C3.ai Inc (AI) 2023 Q4 法說會逐字稿

Good afternoon, and welcome to C3 AI's earnings call for the fourth quarter fiscal year 2023, which ended on April 30, 2023. My name is Amit Barry, and I lead Investor Relations at C3 AI.

下午好，歡迎來到 C3 AI 的 2023 財年第四季度財報電話會議，該電話會議於 2023 年 4 月 30 日結束。我叫 Amit Barry，我是 C3 AI 的投資者關係負責人。

With me on the call today is Tom Siebel, Chairman and Chief Executive Officer; and Juho Parkkinen, Chief Financial Officer. After market close today, we issued a press release with details regarding our fourth quarter results as well as the supplemental of 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.

今天與我通話的是董事長兼首席執行官 Tom Siebel；首席財務官 Juho Parkkinen。今天收盤後，我們發布了一份新聞稿，其中包含有關我們第四季度業績的詳細信息以及我們業績的補充資料，兩者都可以通過我們網站 ir.c3.ai 的投資者關係部分訪問。此電話會議正在進行網絡直播，電話會議結束後將在我們的 IR 網站上提供重播。

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. 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 be caused -- that could cause the actual results to differ materially from expectations. For a further discussion on the material risks and other important factors affect our actual results, please refer to our filings with the SEC.

在今天的電話會議上，我們將發表與我們的業務相關的聲明，根據聯邦證券法，這些聲明可能被視為前瞻性的。這些聲明僅反映我們截至今天的觀點，不應被視為代表我們在任何後續日期的觀點。我們不承擔任何更新任何前瞻性陳述或展望的義務。這些陳述受到可能導致的各種風險和不確定性的影響——這可能導致實際結果與預期存在重大差異。有關影響我們實際結果的重大風險和其他重要因素的進一步討論，請參閱我們向美國證券交易委員會提交的文件。

All figures will be discussed on a non-GAAP basis unless otherwise noted. Also during the course of today's call, we will refer to certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in our press release. Finally, at times in our prepared remarks, in response to your questions, we may discuss metrics that are incremental to our usual business 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.

除非另有說明，否則所有數據都將在非 GAAP 基礎上進行討論。同樣在今天的電話會議中，我們將參考某些非 GAAP 財務措施。我們的新聞稿中包含 GAAP 與非 GAAP 措施的對賬。最後，有時在我們準備好的評論中，為了回答您的問題，我們可能會討論對我們通常的業務演示來說是增量的指標，以便更深入地了解我們的業務動態或我們的季度業績。請注意，我們將來可能會或可能不會繼續提供此額外詳細信息。

And with that, let me turn the call over to Tom.

就這樣，讓我把電話轉給湯姆。

Thank you, Amit. Good afternoon, everyone, and thank you for joining our call today. We finished the fourth quarter strong and the coming year looks stronger. I believe that is generally agreed that the overall market for enterprise AI now appears substantially larger and is growing at a much greater rate than most analysts and experts predicted. We have been working since 2009 to develop product leadership and established thought leadership in enterprise AI, assisting private and popular sector enterprises to apply AI to improve operational processes. C3 AI has been at the vanguard of enterprise AI of the enterprise AI market for over a decade.

謝謝你，阿米特。大家下午好，感謝您今天加入我們的電話會議。我們以強勁的勢頭結束了第四季度，來年看起來更強勁。我相信人們普遍認為，企業人工智能的整體市場現在看起來比大多數分析師和專家預測的要大得多，而且增長速度要快得多。自 2009 年以來，我們一直致力於發展產品領導力並在企業 AI 領域建立思想領導力，協助私營和熱門行業企業應用 AI 來改進運營流程。十多年來，C3 AI一直處於企業AI市場的企業AI排頭兵。

As the market has developed from its roots in IoT to supervised learning -- unsupervised learning, NLP, deep learning, reinforcement learning and now Generative AI. In the past 14 years, we have developed and enhanced the C3 AI platform and now offer over 40 enterprise AI applications developed with that platform that allow our customers to rapidly take advantage of AI to improve their business processes.

隨著市場從 IoT 的根源發展到監督學習——無監督學習、NLP、深度學習、強化學習和現在的生成 AI。在過去的 14 年裡，我們開發並增強了 C3 AI 平台，現在提供了 40 多個使用該平台開發的企業 AI 應用程序，使我們的客戶能夠快速利用 AI 來改進他們的業務流程。

We have been communicating for over a decade that we believe that the market for enterprise AI solutions would be quite large. And now as we enter the summer of 2023, it's become a dominant theme in technology discussions, government -- or AI has become a dominant theme in technology discussions, government discussions, media reports, defense and intelligence imperatives and government and business imperatives. I do not believe that it's an overstatement to say that there is no technology leader, no business leader and no government leader who is not thinking about AI daily.

十多年來，我們一直在溝通，我們相信企業人工智能解決方案的市場會非常大。現在，隨著我們進入 2023 年夏季，它已成為技術討論、政府或人工智能的主導主題，已成為技術討論、政府討論、媒體報導、國防和情報要求以及政府和企業要求的主導主題。我不認為說沒有技術領導者、商業領導者和政府領導者不是每天都在思考 AI 是誇大其詞。

AI chip makers, like NVIDIA are accelerating production to try to keep up with the very real demand that's out there. And all of this is getting accelerated by the advent of generative AI. The interest in AI and in applying AI to business and government processes has never been greater. Business inquiries are increasing. The opportunity pipeline is growing, demand is increasing. And C3 AI is well positioned to serve that increasing demand with our tried, tested and proven AI platform, our applications, our global footprint and our large global ecosystem.

像 NVIDIA 這樣的 AI 芯片製造商正在加速生產，以試圖跟上市場上非常真實的需求。而所有這一切都因生成人工智能的出現而加速。人們對人工智能以及將人工智能應用於商業和政府流程的興趣從未如此強烈。業務查詢越來越多。機會管道在增長，需求在增加。 C3 AI 已做好充分準備，通過我們久經考驗和驗證的 AI 平台、我們的應用程序、我們的全球足跡和我們龐大的全球生態系統來滿足不斷增長的需求。

The world is in many ways now coming to us. The interest in applying AI to business processes is substantially greater than we have ever seen. In the fourth quarter, we increased our customer base, expanded our work with existing clients and saw especially strong growth in our federal business. In the fourth quarter, our total revenue was $72.4 million, our free cash flow was $16.3 million, and we ended the quarter with over $812 million in cash and cash equivalents.

世界正以多種方式向我們走來。將 AI 應用於業務流程的興趣比我們以往任何時候都大得多。在第四季度，我們增加了客戶群，擴大了與現有客戶的合作，並且我們的聯邦業務增長尤為強勁。第四季度，我們的總收入為 7240 萬美元，自由現金流為 1630 萬美元，本季度末我們擁有超過 8.12 億美元的現金和現金等價物。

Importantly, we have a well-defined plan to be sustainably cash positive and non-GAAP profitable by the end of this fiscal year. For fiscal year 2024 -- I'm sorry, for the fiscal year 2023, okay, our total revenue was $266.8 million, an increase of 5.6% over fiscal year '22, okay. Subscription revenue was $230.4 million, representing an 11.4% increase over the prior year.

重要的是，我們有一個明確的計劃，要在本財年結束前實現可持續現金正數和非 GAAP 盈利。對於 2024 財年——對不起，對於 2023 財年，我們的總收入為 2.668 億美元，比 22 財年增長 5.6%，好吧。訂閱收入為 2.304 億美元，比上年增長 11.4%。

Let's talk a little bit about the AI applications market. Now as the enterprise AI market has developed, it appears that the bulk of the demand is increasingly for turnkey enterprise AI applications rather than for development tools. This thesis is supported by an evaluation of our bookings for the past fiscal year that indicates that 83% of our bookings were driven by application sales, 17% of our bookings were driven by the sales of the C3 AI platform.

讓我們談談人工智能應用市場。現在，隨著企業 AI 市場的發展，大部分需求似乎越來越多地用於交鑰匙企業 AI 應用程序，而不是開發工具。我們對上一財年預訂的評估支持了這篇論文，該評估表明我們 83% 的預訂是由應用程序銷售推動的，17% 的預訂是由 C3 AI 平台的銷售推動的。

Importantly, we are seeing increasing diversity in the industries we serve. For fiscal year '23, an analysis of our bookings includes oil and gas was 34%, federal defense and Aerospace was 29%; hi-tech was 13%; energy and utilities, 11%; manufacturing, 4%; food processing 2%; chemicals 2%, life sciences, 1.5%; and other industries made up the remaining 3%. An important leading indicator of our increasing industry diversity is evidenced by the trial and pilot agreements closed in Q4.

重要的是，我們看到我們所服務的行業越來越多樣化。對於 23 財年，我們的預訂分析包括石油和天然氣為 34%，聯邦國防和航空航天為 29%；高科技為13%；能源和公用事業，11%；製造業，4%；食品加工 2%；化學品 2%，生命科學 1.5%；其餘3%來自其他行業。第四季度結束的試驗和試點協議證明了我們日益增加的行業多樣性的一個重要領先指標。

Federal Defense and Aerospace made up almost 37%. The manufacturing comprised approximately 16% and hi-tech made up more than 10%, oil and gas also made up more than 10%. When we look at ag, state and local, chemicals, energy and financial services, each made up approximately 5% of our bookings. As a result of the increased demand for enterprise AI helped by our transition to consumption-based pricing, we are seeing a substantial increase in opportunities and shorter sales cycles.

聯邦國防和航空航天佔近 37%。製造業約佔16%，高科技佔10%以上，石油和天然氣也佔10%以上。當我們查看農業、州和地方、化學品、能源和金融服務時，每個服務約占我們預訂的 5%。由於我們向基於消費的定價過渡，對企業人工智能的需求增加，我們看到機會大幅增加，銷售週期縮短。

In Q4, we closed 43 agreements, including 19 pilots that were initiated in the quarter. The number of qualified enterprise opportunities targeted for closure within 12 months in our sales pipeline has increased by more than 100% in the past year. During fiscal year '23, we closed 126 agreements, up from 83% in the prior year. The average sales cycle for new and expansion deals was 3.7 months, down from 5 months in Q4 of the previous year.

在第四季度，我們完成了 43 項協議，其中包括本季度啟動的 19 項試點。在過去的一年中，我們銷售管道中目標為在 12 個月內關閉的合格企業機會數量增加了 100% 以上。在 23 財年，我們完成了 126 項協議，高於上一年的 83%。新交易和擴展交易的平均銷售週期為 3.7 個月，低於去年第四季度的 5 個月。

An examination of the composition of our pilot account profile suggests there is significant opportunity for growth as these accounts convert to consumption pricing. Of the 19 pilot accounts signed in Q4, 7 were accounts greater than $100 billion in revenue. Seven were accounts between $10 billion and $100 billion in revenue. 4 were accounts between $1 billion and $10 billion, and 1 was an account less than $100 million in annual revenue.

對我們試點賬戶概況的構成進行檢查表明，隨著這些賬戶轉化為消費定價，存在巨大的增長機會。在第四季度簽署的 19 個試點賬戶中，有 7 個賬戶的收入超過 1000 億美元。七個賬戶的收入在 100 億美元到 1000 億美元之間。 4 個賬戶在 10 億美元到 100 億美元之間，1 個賬戶年收入低於 1 億美元。

In fiscal year '23, we expanded our application footprint with a number of our customers, including Shell, Koch Industries, the United States Air Force Rapid Sustainment office, PwC, Ball, ExxonMobil, Con Edison, the Defense Counterintelligence and Security Agency, Baker Hughes, New York Power Authority, Duke Energy, ATB in Canada, Defense Innovation Unit, Roche, Cargill and ENGIE. We also established many new relationships during the year, including the Department of Defense common DoD AI office, Daily City, California, DOW, ExxonMobil, Flex, Hexagon, Nucor, Owens-Illinois, Pantelion, Riverside County, California, Start County, Ohio, Telus, Department of Defense, SOCOM, Department of Defense TRANSCOM and ESAB.

在 23 財年，我們擴大了我們與許多客戶的應用足跡，包括殼牌、科赫工業、美國空軍快速維持辦公室、普華永道、鮑爾、埃克森美孚、聯合愛迪生、國防反情報和安全局、貝克休斯、紐約電力局、杜克能源、加拿大 ATB、國防創新部門、羅氏、嘉吉和 ENGIE。我們還在這一年建立了許多新的關係，包括國防部共同的 DoD AI 辦公室、加利福尼亞州 Daily City、DOW、ExxonMobil、Flex、Hexagon、Nucor、Owens-Illinois、Pantelion、Riverside County、California、Start County、Ohio 、Telus、國防部、SOCOM、國防部 TRANSCOM 和 ESAB。

Many of these also expanded their AI engagements with us in the course of the year. Let's address the C3 AI partner network. The C3 AI partner ecosystem is increasingly effective at opening new doors. With our partners, we are able to provide prospects the assurance of success with -- and the highest quality service. In fiscal year '23, we closed 71 agreements with and through our partner network, including Google Cloud, AWS, Microsoft, Baker Hughes and Booz Allen. C3 AI increased its qualified pipeline with AWS by over 24% in the fourth quarter, with particular focus on state and local government.

在這一年中，其中許多人還擴大了與我們的 AI 合作。讓我們來談談 C3 AI 合作夥伴網絡。 C3 AI 合作夥伴生態系統在打開新大門方面越來越有效。與我們的合作夥伴一起，我們能夠為潛在客戶提供成功的保證——以及最優質的服務。在 23 財年，我們與合作夥伴網絡達成了 71 項協議，這些合作夥伴網絡包括谷歌云、AWS、微軟、貝克休斯和博思艾倫。 C3 AI 在第四季度將其與 AWS 的合格管道增加了 24% 以上，特別關注州和地方政府。

With Google Cloud, our joint qualified 12-month opportunity pipeline grew from 25 opportunities at the end of fiscal year '22 to 140 opportunities at the end of fiscal year '23, a 460% increase. And importantly, we closed 10 new oil and gas accounts in the year with our strategic partner, Baker Hughes, with accounts, including ExxonMobil, ADNOC, ENI and others.

借助 Google Cloud，我們共同的合格 12 個月機會管道從 22 財年末的 25 個機會增加到 23 財年末的 140 個機會，增長了 460%。重要的是，我們在這一年與我們的戰略合作夥伴貝克休斯關閉了 10 個新的石油和天然氣賬戶，賬戶包括埃克森美孚、ADNOC、ENI 等。

In Q4, we released the C3 Generative AI solution to the market. Our Generative AI solution leverages the capabilities of the C3 AI platform and is distinguished from other GPT/LLM solutions in the market in several ways. Number one, it allows enterprises to access all their enterprise and open source data, ERP, CRM, SCADA, TEXT, PDFs, Excel, PowerPoint, sensor data, you name it. Secondly, importantly, it provides traceable, deterministic, consistent answers. Thirdly, it enforces the corporate information access controls and security protocols that are currently in place. Fourthly, it has no risk of IP or data exfiltration caused by the large language model. And importantly, it is hallucination free.

在第四季度，我們向市場發布了 C3 Generative AI 解決方案。我們的生成式 AI 解決方案利用了 C3 AI 平台的功能，並在多個方面與市場上的其他 GPT/LLM 解決方案區分開來。第一，它允許企業訪問他們所有的企業和開源數據，ERP、CRM、SCADA、TEXT、PDF、Excel、PowerPoint、傳感器數據，應有盡有。其次，重要的是，它提供了可追溯的、確定性的、一致的答案。第三，它強制執行當前實施的公司信息訪問控制和安全協議。第四，沒有大語言模型帶來的IP或數據洩露風險。重要的是，它沒有幻覺。

So if the system doesn't know an answer, it doesn't fabricate it, which is clearly unacceptable for any commercial or serious government applications. After releasing the product in March, we rapidly closed 3 generative AI applications in the quarter with large enterprises, including Georgia Pacific, Flint Hills Resources and the U.S. Department of Defense Missile Defense Agency.

因此，如果系統不知道答案，它就不會偽造答案，這對於任何商業或嚴肅的政府應用來說顯然是不可接受的。在 3 月份發布產品後，我們在本季度迅速關閉了與大型企業的 3 個生成 AI 應用程序，包括 Georgia Pacific、Flint Hills Resources 和美國國防部導彈防禦局。

We expect these applications to be live during this current quarter. We are currently working quite a substantial pipeline of additional C3 Generative AI opportunities with large corporations. The C3 AI generation is now available today available on both AWS Marketplace and the Google Cloud Marketplace. It is difficult to estimate the size of the addressable market for these generative AI solutions but it appears to be extraordinarily large.

我們預計這些應用程序將在本季度上線。我們目前正在與大公司合作大量額外的 C3 生成 AI 機會。 C3 AI 代現已在 AWS Marketplace 和 Google Cloud Marketplace 上發售。很難估計這些生成式 AI 解決方案的潛在市場規模，但它似乎非常大。

We saw a lot of momentum last year and in the fourth quarter with the -- our U.S. federal business. The U.S. federal sector represented 29% of our bookings in fiscal year '23 and continues to show significant strength. Our predictive maintenance solution, predictive -- our predictive analytics and decision assistant, also known as PANDA, has been in production used for several years at the United States Air Force Rapid Sustainment Office. And last quarter, it was selected as the system of record for all predictive maintenance for virtually all United States Air Force assets, okay? This important designation expands our opportunity really substantially in the U.S. Air Force and their services.

我們在去年和第四季度看到了很大的勢頭——我們的美國聯邦業務。在 23 財年，美國聯邦部門占我們預訂量的 29%，並且繼續表現出顯著的實力。我們的預測性維護解決方案，預測性——我們的預測分析和決策助手，也稱為 PANDA，已在美國空軍快速維持辦公室投入生產使用多年。上個季度，它被選為幾乎所有美國空軍資產的所有預測性維護的記錄系統，好嗎？這一重要任命大大擴展了我們在美國空軍及其服務中的機會。

Let's talk about guidance. C3 AI has a consistent and solid track record of meeting or exceeding guidance as we have done in every quarter since we've been public, okay? And we are -- at this time, we are not inclined to pat on the table regarding guidance.

讓我們談談指導。自上市以來，C3 AI 在每個季度都有達到或超過指導的一致而可靠的記錄，好嗎？而我們——此時，我們不傾向於拍拍指導。

In general, we feel comfortable with the expectations that the sell-side analysts have set for the coming year, and we are not inclined to change those expectations at this time. For fiscal -- for Q1 fiscal year '24, we see revenue in the range of $70 million to $72.5 million. For the full year, fiscal year 2024, we expect revenue to be in the range between $295 million and $320 million. As it relates to non-GAAP loss from operations, we expect to fall between $25 million, $30 million in Q1 and $50 million to $70 million for the year.

總的來說，我們對賣方分析師為來年設定的預期感到滿意，我們目前不打算改變這些預期。對於財政——24 財年第一季度，我們看到收入在 7000 萬美元到 7250 萬美元之間。對於全年，即 2024 財年，我們預計收入將在 2.95 億美元至 3.2 億美元之間。由於它與非 GAAP 運營虧損有關，我們預計第一季度將下降 2500 萬美元至 3000 萬美元，全年將下降 5000 萬至 7000 萬美元。

As we begin fiscal year '24, C3 AI has never been better positioned. The addressable market is large and expanding. The overall business environment for enterprise AI is strong, and C3 AI is front and center in the minds of CEOs and government leaders. Our balance sheet is strong and with over $812 million in cash and cash equivalents, we are in a great position to expand market share.

在我們開始 24 財年之際，C3 AI 處於前所未有的有利地位。可尋址市場很大，而且還在不斷擴大。企業 AI 的整體商業環境很強，C3 AI 是 CEO 和政府領導人心目中的前沿和中心。我們的資產負債表強勁，擁有超過 8.12 億美元的現金和現金等價物，我們處於擴大市場份額的有利位置。

As the dynamics of the enterprise AI market are developing so rapidly, we thought it appropriate to host a mid-quarter Investor Day in New York City on June 27. We will provide -- at that time, we will provide C3 AI investors a company update, additional information about our product road map, product demonstrations direct access to the C3 AI executive team, updates on our partner ecosystem, C3 Generative AI demonstrations and additional company developing news.

由於企業 AI 市場的動態發展如此迅速，我們認為 6 月 27 日在紐約市舉辦季度中期投資者日是合適的。我們將提供 - 屆時，我們將為 C3 AI 投資者提供一家公司更新、有關我們產品路線圖的其他信息、直接訪問 C3 AI 執行團隊的產品演示、我們合作夥伴生態系統的更新、C3 生成式 AI 演示和其他公司開發新聞。

We hope you can attend either in person or online. And that Investor Day event will be available to view online live, okay, for all investors via webcast.

我們希望您可以親自或在線參加。所有投資者都可以通過網絡直播在線觀看投資者日活動。

I will now turn this call over to my colleague, Juho Parkkinen, Chief Financial Officer, for additional details regarding our financial results. Juho?

我現在將把這個電話轉給我的同事，首席財務官 Juho Parkkinen，了解有關我們財務業績的更多詳細信息。巨虎？

Thank you, Tom. I will now provide a recap of our financial results, add some color to the drivers of our financials, provide more detail on our first quarter and full year 2024 guidance and I will conclude with some additional color related to the consumption-based revenue model we introduced 3 quarters ago. All figures will be discussed on a non-GAAP basis, unless otherwise noted.

謝謝你，湯姆。我現在將回顧我們的財務業績，為我們的財務驅動因素添加一些色彩，提供有關我們第一季度和 2024 年全年指導的更多細節，我將以與我們基於消費的收入模型相關的一些額外色彩作為結尾。 3 個季度前推出。除非另有說明，否則所有數字都將在非 GAAP 基礎上進行討論。

Overall, the business activity is higher than we have ever seen. Our sales reps are more engaged. There are more opportunities, they're working on and there are more interest from our prospects. During Q4, our ability to close agreements was more consistent throughout the quarter compared to prior quarters this fiscal year. We ended the fourth quarter with a total revenue of $72.4 million, of which, subscription revenue was 78.5%. As we discussed last quarter, we expected professional services would be within our historical range of 10% to 20% with our actual professional services coming in at 21.5% of the mix. Gross profit for the fourth quarter was $53.9 million, and our gross margin was 74.4%. We generated $27.1 million in positive operating cash flow and $16.3 million in free cash flow for the quarter.

總體而言，商業活動高於我們以往所見。我們的銷售代表更加投入。有更多的機會，他們正在努力，我們的前景也有更多的興趣。在第四季度，與本財年的前幾個季度相比，我們在整個季度達成協議的能力更加一致。截至第四季度，我們的總收入為 7240 萬美元，其中訂閱收入佔 78.5%。正如我們上個季度所討論的那樣，我們預計專業服務將在我們 10% 至 20% 的歷史範圍內，而我們的實際專業服務將佔組合的 21.5%。第四季度的毛利潤為 5390 萬美元，毛利率為 74.4%。本季度我們產生了 2710 萬美元的正經營現金流和 1630 萬美元的自由現金流。

As mentioned during the prior updates, we have a short-term pressure on our gross margins due to a higher mix of targets, which carry a higher cost of revenue than production deployment. Operating loss of $23.5 million was improved due to more rigorous expense management. As a reminder though, the fourth quarter is when we host our C3 AI transform customer events, as such, our marketing expenses ramped up to support the successful execution of that event.

正如在之前的更新中提到的，由於更高的目標組合，我們的毛利率面臨短期壓力，這比生產部署帶來更高的收入成本。由於更嚴格的費用管理，運營虧損減少了 2350 萬美元。不過提醒一下，第四季度是我們舉辦 C3 AI 轉型客戶活動的時候，因此，我們的營銷費用增加以支持該活動的成功執行。

Operating loss margin was 32.5% in Q4 where the sequential increase was driven by our annual customer conference. For the full year fiscal 2023, our revenue was $266.8 million, an increase of 5.6% from fiscal 2022. Non-GAAP loss from operations was $68.1 million and free cash flow was negative $187 million. Our gross margin for the year was 77%. Our subscription revenue was 86% of total revenue compared to 82% in fiscal '22. We ended fiscal '23 with $812.4 million in cash and investments.

第四季度的營業虧損率為 32.5%，環比增長是由我們的年度客戶會議推動的。 2023 財年全年，我們的收入為 2.668 億美元，比 2022 財年增長 5.6%。非 GAAP 運營虧損為 6810 萬美元，自由現金流為負 1.87 億美元。我們當年的毛利率為 77%。我們的訂閱收入佔總收入的 86%，而 22 財年這一比例為 82%。我們以 8.124 億美元的現金和投資結束了 23 財年。

At the end of Q4, our accounts receivable, including unbilled receivables, was $134.6 million. Unbilled receivables at quarter end was $77.6 million, inclusive of $70.7 million related to Baker Hughes. During the quarter, we collected from Baker Hughes nearly $35 million.

第四季度末，我們的應收賬款（包括未開票的應收賬款）為 1.346 億美元。季度末未開票應收賬款為 7760 萬美元，其中包括與貝克休斯相關的 7070 萬美元。本季度，我們從 Baker Hughes 收取了近 3500 萬美元。

The general health of our accounts receivable is excellent. 76% of our receivables were current or less than 30 days past due. For the entirety of FY '23, our bad debt expense was approximately $300,000.

我們的應收賬款總體狀況良好。我們 76% 的應收賬款是流動的或逾期不到 30 天。在整個 23 財年，我們的壞賬費用約為 300,000 美元。

Now turning to RPO and bookings. As consumption-based go-to-market model continues to pick up. RPO is a less important indicator of future performance. We reported GAAP RPO of $381.4 million down 20% from last year, which is expected as a result of the transition to consumption-based pricing. Current GAAP RPO of $186.3 million is up 9.8% from last year-end and up 5.7% on a sequential basis. We continue to see positive trends in target bookings diversity as we have sold pilots to a broad range of 9 different industries during the quarter.

現在轉向 RPO 和預訂。隨著以消費為基礎的上市模式繼續興起。 RPO 是一個不太重要的未來績效指標。我們報告的 GAAP RPO 為 3.814 億美元，比去年下降 20%，預計這是向基於消費的定價過渡的結果。目前的 GAAP RPO 為 1.863 億美元，比去年年底增長 9.8%，環比增長 5.7%。我們繼續看到目標預訂多樣性的積極趨勢，因為我們在本季度向 9 個不同行業出售了飛行員。

Regarding our outlook for fiscal '24. We're guiding Q1 revenue to range between $70 million to $72.5 million. For the full year 2024, we expect revenue to range between $295 million and $320 million. As it relates to the full year, we finished the third quarter of our transition under the consumption pricing model. As a recent remodel, we expect flatness and somewhat of a decline in revenue during the transition with an acceleration as consumption starts to have a meaningful portion of our in-quarter revenue. As such, we expect the second half of FY '24 to have higher growth rates on a sequential basis than the first half.

關於我們對 24 財年的展望。我們指導第一季度收入在 7000 萬美元到 7250 萬美元之間。對於 2024 年全年，我們預計收入將在 2.95 億美元至 3.2 億美元之間。就全年而言，我們在消費定價模式下完成了第三季度的轉型。作為最近的改造，我們預計隨著消費開始在我們的季度收入中佔據重要部分，過渡期間收入將持平並有所下降。因此，我們預計 24 財年下半年的環比增長率將高於上半年。

We expect our non-GAAP loss from operations to range between $25 million and $30 million for Q1, and for full fiscal '24, we expect the non-GAAP loss from operations between $50 million and $75 million. As a reminder, we expect to be non-GAAP profitable for Q4 '24 and beyond. And as it relates to full fiscal '24, we are guiding to a range in operating loss due to the potential investments we made for C3 Generative AI applications. We expect our cash and investments to be at its lowest at around $700 million during fiscal '24.

我們預計第一季度的非 GAAP 運營虧損將在 2500 萬至 3000 萬美元之間，而對於整個 24 財年，我們預計非 GAAP 運營虧損將在 5000 萬至 7500 萬美元之間。提醒一下，我們預計 24 年第四季度及以後將實現非 GAAP 盈利。由於它涉及整個 24 財年，由於我們對 C3 生成 AI 應用程序的潛在投資，我們正在指導一系列的運營損失。我們預計我們的現金和投資在 24 財年將處於最低水平，約為 7 億美元。

Turning to customer metrics. Historically, we have provided a quarterly customer count estimate as a proxy for the adoption of our products and solutions. However, due to the complexity of our contractual and pricing structures and the involvement of resellers we believe comparing customer accounts from quarter-to-quarter based on our current methodology, we believe -- apologies, customer accounts from quarter-to-quarter based on our current methodology does not fully convey the acceptance and adoption of our products and solutions. To help address this, we retained an external Big 4 consulting firm to update our current customer accounts methodology consistent with best practices to be consistent, systematic and auditable.

轉向客戶指標。過去，我們提供季度客戶數量估算作為採用我們產品和解決方案的指標。然而，由於我們的合同和定價結構的複雜性以及經銷商的參與，我們認為根據我們目前的方法比較每個季度的客戶賬戶，我們相信 - 抱歉，每個季度的客戶賬戶基於我們目前的方法並不能完全表達對我們產品和解決方案的接受和採用。為了幫助解決這個問題，我們聘請了一家外部四大諮詢公司來更新我們當前的客戶賬戶方法，使其符合最佳實踐，以保持一致、系統和可審計。

As a result of that review and adoption of those recommendations we believe a metric that demonstrates contracted use cases that our customers are using our solutions to solve would provide a more meaningful understanding of the product adoption. This is defined as customer engagement. The customer engagement increased from 247 to 287 comparing Q3 '23 to Q4 '23. Our traditional customer account metric went from 236 to 244 for the same period. There would be additional detail included in the supplement, which is available on our website.

作為審查和採納這些建議的結果，我們相信一個指標可以證明我們的客戶正在使用我們的解決方案解決的合同用例將提供對產品採用的更有意義的理解。這被定義為客戶參與。與 23 年第 3 季度和 23 年第 4 季度相比，客戶參與度從 247 增加到 287。同期，我們的傳統客戶帳戶指標從 236 增加到 244。補充資料中將包含更多詳細信息，可在我們的網站上獲取。

We are on track with our plan for profitability for Q4 '24 and expect to have cash positive quarter starting Q4 '24 on a consistent go-forward basis. The entire executive team is managing the business to a detailed budget on our plan for profitability. We are expecting to invest aggressively to generate AI initiatives during the first half of the year, which is reflected in the operating income guidance. As it relates to the model assumptions that we provided 3 quarters ago for our consumption-based pricing, our preliminary analysis of the actual results suggest we are on that model. Overall, we're very excited about the business momentum as we start FY '24.

我們正按計劃執行 24 年第四季度的盈利計劃，並預計從 24 年第四季度開始，在持續向前的基礎上將有現金正季度。整個執行團隊正在根據我們的盈利計劃制定詳細的預算來管理業務。我們預計在今年上半年積極投資以產生人工智能計劃，這反映在營業收入指導中。由於它與我們 3 個季度前為基於消費的定價提供的模型假設相關，我們對實際結果的初步分析表明我們使用的是該模型。總體而言，我們對 24 財年開始時的業務勢頭感到非常興奮。

As a go-forward KPI for the investing community to assess our performance, we believe good KPIs to focus are the number of pilots started during the quarter, the conversion of those pilots to production; and finally, the actual vCPU consumption fees generated.

作為投資界評估我們業績的前瞻性 KPI，我們認為值得關注的良好 KPI 是本季度開始的試點數量，這些試點向生產的轉化；最後，實際產生的 vCPU 消耗費用。

With that, I would like to open this up for questions. Operator?

有了這個，我想打開這個問題。操作員？

(Operator Instructions) Our first question comes from the line of Kingsley Crane of Canaccord.

（操作員說明）我們的第一個問題來自 Canaccord 的 Kingsley Crane。

So Tom, you said that sales cycles were down to 3.7 months from 5 months last year. Why do you think that is? Is this entirely due to the consumption model? How much of this is due to general excitement around the potential in the space and even potentially increase sales force productivity?

所以湯姆，你說銷售週期從去年的 5 個月下降到 3.7 個月。你認為這是為什麼？這完全是消費模式造成的嗎？其中有多少是由於對該領域潛力的普遍興奮，甚至可能提高銷售人員的生產力？

No, I think -- thanks, Kingsley. I think it's all of that. I mean, clearly, AI is on everybody's mind, the consumption-based pricing model that we have makes it much easier to adopt our technology. I mean in the old days, 1 and 2 years ago to do business with us was $5 million, $10 million, $20 million, $50 million to open the door. And now the transaction is pretty much -- we're bringing the app live in 6 months or $0.5 million. If you like it, keep it and paid $0.55 per CPU hour -- vCPU hour, so we're pretty easy to do business with. And so we're seeing the number of transactions increased dramatically as we'd expect.

不，我想——謝謝，金斯利。我認為就是這些。我的意思是，很明顯，人工智能在每個人的腦海中，我們擁有的基於消費的定價模型使得採用我們的技術變得更加容易。我的意思是在過去，1 年和 2 年前與我們做生意是 500 萬美元、1000 萬美元、2000 萬美元、5000 萬美元開門。現在這筆交易差不多了——我們將在 6 個月或 50 萬美元內推出該應用程序。如果您喜歡它，請保留它並支付每 CPU 小時 0.55 美元 -- vCPU 小時，所以我們很容易做生意。因此，我們看到交易數量如我們預期的那樣急劇增加。

The ease of contracting with us. As you know, we have largely reconstituted the sales organization in the last 1.5 years to a sales team that is candidly much more productive and effective than our other sales organizations. So I think all of those are contributing to increased pipeline, increased business, increased business activity by which we're quite optimistic.

與我們簽訂合同的便利性。如您所知，在過去的 1.5 年裡，我們在很大程度上重組了銷售組織，使其成為一支比我們其他銷售組織更有生產力和效率的銷售團隊。所以我認為所有這些都有助於增加管道、增加業務、增加我們非常樂觀的業務活動。

That's really helpful. And then 1 for Juho. When I think about the timing of the transition. So if it is the case that the vast majority of existing customers are not necessarily migrating to the consumption model, how should we think about the contribution of consumption over time and particularly in the back half? Because I think that you said revenue could accelerate as consumption increases in mix?

這真的很有幫助。然後 1 給 Juho。當我考慮過渡的時機時。那麼，如果絕大多數現有客戶都不一定遷移到消費模式，我們應該如何考慮消費隨著時間的推移，特別是後半部分的貢獻？因為我認為你說收入會隨著消費的增加而加速增長？

Yes, Kingsley, thanks for that question. So that's exactly as we sign and initiate more pilots within the quarter. The pilots are generally 2 quarters long, and then you start to see the consumption revenue kick in. As we finished the quarter with 19 pilots last quarter, we had a good increase in pilots with 17 pilots as well. You can start seeing those layer on to the revenue by Q3 and Q4 of this fiscal year.

是的，金斯利，謝謝你提出這個問題。所以這正是我們在本季度簽署並啟動更多試點的時候。試點通常持續 2 個季度，然後你會開始看到消費收入開始增加。上個季度我們以 19 名飛行員結束了這個季度，我們的飛行員也有了很好的增長，也有 17 名飛行員。您可以在本財年的第三季度和第四季度開始看到這些收入層。

Now to your point about renewals, we do expect our existing customers with the large enterprise agreements to continue to remain on those types of agreement structures, but you will see the RPO trickle down as these contracts enter into renewal phase, and then we would expect to see a pickup as they renew.

現在關於續約的問題，我們確實希望與大型企業協議的現有客戶繼續保留這些類型的協議結構，但是隨著這些合同進入續約階段，您會看到 RPO 逐漸下降，然後我們預計在他們更新時看到皮卡。

Our next question comes from the line of Pat Walravens of JMP Securities.

我們的下一個問題來自 JMP Securities 的 Pat Walravens。

Tom, can you talk some more about the opportunity with National Security and the Department of Defense? And then also, you said something I thought was interesting about a version of Generative AI that doesn't hallucinate, if you could maybe comment a little more on what hallucinating is? And how you prevent it from doing that, I think that would be really interesting?

湯姆，你能再談談與國家安全部和國防部的機會嗎？然後，你還說了一些我認為很有趣的關於不會產生幻覺的生成 AI 版本的內容，如果你能再多評論一下幻覺是什麼？你如何阻止它這樣做，我認為這真的很有趣？

DoD, well, Pat, you asked kind of many times about the -- we have 2 basically authorities to operate contract vehicles one is for $100 million and one is $1.5 billion in DoD that are associated. It could be applicable to what we're doing at RSO, that was the Rapid Sustainment Office and the predictive maintenance application that we're doing for the United States Air Force for F-15, F-16, F-18, F-35, KC-135, et cetera.

國防部，好吧，帕特，你問了很多次關於 - 我們有 2 個基本上授權運營合同車輛，一個是 1 億美元，一個是 15 億美元的相關國防部。它可能適用於我們在 RSO 所做的工作，即快速維持辦公室和我們正在為美國空軍為 F-15、F-16、F-18、F- 35、KC-135 等。

And what we made a proposal to the Secretary of the Air Force to take that into full production for all the aircraft in the Air Force, which is 5,000. I think the proposal would have increased aircraft availability for the Air Force by 25%. And I think decrease their cost of maintenance and readiness by about $6 billion. So he considered that as did his Chief of Staff, General Brown, and they went off on their own for a few months why you were asking the questions, and we didn't have the answers and these guys go into their star chamber the way they do. What they came out with was not -- was a selection of C3 as the standard -- as the system of record, not only for aircraft in the United States Air Force, but for all AI-based -- all predicted maintenance, okay, in the United States Air Force for all assets. So this is genuinely a big deal. Okay.

我們向空軍部長提出了一項建議，即全面生產空軍所有飛機，即 5,000 架。我認為該提案將使空軍的飛機可用性增加 25%。我認為可以將他們的維護和準備成本降低約 60 億美元。所以他和他的參謀長佈朗將軍一樣認為，他們自己離開了幾個月，為什麼你問這些問題，我們沒有答案，這些人進入了他們的星室他們是這樣。他們得出的結果不是——選擇 C3 作為標準——作為記錄系統，不僅適用於美國空軍的飛機，而且適用於所有基於人工智能的——所有預測維護，好吧，在美國空軍的所有資產。所以這真的很重要。好的。

Now we have the opportunity to make this a line item in the budget. So this is -- it's hard to over describe the impact of this or overestimate the impact of this. And then not only do we have it in Air Force, we can talk now to other services like Army and the Navy and the Marines and the National Guard, what have you. So this is a big one.

現在我們有機會將其作為預算中的一個項目。所以這是 - 很難過度描述它的影響或高估它的影響。然後我們不僅在空軍擁有它，我們現在可以與陸軍、海軍、海軍陸戰隊和國民警衛隊等其他部門交談，你有什麼。所以這是一個大問題。

The second one has to do with generative AI. So one of the problems with Generative AI is the -- is you're limited to the number of data sources that you can use with these large language typically is text, HTML and sometimes code. And the large language model will interact directly with the data. But one of the problems is you get kind of random answers. Every time you ask the question, you get a different answer. If 2 people have an question, they get a different answer.

第二個與生成人工智能有關。因此，生成式 AI 的問題之一是——您可以使用這些大型語言的數據源數量有限，通常是文本、HTML，有時是代碼。並且大型語言模型將直接與數據進行交互。但問題之一是你得到的是隨機答案。每次你問這個問題，你都會得到不同的答案。如果 2 個人有問題，他們會得到不同的答案。

And the -- there's no traceability. It doesn't tell you where the answer came from, okay? And finally, if it doesn't know the answer, it makes 1 up. This is what they call hallucination. So it doesn't know it just kind of wings it makes up an answer.

而且 - 沒有可追溯性。它不會告訴你答案來自哪裡，好嗎？最後，如果它不知道答案，它會補上 1。這就是他們所說的幻覺。所以它不知道它只是一種翅膀，它構成了一個答案。

So we've leveraged -- we're using the entire C3 platform. And the way that we do that is we incorporate -- as you, I think, all know, we're very good at aggregating enterprise data, extraprise data, code, images, text, sensor data, what have you, into a unified federated image. When we do that, those data are read by a deep learning model and they happen to be stored in a vector database that we have a kind of a firewall between that and the large language model. Now our customer uses any language model they want, be it ChatGPT, be it PaLM, be it Bard, be it FLAN-T5, whatever comes along next.

所以我們利用了——我們正在使用整個 C3 平台。我們這樣做的方式是我們整合——我想你們都知道，我們非常擅長將企業數據、外部數據、代碼、圖像、文本、傳感器數據，你擁有的，整合到一個統一的系統中。聯合圖像。當我們這樣做時，這些數據被深度學習模型讀取，它們恰好存儲在矢量數據庫中，我們在矢量數據庫和大型語言模型之間有一種防火牆。現在我們的客戶可以使用他們想要的任何語言模型，無論是 ChatGPT、PaLM、Bard、FLAN-T5 還是接下來出現的任何語言模型。

Now we built a firewall within the large language model and the data. So it will -- every time -- I mean what's really -- every time you ask the question, it will give you the same answer. Okay, if 2 people ask the same question and they have the authority, they will both get the same answer every time. Associated with the answer, it provides you traceability to see if they click on it, you can see exactly where the data can come from, okay? And very importantly, there's no risk of LLM cause data exfiltration, see Samsung for details where they find out that all of their proprietary information is not published on the Internet, okay?

現在我們在大型語言模型和數據中構建了防火牆。所以它會——每次——我的意思是真正的——每次你問這個問題，它都會給你同樣的答案。好的，如果 2 個人問同樣的問題並且他們有權限，他們每次都會得到相同的答案。與答案相關聯，它為您提供可追溯性，看看他們是否點擊它，您可以準確地看到數據的來源，好嗎？非常重要的是，沒有 LLM 導致數據洩露的風險，詳情請參閱三星，他們發現他們所有的專有信息都沒有在 Internet 上發布，好嗎？

And finally, there's no risk of LLM caused hallucination. It doesn't know the answer, it tells you, I don't know the answer rather than making one up. So for these, you think would be kind of table stakes, and they are table stakes for any large commercial or government installation, and this is something that really distinguishes the C3 Generative offering. And one of the reasons that we're seeing very high levels of interest.

最後，沒有 LLM 引起幻覺的風險。它不知道答案，它告訴你，我不知道答案而不是編造一個。因此，對於這些，您認為是一種籌碼，它們是任何大型商業或政府設施的籌碼，這是 C3 Generative 產品真正與眾不同的地方。這也是我們看到非常高的興趣的原因之一。

Our next question comes from the line of Sanjit Singh of Morgan Stanley. Again, our next question comes from the line of Sanjit Singh at Morgan Stanley.

我們的下一個問題來自摩根士丹利的 Sanjit Singh。同樣，我們的下一個問題來自摩根士丹利的 Sanjit Singh。

I appreciate you guys squeezing me in for the question. Tom, earlier this week, you guys announced had a press release about the C3 Generative AI suite being available in the Amazon Marketplace. And it got me thinking about what the sales motion going forward is going to look like? As you sort of mentioned, Generative AI is permeating the boardroom, the C-suite in a pretty substantial way. And when we look at sort of converting this interest into deals and ultimately revenue. How much of this is going to be like flywheel kind of self-service consumption-based marketplace type deals versus you working with partners to get more consultative approach as it's helping these large enterprise customers sort of navigate the world of generative AI actually deliver value?

感謝你們邀請我來回答這個問題。 Tom，本週早些時候，你們宣布了一份關於 C3 Generative AI 套件在 Amazon Marketplace 上可用的新聞稿。這讓我開始思考未來的銷售動議會是什麼樣子？正如您提到的那樣，生成式人工智能正在以相當大的方式滲透到董事會和最高管理層。當我們考慮將這種興趣轉化為交易並最終轉化為收入時。這其中有多少類似於飛輪式的基於消費的自助式市場類型交易，而不是你與合作夥伴合作以獲得更多諮詢方法，因為它正在幫助這些大型企業客戶在某種程度上駕馭生成人工智能的世界，真正創造價值？

Great question, Sanjit. So our first 3 engagements that are valid now will be -- our organization is the order of $100 billion or greater in revenue, okay, and have -- we'll bring the application live 12 weeks. We're not doing it -- and we have like 3 people on the project. So it's pretty straightforward.

好問題，桑吉特。因此，我們現在有效的前 3 個約定將是——我們的組織的收入約為 1000 億美元或更多，好的，並且已經——我們將在 12 週內將應用程序上線。我們沒有這樣做——我們有大約 3 個人參與該項目。所以這很簡單。

Now the issue of going from, say, 6 customers to 60 customers to 100 customers, it's pretty straightforward. We know how to do that, okay? The real key is, okay, in terms of blowing the doors off this thing, can we go from 6 customers to 60 customers to 6,000. So for 6,000, now we have to leverage these channels like the AWS marketplace where the product is available today, the Google marketplace where they're available today. But in terms of usability, it needs to be with the Apple iPhone. You open the box, you take the cellophane off, you turn it on and it works.

現在，從 6 個客戶到 60 個客戶再到 100 個客戶的問題非常簡單。我們知道該怎麼做，好嗎？真正的關鍵是，好吧，就吹掉這件事的大門而言，我們能否從 6 個客戶增加到 60 個客戶再到 6,000 個。因此，對於 6,000 人，現在我們必須利用這些渠道，例如今天提供產品的 AWS 市場，以及今天提供產品的 Google 市場。但就可用性而言，它需要與 Apple iPhone 搭配使用。打開盒子，取下玻璃紙，打開它，它就可以使用了。

And so now we're -- the next generation -- the next -- the really serious development work that we're doing now on that product kind of relates to really product design, okay, and making it like an Apple product, you open it up, you turn it on and it works. And so that's the challenge that's before us. I think we're up to it, okay? And if we're able to hit that note, hold on to your stock.

所以現在我們 - 下一代 - 下一代 - 我們現在正在做的真正嚴肅的產品開發工作與真正的產品設計有關，好吧，讓它像蘋果產品一樣，你打開它，你打開它，它就可以工作了。這就是擺在我們面前的挑戰。我想我們可以做到，好嗎？如果我們能夠做到這一點，請持有您的股票。

I appreciate the color, Tom. And then maybe 1 follow-up. Maybe this is for Juho and Tom as well. And it sort of relates to the guidance for the full year. I'm trying to contextualize like what's really driving the guidance for next year? Because we're coming off a year, fiscal year '21, I think you guys grew north of 30%, 33%, 34%. And this past year, you guys grew sort of mid-single digits. The initial guidance calls for growth sort of mid-teens at the midpoint sort of 20% at the high end. And I want to understand, like is the acceleration you're seeing a function that you're coming off a tougher year where you had -- spending environment is more difficult, sales reorg, those types of things versus Generative AI really coming online in fiscal year '24. And so is there any way you can sort of attribute those 2 things between sort of coming off of a tougher year versus the demand that you're seeing in pilots out in the field?

我喜歡這種顏色，湯姆。然後可能有 1 次跟進。也許這也適用於 Juho 和 Tom。這在某種程度上與全年的指導有關。我正在嘗試像真正推動明年指導的內容一樣進行背景化？因為我們即將結束一年，21 財年，我認為你們增長了 30%、33%、34%。在過去的一年裡，你們增長了中個位數。最初的指導要求在高端的中點增長 20%。我想知道，就像你看到的加速一樣，你正在度過一個艱難的一年——支出環境更加困難，銷售重組，這些類型的東西與生成人工智能真正上線財政年度'24。那麼，您有什麼方法可以將這兩件事歸因於艱難的一年與您在現場飛行員中看到的需求之間的關係？

Sanjit, let me address the premise, okay? Before we all bring our hands about tougher year, tougher year tougher year. I think we got that in 4 times in the call for all the audience. Okay, let's remember, okay? When we are now the transition to consumption-based pricing, we made it very clear that this was going to have a short and midterm, okay, negative effect on revenue growth. It's actually met. Anybody who knows how to use a spreadsheet can figure this out. If we're closing $0.5 million deals instead of $10 million, $20 million, $30 million, $40 million, $50 million deals, the short-term impact on revenue is dampened revenue growth. So I'm not certain that's so tough. Okay, that is basically we're actually getting exactly the plan that we set. So this thing is exactly on track.

Sanjit，讓我談談前提，好嗎？在我們所有人開始迎接更艱難的一年之前，更艱難的一年更艱難的一年。我想我們在面向所有聽眾的電話會議中進行了 4 次。好吧，讓我們記住，好嗎？當我們現在向基於消費的定價過渡時，我們非常清楚這將對收入增長產生短期和中期的負面影響。其實是遇到了。任何知道如何使用電子表格的人都可以解決這個問題。如果我們要完成 50 萬美元的交易，而不是 1000 萬美元、2000 萬美元、3000 萬美元、4000 萬美元、5000 萬美元的交易，那麼對收入的短期影響就是收入增長受到抑制。所以我不確定這是否如此艱難。好的，這基本上就是我們實際上得到了我們設定的計劃。所以這件事完全走上了正軌。

Now when you run this 3-year a (inaudible) spreadsheet model and you hit the carriage return, okay, and you run it out a few years -- a few quarters out there, you can do the math and you know what happens. But I'm not -- so I think we're exactly on plan with what we did. We made the investment. I think it was a great decision. It was a good investment. And now in fiscal year '24 and '25, we're going to yield the returns from that investment.

現在，當你運行這個 3 年的（聽不清）電子表格模型時，你點擊了回車，好吧，你運行了幾年——幾個季度，你可以做數學，你知道會發生什麼。但我不是——所以我認為我們所做的事情完全符合計劃。我們進行了投資。我認為這是一個偉大的決定。這是一項很好的投資。現在，在 24 和 25 財年，我們將從該投資中獲得回報。

Our next question comes from the line of John Katsingris of Wedbush.

我們的下一個問題來自 Wedbush 的 John Katsingris。

John on for Dan Ives. So given the increased diversity seen, I guess, across industries served, how have you seen these use cases develop? And how do you see them playing out in the future?

約翰換下丹·艾夫斯。因此，鑑於所看到的多樣性增加，我猜，跨行業服務，你如何看待這些用例的發展？您如何看待他們未來的表現？

Great question, John. Right now, I mean, in terms of applying AI to enterprise we're in first half of the first inning and the first guys to do that, okay. So this is an embryotic market. I mean, where we're seeing the biggest uptake in media. First, it was in the SmartGrid. Okay. Why the SmartGrid because they had invested $2 trillion to upgrade and create infrastructure globally to make all the devices in the SmartGrid, remotely machine addressable, a huge IoT constellation. So that's where we saw it first.

好問題，約翰。現在，我的意思是，就將 AI 應用於企業而言，我們處於第一局的前半段，並且是第一批這樣做的人，好吧。所以這是一個胚胎市場。我的意思是，我們在媒體上看到了最大的吸收。首先，它在 SmartGrid 中。好的。為什麼選擇 SmartGrid，因為他們已投資 2 萬億美元在全球範圍內升級和創建基礎設施，使 SmartGrid 中的所有設備都可以遠程機器尋址，成為一個巨大的物聯網星座。這就是我們首先看到它的地方。

The next large -- what we're seeing in the past year, the largest market is in AI reliability, basically predictive maintenance. So they can move the military, they called readiness, okay, or in the private sector, they call reliability. So AI-based predictive maintenance is the largest segment today. How will this evolve? I mean it's clear we will be applying AI to all business processes, production optimization, demand forecasting, supply chain risk okay, stochastic optimization of the supply chain, CRM. I think there is no aspect of business operations that will not be or -- and medicine, okay, and research and the science and literature and entertainment that will not be accelerated by the use of AI. So we're just going to have to -- we're along for the ride and we're going to see where this goes in the next few years and stay on the balls of our feet as it develops, but it is a rocket ship.

下一個大市場——我們在過去一年看到的，最大的市場是人工智能可靠性，基本上是預測性維護。所以他們可以調動軍隊，他們稱之為準備就緒，好吧，或者在私營部門，他們稱之為可靠性。因此，基於人工智能的預測性維護是當今最大的部分。這將如何演變？我的意思是很明顯，我們將把 AI 應用於所有業務流程、生產優化、需求預測、供應鏈風險管理、供應鏈隨機優化、CRM。我認為商業運營的任何方面都不會或 - 醫學、好吧、研究、科學、文學和娛樂都不會通過使用 AI 來加速。因此，我們將不得不——我們一路順風，我們將看到未來幾年的發展方向，並隨著它的發展保持警惕，但它是一枚火箭船。

Our next question comes from the line of Mike Cikos of Needham Company.

我們的下一個問題來自 Needham 公司的 Mike Cikos。

Maybe the first would be going to Juho. So I know that you guys have cited the 43 deals you closed this quarter, 19 of those are pilots. Can you further refine that for us? And maybe it's just the classifications or names we're using for this. But like how many of those pilots are purely consumption-based versus maybe pilots that are still coming in under the old pricing model?

也許第一個會去 Juho。所以我知道你們引用了本季度完成的 43 筆交易，其中 19 筆是試點交易。你能為我們進一步完善嗎？也許這只是我們為此使用的分類或名稱。但是，這些試點中有多少是純粹基於消費的，而可能仍在舊定價模式下進行的試點呢？

Mike, these are all -- these would all follow the new consumption-based approach. These are not under the old model at all.

邁克，這些都是——這些都將遵循新的基於消費的方法。這些根本不在舊模型之下。

Okay. And so I guess the follow-up that I have on that is with the 19 deals that are consumption based, and I know that you guys have pulled -- I'm sorry, 19 pilots that you guys closed or initiated that are a consumption base this quarter and the other pilots that we've decided in previous quarters. Do we have a feel for how many of these pilots have now converted to production? And do we have a gauge for what the vCPU is for those consumption deals once they move into production?

好的。所以我想我的後續行動是 19 項基於消費的交易，我知道你們已經取消了——對不起，你們關閉或發起的 19 項試點是消費本季度的基礎以及我們在前幾個季度決定的其他試點項目。我們是否知道這些試點中有多少現在已經轉為生產？一旦這些消費交易投入生產，我們是否有衡量 vCPU 的標準？

That's a great question. So Michael, on the first quarter, we announced this would have been Q2, which obviously, you take 6 months from that, we get towards the end of Q4. So we are very early in that in the conversions. We are standing by with the model assumptions, i.e., whatever we provided 3 quarters ago where it is, each pilot is expected at 70% likelihood to convert into a follow-on consumption deal. But I would say that the first quarter before consumptions, we really will start seeing more of that this quarter since it was late in Q2 as we entered into those original pilot arrangements.

這是一個很好的問題。所以邁克爾，在第一季度，我們宣布這將是第二季度，顯然，你需要 6 個月的時間，我們將在第四季度末結束。所以我們在轉換中很早就開始了。我們支持模型假設，即無論我們在 3 個季度前提供的是什麼，預計每個試點都有 70% 的可能性轉化為後續消費交易。但我要說的是，在消費之前的第一季度，我們真的會在本季度開始看到更多的消費，因為我們在第二季度末進入了那些最初的試點安排。

Understood. Understood on that. And then just 1 quick follow-up, if I could. But I wanted to add just on the professional services revenue. I know it's you just a tick higher versus the typical 10% to 20% range we've been talking about. And I just wanted to see, is 10% to 20% still the appropriate range we should be thinking through? Or is there maybe more handholding for these pilots as you guys engage in them? Or is it maybe handholding of potentially federal sector customers? Like how do we think about the higher preserve revenue generation in Q4 versus what you guys are thinking about over the next year?

明白了。明白這一點。如果可以的話，然後只需 1 次快速跟進。但我只想增加專業服務收入。我知道你只是比我們一直在談論的典型 10% 到 20% 的範圍高一點。我只是想看看，10% 到 20% 是否仍然是我們應該考慮的合適範圍？或者當你們參與其中時，這些飛行員是否有更多的手持設備？或者它可能是潛在的聯邦部門客戶的代言人？比如我們如何看待第四季度更高的保留收入產生與你們明年的想法？

I think on a go-forward basis, we expect to be in the 10% to 20% range. There's always going to be these types of projects that our customers want, and it's difficult to forecast a specific in a go-forward revenue, but we believe 10% to 20% is appropriate on a go-forward basis.

我認為在前進的基礎上，我們預計會在 10% 到 20% 的範圍內。總會有我們的客戶想要的這些類型的項目，而且很難預測未來收入的具體情況，但我們認為在未來的基礎上 10% 到 20% 是合適的。

(Operator Instructions) Our next question comes from the line of Brad Sills of Bank of America.

（操作員說明）我們的下一個問題來自美國銀行的 Brad Sills。

This is Adam Bergere on for Brad Sills. So you're pretty well positioned in the current market, just given AI use cases are coming into focus. So kind of curious if it's changed your cadence for R&D investments at all?

這是 Brad Sills 的 Adam Bergere。所以你在當前市場中處於非常有利的位置，只是考慮到 AI 用例正在成為焦點。很好奇它是否完全改變了您的研發投資節奏？

Well, this is Tom. I mean, clearly, the investments we've made in the last 14 years are paying off, okay, in that we have over 40 applications and people want applications. And I think we're the only company in the world, but that has 40 applications. I think that -- I think the only recent change that we've made is we're a little bit shocked by the response that we had to C3 Generative AI. I mean that is -- we're a little bit overwhelmed by that. But that's a big opportunity. And so now we just came off a plane mean and we decided to really invest in that product category in a big way because it's just difficult to estimate the size of that market, but it's extraordinarily large.

嗯，這是湯姆。我的意思是，很明顯，我們在過去 14 年中所做的投資正在得到回報，好吧，因為我們有 40 多個應用程序，而且人們想要應用程序。我認為我們是世界上唯一一家有 40 份申請的公司。我認為 - 我認為我們最近所做的唯一改變是我們對 C3 生成 AI 的反應感到有點震驚。我的意思是——我們對此有點不知所措。但這是一個很大的機會。因此，現在我們剛剛脫離了平面平均水平，我們決定真正大力投資該產品類別，因為很難估計該市場的規模，但它非常大。

Yes. Fair enough. And then for kind of the Generative AI use cases and solutions thus far, I guess, the first -- this's your first take on it. But do you see any outsized uptick or expect any outsized uptick within certain verticals over others in your view?

是的。很公平。然後對於到目前為止的生成人工智能用例和解決方案，我想，第一個——這是你的第一次嘗試。但是，在您看來，您是否看到某些垂直領域內的任何大幅上漲或預期任何大幅上漲？

It's a good question. It kind of seems like everybody is interested in this. They want -- at the level of the CEO or the person who operates manufacturing and the person to operate sales they want basically a Google-like interface where they go -- a web browser like interface where they can ask any question about their business, okay? What are the problems in our supply chain. If I'm the chair of the joint chief, what am I ready to less levels, they have 35-ish quadrants and okay, in Central Europe. I mean that's what we call Google for DoD, but their open AI initiatives can provide the Secretary of Defense or the Chair of the Joint Chiefs of Staff answers to that question in seconds. Right now, it actually takes a week for him or most people to get those answers. So it's -- I don't know any industry that will not be taking use of this technology. It's really quite amazing.

這是個好問題。似乎每個人都對此感興趣。他們想要——在首席執行官或經營製造的人和經營銷售的人的層面上，他們基本上想要一個類似谷歌的界面——一個類似網絡瀏覽器的界面，他們可以在其中詢問有關他們業務的任何問題，好的？我們的供應鏈存在哪些問題。如果我是聯合酋長的主席，我準備好降低什麼級別，他們在中歐有 35 個左右的象限。我的意思是這就是我們所說的 DoD 谷歌，但他們的開放人工智能計劃可以讓國防部長或參謀長聯席會議主席在幾秒鐘內回答這個問題。現在，他或大多數人實際上需要一周的時間才能得到這些答案。所以它——我不知道有哪個行業不會使用這項技術。這真的很神奇。

Our next question comes from the line of Mike Cikos of Needham Company.

我們的下一個問題來自 Needham 公司的 Mike Cikos。

I did just have 1 quick follow-up. And maybe building on the question that Sanjit had asked earlier, but taking a different look rather than looking at the revenue, let's talk profitability for a second. But obviously, you guys are issuing guidance now, which is below Street and below what you guys had initially flagged if we go back a quarter ago, maybe for Juho. Can you help us think about the additional levers you have to pull on to ensure that C3 is achieving its target of exit fiscal '24 with non-GAAP profitability?

我確實只有 1 次快速跟進。也許基於 Sanjit 之前提出的問題，但從不同的角度而不是看收入，讓我們談談盈利能力。但很明顯，你們現在正在發布指導意見，如果我們回到一個季度前，可能會低於 Street 和你們最初標記的指導意見，也許是針對 Juho。您能否幫助我們考慮您必須採取的額外措施，以確保 C3 以非 GAAP 盈利能力實現其退出財政 '24 的目標？

Before we answer it, Mike. I do want to poke at the premise a little bit. Okay. I think our guidance is pretty much in line with what the Street expectations are once you take out like 1 outlier or 2 outliers. So our current guidance is in line with what the Street currently has. I'm pretty confident in that.

在我們回答之前，邁克。我確實想稍微戳一下這個前提。好的。我認為我們的指導非常符合華爾街的預期，一旦你拿出 1 個異常值或 2 個異常值。因此，我們目前的指引與華爾街目前的指引一致。我對此很有信心。

Now Juho the other question related to how are you sure you're going to get to profitability?

現在 Juho 的另一個問題是你如何確定你會盈利？

Right. So Mike, 1 of the things that I had on the prepared remarks was our planned investments into Generative AI, which combine that and vendor expenses, I think we can control spending towards the end of the year, if for whatever reason, the expected revenue would not occur from those. But we're pretty bullish about the Generative AI opportunity.

正確的。所以邁克，我在準備好的發言中提到的一件事是我們計劃對生成人工智能的投資，它將投資和供應商費用結合起來，我認為我們可以在年底前控制支出，如果出於某種原因，預期收入不會發生那些。但我們非常看好 Generative AI 的機會。

Said, we don't need the Generative AI for (inaudible) to be, Generative AI could be 0, okay? And we're still going to run a cash positive profitable business in Q4. Well, you have a very, very detailed plan that's been distributed to all the members of the management team. They all have big budgets. They know that's going to operate and you can expect it to be in cash positive profitable business non-GAAP profitable business in Q4, hard stock.

說，我們不需要生成 AI（聽不清），生成 AI 可以是 0，好嗎？而且我們仍將在第四季度開展現金盈利業務。嗯，你有一個非常非常詳細的計劃，已經分發給管理團隊的所有成員。他們都有很大的預算。他們知道這將會運作，你可以預期它會在第四季度成為現金正盈利業務非 GAAP 盈利業務，硬庫存。

Our next question comes from the line of Noah Herman of JMP Securities.

我們的下一個問題來自 JMP Securities 的 Noah Herman。

It is great to see the average sales cycles for agreements ticked down, I think, by about 1.3 months year-over-year. What's really driving that? And where do you think a sustainable sales cycle basically concludes that maybe thinking about the rest of this year?

很高興看到協議的平均銷售週期比去年同期減少了大約 1.3 個月。是什麼真正推動了這一點？您認為可持續的銷售週期在哪里基本得出結論，也許會考慮今年餘下的時間？

Well, I think the consumption-based pricing model is driving it where it's pretty easy to do. We're not going to have a large-scale enterprise AI application live in production in 6 months for $0.5 million. I mean that's nothing guys in terms of what it costs to bring in an Accenture or an IBM or somebody to try to bring one of these things, , that's going to be scores of millions of dollars in the years. So it's a pretty easy sale. It's a shorter sales cycle. And so I'm not sure where it ends up, but as we move more into more of our products, onto the AWS marketplace, the Google marketplace and other leverage channels like this, we'd expect to see it get shorter.

好吧，我認為基於消費的定價模型正在推動它變得非常容易做到。我們不會以 50 萬美元的價格在 6 個月內將大型企業 AI 應用程序投入生產。我的意思是，就引入 Accenture 或 IBM 或其他人試圖引入其中之一的成本而言，這不算什麼，幾年後將達到數百萬美元。所以這是一個非常容易的銷售。這是一個更短的銷售週期。所以我不確定它會在哪裡結束，但隨著我們更多地進入我們的產品，進入 AWS 市場、谷歌市場和其他類似的槓桿渠道，我們希望看到它變得更短。

At this I'd like to turn the call back over to Mr. Siebel for any closing remarks.

在此，我想將電話轉回給 Siebel 先生，聽取任何結束語。

Ladies and gentlemen, we thank you so much for your attention today. Thank you for tuning in. I encourage you to mark your calendars for June 22. I think you'll find that we'll talk about some interesting developments at our Investor Conference at that time, and we hope you'll have time to join us for that exchange. So thank you very much for your time today, and we wish you all a good night.

女士們，先生們，我們非常感謝你們今天的關注。感謝您收看。我鼓勵您在日曆上標記 6 月 22 日。我想您會發現我們會在那時的投資者大會上討論一些有趣的發展，我們希望您有時間加入我們交換。非常感謝您今天抽出時間，祝大家晚安。

Thank you. Ladies and gentlemen, this does conclude today's conference. Thank you all for participating. You may now disconnect. Have a great day.

謝謝。女士們，先生們，今天的會議到此結束。謝謝大家的參與。您現在可以斷開連接。祝你有美好的一天。