thomas M. Siebel: So there is no IP liability problem. And finally, our solutions are LLP, you know. I already mentioned LLP, and LLM agnostic. So our solutions are highly differentiated from the other solutions that are out there. And for any one of those reasons I mentioned, okay, that system does not get installed at Goldman Sachs, does not get involved at Morgan Stanley, Coke Industries, the United States Air Force, or the CIA. That dog doesn't hunt, and ours does.
Speaker Change: I already mentioned LLP.
Speaker Change: Agnostic so our solutions are highly differentiated from the other solutions that are out there and for any one of those reasons I mentioned, okay. That's system does not get installed at Goldman Sachs does not get involved with Morgan Stanley. Okay. Koch industries, the United States Air Force or the CIA that dog doesn't hunt and ours does.
Thomas M. Siebel: That's the difference. That's a super comprehensive answer, Tom, and I'm really looking forward to watching some of those sessions at D3 Transform next week. And there is a session specifically on that with Nikhil Krishnan, who you know, James Lawrence from RSO, and Rowan Kern from Forrester Research on exactly that at 9.15 on March 6th. I highly recommend it.
Speaker Change: That's the difference.
Speaker Change: That's super comprehensive answer Tom.
Speaker Change: I'm really looking forward to a lot.
Speaker Change: Some of those sessions that are deeply transform.
Speaker Change: And specifically on that.
Speaker Change: With with DXP.
Speaker Change: They feel Christian who you know James Lawrence.
Speaker Change: Okay and for enrolling current from Forrester research on exactly that.
Speaker Change: And at <unk>.
Speaker Change: 915 on March six I highly recommended.
Thomas M. Siebel: Perfect. Um, I do have one follow-up, and it goes to some of the color that you provided on, you know, the customers coming out of pilot and how they're choosing to license going forward. And so with the kind of more of a shift or more of a preference, I guess, or kind of subscription contract, Directly, what does that imply for like quarterly revenue over the next couple of quarters, right? Because we've been trying to think that, you know, there might be a headwind as customers move to like consumption contracts, and their consumption will eventually sort of, you know, grow, and that becomes revenue accretive. But now with this mix shift, directly, how should I think about that impact?
Speaker Change: Perfect.
Speaker Change: I have one follow up and it goes to some of the color that you provided.
Speaker Change: The customers coming out of pilot.
Speaker Change: There are few things to license going forward.
Speaker Change: The kind of more of a shift for more of a preference I guess.
Speaker Change: Subscription contract.
Speaker Change: What does that imply for like quarterly for the next couple of quarters.
Speaker Change: Great I think that you had.
Speaker Change: Wind.
Speaker Change: As customers move to like consumption.
Speaker Change: Consumption will eventually sort of.
Speaker Change: Grow and that becomes revenue accretive, but now looks like next year.
Speaker Change: How can I think about that impact.
Thomas M. Siebel: quarterly revenue. That trend continues from here on going forward. Let's see, I'm trying to find a headwind in either of these stories. Okay. Sometimes I have to, like, offline, tell me where the headwind is.
Speaker Change: Quarterly revenue.
Speaker Change: Hum.
Speaker Change: From here on going forward.
Speaker Change: Let's see I'm trying to find a headwind in either of these stories okay.
Speaker Change: Sometimes after like offline tell me, where the headwind is okay.
Thomas M. Siebel: Okay. The bottom line is the customer has the option of licensing it, you know, playing the pilot, okay, we'll take it month to month and we'll pay for it up for per CPU hour, or many of them want to deal with price certainty because they plan on expanding in a pretty big way, and they say, hey, guys, let's talk about a three-year commitment. We're going to make a certain amount of money in year one, year two, year three, and there's the consumption pricing component. Now the bottom line is, Sanjit, it's revenue neutral to us over 10 quarters, so it doesn't matter. Our business is we're in the customer service business. If the customer wants to buy it, we're going to sell it, but it has really no meaningful impact on our revenue modeling. But it did come as a surprise.
Speaker Change: The bottom line is the customer has the option of licensing it.
Speaker Change: Okay, we'll take it month to month, and we will pay for.
Speaker Change: For the for per CPU hour.
Speaker Change: Or many of them.
Speaker Change: Wanted to deal with price certainty because they plan on expanding in a pretty big way and they say hey, guys. So let's talk about a three year commitment we make.
Speaker Change: To a certain amount of money in year, one year two year, three and there is a consumption pricing about it now the bottom line is <unk>.
Speaker Change: <unk> is revenue neutral to us over 10 quarters, so it doesn't matter.
Speaker Change: Our business is our business is when the customer service business. However, the customer wants to buy it we're going to sell it but it is really no meaningful impact on our revenue modeling, but it did come as a surprise it's counterintuitive.
Thomas M. Siebel: Yeah, no, that's great. And I'll leave it there and give the floor to the other animals. Thank you so much, Tom. Thank you. One moment for our next question, and our next question comes from Pat Walravens of JMP Securities. Oh, great. I'd like to start with one sort of financial one, and then, and then, Tom, I have a big picture one for you. So Juho, maybe on your way out.
Speaker Change: Yes.
Speaker Change: And I'll leave it there.
Speaker Change: Peter do you want to.
Peter: Thank you so much Tom.
Peter: Thank you one moment for our next question.
Peter: And our next question comes from Pat Wall Ravens of JMP Securities.
Peter: Okay.
Speaker Change: Oh great.
Speaker Change: I'd like to start with one sort of.
Speaker Change: Financial one and then Tom I have a big picture one for you so.
Speaker Change: You hope maybe on your way out I mean this is your Q3 next quarters Q4, and then youre going to Youre going to give us some guidance for fiscal 'twenty five just to keep us all.
Patrick D. Walravens: I mean, this is your Q3 next quarter's Q4. And then you're going to give us some guidance for fiscal 25 just to keep us all in check, you know, a quarter ahead of it. Yeah, let's not let's not get ahead of ourselves.
Peter: In check.
Thomas M. Siebel: Yes, let's not get ahead of ourselves can we just can you just get some sense of what.
Patrick D. Walravens: Can we just, can you just get some sense of what, you know, some boundaries in terms of what we should think about for fiscal 25? I think, Pat, thanks, first of all, for that question. But I mean, we're still planning for FY 25.
Thomas M. Siebel: Some boundaries in terms of what we should think about for fiscal 'twenty five.
Thomas M. Siebel: Thanks.
Speaker Change: Thanks first of all for that question, but I mean.
Peter: We're still we're still planning for FY 'twenty five.
Juho Parkkinen: I mean, we think the opportunity is massive. We're very excited about the generative AI opportunity. But it's too early for us to give you any sort of guidance as to what the FY 25 revenues look like.
Speaker Change: I mean, we think the opportunity is massive we're very excited about the generative AI opportunity.
Peter: But it's too early for us to give you any sort of guidance as to what the FY 'twenty five revenues look like we are confident on free cash flow positivity for 25. However.
Juho Parkkinen: We are confident on free cash flow positivity for 25, however. Okay, all right, well, that's helpful. All right, and then Tom, the big one for you is, I'm just wondering about the sort of. I think the future demand curve for, you know, nation states, sovereign clouds, that sort of thing. I had breakfast with another AI executive this week, and one of the comments he made was, If you don't have access to, or you don't have your own committed access to, AI in your country, you are dead.
Speaker Change: Okay, Alright, well that's helpful. All right and then Tom the Big one for you is I'm just wondering about the sort of.
Thomas M. Siebel: I think future demand curve for nascent state sovereign cloud.
Thomas M. Siebel: Everything I had breakfast with another AI executives this week and one of the comments he made was.
Peter: If you don't have access to <unk>. If you don't have your own committed access to AI in country you are dead.
Patrick D. Walravens: So. Are you overstating the case, or is this another area where there's potentially a lot of work for you guys to do? Who are you? You don't have access.
Peter: <unk>.
Peter: The overstating the case or is this is this is another area, where there's potentially a lot of work for you guys to do.
Speaker Change: <unk> you.
Speaker Change: You don't have access.
Thomas M. Siebel: Pick whatever, pick whatever, pick the Prime Minister or President of any of our allies. Well, I think you know, France, Germany, the UK; we do have sovereign access. Okay. And so we're not finding this a problem, data sovereignty, because one or more of the cloud providers do guarantee data sovereignty. I think actually, the interesting trend, Pat, that we're seeing, and this is really counterintuitive, I think, I think we're going to see the return of in-house data centers. Okay, and yeah, I think this, you know, like what HP is leading, you know, with what do they call it? Green, green grass, greenhouse, they with these supercomputers that'll be inside of, you know, Goldman Sachs and, okay, and, and Bank of America and other firms. I think, I think we're going to see a return to in-house data centers, believe it or not, okay, where people have the G, and we'll get the GPUs inside. But data sovereignty is not a difficult problem to solve, and we're able to address it. We have customers all over the world, and I believe it's a level zero requirement.
Speaker Change: All of our big pick whatever pick whatever pick the prime minister president of any of our allies.
Peter: Well, I think Youre, France, Germany U K, we do have sovereign access okay, and so we're not finding this a problem or data sovereignty a problem because one or more of a cloud providers does guarantee data sovereignty I think actually the interesting trend.
Peter: Add that we're seeing and this is really counter intuitive I think I think we're going to see the return of announced data centers.
Peter: Okay, and I think Thats, you know like what HP is leading with what do they call. It green Green grass greenhouse where would these supercomputers there'll be inside of <unk>.
Peter: Goldman Sachs.
Peter: And.
Peter: And bank of America, and other firms I think I think we're going to see a return to announce data centers believe it or not okay, where people have the <unk>, we would get the gpus inside but data sovereignty is not a difficult problem to solve and we're able to address it.
Peter: Customers all over the world.
Peter: I believe it's a level zero requirement and the.
Patrick D. Walravens: And the, you know, our friends at Azure and AWS, in particular, do kind of nail that quite well. Okay, can I go a little deeper on your comment about why we're returning to in-house data centers? (Inaudible) Why do I think that?
Peter: Our friends at <unk> and AWS in particular do kind of nailed that.
Peter: Quite well.
Speaker Change: Okay can I go a little deeper on your comment about why were returning to in house data centers.
Speaker Change: Yeah.
Speaker Change: Why do I think that yes.
Thomas M. Siebel: Yeah, well, what are you seeing that's driving that? I'm hearing this in the marketplace, and even my engineers have said, Okay, that it's going to be cost-effective for us to build. Now, the constraint is that, you know, you'd think, well, somebody needs to call up Jensen and beg for GPUs. Let's say we could figure out how to do that. Maybe we know somebody who knows Jen
Speaker Change: What are you seeing that drive.
Peter: Hearing this in the marketplace.
Peter: Even my engineers, you've talked about it.
Peter: Okay that is going to be cost effective for us to build now the constraint is it you think or somebody needs to call up Janssen and beg for Gpus. So, let's say, we could figure out how to do that maybe we know somebody knows janssen okay.
Thomas M. Siebel: Okay, the hard part is, we can't get power. So I think the constraint on this going for everybody sees the constraint is the availability of GPUs. I think a constraint on this soon is going to be the availability of power. You cannot get power to build a data center in Silicon Valley.
Peter: The hard part is we can't get power.
Peter: I think the constraint on this going for everybody sees that the constraint is availability of Gpus I think I can say.
Peter: And this soon it's going to be the availability of power you cannot get power to build a data center in Silicon Valley you notice right.
Thomas M. Siebel: You know this, right? You get in northern Silicon Valley is PG&E, which is, I have no comment on that, and in southern Silicon Valley, some other power company. I do not know what, but they will not give you power for a data center. So it's, I think this GPU constraint is ephemeral as soon as it's going to be power. All right, awesome. Thank you. Thank you. One moment for our next question. And our next question comes from Mike Cikos of Niederman Company. Good to hear that the consumption transition is tracking in line with your initial targets. On that note, what can you tell us about the size of your sales force, the ramping of these reps, and the number of pilots being signed per sales rep relative to your expectations? Hi Matt, this is Juho.
Peter: Northern Silicon Valley is the <unk>, which is.
Speaker Change: I have no comment on that.
Speaker Change: Southern Silicon Valley or some other power company I know not what but they will not give you power for data center.
Peter: I think I think this I think this GPU constraint is a femoral as soon it is going to be power.
Peter: Okay.
Speaker Change: Alright, thank you.
Speaker Change: Thank you one moment for our next question.
Speaker Change: And our next question comes from Mike Cecos of Needham <unk> Company.
Speaker Change: Great. Thanks, guys. This is Matt <unk> on for Mike So it goes over at Needham.
Matt: Good to hear that the consumption transition is tracking in line with your initial targets on that note. What can you tell us about the size of your sales force the ramping of these reps and the number of pilots being signed per sales rep relative to your expectations.
Speaker Change: Hi, Matt as you hope so.
Juho Parkkinen: So the sales We are still hiring actively in all of our sales functions, but not as fast as we'd like. So our sales force is not as high as we initially projected when we provided these sorts of assumptions, but we continue to ramp up on that. As it comes to ramping up the sales force, I think previously we've said that everybody should make some sort of expectations and assumptions in their models until they close their first buy get, but a reasonable assumption would be, you know, one and a half, two quarters before they get fully ramped up and get going on, on, closing their first buy get. And then, uh, Matt, what was your third question? Just if anything has changed as far as how many pilots you're expecting each rep to close. I know that was part of the initial assumptions. Yeah, one thing. Yeah, once.
Matt: Sales we are.
Matt: Still hiring activity in all of our sales functions, but not as fast as we'd like so we our sales force is not as high as we initially projected when we provided the sort of assumptions, but we continue to ramp up on that as it becomes to the ramping up the sales force I think previously we've said that everybody should make some.
Matt: The expectations and assumptions and their model is something that they closed their first pilots, but a reasonable assumption would be one and a half two quarters before they get fully ramped up and get going on closing their first pilots and then.
Speaker Change: What was your third question.
Speaker Change: Just if anything has changed as far as like how many pilots you expecting each each rep. Because I know that was part of the initial assumptions I think yes, yes, yes.
Juho Parkkinen: Yeah, once again, we lead with the pilot sales motion. So all the sales reps, when they close new business, are expected to meet with a pilot. So we would expect each of the sales guys to bring in at least one pilot a quarter once they're fully ramped up, and everything's at scale. But we're not quite there yet.
Speaker Change: Again, we lead with the pilot sales motion so all the sales reps.
Speaker Change: When they closed new business is expected to get with a pilot. So we would expect each of the sales guys to bring into piece the part of the quarter. Once they are fully ramped up on everything so to scale, but we're.
Juho Parkkinen: Okay, great. Thanks for that. And then, has the company noted any change in the length of sales cycles this quarter versus the prior quarter, given management's comments on customer considerations for AI governance? I think we published that, didn't we? We took it out of the queue. But the sales cycle is about the same. It's pretty much the same.
Speaker Change: Not quite yet there.
Speaker Change: Okay, great. Thanks for that.
Speaker Change: And then has the company noted any change in the length of sales cycles this quarter versus the prior quarter, given management's comments on customer considerations for AI governance.
Speaker Change: We've published acid with.
Speaker Change: We took it out from <unk>, so, but the sales cycle is about the same.
Speaker Change: It's about the same yes.
Juho Parkkinen: It's about the same, Matt. It hasn't changed, which is about three and a half months. Yeah, all right, beautiful, thanks so much guys. One moment for our next question. And our last question comes from Kingsley Crane of Canaccord Genuity. Great, thank you for taking the question. I commend you on a great Q3 and really strong momentum in the business. With respect to your comments on NVIDIA and enterprise AI, I think what we're all trying to figure out is when will NVIDIA's 200 plus percent growth and hardware investments start flowing into the software layer? We're seeing some of it already. But is that more like one year or five years?
Speaker Change: Yes.
Speaker Change: Which is about five months.
Speaker Change: Alright beautiful thanks, so much guys.
Speaker Change: Okay.
Speaker Change: Thank you one moment for our next question.
Speaker Change: Okay.
Speaker Change: And our last question comes from Kingsley Crane of Canaccord Genuity.
Speaker Change: Yeah.
William Kingsley Crane: Great. Thank you for taking the question I commend you for the Great Q3, and really strong momentum in the business with respect to your comments on Nvidia and enterprise AI I think we're all trying to figure out is when in.
William Kingsley Crane: Videos 200, plus percent growth in hardware investments start flowing into the software layer.
William Kingsley Crane: Some of it already but is that more like one year five years, I think we see that by the way coming but we're all trying to time it.
William Kingsley Crane: I think we see the tidal wave coming, but we're all trying to time it. Well, you know, Kingsley, it's a good question, you know, but I tell you all this infrastructure is not being put out there to like play games. Okay, is put out there to run enterprise AI applications. And so these guys are out there building the highway for us. And thank goodness for that. And I think that, you know, I think you're generally aware of the market interest in AI applications, and I think you're generally aware, maybe more than generally, probably specifically aware of the interest in generative AI applications. And that's what those GPOs are going to be doing.
William Kingsley Crane: Well kings.
William Kingsley Crane: Kingsley, it's a good question, but I can tell you. All this infrastructure is not being put out there to like play games.
William Kingsley Crane: <unk> put out there to run enterprise AI applications.
William Kingsley Crane: So these guys are out there building highway for us and thank goodness for that and I think that.
William Kingsley Crane: No we.
William Kingsley Crane: In terms of if you look at the I think you're generally aware of the market interest in AI applications and I think you're generally aware maybe more than generally probably specifically aware of the of the interest in generative AI applications.
Thomas M. Siebel: They're going to be running them, and the good news is, they'll be there. So it's a good thing.
William Kingsley Crane: And that's what those Gpus are you going to be doing and theyre going to be around them and the good news is there'll be there. So it's a.
Thomas M. Siebel: You know, there are a lot of things coming into play. Thank you, that's really helpful. And so last one is just that we're seeing so much investment domestically, you've had such great success, both with federal and state and local governments. How are you viewing the international opportunity today, both in Europe and then in regions like APAC? Well, I disclosed last quarter that our performance in EMEA was significantly substandard, okay, and that was pretty clear about that. It came as a big surprise to everybody on this call that maybe we made some organizational changes, and I'm pleased to report that those changes have been quite positive, and we're seeing the levels of sales activity and customer engagement increasing dramatically in the EMEA theater and, interesting enough, the South American theater too, so there's that That's great!
William Kingsley Crane:
William Kingsley Crane: There's a lot of things coming into place.
Speaker Change: Thank you.
Speaker Change: Really helpful and so last one is just that we're seeing so much investment domestically you've had such great success, both with federal and state and local are you viewing the international opportunity today, both in Europe, and then in regions like APAC.
Speaker Change: Well I I.
William Kingsley Crane: Closed I think last quarter that our performance in EMEA was.
William Kingsley Crane:
William Kingsley Crane: Significantly substandard, okay, and any and that was pretty clear about that and.
William Kingsley Crane: Come as a big surprise to everybody on this call that maybe we've made some organizational changes and.
William Kingsley Crane: I am pleased to report that those changes have been quite positive and we're seeing the.
William Kingsley Crane: The levels of sales.
William Kingsley Crane: Sales activity and customer engagement, increasing dramatically in the EMEA theater and interesting enough the South American theater too so there's that.
Speaker Change: Thanks for the question and we're seeing very positive news there.
Thomas M. Siebel: Thank you. And Juho, it's been fantastic working with you. I wish you the best of luck. Thanks again.
Speaker Change: That's great. Thank you and you heard its been fantastic work with you I wish you the best of luck. Thanks again quite quickly.
Thomas M. Siebel: Thank you. I would now like to hand it back to Mr. Siebel for closing remarks. Ladies and gentlemen, thank you for your time this afternoon. We appreciate the opportunity to update you on the state of our business. I can tell you that, you know, for those of you who have visited us, you know this is a very unique place. We have the only full parking lot in Silicon Valley.
Speaker Change: Thank you I would now like to hand, it back to Mr. <unk> for closing remarks.
Speaker Change: Ladies and gentlemen.
Speaker Change: Thank you for your time. This afternoon, we appreciate the opportunity to update you on the state of our business I can tell you that.
Speaker Change: For those of you who visited US you know this is a very unique place wherever the only full parking lot in Silicon Valley. There are five or 600 people here working with us today shoulder to shoulder to their here Monday through Friday, and we're working in.
Thomas M. Siebel: There are five or six hundred people here working with us today, shoulder to shoulder. They're here Monday through Friday. And we're working in, you know, Chicago, Atlanta, Tysons, Washington, D.C., London, Rome, Paris. We're all doing it. We have a very unique, high-performance corporate culture that I think is going to serve as a really strong competitive advantage in the long run. So this place is just kind of vibrating with excitement.
Speaker Change: Chicago.
Speaker Change: Atlanta, Tysons, Washington, D C, London, Rome, Paris were.
Speaker Change: We're all at it we have a very unique high performance corporate culture that I think is going to serve as a.
Speaker Change: Real strong competitive advantage in the long run. So this places just kind of a vibrating with excitement.
Thomas M. Siebel: And I think for all of us involved, it's the professional experience of a lifetime, and we thank you for the opportunity to share it with you. And we look forward to bringing you up to speed next quarter. And let me just give you one last thought, for those of you who have time, I really encourage you to dial in to C3 Transform next week, because I think you'll find it. These are professional presentations that are quite substantive, and it will be a good use of your time if you have time. Ladies and gentlemen, thank you very much, and we look forward to talking again. This concludes today's conference call. Thank you for participating, and you may now disconnect.
Speaker Change: <unk>.
Speaker Change: For all of US involved is the professional experience of a lifetime and we.
Speaker Change: Thank you for the opportunity to share with you and we look forward to.
Speaker Change:
Speaker Change: Bringing up to speed next quarter elaborate just last thought for those of your time I really encourage you to dial in to the <unk> pharma next week, because I think you'll find it.
Speaker Change: These are professional presentations that are quite substantive and.
Speaker Change: We will be a good use of your time, if you have time ladies.
Speaker Change: Ladies and gentlemen, thank you very much and we look forward to.
Speaker Change: Talking to you again soon.
Speaker Change: This concludes today's conference call.
Speaker Change: Thank you for participating and you may now disconnect.
Speaker Change: Okay.
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