C3.ai Inc (AI) 2024 Q2 法說會逐字稿

Good day, and thank you for standing by. Welcome to the C3 AI's Second Quarter Fiscal Year '24 Conference Call. (Operator Instructions) Please be advised that today's call is being recorded. I would now like to turn the conference over to your host, Mr. Amit Berry. Please begin.

美好的一天，感謝您的支持。歡迎參加 C3 AI '24 財年第二季電話會議。 （操作員說明）請注意，今天的通話正在錄音。現在我想將會議交給東道主阿米特·貝裡先生。請開始。

Good afternoon, and welcome to C3 AI's earnings call for the second quarter of fiscal year 2024, which ended on October 31, 2023. My name is Amit Berry, and I lead Investor Relations at C3 AI.

下午好，歡迎參加 C3 AI 於 2023 年 10 月 31 日結束的 2024 財年第二季財報電話會議。我叫 Amit Berry，負責 C3 AI 的投資人關係。

With me on the call today is Tom Siebel, Chairman and Chief Executive Officer; and Juho Parkkinen, Chief Financial Officer. After the market closed today, we issued a press release with details regarding our second quarter results as well as a supplemental to our results. Both of which can be accessed through the Investor Relations section of our website at ir.c3.ai. This call is being webcast, and a replay will be available on our IR website following the conclusion of the call.

今天與我一起參加電話會議的是董事長兼執行長湯姆·西貝爾 (Tom Siebel)；和財務長 Juho Parkkinen。今天收盤後，我們發布了一份新聞稿，其中詳細介紹了第二季業績以及業績補充。兩者均可透過我們網站 ir.c3.ai 的投資者關係部分存取。本次電話會議正在網路直播，電話會議結束後，我們的 IR 網站將提供重播。

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.

在今天的電話會議中，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聲明。這些聲明僅反映我們今天的觀點，不應被視為代表我們任何後續日期的觀點。我們不承擔更新任何前瞻性陳述或展望的義務。

These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations. For a further discussion of the material 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 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.

這些陳述受到各種風險和不確定性的影響，可能導致實際結果與預期有重大差異。有關可能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 SEC 提交的文件。除非另有說明，所有數據都將在非公認會計原則的基礎上討論。此外，在今天的電話會議中，我們也將提及某些非公認會計準則財務指標。我們的新聞稿中包含了 GAAP 與非 GAAP 指標的調整表。

Finally, at times 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.

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季度業績。請注意，我們將來可能會也可能不會繼續提供此附加詳細資訊。

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

接下來，讓我把電話轉給湯姆。

Thank you, Amit. Good afternoon, everyone, and thank you for joining our call today. Results. Bottom line, we continue to accelerate our revenue growth and our customer engagement count and continue to gain traction with C3 generative AI and our enterprise AI applications in the second quarter. Total revenue for the second quarter was $73.2 million, an increase of 17% compared to $62.4 million 1 year ago, and accelerating from an 11% increase in the first quarter.

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。結果。最重要的是，我們繼續加速收入成長和客戶參與度成長，並在第二季度繼續透過 C3 生成式人工智慧和企業人工智慧應用程式獲得吸引力。第二季總營收為 7,320 萬美元，比一年前的 6,240 萬美元成長 17%，較第一季 11% 的增幅有所加快。

The total number of customer engagements was 404, an increase of 81% compared to 223 last quarter. North American revenue of $61.2 million increased 28% year-over-year, while EMEA revenue of $10.6 million decreased 11% year-over-year, and federal revenue increased 100% year-over-year. Subscription revenue for the quarter was $66.4 million, constituted 91% of total revenue and increasing 12% from a year ago. GAAP gross profit for the quarter was $41.1 million, representing a 56% gross margin.

客戶參與總數為 404 人，比上季的 223 人增加了 81%。北美地區收入為 6,120 萬美元，年增 28%；歐洲、中東和非洲地區收入為 1,060 萬美元，年減 11%；聯邦收入年增 100%。該季度訂閱營收為 6,640 萬美元，佔總營收的 91%，比去年同期成長 12%。該季度 GAAP 毛利為 4,110 萬美元，毛利率為 56%。

Our non-GAAP gross profit for the quarter was $50.4 million, representing a 69% non-GAAP gross margin. Our GAAP net loss per share was -- the loss was $0.59, and non-GAAP net loss per share was $0.13. We ended the quarter with $762.3 million in cash, cash equivalents and investments. C3 AI's partner ecosystem continues to drive significant growth. In Q2, the company closed 40 agreements through our partner network. Including AWS, Booz Allen, Baker Hughes, Google Cloud and Microsoft. The qualified opportunity pipeline with partners has increased by 75% in the past year.

我們本季的非 GAAP 毛利為 5,040 萬美元，相當於 69% 的非 GAAP 毛利率。我們的 GAAP 每股淨虧損為 0.59 美元，非 GAAP 每股淨虧損為 0.13 美元。本季結束時，我們的現金、現金等價物和投資為 7.623 億美元。 C3 AI 的合作夥伴生態系統持續推動顯著成長。第二季度，該公司透過我們的合作夥伴網路達成了 40 項協議。包括 AWS、博思艾倫、貝克休斯、谷歌雲端和微軟。去年，與合作夥伴合作的合格機會管道增加了 75%。

We've signed new and expanded agreements with Nucor Corporation, Roche, Con Edison, Hewlett Packard Enterprise, GSK formerly SmithKline, the United States Navy, the Administration for Children & Families, a division of Health & Human Services, Indorama and First Bank amongst others. Over the past several months, C3 AI has helped Nucor, the largest steel producer in the United States to better optimize caster production schedules specifically to improve production levels and reduced cost levels in the steel casting process.

我們與紐柯公司、羅氏公司、聯合愛迪生公司、惠普企業公司、葛蘭素史克公司（原史密斯克公司）、美國海軍、兒童和家庭管理局、衛生與公眾服務部、Indorama 和第一銀行簽署了新的和擴展的協議。其他的。在過去的幾個月裡，C3 AI幫助美國最大的鋼鐵生產商紐柯公司更好地優化連鑄機生產計劃，特別是提高生產水平並降低鑄鋼工藝的成本水平。

C3 AI is now helping Nucor scale this across several additional mills. In Q2, C3 AI also kicked off 2 new additional use cases at Nucor, tackling process optimization and demand forecasting, and we also completed a C3 generative AI pilot. Targeting operational health and safety. GSK formally GlaxoSmithKline, is now using C3 AI supply chain suite to increase efficiency in its supply chain, using AI to optimize yield and improve demand forecasting processes.

C3 AI 現在正在幫助紐柯在另外幾家工廠擴展這一規模。在第二季度，C3 AI 也在紐柯公司啟動了 2 個新的附加用例，解決流程最佳化和需求預測問題，我們也完成了 C3 生成式 AI 試點。以營運健康和安全為目標。 GSK（原名葛蘭素史克）目前正在使用 C3 AI 供應鏈套件來提高其供應鏈效率，利用 AI 來優化產量並改善需求預測流程。

Con Edison, a C3 customer since 2017 continues to expand its use of the C3 AI applications. Most recently, by adding C3 generative AI. Con Ed is using C3 generative AI to help workers quickly find answers to questions and analysis related to smart meters, service levels and infrastructure data. In the second quarter, Con Edison completed 2 pilots of C3 generative AI, which have now converted to production.

自 2017 年起成為 C3 客戶的聯合愛迪生公司 (Con Edison) 繼續擴大 C3 AI 應用程式的使用。最近，透過添加 C3 來產生人工智慧。 Con Ed 正在使用 C3 生成式人工智慧來幫助工作人員快速找到與智慧電錶、服務等級和基礎設施數據相關的問題和分析的答案。第二季度，聯合愛迪生公司完成了 2 個 C3 生成式人工智慧試點，現已轉產。

We also continue to expand our footprint in state and local governments with particular interest in C3 AI law enforcement from San Mateo County, California. And C3 AI residential property appraisal from Stark County, Ohio and Charlotte County, Florida. Our federal business continues to show significant strength with bookings up 187% year-over-year. We closed new and expanded deals with the United States Navy, the intelligence community, Joint Staff J8, the Defense Logistics Agency, and the Administration for Children & Families.

我們也繼續擴大在州和地方政府的影響力，特別關注加州聖馬刁縣的 C3 AI 執法。還有來自俄亥俄州斯塔克縣和佛羅裡達州夏洛特縣的 C3 AI 住宅房產評估。我們的聯邦業務持續展現出強勁的實力，預訂量較去年同期成長 187%。我們與美國海軍、情報界、聯合參謀部 J8、國防後勤局以及兒童與家庭管理局達成了新的和擴大的協議。

We've talked many times about our success. Our successes in helping them monetize or to modernize -- sorry, the Department of Defense and we're proud now to say that our products are helping civilian government agencies as well. This quarter, we began work with the Administration for Children & Families, a division of the U.S. Department of Health & Human Services. The agreement with C3 AI was part of their first order under a $90 million purchase -- blanket purchase agreement. And this part of ACF's work involves helping unaccompanied children who across the U.S. border find temporary shelter and permanent homes.

我們已經多次談論過我們的成功。我們在幫助他們貨幣化或現代化方面取得的成功——對不起，國防部，我們現在很自豪地說，我們的產品也正在幫助民間政府機構。本季度，我們開始與美國衛生與公眾服務部下屬的兒童與家庭管理局合作。與 C3 AI 達成的協議是他們 9,000 萬美元購買協議中第一筆訂單的一部分。 ACF 的這部分工作涉及幫助跨越美國邊境的無人陪伴兒童找到臨時庇護所和永久住所。

Our platform will be used in complex modeling and predictive analytics at ACF to help them keep track of the number of unaccompanied children in the agencies care, staffing needs and determine how long these children are with their case managers amongst other tasks.

我們的平台將用於 ACF 的複雜建模和預測分析，幫助他們追蹤機構護理中無人陪伴兒童的數量、人員配置需求，並確定這些兒童與案件經理在一起的時間以及其他任務。

Our C3 AI continues to leverage its extensive commercial supply chain experience in the federal government and is now applying this experience in the defense sector with the C3 AI contested logistics application for Transcom and for DLA.

我們的 C3 AI 繼續利用其在聯邦政府的豐富商業供應鏈經驗，現在正在將這些經驗應用於國防部門，為 Transcom 和 DLA 提供 C3 AI 競爭性物流應用程式。

During the quarter, C3 AI converted 2 defense logistics agency pilots in the follow-on projects for the Department of Defense. The first project delivers common operating picture of the supply chain for DoD and enables leaders at multiple echelons to see in near real time, their global Class 9 supply posture. The application unifies disparate supply data and provides the defense logistics agency, the ability to identify supply chain inefficiencies forecast, parts consumption and parts shortage and conduct impact assessments and put into place mitigation plans.

本季度，C3 AI 在國防部的後續計畫中改造了 2 名國防後勤機構飛行員。第一個項目為國防部提供了供應鏈的通用營運圖，並使多個梯隊的領導者能夠近乎即時地了解其全球 9 級供應態勢。該應用程式統一了不同的供應數據，並為國防後勤機構提供了識別供應鏈效率低下預測、零件消耗和零件短缺的能力，並進行影響評估和實施緩解計劃。

The second project supports DLA's energy directory, leveraging C3 AI's commercial expertise in the oil and gas sector. The C3 AI's contested logistics application modernizes and streamlines global fuel distribution for the Department of Defense. Users can see global fuel inventories anticipate fuel consumption, identify supply network risks and create distribution and transportation plans to prevent disruption and assure supply. These applications promise to significantly impact the efficiency of the Department of Defense Logistic enterprise and improve readiness.

第二個專案利用 C3 AI 在石油和天然氣領域的商業專業知識，支持 DLA 的能源目錄。 C3 AI 備受爭議的物流應用為國防部實現了現代化並簡化了全球燃料分配。用戶可以查看全球燃料庫存、預測燃料消耗、識別供應網路風險並制定配送和運輸計劃，以防止中斷並確保供應。這些應用程式有望顯著影響國防部後勤企業的效率並提高準備。

Our partnership with AWS deepened with an expanded strategic collaboration agreement in the quarter, okay? And the availability of our new no-code self-service generative AI applications, C3 generative AI now available on the AWS marketplace. I think we announced that last week. This new application allows customers -- users of all technical levels to begin using generative AI within minutes of signing up. And this application, C3 generative AI is now available to you on the AWS marketplace under a 14-day free trial. So I encourage you to take a look at it for those of you who are interested.

我們與 AWS 的合作關係在本季度擴大了戰略合作協議，從而加深了，好嗎？我們新的無代碼自助生成式 AI 應用程式 C3 生成式 AI 現已在 AWS 市場上推出。我想我們上週就宣布了這一點。這個新應用程式讓客戶可以——所有技術水平的用戶在註冊後幾分鐘內開始使用生成式人工智慧。此應用程式 C3 生成式 AI 現已在 AWS 市場上提供 14 天免費試用。所以我鼓勵有興趣的人去看看。

Under the expanded collaboration agreement with AWS, we're focusing on offering advanced generative AI solutions, combined with what they're doing in Bedrock, okay, and other initiatives for enterprises and for AI applications for customers in multiple verticals, including manufacturing, power and utilities, consumer packaged goods, state and local government and the federal government.

根據與AWS 擴大的合作協議，我們專注於提供先進的生成式AI 解決方案，結合他們在Bedrock 所做的工作，以及為企業和多個垂直領域（包括製造、電力）客戶的AI 應用程式提供的其他計劃以及公用事業、消費品、州和地方政府以及聯邦政府。

C3 AI and AWS' joint qualified pipeline has more than doubled year-over-year with heightened interest in the C3 generative AI suite. In Q2, C3 has been recognized multiple times for its innovation in the AI space. We've been named to the Fortune 50 AI Innovators list and the list goes on and on. So I'm not going to bore you with that. We do get recognized all the time.

隨著人們對 C3 生成式 AI 套件的興趣日益濃厚，C3 AI 和 AWS 的聯合合格管道比去年同期增長了一倍多。第二季度，C3 因其在人工智慧領域的創新而多次受到認可。我們已入選《財星》50 強人工智慧創新者名單，而且這個名單還在增加。所以我不會讓你覺得無聊。我們確實總是得到認可。

Pilot growth, this is important. In Q2, we closed 62 agreements, including 36 pilots and trials. Our new pilot count is up 270% from a year ago. Notably, 20 of these were generative AI pilots, 150% increase from Q1. With the lower entry price points of our pilots, we are more easily able to land new accounts. With our pilots, we are engaging customers across a diverse set of industries in this quarter. Our pilots came from manufacturing federal, defense, aerospace, pharmaceuticals and other industries. Now we did see sales headwinds in the quarter. Okay.

試點成長，這個很重要。第二季度，我們達成了 62 項協議，其中包括 36 項試點和試驗。我們的新飛行員數量比一年前增加了 270%。值得注意的是，其中 20 名是生成式 AI 飛行員，比第一季增加了 150%。由於我們的試點計畫的入門價格較低，我們更容易獲得新客戶。透過我們的試點，我們在本季吸引了不同行業的客戶。我們的飛行員來自聯邦製造業、國防、航空航太、製藥和其他行業。現在我們確實看到了本季的銷售逆風。好的。

While the interest in AI applications and especially generative AI is growing substantially, we're also seeing, in many cases, lengthening decision cycles. Virtually every company, okay, in the last 3 to 6 months has created a new AI governance function as part of its decision-making process. These AI governance functions assess and approve those AI applications that will be allowed to be installed in the enterprise. This has candidly added a step to the decision process in AI. You might have heard it here first, okay, but you will be hearing this from every AI vendor, okay, in the next few quarters. Take it to the bank.

儘管人們對人工智慧應用（尤其是生成式人工智慧）的興趣大幅增長，但我們在許多情況下也看到決策週期在延長。好吧，在過去的 3 到 6 個月裡，幾乎每家公司都創建了新的人工智慧治理功能，作為其決策過程的一部分。這些人工智慧治理功能評估並批准那些允許在企業中安裝的人工智慧應用程式。這無疑為人工智慧的決策過程增加了一個步驟。您可能首先在這裡聽到過，好吧，但是在接下來的幾個季度裡，您將從每個人工智慧供應商那裡聽到這一點。把它帶到銀行。

It has simply -- it has added a step of the process. It is -- and it is lengthening the normal sales cycle. So it's in -- so this -- this provided a sales headwind in the quarter. Okay. And while the increased scrutiny lengthens the sales process, we believe that this is a healthy process to ensure that companies are adopting safe and appropriate AI solutions. So we're all for it, okay. And did it move revenue a little bit a click below the center of the range? Yes, it did, okay. But get over it. The world is a better place, people are making very careful well-informed decisions. They have their best people on it, and we will all be happier for this in the long run.

它只是簡單地添加了流程的一個步驟。確實如此，而且它正在延長正常的銷售週期。所以這對本季的銷售帶來了阻力。好的。雖然加強審查會延長銷售流程，但我們相信這是一個健康的流程，可確保公司採用安全且適當的人工智慧解決方案。所以我們都贊成，好吧。單擊是否會使收入稍微低於範圍中心？是的，確實如此，好吧。但克服它。世界變得更加美好，人們正在做出非常謹慎、明智的決定。他們擁有最優秀的人才，長遠來看，我們都會為此感到高興。

So it did -- that dynamic did provide an unexpected headwind to our Q2 sales revenue performance. In addition, our sales execution in Europe was candidly unacceptable. Okay. And since then, we've taken -- we've been through our planning meetings and we've taken appropriate organizational steps to immediately improve sales execution in Europe.

事實確實如此——這種動態確實為我們第二季的銷售收入表現帶來了意想不到的阻力。此外，我們在歐洲的銷售執行情況確實令人無法接受。好的。從那時起，我們已經召開了計劃會議，並採取了適當的組織措施，以立即改善歐洲的銷售執行情況。

Now let's take a look at -- if this is the big story, this is the top line, okay. And really what this whole story has been about for the last 6 to 7 quarters has been from the transition from subscription-based pricing to consumption-based pricing.

現在讓我們來看看——如果這是一個大故事，那麼這就是最重要的，好吧。過去 6 到 7 個季度的整個故事實際上是從基於訂閱的定價到基於消費的定價的轉變。

And before we switch to consumption-based pricing, you will recall the company was growing at a quite a rapid growth rate, like I think, 7 quarters ago, order of 38% year-over-year growth rate. So we were definitely in the top quartile. And we announced the transition to consumption-based pricing that we believe would be and has become the standard in the industry. Okay, the consumption-based pricing is based upon per virtual CPU or virtual GPU hour, similar to the pricing at Snowflake, Google Cloud, AWS, Microsoft, Azure et cetera. Prior to this, we were doing large enterprise subscription deals of $1 million, $5 million, $20 million, $50 million.

在我們轉向基於消費的定價之前，您會記得該公司正在以相當快的成長率成長，就像我認為的那樣，7 個季度前，年成長率為 38%。所以我們絕對是前四分之一。我們宣布轉向基於消費的定價，我們相信這將成為並且已經成為行業標準。好的，基於消耗的定價是基於每個虛擬 CPU 或虛擬 GPU 小時，類似於 Snowflake、Google Cloud、AWS、Microsoft、Azure 等的定價。在此之前，我們做過100萬美元、500萬美元、2000萬美元、5000萬美元的大型企業訂閱交易。

And it was a good business. That being said, the downside of that model was lumpiness in bookings, lengthy sales cycles and low levels of revenue predictability. We believe the transition from a primarily subscription-based pricing model to an assumption-based price remodel brought us into line with what we believe are today, the industry standard cloud pricing standards. Making it easier and less costly for new customers to acquire our solutions and then increase their spending as their usage and adoption increase.

這是一筆好生意。話雖如此，該模式的缺點是預訂量不穩定、銷售週期長以及收入可預測性低。我們相信，從主要基於訂閱的定價模型到基於假設的價格重塑的轉變使我們符合我們今天所認為的行業標準雲端定價標準。讓新客戶能夠更輕鬆、更低成本地獲得我們的解決方案，然後隨著使用率和採用率的增加而增加支出。

We anticipated and announced when we made that transition, it would have a short to medium negative effect on revenue growth, a long-term drag on RPO as the sales price was significantly reduced and the contracts often lack a time-certain multi-period commitment. We believe when we made the announcement that the consumption-based pricing model would increase the number of customers, okay, and increase the total amount of system consumption, returning -- resulting in a return to increased revenue growth, increased customer growth, decreased average selling price and decreased RPO over time.

當我們進行這一轉變時，我們預計並宣布，這將對收入成長產生短期到中度的負面影響，對 RPO 產生長期拖累，因為銷售價格大幅降低，而且合約通常缺乏確定時間的多期承諾。我們相信，當我們宣布基於消費的定價模式會增加客戶數量，好吧，並增加系統消費總量，返回 - 導致收入增長增加，客戶增長增加，平均水平下降銷售價格和RPO 隨著時間的推移而下降。

Now while we are still in the process of working through -- completely through this transition to the new pricing model, the preliminary empirical results that we are seeing evidenced by year-over-year growth rates appear to be proving out exactly as expected and exactly as we predicted. Since the transition revenue growth initially decreased, then it flattened, okay.

現在，雖然我們仍在努力完成向新定價模型的過渡，但我們看到的逐年增長率所證明的初步實證結果似乎證明完全符合預期並且完全準確正如我們預測的那樣。由於轉型收入增長最初下降，然後就趨於平緩，好吧。

And now it is increasing as the consumption-based pricing model take effect -- takes effect. Average selling prices decreased, RPO has decreased, customer engagement has increased substantially. If we look back over the last, say, 1, 2, 3, 4 quarters, 4 quarters ago, our revenue growth was negative 4% and then 0%. The last quarter, it was 11%, now it's 17%. Bookings growth, 71% year-over-year. I'm sorry, bookings growth 100% year-over-year. The new contract growth of 148% year-over-year, okay. Pilot growth, 50% quarter-over-quarter, 170% year-over-year. So this is basically the beginning, the middle and the end of this story, okay.

現在，隨著基於消費的定價模式的生效，這一數字正在增加。平均售價下降，RPO 下降，顧客參與度大幅提高。如果我們回顧過去，比如說1、2、3、4個季度、4個季度前，我們的營收成長是負4%，然後是0%。上個季度是 11%，現在是 17%。預訂量較去年同期成長 71%。抱歉，預訂量年增 100%。新簽合約年增148%，還好。試點成長，季增 50%，年增 170%。這基本上就是這個故事的開始、中間和結尾，好吧。

We announced 6, 7 quarters ago, a transition to our consumption-based pricing. We predicted that revenue would decline and then flatten and then increase, and we are now seeing these increases that we predicted. So now let's talk about generative AI. Generative AI simply changes everything. okay. I believe that it more than doubles the size of our addressable market overnight. We've all seen the predictions from Bloomberg that predicts this is 100 -- this is in excess of $1 trillion, $1.3 trillion market by 2032. Goldman Sachs predicts that this could increase corporate profits by 30% in the next decade. And the generative AI alone could raise the global GDP by 7%. People, this is a big deal. It is difficult to overestimate the levels of interest that we're seeing in the category of generative AI.

我們在六、七個季度前宣布過渡到基於消費的定價。我們預測收入會下降，然後趨於平緩，然後增加，現在我們看到了我們預測的這些成長。現在我們來談談生成人工智慧。生成式人工智慧改變了一切。好的。我相信它一夜之間將我們的潛在市場規模擴大了一倍以上。我們都看過彭博社的預測，預測這是100——這將超過1 兆美元，到2032 年將達到1.3 兆美元的市場。高盛預測，這可能會在未來十年將企業利潤增加30% 。僅生成式人工智慧就可以使全球 GDP 提高 7%。人們，這是一件大事。很難高估我們對產生人工智慧領域的興趣程度。

Now by combining our multibillion dollar, say, 14-year investment in the C3 AI platform, with the recent developments in large language models and retrieval augmented generation, C3 AI is unique in the market and that we are able to solve the disqualifying hobgoblin that are preventing the adoption of generative AI, okay, in government, in defense, in intelligence, in the private sector. What are those hobgoblin.

現在，透過將我們在C3 AI 平台上數十億美元的投資（例如14 年的投資）與大型語言模型和檢索增強生成的最新發展相結合，C3 AI 在市場上是獨一無二的，我們能夠解決以下問題：正在阻止生成式人工智慧在政府、國防、情報和私部門的採用。那些妖精是什麼？

Those are the facts that the answers that come out of these large language models are stochastic. They're random. They're not traceable. We have this hallucination problem, which is extraordinarily problematic. We have research, none of our data access controls yet, be it DoD or Bank of America are enforced. We have these problems with LLM cause data exfiltration, LLM cause cyber threats and IP liability. In addition, all the solutions that are out there, almost all those solutions, I would say, with the exception of AWS, Bedrock, tend to be LLM specific.

事實是，這些大型語言模型得出的答案是隨機的。它們是隨機的。它們是不可追蹤的。我們有這個幻覺問題，這是一個非常嚴重的問題。我們進行了研究，但我們的資料存取控制尚未執行，無論是國防部還是美國銀行。我們的法學碩士問題會導致資料洩露，法學碩士會導致網路威脅和智慧財產權責任。此外，我想說，所有現有的解決方案，幾乎所有這些解決方案，除了 AWS、Bedrock 之外，往往都是 LLM 特定的。

And I don't think anybody wants to be a LLM, hook their wagon on to any given LLM today with all the innovation that's going on in the market. and to be dependent on any LLM provider that could make some announcement on Friday and be gone on Monday. See OpenAI for details. So this LLM agnostic is firstly, the bottom line is our solution in the market addresses every one of those hobgoblin that prevent the installation of generative AI in the enterprise.

我認為沒有人想成為法學碩士，將他們的馬車掛在當今市場上正在發生的所有創新的任何特定法學碩士上。並依賴任何可能在周五發布一些公告並在周一消失的法學碩士提供者。詳情請參閱 OpenAI。因此，這個 LLM 不可知論者首先，底線是我們在市場上的解決方案解決了每一個阻止在企業中安裝生成式人工智慧的大妖精。

So this is really unique and it took 14 years and $2 billion worth of software engineering for us to be ready for this. This is why we could solve it. So while the rest of the world is playing catch-up. How about multi-modal. I mean we're completely nail multi-modal. We've been doing it for 14 years. Multi-modal, what does this mean? Rather than all these LLM solutions basically handle text, we handle text, we have telemetry. We handle images. We handle signals. There we handle enterprise data, we handle the structure data. We handle unstructured data.

所以這確實是獨一無二的，我們花了 14 年時間和價值 20 億美元的軟體工程才為此做好準備。這就是為什麼我們可以解決它。因此，當世界其他地區正在追趕時。多式聯運怎麼樣？我的意思是我們完全掌握了多式聯運。我們已經這樣做了 14 年。多式聯運，這是什麼意思？所有這些法學碩士解決方案基本上都不是處理文本，而是我們處理文本，我們有遙測技術。我們處理圖像。我們處理訊號。在那裡我們處理企業數據，我們處理結構數據。我們處理非結構化資料。

So we are unique in the market, and the result is quite exciting. So while the rest of the world is playing catch-up and we have scores of start-ups with 3 guys, 4 girls and 2 cats in an apartment in San Francisco, being they're getting $1 billion funding and multibillion dollar market valuation, see pitch book for details. We have I don't know how many customers, we have [through order] of 1,000 employees. I don't know how many countries, and we're delivering these solutions today. And -- so while the rest of the world is playing catch-up, we're working closely with our customers and new customers to install high value generative AI solutions that rapidly realize value to their organization.

所以我們在市場上是獨一無二的，結果是相當令人興奮的。因此，當世界其他地方正在追趕時，我們在舊金山的一間公寓裡有許多新創公司，有3 個男孩、4 個女孩和2 隻貓，他們獲得了10 億美元的資金和數十億美元的市場估值，詳情請參閱宣傳手冊。我們有不知道有多少客戶，我們有1000名員工[透過訂單]。我不知道有多少個國家，我們今天正在提供這些解決方案。而且，當世界其他地區正在追趕時，我們正在與我們的客戶和新客戶密切合作，安裝高價值的生成式人工智慧解決方案，快速為其組織實現價值。

We believe that our strategic decision to invest in generative AI could address our addressable market opportunity. Our suite of 28, now I think 29 generative AI products wins on reliability, flexibility, adaptability, accuracy and security, all of the same qualities that are inherent in our enterprise AI platform. Our vision to expand our customer base is working. The idea, and this is very much idea about the work that we're doing on the AWS marketplace is to go from 8 customers to 80 customers to 8,000 customers to 80,000 customers.

我們相信，我們投資生成人工智慧的策略決策可以解決我們潛在的市場機會。我們的 28 套生成式 AI 產品（現在我認為是 29 款）在可靠性、靈活性、適應性、準確性和安全性方面獲勝，所有這些都與我們的企業 AI 平台固有的品質相同。我們擴大客戶群的願景正在發揮作用。這個想法，也是我們在 AWS 市場上所做的工作的一個非常重要的想法，就是從 8 個客戶到 80 個客戶，再到 8,000 個客戶，再到 80,000 個客戶。

So what we're dealing now is kind of a new game with massive market leverage, and we are the first to market. And we -- so I think we have the opportunity here through our innovation, through our applications that will proliferate across the business. C3 generative AI has enabled us to land high-caliber new customers and expand agreements with the current customers. The surge of interest led to our C3 generative AI qualified pipeline increasing new opportunities, increasing 55% sequentially quarter-over-quarter in the second quarter, representing the most rapid acceleration of all our product offerings.

因此，我們現在正在處理的是具有巨大市場槓桿的新遊戲，而且我們是第一個進入市場的遊戲。所以我認為，透過我們的創新，透過我們將在整個企業中推廣的應用程序，我們在這裡擁有機會。 C3 生成式人工智慧使我們能夠吸引高素質的新客戶並擴大與現有客戶的協議。興趣的激增導致我們的 C3 生成式 AI 合格管道增加了新的機會，第二季度環比增長了 55%，這是我們所有產品中最快的加速。

We expect this momentum to grow as we continue to innovate and build the increasingly exciting products. Our November announcement of the self-service C3 generative AI on the AWS marketplace plays a big part in this story, potentially expanding our addressable customer pool and our user base exponentially. This new application allows users of all technical levels to enroll in the application and begin productively using generative AI in minutes. Again, this product is available today on the AWS marketplace, should you have interest.

隨著我們不斷創新和打造越來越令人興奮的產品，我們預計這種勢頭將會成長。我們 11 月在 AWS 市場上發布的自助式 C3 生成人工智慧在這個故事中發揮了重要作用，有可能以指數方式擴大我們的潛在客戶群和用戶群。這個新應用程式允許所有技術級別的用戶註冊該應用程序，並在幾分鐘內開始有效地使用生成式人工智慧。同樣，如果您有興趣，該產品現已在 AWS 市場上提供。

As I introduced last quarter, we made a well-considered decision to seize the immediate and candidly staggering market opportunity that we see in generative AI. As such, we are making and increasing a sizable and timely investment in application development, model engineering, lead generation, branding and market awareness to seize market share in generative AI as rapidly as possible. This will put short-term downward pressure on free cash flow and profitability.

正如我上個季度介紹的那樣，我們做出了一個經過深思熟慮的決定，以抓住我們在生成人工智慧領域看到的直接且坦率的驚人市場機會。因此，我們正在應用程式開發、模型工程、潛在客戶開發、品牌推廣和市場知名度方面進行大量及時的投資，以盡快搶佔生成式人工智慧的市場份額。這將對自由現金流和獲利能力帶來短期下行壓力。

Closing thoughts. The generative AI opportunity is staggering. We believe that it is in the best interest of our shareholders to further accelerate our investment in generative AI, deepening our investments in lead generation, branding market awareness and customer success. Given our substantial cash balance, we believe it is a strategic imperative to invest further in the generative AI opportunity at this time.

結束思想。生成式人工智慧的機會是驚人的。我們相信，進一步加速對生成式人工智慧的投資，深化對潛在客戶開發、品牌市場知名度和客戶成功的投資，符合股東的最佳利益。鑑於我們擁有大量現金餘額，我們認為目前進一步投資生成式人工智慧機會具有戰略意義。

Separately, now with the release of our platform version of our 8.3 product line, which is really quite remarkable in terms of the benefits that it brings to our customers and the increase in performance that it brings to our customers we have decided to further invest in our customer base to accelerate their upgrade from Version 7 to version 8.3, which we believe will further increase our customer satisfaction levels that are already quite high.

另外，現在隨著我們8.3 產品線的平台版本的發布，就它給我們的客戶帶來的好處以及它給我們的客戶帶來的性能提升而言，這確實是相當顯著的，我們決定進一步投資我們的客戶群加速從版本 7 升級到版本 8.3，我們相信這將進一步提高我們已經相當高的客戶滿意度。

We continue -- that being said, we continue to expect positive cash flow in Q4. And while we're not giving fiscal year '25 guidance yet, we continue to expect positive cash flow for full year -- fiscal year '25. C3 AI remains focused. We are 1 of the few AI software pure plays that have established relationships, a tried test and proven technology platform add reputational equity to capitalize on this generative AI market opportunity.

話雖這麼說，我們仍然預期第四季將出現正現金流。雖然我們尚未給出 25 財年的指引，但我們仍然預計全年（25 財年）將出現正現金流。 C3 AI 仍然是重點。我們是為數不多的建立了合作關係的人工智慧軟體專業公司之一，經過考驗和驗證的技術平台增加了聲譽，可以利用這一生成式人工智慧市場機會。

I'll turn the call over to Juho Parkkinen , our Chief Financial Officer, to talk more about our financial performance and provide guidance for the remainder of the fiscal year. Juho?

我會將電話轉給我們的財務長 Juho Parkkinen，更多地討論我們的財務表現並為本財年剩餘時間提供指導。朱霍？

Thank you, Tom. I will now provide a recap of our Q2 financial results and some additional color on our consumption-based revenue model, which we introduced 5 quarters ago. Then I'll discuss factors that will drive our financials in the back half of the year. All figures are non-GAAP on as otherwise noted.

謝謝你，湯姆。現在，我將回顧我們第二季度的財務業績，並對我們 5 個季度前推出的基於消費的收入模式進行一些補充。然後我將討論下半年推動我們財務狀況的因素。除非另有說明，所有數據均以非公認會計準則計算。

Total revenue for the second quarter increased 17.3% year-over-year to $73.2 million. Subscription revenue increased to 11.7% year-over-year to $66.4 million and represented 90.7% of total revenue. Professional services revenue was $6.8 million and represented 9.3% of total revenue. Gross profit for the second quarter was $50.4 million, and gross margin was 68.8%, and as a reminder, we continue to expect short-term pressure on our gross margins due to a higher mix of packets, which carry a greater cost of revenue during the pilot phase of the customer life cycle.

第二季總營收年增 17.3% 至 7,320 萬美元。訂閱收入年增 11.7%，達到 6,640 萬美元，佔總營收的 90.7%。專業服務收入為 680 萬美元，佔總收入的 9.3%。第二季的毛利為 5,040 萬美元，毛利率為 68.8%，提醒一下，我們仍然預計，由於包裝組合的增加，我們的毛利率將面臨短期壓力，這會帶來更大的收入成本。客戶生命週期的試點階段。

Operating loss for the quarter was negative $25 million compared to our guidance range of negative $27 million to negative $40 million. The improvement in operating loss versus guidance was driven by timing and amounts of the generative AI-regated investments we made to capture market share as well as our team's ongoing focus on disciplined expense management. At the end of Q2, our accounts receivable was $143.2 million, including unbilled receivables of $104.8 million The general health of our accounts receivable remains strong. Now turning to RPO and bookings.

本季營運虧損為負 2,500 萬美元，而我們的指導範圍為負 2,700 萬美元至負 4,000 萬美元。營運虧損相對於指引的改善是由於我們為佔領市場份額而進行的人工智慧監管投資的時機和金額，以及我們團隊對嚴格費用管理的持續關注。在第二季末，我們的應收帳款為 1.432 億美元，其中未開立應收帳款為 1.048 億美元。我們的應收帳款整體健康狀況依然強勁。現在轉向 RPO 和預訂。

Reflecting our transition to consumption-based contracts, we reported second quarter GAAP RPO of $303.6 million which is down 27.3% from last year and current GAAP RPO of $170.2 million, which is up 3.5% from last year. We continue to see positive trends in the diversity of our pilot bookings with 10 industry segments represented in Q2 pilots as compared to 8 in Q1. Free cash flow for the quarter was negative $55.1 million, we continue to be very well capitalized and closed the quarter with $762.3 million in cash, cash equivalents and marketable securities.

我們報告第二季度 GAAP RPO 為 3.036 億美元，比去年下降 27.3%，目前 GAAP RPO 為 1.702 億美元，比去年增長 3.5%，反映出我們向基於消費的合約的過渡。我們繼續看到試點預訂多樣性的積極趨勢，第二季度試點涉及 10 個行業領域，而第一季有 8 個行業領域。本季的自由現金流為負 5,510 萬美元，我們的資本狀況依然良好，本季末現金、現金等價物和有價證券為 7.623 億美元。

Now I'll provide an update on our consumption business model for the second quarter. During the quarter, we started 36 pockets, a 50% increase from last quarter. We are pleased to report that the actual vCPU consumption data that we're seeing from pilot activity has validated the assumptions we made when we transition to the consumption-based pricing model 5 quarters ago. Our pilot conversion rates are trending upwards or getting close to our target of 70%.

現在我將提供第二季消費商業模式的最新情況。本季度，我們啟動了 36 個口袋，比上個季度增加了 50%。我們很高興地報告，我們從試點活動中看到的實際 vCPU 消耗數據驗證了我們在 5 個季度前過渡到基於消耗的定價模型時所做的假設。我們的試點轉換率呈上升趨勢或接近我們 70% 的目標。

At quarter end, we had cumulatively signed 109 pilots, of which 103 are still active. This means they are still in their original 3- to 6-month term extended for 1 to 2 months, converted to consumption or a license contract or are currently being negotiated for a production license. Finally, our customer engagement count for the quarter was 404, an 81% increase from 223 a year ago.

截至季度末，我們已累計簽約 109 名飛行員，其中 103 名仍然活躍。這意味著它們仍處於原來的 3 至 6 個月期限，延長 1 至 2 個月，轉換為消費或許可合同，或目前正在就生產許可進行談判。最後，本季我們的客戶參與人數為 404 人，比一年前的 223 人增加了 81%。

Turning to guidance. As Tom mentioned, we expect Q3 revenue range from $74 million to $78 million, and non-GAAP loss from operations to range from negative $40 million to negative $46 million. We remain committed to delivering positive cash flow in Q4 FY '24 and for the full year of fiscal year '25 and non-GAAP profitability in the second half of fiscal '25. For the full fiscal year '24, we are maintaining our previous revenue guidance in the range of $295 million to $320 million. We are increasing our non-GAAP loss from operations guidance to a range of negative $115 million to negative $135 million.

轉向指導。正如 Tom 所提到的，我們預計第三季營收範圍為 7,400 萬美元至 7,800 萬美元，非 GAAP 營運虧損範圍為負 4,000 萬美元至負 4,600 萬美元。我們仍致力於在 24 財年第四季和 25 財年全年實現正現金流，並在 25 財年下半年實現非 GAAP 獲利能力。對於 24 年整個財年，我們維持先前 2.95 億至 3.2 億美元的營收指引。我們正在將營運指引中的非 GAAP 虧損增加至負 1.15 億美元至負 1.35 億美元的範圍。

I'd like to turn the call over to the operator to begin the Q&A session. Operator?

我想將電話轉給接線員開始問答環節。操作員？

Our first question comes from the line of Timothy Horan of Oppenheimer.

我們的第一個問題來自奧本海默的蒂莫西·霍蘭（Timothy Horan）。

Really appreciate the time. Can you give us a sense of what you're seeing with AI in terms of productivity improvements. And what is the major bottleneck that you think customers need to overcome to really start implementing services?

真的很感激這段時間。您能為我們介紹一下您所看到的人工智慧在生產力提高方面的效果嗎？您認為客戶需要克服的主要瓶頸是什麼才能真正開始實施服務？

I'm sorry, the question related to Gen AI?.

抱歉，問題與Gen AI有關？。

Yes. Specifically on Gen AI, what type of productivity improvements do you think customers can see on specific applications? And what is the major bottleneck for them adopting Gen AI.

是的。特別是在 Gen AI 方面，您認為客戶可以在特定應用程式上看到哪種類型的生產力改進？他們採用 Gen AI 的主要瓶頸是什麼？

The major bottleneck as it relates to generative AI relates to the problems that are inherent in these large language models, and they're very real. I mean, as you know, if you ChatGPT or Google Bard, both of which are like excellent products, but the answers tend to be stochastic. So every time you ask a question, getting them to answer, the -- if it doesn't know the answer, it hallucinates. The data access controls are not in force. So the CEO and the person on the factory floor to get access to the same information.

與生成人工智慧相關的主要瓶頸與這些大型語言模型固有的問題有關，而且它們是非常真實的。我的意思是，如您所知，如果您使用 ChatGPT 或 Google Bard，這兩者都是出色的產品，但答案往往是隨機的。所以每次你問一個問題，讓他們回答時，如果它不知道答案，它就會產生幻覺。資料存取控制未生效。因此執行長和工廠車間的人員可以獲得相同的資訊。

Where Carnegie Mellon and others are now identifying huge cybersecurity risk that are associated with these large language models to corporations and government entities. We have IP liability problems that people are concerned about because these large language models are trained on and have access to all the data into the Internet.

卡內基美隆大學和其他機構現在正在識別與這些大型語言模型給企業和政府實體相關的巨大網路安全風險。我們有人們擔心的智慧財產權責任問題，因為這些大型語言模型經過訓練並且可以存取網路上的所有資料。

This is like weather, the stock prices, what have you. Those -- somebody has the copyright to all those data, be it the weather company or Bloomberg, and they want to get money. So the quintals of the world are going to build big businesses litigating businesses issues in the next 10 years. We have -- so there's very real issues. The other issue relates to almost all the solutions that are being offered are LLM specific and in, say, December of 2023, to hook your wagon on any specific LLM is kind of crazy because next week, somebody is going to leave frocked by a factor of temps.

這就像天氣、股票價格等等。那些人擁有所有這些數據的版權，無論是氣象公司還是彭博社，他們都想賺錢。因此，世界上的公擔將在未來十年內建立大型企業，對企業問題進行訴訟。我們有——所以存在非常現實的問題。另一個問題涉及幾乎所有提供的解決方案都是特定於法學碩士的，比如說，在2023 年12 月，將你的馬車掛在任何特定的法學碩士上有點瘋狂，因為下週，有人會因為一個因素而離開。溫度。

You need to be able to switch, you need to be LLM agnostic. So I think those are really the hobgoblin cybersecurity hallucination information security that are basically making it, so many organizations will not allow any Generative AI application to be installed. What's unique about the C3 AI solution is when you talk about this some other time or you can look it up on the Internet.

你需要能夠轉換，你需要對法學碩士不可知。所以我認為這些實際上是網路安全幻覺資訊安全，因此許多組織不會允許安裝任何生成式人工智慧應用程式。 C3 AI 解決方案的獨特之處在於，您可以在其他時間談論這個問題，或者您可以在網路上找到它。

But by combining with the 14 years of work that we did with the C3 AI platform, we've addressed all those problems, cybersecurity, data security, hallucination, what have you. So I think that's the hobgoblin. That's what slows things down and people need to be satisfied to those issues resolved and if they're not resolved, and not being installed to some at any reasonable organization like General Motors or JPMorgan Chase or you name it.

但結合我們 14 年在 C3 AI 平台上所做的工作，我們已經解決了所有這些問題，網路安全、資料安全、幻覺等等。所以我認為這就是妖精。這就是減慢速度的原因，人們需要對這些已解決的問題感到滿意，如果問題沒有得到解決，而不是被安裝到任何合理的組織中，如通用汽車或摩根大通或你能想到的組織中。

Now as it relates to productivity increases, holy moly, they're going to be staggering, whether you're a lawyer, whether you're a realtor, whether you're a physician or whether you're running a paper machine or whether you're operating the inventory or the space command. I mean you -- if you do not have or not being supercharged by generative AI a year competition will be. And if they are, and you're not, they win, you lose, hard stock.

現在，當它涉及生產力的提高時，天哪，它們將是驚人的，無論你是律師，無論你是房地產經紀人，無論你是醫生還是運行造紙機或者你是否正在操作庫存或空間命令。我的意思是你——如果你沒有或沒有被生成人工智慧所增強，那麼一年的比賽將會是。如果他們是，而你不是，他們贏了，你輸了，硬股票。

So specifically to your customers, what do you think the bottleneck is for adoption? If you have -- it sounds like you have all these problems pretty much resolved for them. What do you think they require at this point to really start adopting?

那麼，對於您的客戶來說，您認為採用的瓶頸是什麼？如果你有——聽起來你已經為他們解決了所有這些問題。您認為他們此時需要什麼才能真正開始採用？

Well, we just -- our sales segments are pretty fast. Our sales cycles for generative AI has been close as 24 hours. And basically, our offering is, we'll bring the application live, in 1 or 2 months, if you like it for, I don't know, $0.25 million or something. And if you like it, keep it. So this has to do with people evaluating bond portfolios, people running paper machines, people running steel mills, the intelligence community, missile defense agency, others. So we just -- we -- many of them are existing C3 customers although increasingly, we will be serving 9 out of 10 will not be existing C3 customers.

嗯，我們只是 - 我們的銷售部門非常快。我們的生成式 AI 銷售週期接近 24 小時。基本上，我們的報價是，如果您喜歡的話，我們將在 1 或 2 個月內推出該應用程序，我不知道，我們將提供 25 萬美元或其他費用。如果你喜歡它，就保留它。因此，這與評估債券投資組合的人們、運作造紙機的人們、運作鋼廠的人們、情報界、飛彈防禦機構等有關。因此，我們只是 - 我們 - 他們中的許多人都是現有的 C3 客戶，儘管我們將越來越多地為十分之九的客戶提供服務，而不是現有的 C3 客戶。

But we have to address the concerns that identified. We seem to be able to address those. After that, we just bring the application live, we get it live in 4 to 8 weeks and if they like it, keep it and so it's a pretty short sales cycle for us, and you're seeing a very substantial increase in the pilots that we're deploying. You can expect -- we're expecting a pilot to production conversion rate of, it looks like about 70%. And -- so it does look like a big opportunity.

但我們必須解決所發現的問題。我們似乎能夠解決這些問題。之後，我們只需將應用程式上線，我們會在4 到8 週內上線，如果他們喜歡它，就保留它，所以這對我們來說是一個相當短的銷售週期，而且您會看到試點數量大幅增加我們正在部署的。你可以預期——我們預計試點到生產的轉換率約為 70%。而且——所以這看起來確實是一個巨大的機會。

(Operator Instructions)

（操作員說明）

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

我們的下一個問題來自尼達姆的邁克·西科斯（Mike Cikos）。

I wanted to ask first about the subscription gross margins, and this probably goes back to Juho's prepared remarks, but it was good to see gross margins actually increased sequentially despite the increased pilot count. And I know that you guys are calling out the short-term pressure just based on the growing mix of pilots. And so -- can you help us think about like what was it that actually went better for you guys? Because I think we were expecting a little bit more degradation in the subscription gross margins versus how you guys -- how the quarter actually came through?

我想先問訂閱毛利率，這可能可以追溯到 Juho 準備好的評論，但很高興看到毛利率實際上連續增加，儘管飛行員數量增加了。我知道你們只是因為飛行員數量的增加而大聲疾呼短期壓力。那麼——你能幫助我們思考什麼對你們來說實際上變得更好嗎？因為我認為我們預計訂閱毛利率會進一步下降，而你們這個季度的實際情況如何？

Thanks, Mike. This is Juho. So yes, in the big picture, as we announced 5 quarters ago, as we're seeing, we are expecting the gross margin degradation for the subscription to continue. Now in this particular quarter, we were very pleased to see some improvement on a sequential basis, but I think we would expect flattening to down again on the next quarter as the target count increases and is going to put pressure before the consumption amount start picking up and offsetting that.

謝謝，麥克。這是朱浩。所以，是的，從大局來看，正如我們在 5 個季度前宣布的那樣，正如我們所看到的，我們預計訂閱的毛利率將繼續下降。現在，在這個特定的季度，我們很高興看到環比有所改善，但我認為，隨著目標數量的增加，我們預計下個季度的情況將再次趨平，並且將在消費量開始回升之前施加壓力並抵消它。

Got it. And if I just shift down to OpEx for a second as well. I guess 2 quarters here. So first, I know that you guys are increasing the anticipated operating losses here. Last quarter, we had cited increased investment in like branding and lead gen and awareness, right? So can you help us think through where you guys are doubling down?

知道了。如果我也轉向營運支出一秒鐘。我想這裡有兩個季度。首先，我知道你們正在增加這裡的預期營運損失。上個季度，我們提到了在品牌、潛在客戶發掘和知名度等方面的投資增加，對吧？那麼你能幫助我們思考一下你們在哪些方面加倍努力嗎？

And then the second piece there, there was obviously that article that came out in Bloomberg, I think it was in mid- to late November citing head count costs -- head count cutting, I'm sorry. So can you just comment on the validity of the Bloomberg article just because I think people are trying to see if you did make those head count cuts, how much are we doubling down on these investments or if that had article proved to be false?

然後是第二篇文章，顯然是彭博社發表的那篇文章，我認為那是在 11 月中下旬，引用了員工人數成本——員工人數削減，我很抱歉。那麼，您能否就彭博社文章的有效性發表評論，因為我認為人們想知道您是否確實進行了裁員，我們在這些投資上加倍了多少，或者該文章是否被證明是錯誤的？

Mark, it's Tom. Doubling down. We're doubling down on data scientists. We're doubling down on large language model engineers, we're doubling down. A lot of it is going into engineering, but also candidly in lead generation. I mean there's an opportunity now as we move to these marketplaces to be dealing transactions in hundreds to thousands to tens of thousands of units rather than scores.

馬克，是湯姆。加倍。我們正在加倍投入資料科學家。我們正在加倍投入大型語言模型工程師，我們正在加倍投入。其中許多都投入了工程設計中，但坦白說，也投入了潛在客戶開發。我的意思是，當我們轉向這些市場時，現在有機會處理數百到數千到數萬單位而不是數十單位的交易。

And that I can assure you is the plan that we have. As it relates to -- I'm not familiar with Bloomberg article that you talked about. It sounds like somebody mentioned something that we did some layoffs in the quarter. Mike, we do performance-related layoffs every quarter, okay?

我可以向你保證這就是我們的計劃。因為它涉及——我不熟悉你談到的彭博文章。聽起來有人提到我們在本季進行了一些裁員。麥克，我們每季都會進行與績效相關的裁員，好嗎？

And the -- so we -- I think last quarter, we had 42,000 job applicants. We -- how many people did we hire, Juho?

我想上個季度，我們有 42,000 名求職者。我們－我們僱用了多少人，Juho？

Order of 100.

訂購 100 個。

Order of 100. And these people, yes, they went to MAT. Yes, they worked at Bank of America. Yes, they went to Chicago GSB and they command an F18 squadron. And so we're constantly upgrading our human capital, and we move underperformers out regularly. So if somebody said that in a Bloomberg article -- I don't know what they said. What I told you is the truth.

100 人。這些人，是的，他們去了 MAT。是的，他們在美國銀行工作。是的，他們去了芝加哥 GSB，指揮著一個 F18 中隊。因此，我們不斷提升人力資本，並定期淘汰表現不佳的員工。因此，如果有人在彭博社的文章中這麼說——我不知道他們說了什麼。我告訴你的是事實。

Our next question comes from the line of Kingsley Crane of Canaccord Genuity.

我們的下一個問題來自 Canaccord Genuity 的 Kingsley Crane。

I wanted to touch on the pilot program. You mentioned that you'd move to a lower entry price point for pilots. Could you give us a sense of the magnitude of that change and then has the minimum fee post pilot also changed? I'm curious what kind of upsell you're seeing upon conversion, if any?

我想談談試點計劃。您提到您會降低試點的入門價格。您能否讓我們了解一下這項變更的幅度以及試點後的最低費用是否也發生了變化？我很好奇您在轉換後看到了什麼樣的追加銷售（如果有的話）？

Kingsley, it's Tom. I think the standard pilot that we have at Generative AI and the enterprise is like $250,000. But that being said, you can get the AWS -- Generative AI for AWS, which basically handles documents like every other LLM, it handles tax. It's not really multimodal, but that's free for 14 days. So that would be pretty available. Is there a question that he asked that I didn't answer?

金斯利，是湯姆。我認為我們在 Generative AI 和企業中的標準試點大約是 25 萬美元。但話雖這麼說，你可以獲得 AWS——AWS 的生成人工智慧，它基本上像其他法學碩士一樣處理文檔，它處理稅務。它並不是真正的多式聯運，但可以免費使用 14 天。所以這將是非常可用的。是不是有什麼問題他問了我卻沒有回答？

No, that's all I think.

不，我就是這麼想的。

Okay. Yes. That's helpful. And I just want to touch on OpEx as well. So I think it makes sense that you want to invest more in both LLM engineers and lead gen and it looks like that's particularly hitting harder in Q4 of this year. But as we think about fiscal '25, it seems like some of the nature of those investments would naturally continue as you scale in this large opportunities. So is it about timing in this year? Or are you expecting those to continue next year?

好的。是的。這很有幫助。我也想談談營運支出。因此，我認為您希望對法學碩士工程師和潛在客戶進行更多投資是有道理的，而且看起來今年第四季的打擊尤其更大。但當我們考慮 25 財年時，隨著您擴大這一巨大機會，這些投資的某些性質似乎會自然地繼續下去。那麼今年的時間安排是這樣的嗎？或者你預計這些明年還會繼續嗎？

Well, Kingsley, I expect them to continue next year. But if you look at the guidance that we gave you in terms -- about 6 quarters ago, what we see is the consumption over the first 12 quarters in terms of CPU seconds per new customer. We just did an analysis of -- I don't know, about 30 customers or 12 customers and those data that we predicted, I think 6 or 7 quarters ago and provided you, it's uncanny and how accurate it is. It's basically plus or minus 10%.

好吧，金斯利，我希望他們明年繼續。但是，如果您查看我們在大約 6 個季度前為您提供的指導，我們會看到前 12 個季度的每個新客戶的 CPU 秒數消耗情況。我們剛剛對大約 30 個客戶或 12 個客戶以及我們在 6 或 7 個季度前預測的數據進行了分析，並向您提供了這些數據，這非常不可思議，而且非常準確。基本上是正負10%。

And so if you look, as these things kick in, in quarter 5, 6, 7 and 8, the consumption numbers get pretty big. So you can expect for that we don't really need to cut back on the investments to get to the point of cash positive and non-GAAP profitable. So the top line kind of takes care of that.

因此，如果你看一下，隨著這些事情在第 5、6、7 和 8 季開始，消費數字會變得相當大。因此，您可以預期，我們實際上並不需要削減投資就能達到現金正值和非公認會計原則獲利的程度。所以頂線負責處理這個問題。

Our next question comes from the line of Sanjit Singh of Morgan Stanley.

我們的下一個問題來自摩根士丹利的桑吉特辛格。

Great. This is [Theon] for Sanjit. Tom, maybe starting with you. I mean, with a couple of quarters of the consumption model now under your belt, clearly, you're seeing a lot of sort of quantity of deals and pilots. Is there any way that you can frame or give us a sense of the quality of those customers that went with the consumption model early on. I guess any sort of scale in terms of spending or growth profile that they're hitting now that you can kind of shed up some light and give us the quality piece where you've given us, I think, a lot on kind of the quantity piece of those yields? And then for you or maybe.

偉大的。這是 Sanjit 的 [Theon]。湯姆，也許從你開始。我的意思是，現在你已經掌握了幾個季度的消費模式，顯然，你會看到大量的交易和試點。有什麼方法可以讓我們了解那些早期採用這種消費模式的客戶的品質嗎？我想他們現在所達到的支出或增長狀況方面的任何規模，你都可以透露一些信息，並為我們提供高質量的內容，我認為，你已經給了我們很多關於這些產量的數量？然後為你或也許。

Could you just give us some color on the subscription revenue versus the services revenue this quarter? And then also maybe the partner impact and sort of what that looks like on a go-forward basis.

您能為我們介紹一下本季的訂閱收入與服務收入嗎？然後也許還有合作夥伴的影響以及未來的情況。

Sanjit (sic) [Theon], Okay. Regarding quality, I think there's only 2 ways to look at pilot quality. It's going to be what's the conversion rate, okay? And what's -- and what are they going to consume. Based upon our best guess at this time, based on looking at every path we have out there, going to look at what actually has converted and what we think we will convert. We think our guesstimate that we gave you 6 or 7 quarters ago, 70% is about right. So there's one indication of quality.

Sanjit（原文如此）[Theon]，好的。關於質量，我認為只有兩種方法來看待飛行員的質量。轉換率是多少，好嗎？他們將消費什麼？基於我們目前的最佳猜測，基於對我們現有的每一條路徑的觀察，我們將看看實際已經轉換的內容以及我們認為將轉換的內容。我們認為我們在 6 或 7 個季度前給您的猜測 70% 大約是正確的。因此，品質有一個指標。

The other indication of quality is how many CPU seconds are they consuming? Okay, over -- as you go from quarter 0 to quarter 12. And it's tracking right in line. I mean it varies a little bit from 1 quarter to another, but it's basically right in line with what we told you. The quality is pretty high. Now that being said, as we move now to mass markets and start dealing with hundreds of thousands of people just either kind of ordering this online and playing with it, you're going to expect that conversion rate from that level of pilot to be I would say, I mean, the quality there will be much lower.

品質的另一個指標是它們消耗了多少 CPU 秒？好的，結束了——從第 0 季到第 12 季。它正在按順序進行。我的意思是，每個季度的情況略有不同，但基本上與我們告訴您的相符。品質相當高。話雖這麼說，當我們現在轉向大眾市場並開始與數十萬人打交道時，無論是在線訂購還是玩它，您都會期望該級別的試點的轉換率是我會說，我的意思是，那裡的品質會低很多。

And I think we need to measure quality by conversion rate and concession levels. A lot of those people will try it for 5 minutes and drop off. And that's just the way that it is with 3 stuff. Now the rest of the question, I think, goes to you.

我認為我們需要透過轉換率和優惠水平來衡量品質。很多人會嘗試 5 分鐘就放棄了。這就是 3 個東西的情況。我想現在剩下的問題就交給你了。

Yes, right. So your second part about subscription versus services. So we were 9.3 -- 9.2% professional services, this period, which is a little bit lighter than our expected long-term model of 10% to 20% on professional services. We continue to expect that we will be at that range on a go-forward basis. And then I think you were asking about how we feel about the partners in a go-forward basis. And partners are hugely important for us, and we continue to believe that they're the key part of our go-to-market approach going forward.

是的，沒錯。所以你的第二部分是關於訂閱與服務。因此，這段期間我們的專業服務佔比為 9.3 - 9.2%，比我們預期的專業服務 10% 至 20% 的長期模式要輕一些。我們繼續預計我們將在未來的基礎上保持在這個範圍內。然後我想你問的是我們對夥伴未來的看法。合作夥伴對我們來說非常重要，我們仍然相信他們是我們未來進入市場的關鍵部分。

It looks like we have time for one last question. Our last question will be from Pat Walravens of JMP Security.

看來我們還有時間回答最後一個問題。我們的最後一個問題將來自 JMP Security 的 Pat Walravens。

This is Owen Hobbs, on for Pat. I guess first one for Tom. What would you say are the top 1 or 2 federal use cases for Generative AI that you're seeing with those new -- those 5 new federal degenerative AI deals this quarter?

我是歐文‧霍布斯，替帕特發言。我想第一個是給湯姆的。您認為您在本季度看到的 5 項新的聯邦退化人工智慧交易中看到的最重要的 1 或 2 個聯邦生成人工智慧用例是什麼？

Our largest federal use case, as you know, is predictive maintenance to the United States Air Force, okay? This was chosen by the Chief of Staff and we now are doing that, this is the Panda system which is the only AI system of record that we're aware of in all of DoD. So this is a system record for the Air Force for predictive maintenance for all assets.

如您所知，我們最大的聯邦用例是美國空軍的預測性維護，好嗎？這是由參謀長選擇的，我們現在正在這樣做，這就是 Panda 系統，它是我們所知的整個國防部唯一的人工智慧記錄系統。這是空軍所有資產預測性維護的系統記錄。

So far, we have loaded the data, I believe, from 22 weapon systems. F-15, F-16, F-18, F-35, KC-135 F-22, et cetera, into unified federated image. This is 100 terabytes of day, okay? Some of it is maintenance data, sorting data, inventory data, flight data, flight history, telemetry and one aircraft like B-50 each B1 bomber has 42,000 sensors on it, admitting telemetry, and I'm not sure what hertz cycles but pretty fast. So this is a stack of data, okay? I will be there on Monday, that is by next Monday. I will be in Washington, D.C., showing the list to our customers with a Generative AI front end. So think about this as a Mosaic browser front end where a general officer can ask any question about -- and this a 100-terabyte production system.

到目前為止，我相信我們已經加載了來自 22 個武器系統的數據。 F-15、F-16、F-18、F-35、KC-135、F-22 等，形成統一的聯合影像。這是一天 100 TB，好嗎？其中一些是維護數據、分類數據、庫存數據、飛行數據、飛行歷史記錄、遙測數據和一架像B-50 這樣的飛機，每架B1 轟炸機上都有42,000 個感測器，承認遙測數據，我不確定赫茲週期是多少，但很漂亮快速地。所以這是一堆數據，好嗎？我周一會到那裡，也就是下週一。我將在華盛頓特區，透過生成式人工智慧前端向我們的客戶展示該清單。因此，可以將其視為 Mosaic 瀏覽器前端，將軍可以在其中提出任何問題 - 這是一個 100 TB 的生產系統。

This is one of the largest production enterprise AI applications in existence, okay? And that person will be able to ask on Monday. Be able to ask any question that you could ask of the weapon system, for example, where craft are operative at Travis Air Force base now? What is my cost of operating the B-1 bottler program in the last year, okay? What is the -- as it relates to F-35, where are my largest part shortages. And rather than going through some cold war era, menu-based SAP or even Cboe, I don't want to take shots at SAP enterprise information system user interface that it constantly can looks like your Bloomberg terminal, okay, which is -- I have one I might guess it's unusable. The -- it'll just be a Mosaic browser, you could ask any questions and get the answer related to any one of these weapon systems in the United States Air Force. I guess their production data. And we will show it on Monday, on Tuesday, on Wednesday, and I am telling you we expect some light bulbs to flash.

這是現有最大的生產企業人工智慧應用之一，好嗎？那個人可以在周一提出詢問。能夠提出有關武器系統的任何問題，例如，特拉維斯空軍基地的飛行器現在在哪裡運行？我去年營運 B-1 裝瓶商計畫的成本是多少？與 F-35 相關的是，我最大的零件短缺在哪裡。我不想經歷一些冷戰時代、基於選單的 SAP 甚至 Cboe，我不想對 SAP 企業資訊系統使用者介面進行攻擊，它總是看起來像你的彭博終端，好吧，那就是——我有一個我可能猜它無法使用。它只是一個 Mosaic 瀏覽器，您可以提出任何問題並獲得與美國空軍的任何一種武器系統相關的答案。我猜他們的生產數據。我們將在周一、週二、週三展示它，我告訴你們，我們預計會有一些燈泡閃爍。

And if I could sneak one last one in for you Juho. Can you please explain the dynamics between the increase in accounts receivable from last quarter to this quarter despite revenues kind of staying flattish?

如果我能為你偷偷帶上最後一張 Juho 的話。您能否解釋儘管收入持平，但從上季度到本季應收帳款成長之間的動態？

Well, accounts receivable is timing of invoicing. So obviously, when we drop an invoice, it shows up in the accounts receivable. So it's just timing of invoicing.

那麼，應收帳款就是開立發票的時間。顯然，當我們刪除發票時，它會顯示在應收帳款中。所以這只是發票的時間。

Ladies and gentlemen, I think we're at end of program. We appreciate your time and your attention. And thank you very much, and we look forward to talking with you next quarter, standby, it does appear to be a game on in the AI industry at global scale, and I can assure you we are very much in the game. So, thank you all, and we're signing off.

女士們先生們，我想我們的計畫已經結束了。我們感謝您的時間和關注。非常感謝您，我們期待下個季度與您交談，等待，這似乎確實是全球範圍內人工智慧行業的一場遊戲，我可以向您保證，我們非常參與其中。所以，謝謝大家，我們就結束了。

Thank you. Ladies and gentlemen, this does conclude today's conference. Thank you all for participating, and have a good night. You may now disconnect.

謝謝。女士們、先生們，今天的會議到此結束。感謝大家的參與，祝大家有個美好的夜晚。您現在可以斷開連線。