Snowflake Inc (SNOW) 2025 Q4 法說會逐字稿

Good afternoon.

午安.

Thank you for attending the Q4 fiscal year '25 Snowflake earnings conference call.

感謝您參加25財年第四季Snowflake收益電話會議。

My name is Matt and I'll be your moderator for today's call.

我叫馬特，我將擔任今天電話會議的主持人。

(Operator Instructions)

（操作員指令）

I'll now have to pass the conference over to our host, Jimmy Sexton, Head of Investor Relations.

現在我必須將會議交給我們的主持人、投資者關係主管吉米·塞克斯頓 (Jimmy Sexton)。

Jimmy, please go ahead.

吉米，請繼續。

Good afternoon and thank you for joining us on Snowflake's Q4 fiscal 2025 earnings call.

下午好，感謝您參加 Snowflake 2025 財年第四季財報電話會議。

Joining me on the call today are Sridhar Ramaswamy, our Chief Executive Office; Mike Scarpelli, our Chief Financial Officer; and Christian Kleinerman, our Executive Vice President of Product, who will participate in the Q&A session.

今天與我一起參加電話會議的還有我們的執行長 Sridhar Ramaswamy；我們的財務長 Mike Scarpelli；以及我們的產品執行副總裁 Christian Kleinerman，他將參加問答環節。

During today's call, we will review our financial results for the fourth quarter of fiscal 2025 and discuss our guidance for the first quarter in full year fiscal 2026.

在今天的電話會議上，我們將回顧 2025 財年第四季的財務業績，並討論 2026 財年全年第一季的指引。

During today's call, we will make forward-looking statements, including statements related to our business operations and financial performance.

在今天的電話會議中，我們將做出前瞻性陳述，包括與我們的業務營運和財務績效相關的陳述。

These statements are subject to cause them to differ materially from our actual results.

這些聲明可能會與我們的實際結果有重大差異。

Information containing these risks and uncertainties is available in our earnings press release, our most recent Forms 10-K, and our other SEC reports.

包含這些風險和不確定性的資訊可在我們的收益新聞稿、我們最新的 10-K 表格和我們的其他 SEC 報告中找到。

All our statements are made as of today based on information currently available to us.

我們所有的聲明都是根據今天掌握的資訊做出的。

Except as required by law, we assume no obligation to update any such statements.

除法律要求外，我們不承擔更新任何此類聲明的義務。

During today's call, we will also discuss certain non-GAAP financial measures.

在今天的電話會議中，我們還將討論某些非公認會計準則財務指標。

See our investor presentation for a reconciliation of GAAP to non-GAAP measures and business metric definitions, including adoption.

請參閱我們的投資者報告，以了解 GAAP 與非 GAAP 指標和業務指標定義的對照，包括採用情況。

The earnings press release and investor presentation are available on our website at investors.snowflake.com. A replay of today's call will also be posted on the website.

收益新聞稿和投資者介紹可在我們的網站 investor.snowflake.com 上查閱。今天的電話會議重播也將發佈在網站上。

With that, I would now like to turn the call over to Sridhar.

說完這些，我現在想把電話轉給 Sridhar。

Thanks, Jimmy, and hi, everyone.

謝謝，吉米，大家好。

Thank you, all, for joining us today.

感謝大家今天的參與。

What a difference a year makes.

一年的時間發生了多大的變化。

It was on this call last year, but it was introduced to you as Snowflake's new CEO.

這是在去年的電話會議上提出的，但當時是作為 Snowflake 新任執行長向你介紹的。

I look at the progress we've made in just one year, and I could not be more proud of our team.

看到我們在短短一年內的進步，我為我們的團隊感到無比自豪。

Our core business is very strong.

我們的核心業務非常強大。

Our product delivery is in overdrive, and our go-to-market engine is humming.

我們的產品交付正在超速發展，我們的市場引擎正在嗡嗡作響。

We're innovating better than ever and fighting on all cylinders, and we have an enormous opportunity ahead of us.

我們的創新能力比以往任何時候都要強，我們全力以赴，面前有巨大的機會。

Right now, Snowflake is the most consequential data and AI company on the planet.

目前，Snowflake 是全球最重要的數據和人工智慧公司。

As I said in our third-quarter call, our North Star is to deliver the world's best end-to-end data platform powered by AI.

正如我在第三季電話會議上所說，我們的北極星是提供由人工智慧驅動的全球最好的端到端資料平台。

And we are making great progress every day to deliver on that vision.

為了實現這個願景，我們每天都在取得巨大進步。

I'm incredibly proud of the operational rigor we have incorporated into our company, delivering greater efficiency, while also aggressively investing and delivering on growth.

我對我們公司所體現的嚴謹營運精神感到無比自豪，它不僅提高了效率，還積極投資並實現了成長。

And our focus on our customers has never been stronger.

我們對客戶的關注從未如此強烈。

We continue to hear how easy and cost effective our platform is.

我們不斷聽到人們說我們的平台是多麼簡單且經濟高效。

And we're hitting more and more multi-product adoption because of the tremendous value we are delivering to our customers.

由於我們為客戶提供了巨大的價值，我們的多產品採用率正在不斷提高。

We're keeping our foot on the gas.

我們正加大油門。

We are building on our strengths and going after the opportunities ahead with urgency and focus to ensure we continue our strong momentum throughout this year.

我們正在發揮我們的優勢，並緊迫而集中地抓住未來的機遇，以確保我們在今年全年繼續保持強勁勢頭。

You can see this progress in our strong fourth-quarter results, and we're just getting started.

您可以從我們強勁的第四季度業績中看到這一進展，而我們才剛剛起步。

Product revenue for Q4 was $943 million, up a strong 28% year over year.

第四季產品營收為 9.43 億美元，較去年同期強勁成長 28%。

The remaining performance obligations totaled $6.9 billion with year-over-year growth of 33%.

剩餘履約義務總額為 69 億美元，年增 33%。

Our net revenue retention was a very healthy 126%.

我們的淨收入保留率達到非常健康的126%。

In the quarter, our non-GAAP operating margin increased to 9%.

本季度，我們的非公認會計準則營業利潤率成長至 9%。

And our non-GAAP adjusted free cash flow margin was 43%.

我們的非公認會計準則調整後自由現金流利潤率為 43%。

As you can see, we delivered another quarter of strong revenue growth and overall, very healthy results.

正如您所看到的，我們又一個季度實現了強勁的營收成長，整體而言，業績非常健康。

As I said last quarter, we are obsessed with driving product cohesion.

正如我上個季度所說，我們熱衷於推動產品凝聚力。

We are continuing to win in the market because Snowflake is easy to use, helps customers break down silos to collaborate and be connected, and is trusted by companies of all sizes and industries.

我們之所以能夠繼續在市場上獲勝，是因為 Snowflake 易於使用、能夠幫助客戶打破孤島進行協作和連接，並且受到各種規模和行業的公司的信賴。

This is why iconic brands like ExxonMobil, Honeywell, the London Stock Exchange Group, and thousands more are betting their business on Snowflake.

這就是為什麼埃克森美孚、霍尼韋爾、倫敦證券交易所集團等數千家知名品牌都將業務押注於 Snowflake 的原因。

Fiserv, a global provider of payments and financial technology, for example, is transforming how businesses and financial institutions use data by providing them with their own analytics platform through Snowflake.

例如，全球支付和金融科技供應商 Fiserv 正在透過 Snowflake 為企業和金融機構提供自己的分析平台，改變企業和金融機構使用資料的方式。

This empowers Fiserv customers to have access to insights from their transaction data, combine it with market information, and train their own AI models, enabling smarter business decisions that were previously only possible for large enterprise.

這使得 Fiserv 的客戶能夠從他們的交易資料中獲取洞察，將其與市場資訊結合，並訓練他們自己的 AI 模型，從而做出以前只有大型企業才能做出的更明智的商業決策。

Last quarter, we had our BUILD Summit, our biggest event of the year for our builders and developers, followed by regional meetups and events all around the world.

上個季度，我們舉辦了 BUILD 高峰會，這是我們今年為建築商和開發商舉辦的最大活動，隨後我們在世界各地舉辦了區域聚會和活動。

So far, a record of more than 20,000 attendees have joined these events, showing incredible momentum and excitement for our product vision.

到目前為止，已有超過 20,000 名與會者參加了這些活動，顯示出我們產品願景的驚人發展勢頭和興奮之情。

We continue to hear how we are making it simpler to develop, build, and innovate on our platform.

我們不斷了解如何使我們平台上的開發、建置和創新變得更簡單。

More and more customers are switching to Snowflake and realizing the incredible ease of use and cost savings our platform delivers.

越來越多的客戶轉向 Snowflake，並意識到我們的平台提供的令人難以置信的易用性和成本節省。

We're also helping our customers develop entirely new revenue streams to monetize their data.

我們也幫助我們的客戶開發全新的收入來源，以實現數據貨幣化。

For example, supply chain leader Blue Yonder leverages Snowflake's robust data management capabilities and scale to help companies transform their operations by offering AI-powered insights.

例如，供應鏈領導者 Blue Yonder 利用 Snowflake 強大的資料管理能力和規模，透過提供人工智慧支援的洞察力來幫助公司轉變營運方式。

The Blue Yonder platform processes over 20 billion AI predictions daily to help retailers, manufacturers, and logistics providers better manage inventory, optimize deliveries, and respond to disruptions.

Blue Yonder 平台每天處理超過 200 億個 AI 預測，幫助零售商、製造商和物流供應商更好地管理庫存、優化交付和應對中斷。

It enables their customers to access powerful supply chain intelligence that would be impossible to build on their own.

它使他們的客戶能夠存取強大的供應鏈情報，而這是他們自己無法建立的。

As our competitors continue to require expensive engineering resources to maintain and scale, more and more customers are seeing real bottom-line impact by turning to Snowflake.

由於我們的競爭對手繼續需要昂貴的工程資源來維護和擴展，越來越多的客戶透過轉向 Snowflake 看到了真正的底線影響。

We have seen more and more Snowflake customers save over 50% by migrating to us from other providers.

我們看到越來越多的 Snowflake 客戶從其他供應商遷移到我們這裡，節省了 50% 以上的費用。

In fact, we recently announced that SnowConvert, Snowflake's native code conversion tooling, is now free for anyone to help accelerate migrations from Oracle, Teradata, and many other systems to realize these benefits in data analytics.

事實上，我們最近宣布，Snowflake 的本機程式碼轉換工具 SnowConvert 現在可供任何人免費使用，以協助加速從 Oracle、Teradata 和許多其他系統的遷移，從而在資料分析中實現這些好處。

Snowflake is also the de facto circulatory system in the enterprise world, the ability to collaborate and share data is one of our core differentiators.

Snowflake也是企業界事實上的循環系統，協作和分享資料的能力是我們的核心差異化因素之一。

We are seeing strong adoption of our data sharing capabilities with customers like Stripe, NTT, and Braze, which each have active data sharing connections with over 160 partner and customer organizations.

我們看到 Stripe、NTT 和 Braze 等客戶廣泛採用我們的資料共享功能，這些客戶都與 160 多個合作夥伴和客戶組織建立了活躍的資料共享連接。

These connections enable them to securely exchange data with their partners and customers, driving value across our ecosystem.

這些連結使他們能夠安全地與合作夥伴和客戶交換數據，從而為我們的整個生態系統帶來價值。

We are continuing to innovate at lightning speed.

我們正以閃電般的速度不斷創新。

This past year, we brought over 400 product capabilities to market, over double the amount we launched the previous year.

去年，我們向市場推出了 400 多種產品，數量是前一年的兩倍多。

We have seen incredible growth in our data engineering business and continue to see strong adoption of open data formats, especially truly open modern data formats like Apache Iceberg, which is transforming how organizations manage and query data at scale.

我們的資料工程業務取得了令人難以置信的成長，並且繼續看到開放資料格式的廣泛採用，特別是像 Apache Iceberg 這樣真正開放的現代資料格式，它正在改變組織管理和查詢大規模資料的方式。

We have also seen amazing growth in the number of companies building and collaborating on Snowflake to over one-third of our capacity customers collaborating with data on a regular basis.

我們也看到，在 Snowflake 上建立和協作的公司數量驚人地成長，超過三分之一的客戶定期進行資料協作。

When it comes to AI, last year was foundational for us.

對人工智慧來說，去年對我們來說是基礎性的一年。

We introduced Cortex AI, which is now being used by customers to seamlessly build data agents for both structured and unstructured data with state-of-the-art retrieval using Cortex Search and Analyst.

我們推出了 Cortex AI，目前客戶正在使用它來無縫建立結構化和非結構化資料的資料代理，並使用 Cortex Search 和 Analyst 進行最先進的檢索。

We are supporting a range of market-leading models, including Anthropic's Claude, Meta's Llama, and DeepSeek.

我們支持一系列市場領先的模型，包括 Anthropic 的 Claude、Meta 的 Llama 和 DeepSeek。

And I'm sure, you saw that we just announced our expanded partnership with Microsoft that brings OpenAI's models into Cortex.

我相信您已經看到，我們剛剛宣布擴大與微軟的合作關係，將 OpenAI 的模型引入 Cortex。

This makes us the only data platform to seamlessly host both Anthropic and OpenAI, world-leading models enabling our customers to build data agents while ensuring that their data remains secure in Snowflake.

這使我們成為唯一無縫託管 Anthropic 和 OpenAI 的資料平台，世界領先的模式使我們的客戶能夠建立資料代理，同時確保他們的資料在 Snowflake 中保持安全。

And just a few weeks ago, we introduced Cortex Agents, a world-class agent orchestration framework to enable seamless planning and execution across structured and unstructured data, all powered by leading models such as Anthtropic's Claude.

就在幾週前，我們推出了 Cortex Agents，這是一個世界一流的代理編排框架，可實現跨結構化和非結構化資料的無縫規劃和執行，所有這些都由 Anthtropic 的 Claude 等領先模型提供支援。

They leveraged Cortex Analyst and Cortex Search to deliver state-of-the-art accuracy along with enterprise-grade reliability and governance so customers can build agents at scale.

他們利用 Cortex Analyst 和 Cortex Search 提供最先進的準確性以及企業級可靠性和治理，以便客戶可以大規模建立代理商。

And today, we announced that we are deepening ownership with Microsoft.

今天，我們宣布將深化與微軟的所有權合作。

We are making Cortex Agents available in Microsoft 365 Copilot and Microsoft Teams, bringing millions of users, seamless access to information, and accelerated productivity, all within the Microsoft platform.

我們正在 Microsoft 365 Copilot 和 Microsoft Teams 中提供 Cortex Agents，為數百萬用戶帶來無縫資訊存取和加速生產力，所有這些都在 Microsoft 平台內完成。

All of these innovations are focused on driving real value for our customers.

所有這些創新都致力於為我們的客戶創造真正的價值。

They make it easy for people to create a chatbot on structured or unstructured data.

它們使人們可以輕鬆地在結構化或非結構化資料上創建聊天機器人。

And these in turn are the essential building block for a strong AI foundation as we head to the next inflection point with Agents.

當我們與代理商一起邁向下一個轉折點時，這些反過來又是強大人工智慧基礎的基本構成要素。

We now have over 4,000 customers using our AI and ML technology on a weekly basis.

現在，每周有超過 4,000 名客戶使用我們的 AI 和 ML 技術。

Take AstraZeneca.

以阿斯特捷利康為例。

They are harnessing the power of data in Snowflake to revolutionize healthcare by making its data AI-ready.

他們正在利用 Snowflake 的數據力量，透過使數據實現 AI 化來徹底改變醫療保健。

By unifying their research data, they're accelerating drug discovery and clinical development to deliver life-saving medicines to patients faster, working towards their ambitious goal of 20 new medicines by 2030.

透過統一研究數據，他們正在加速藥物發現和臨床開發，以便更快地向患者提供救命的藥物，並努力實現 2030 年推出 20 種新藥的宏偉目標。

And State Street, which manages 10% of the world's financial assets, is using Snowflake AI and machine learning to uncover new market insight that help financial institutions make better investment decisions.

管理全球 10% 金融資產的道富銀行正在使用 Snowflake AI 和機器學習來發現新的市場洞察，幫助金融機構做出更好的投資決策。

As our AI offerings continue to scale at lightning speed, our core business continues to be incredibly strong.

隨著我們的人工智慧產品繼續以閃電般的速度擴展，我們的核心業務繼續保持強勁勢頭。

We have talked a lot about delivering on our vision of being the end-to-end technology provider for our customers' data journey.

我們已經多次討論如何實現我們的願景，即成為客戶資料旅程的端到端技術提供者。

Already, we are introducing additional Snowflake connectors in private preview, leveraging the technology from our acquisition of Datavolo to provide seamless connectivity and data integration.

我們已經在私人預覽中引入了額外的 Snowflake 連接器，利用我們收購的 Datavolo 的技術提供無縫連接和資料整合。

With key platforms like SharePoint, Google Drive, Workday, Slack and many more, our customers are loving this capability, and we have strengthened our foundation to deliver an extensible and flexible connectivity platform for unstructured data as well as structured data.

透過 SharePoint、Google Drive、Workday、Slack 等主要平台，我們的客戶非常喜歡這種功能，並且我們加強了基礎，為非結構化資料和結構化資料提供可擴展且靈活的連接平台。

As we continue to bring new innovations to market, we are focused on scaling efficiency.

隨著我們不斷將新的創新推向市場，我們專注於擴大效率。

We are investing in the growth of our go-to-market operations and maintaining our seamless collaboration between engineering, product, marketing, and sales to bring products to market effectively, delivering more value to existing customers as well as winning new ones.

我們正在投資於行銷業務的成長，並保持工程、產品、行銷和銷售之間的無縫協作，以有效地將產品推向市場，為現有客戶提供更多價值並贏得新客戶。

Using our Cortex AI technology, our GTM teams can now quickly discover the most relevant sales content by asking natural language questions of our sales knowledge assistant.

利用我們的 Cortex AI 技術，我們的 GTM 團隊現在可以透過向我們的銷售知識助理詢問自然語言問題來快速發現最相關的銷售內容。

And with our fast stream of the data, they can get deep insight into our customers' consumption trends in our Customer 360 app.

透過我們快速的數據流，他們可以在我們的客戶 360 應用程式中深入了解客戶的消費趨勢。

You'll also see our emphasis on rigor and efficiency in our growth plan.

您還會看到我們的成長計劃強調嚴謹性和效率。

Our headcount growth over the next year is focused on engineering and sales, which are teams with direct impact to revenue.

我們明年的員工數量成長將集中在工程和銷售方面，這兩個團隊對收入有直接影響。

We are using AI internally to drive efficiency in incredible rates.

我們正在內部使用人工智慧來以驚人的速度提高效率。

Our teams are able to tap into a wealth of data and information faster than ever before.

我們的團隊能夠比以往更快地利用大量數據和資訊。

It is this operational rigor that we instituted in fiscal '25 that is now our way of life going forward, investing in growth while having a maniacal focus on driving efficiency throughout our business.

我們在 25 財年制定的這種營運嚴謹性現在已成為我們未來的生活方式，我們在投資成長的同時，高度重視提高整個業務的效率。

Mike, why don't you take us through more of the financial details?

麥克，你為什麼不向我們詳細介紹一下財務細節呢？

Thank you, Sridhar.

謝謝你，Sridhar。

In FY25, product revenue grew 30% year over year to reach $3.5 billion.

25財年，產品營收年增30%，達35億美元。

Our core business is strong.

我們的核心業務非常強勁。

We continue to see stable consumption patterns as evidenced by our 126 net revenue retention rate.

我們的淨收入保留率達到 126，證明我們的消費模式持續保持穩定。

New products are becoming an important growth driver.

新產品正成為重要的成長動力。

Snowpark contributed 3% of FY25 product revenue and we are seeing strong adoption of our new data engineering and AI features.

Snowpark 貢獻了 25 財年產品收入的 3%，我們看到我們的新資料工程和 AI 功能得到了廣泛的採用。

In Q4, technology customers outperformed while financial services continues to be our top vertical, EMEA with another strength -- source of strength.

在第四季度，技術客戶表現出色，而金融服務仍然是我們的首要垂直領域，而歐洲、中東和非洲地區則是我們另一個優勢——力量的來源。

The Q4 holiday impact was consistent with our expectations.

第四季假期的影響與我們的預期一致。

Remaining performance obligations grew 33% year over year.

剩餘履約義務年增33%。

During the quarter, several large customers ran out of capacity before their contract end date as the revenue outpaced their contracted bookings.

在本季度，由於收入超過了合約預訂量，幾家大客戶在合約結束日期之前就用完了產能。

And so instead of pulling forward the renewal cycle, these accounts are now purchasing as they consume.

因此，這些帳戶不再提前續訂週期，而是在消費時購買。

This is common for large customers, and we do not view this choice as indicative of their future consumption patterns.

對於大客戶來說，這種情況很常見，我們不認為這種選擇代表了他們未來的消費模式。

Turning to margin.

轉向保證金。

FY25 non-GAAP product gross margin of 76% landed in line with expectations.

FY25非GAAP產品毛利率76%，符合預期。

FY25 non-GAAP operating margin was 6%.

FY25非GAAP營業利益率為6%。

Last quarter, we discussed our plans to improve efficiency.

上個季度，我們討論了提高效率的計劃。

These efforts include centralizing teams targeted early career hiring, removing redundant management layers, and continuous performance to management.

這些努力包括集中針對早期職業招募的團隊、消除多餘的管理階層以及持續的管理績效。

In Q4, these efforts yielded meaningful margin gains.

在第四季度，這些努力帶來了顯著的利潤成長。

Q4 non-GAAP operating margin of 9% outperformed expectations.

第四季非公認會計準則營業利益率為 9%，超出預期。

FY25 non-GAAP adjusted free cash flow margin of 26% landed in line with our expectations.

FY25非GAAP調整後自由現金流利潤率為26%，符合我們的預期。

In FY25, we used $1.9 billion to repurchase 14.8 million shares at a weighted average share price of $130.87. We did not make any repurchases in Q4.

在25財年，我們耗資19億美元，以130.87美元的加權平均股價回購了1,480萬股。我們在第四季沒有進行任何回購。

We still have $2 billion remaining on our authorization through March 2027 and ended the year with $5.3 billion in cash, cash equivalents, short-term and long-term investments.

截至 2027 年 3 月，我們的授權金額仍有 20 億美元，年底時我們的現金、現金等價物、短期和長期投資總額為 53 億美元。

Moving to our outlook.

轉向我們的展望。

We expect Q1 product revenue between $955 million and $960 million, representing 21% to 22% year-over-year growth.

我們預計第一季產品營收在 9.55 億美元至 9.6 億美元之間，年增 21% 至 22%。

As a reminder, Q1 (technical difficulty) difficult year-over-year comparison as we lap leap year.

提醒一下，由於閏年，Q1（技術難度）較去年同期難度較高。

We expect Q1 non-GAAP operating margin of 5%.

我們預計第一季非 GAAP 營業利潤率為 5%。

This margin outlook includes expenses associated with our annual sales kickoff event posted in Q1.

此利潤前景包括與我們在第一季發布的年度銷售啟動活動相關的費用。

We expect approximately $15 million in expenses similar to last year.

我們預計支出約 1500 萬美元，與去年類似。

For FY26, we expect product revenue of approximately $4.28 billion, representing 24% year-over-year growth.

對於 26 財年，我們預計產品收入約為 42.8 億美元，年增 24%。

We are forecasting stable growth within our core business.

我們預測我們的核心業務將穩定成長。

We expect new product features to contribute step-up in year-over-year growth rates in the second half of the year.

我們預計，新的產品功能將推動下半年年成長率的提升。

As always, our forecast includes headwinds associated with performance improvements.

與往常一樣，我們的預測包括與性能改進相關的阻力。

As I said last quarter, product improvements are an ongoing part of our business, and we will not be breaking out assumptions for specific features moving forward.

正如我上個季度所說，產品改進是我們業務的持續組成部分，我們不會對未來具體功能做出超出預期的假設。

Turning to margins.

轉向利潤。

We expect non-GAAP product gross margin of approximately 75%.

我們預計非GAAP產品毛利率約為75%。

Longer term, we expect easier GPU access and growing AI revenue to benefit product gross margins associated with new product features.

從長遠來看，我們預計更容易的 GPU 存取和不斷增長的 AI 收入將有利於與新產品功能相關的產品毛利率。

Non-GAAP operating margin will expand to reach 8% for the year.

本年度非公認會計準則營業利益率將擴大至 8%。

We expect non-GAAP adjusted free cash flow margin of 25% for the year.

我們預計今年非公認會計準則調整後的自由現金流利潤率為 25%。

Our strong revenue growth, combined with a more thoughtful approach to hiring and increased leverage from AI, will benefit stock-based compensation as a percentage of revenue.

我們強勁的收入成長，加上更周到的招聘方式和人工智慧的增強槓桿作用，將使股票薪酬佔收入的百分比受益。

In FY26, we expect SBC as a percent of revenue to decrease to approximately 37% from 41% and will continue to decrease year on year.

在 26 財年，我們預計 SBC 佔收入的百分比將從 41% 下降至約 37%，並將繼續逐年下降。

We will be hosting our Investor Day in conjunction with our Summit Conference the week of June 2 in San Francisco.

我們將於 6 月 2 日那週在舊金山舉辦投資者日和高峰會。

If you are interested in attending, please e-mail ir@snowflake.com.

如您有興趣參加，請發送電子郵件至ir@snowflake.com。

Before opening up the line for questions, you've likely seen our filing -- sharing that I plan to retire once the successor is in place and up to speed.

在開始提問之前，您可能已經看過我們的文件——我分享了一旦繼任者到位並熟悉情況後我計劃退休。

The company executed well in two under the new leadership of rider and I feel we are set up for success in 2026 and beyond.

在 Rider 的新領導下，公司在兩年內表現良好，我認為我們已經為 2026 年及以後的成功做好了準備。

This is the right time to hand the reins over to a new CFO.

現在是將權力移交給新財務長的最佳時機。

The company will be kicking off a search for my replacement, and I will stay on board full time until a suitable replacement is in place and the transition is completed.

公司將開始尋找我的繼任者，我將全職留任，直到找到合適的繼任者並完成過渡為止。

Mike, before we jump into Q&A, I want to take a moment to express my gratitude.

麥克，在我們進入問答環節之前，我想花點時間表達我的感激之情。

Over the past year, you've been an incredible partner.

在過去的一年裡，您一直是我非常出色的合作夥伴。

And I'm deeply appreciated that you will continue to be as we work together to make this a smooth transition.

我非常感激你們將繼續與我們共同努力，讓過渡順利進行。

Snowflake wouldn't be the iconic company it is today without your years of leadership.

如果沒有您多年的領導，Snowflake 就不會成為如今這樣的標誌性公司。

And I know I speak on behalf of all of our employees when I say, we're so happy for you, and we look forward to celebrating you for the coming.

我知道，我代表全體員工說，我們為你們感到高興，我們期待為你們的到來而慶祝。

We can now open up the line for questions.

現在我們可以開始回答問題了。

(Operator Instructions) Keith Weiss, Morgan Stanley.

（操作員指示） 摩根士丹利 (Morgan Stanley) 的 Keith Weiss。

This is Sanjit Singh for Keith.

我是 Keith 的 Sanjit Singh。

I want to extend my congrats.

我想表達我的祝賀。

Not many software companies at scale are growing 30% in this environment.

在這種環境下，規模龐大的軟體公司能夠實現 30% 的成長的並不多。

And then, Mike, congrats on a stellar distinctive career in software.

然後，麥克，祝賀你在軟體領域取得了輝煌而獨特的職業生涯。

With that, maybe just some of the questions, maybe Mike to start with you.

這樣，也許只是一些問題，也許麥克可以從你開始。

On your comment on these large customers in Q4 exhausting their commitments, but not necessarily renewing going on demand.

關於您對這些大客戶在第四季度已用盡其承諾但不一定會按需續約的評論。

How usual or unusual is that?

這是多麼常見或不尋常的事？

And do you expect these customers just to sign a commitment contract in due course?

您是否希望這些客戶及時簽署承諾合約？

Yeah.

是的。

I fully expect they're going to sign a new commitment.

我完全相信他們會簽署一份新的承諾。

But as you know, we typically sign a three-year contract with our customers once they're up and running.

但正如您所知，一旦客戶開始運營，我們通常會與其簽訂三年的合約。

Many new customers started one year, the first year then go to three years.

許多新客戶從一年開始，第一年就持續三年。

And under their contract, they make a capacity commitment to us based on what they expect they're going to go through.

根據他們的合同，他們根據預計要經歷的情況向我們做出了產能承諾。

But if they burn through that commitment before the end of the contract term, the customer has two options.

但如果他們在合約期限結束前履行了承諾，客戶就有兩種選擇。

They can do an early renewal and make a new capacity purchase.

他們可以提前續約併購買新的產能。

Typically, they only do that if they're going to get some economics for that that makes sense to them, or they continue to purchase under the same terms as they go to the end of their contract period, at which time they must do a new capacity purchase of equal to or greater than to get the same economics that they have in their contract.

通常，他們只有為了獲得一些對他們有意義的經濟效益才會這樣做，或者在合約結束時繼續按照相同的條款進行購買，屆時他們必須進行等於或大於新容量的購買，才能獲得與合約中相同的經濟效益。

So this has always happened.

所以這種事情一直都會發生。

We just had a few big customers that that happened to in this quarter, and I fully expect sometime over the next month to six months, so those people will sign new contracts.

本季我們剛剛有幾個大客戶遇到了這種情況，我完全預計在未來一個月到六個月的某個時候，這些人將會簽署新的合約。

And I'll just add on a couple of obvious statements, which is that these customers reaching their capacity earlier is a good thing.

我只想補充幾個顯而易見的說法，那就是這些客戶提前達到他們的容量是一件好事。

It means that their consumption has gone over what they predicted at the beginning of the contract.

這意味著他們的消費已經超過了合約開始時預測的量。

Generally speaking, these accounts are in a pretty happy place.

整體來說，這些帳戶的狀況都相當良好。

And yes, there's sometimes a little movement here and there with timing.

是的，時間上有時會有一些小動作。

Yeah, that makes complete sense.

是的，這完全有道理。

And then Sridhar for you, Mike also sort of tagged the guidance where the new products probably shows some more muster in the second half of this year.

然後 Sridhar 為您介紹，Mike 也給了一些指導意見，新產品可能會在今年下半年顯示出更多的勢頭。

You've done a lot of work.

你已經做了很多工作。

The team has done a lot of work accelerating the pace of product innovation.

團隊為加快產品創新步伐做了大量工作。

Could you give us some color on the adoption trends within the data engineering portfolio and showing one bucket?

您能否向我們介紹一下數據工程組合中的採用趨勢並展示一個趨勢？

And then looking at sort of the AI/ML application platform side with some of the announcements supporting both OpenAI models and Anthropic models.

然後來看看 AI/ML 應用平台方面，其中一些公告同時支援 OpenAI 模型和 Anthropic 模型。

When do you think that starts to unlock more workloads, more customer adoption, and ultimately a greater revenue as we look to the balance of this year?

展望今年的平衡情況，您認為什麼時候才能開始釋放更多的工作量、更多的客戶採用，並最終帶來更大的收入？

Yeah, that's a great question.

是的，這是一個很好的問題。

And in areas like data engineering, as you know, we've been working on technologies like Snowpark, which is our version of ARC.

如您所知，在資料工程等領域，我們一直在研究 Snowpark 等技術，這是我們的 ARC 版本。

And we have talked about how that has already driven robust adoption.

我們已經討論過這如何推動了強勁的採用。

I think what is new in the world of OpenData is what all of, like the technologies that we are bringing, allows us to do in this like vastly expanded scope of data that is available to us.

我認為開放資料領域的新穎之處在於，我們帶來的所有技術都使我們能夠大幅擴展可用資料的範圍。

And we are increasing that by making investments in companies like Datavolo and turning that into a large set of connectors that can bring in more data.

我們透過對 Datavolo 等公司進行投資並將其轉變為能夠帶來更多數據的大型連接器來增加這一數量。

And both Christian and I and the sales team track these different areas.

克里斯蒂安、我和銷售團隊都專注於這些不同的領域。

We have talked to you previously about product features like dynamic tables.

我們之前已經與您討論過動態表格之類的產品功能。

This truly is an amazing product, where setting up complicated pipelines is roughly as simple as writing a SQL query.

這確實是一個令人驚嘆的產品，其中設定複雜的管道主要就像編寫 SQL 查詢一樣簡單。

So we are seeing a lot of brisk adoption, and it can also reach scale very quickly because it feeds very naturally into large-scale applications.

因此，我們看到了很多迅速的採用，並且它也可以很快達到規模，因為它可以非常自然地融入大規模應用程式。

So both Christian and I and others are very confident on that side.

因此，我、克里斯蒂安和其他人對此都非常有信心。

AI is interesting in the sense that it's a much newer set of products, generally speaking, throughout the world, not just at Snowflake.

人工智慧之所以有趣，是因為它是一套更新的產品，一般來說，它遍及全球，而不僅限於 Snowflake。

We are seeing broad adoption of AI.

我們看到人工智慧的廣泛應用。

The way we approached it, which is to build rock solid primitives, our search product, for example, is among the best in the world.

我們解決這個問題的方式是建立堅如磐石的原語，例如，我們的搜尋產品是世界上最好的。

We published a benchmark recently showing how it was in the top 3.

我們最近發布了一項基準測試，顯示了它如何進入前三名。

And so products like that have a lot of potential, but you'll also see a multiplicative effect.

因此，像這樣的產品具有很大的潛力，但你也會看到乘數效應。

The more the great connectors that you have in portfolio, the more data can be brought in for applications like search.

產品組合中擁有的優秀連接器越多，可以為搜尋等應用程式帶來越多的數據。

In turn, they will drive other applications that our customers or our partners can build on top of Snowflake.

反過來，它們將推動我們的客戶或合作夥伴在 Snowflake 上建立其他應用程式。

For example, let's say, like an insurance underwriting application or like a legal analysis kind of application, more and more of those kinds of things become possible with the combination of data engineering and AI technologies.

例如，像保險承保應用程式或法律分析類型的應用程序，隨著數據工程和人工智慧技術的結合，越來越多的此類事情成為可能。

We have seen broad adoption of AI.

我們已經看到人工智慧的廣泛應用。

We expect that to turn into real revenue over the coming quarters.

我們預計這將在未來幾季轉化為實際收入。

But the point that I want to make is that all of these fit together seamlessly.

但我想說的是，所有這些都是無縫銜接的。

The more we can do with injection, the more options there are for us to do meaningful things to data engineering.

我們用注入能做的事情越多，我們為資料工程做有意義的事情的選擇就越多。

The more we can do with data engineering and support of formats like iceberg, the easier it is for people to use Snowflake ad hoc analytics use cases on data that is sitting in that are sitting in cloud storage.

我們在資料工程和冰山等格式的支援方面做得越多，人們就越容易使用 Snowflake 臨時分析用例來分析雲端儲存中的資料。

And the more data that is sitting in our accessible to Snowflake, the more value you can get out of products like Cortex analyst and now Snowflake intelligence.

Snowflake 中可存取的資料越多，您從 Cortex 分析師和現在的 Snowflake 智慧等產品中獲得的價值就越大。

So it is this tying in that I think is pretty unique to us.

所以我認為這種結合對我們來說非常獨特。

And yes, we expect these to meaningfully contribute in the latter half of the year.

是的，我們預計這些將在今年下半年做出有意義的貢獻。

Kirk Materne, Evercore ISI.

柯克·馬特恩（Kirk Materne），Evercore ISI。

Congrats on a great quarter.

恭喜您度過了一個美好的季度。

Mike, congrats on a great run at Snowflake.

麥克，恭喜你在雪花隊取得的優異成績。

Sridhar, I don't know if it's for you or Christian, but over the last 6 to 12 months, we've seen a lot of new announcements from data companies sort of partnering up with enterprise software vendors like ServiceNow or Salesforce and you guys have partnered with them.

Sridhar，我不知道這是為你還是 Christian 而說的，但在過去的 6 到 12 個月裡，我們看到很多數據公司發布新公告，它們與 ServiceNow 或 Salesforce 等企業軟體供應商合作，你們也與他們合作了。

One of your competitors just partnered with SAP.

您的一個競爭對手剛剛與 SAP 合作。

I guess what's the best way to interpret these announcements in terms of where the center of gravity from a data perspective lives?

我猜想，從資料角度來看，重心在哪裡，如何最好地解讀這些聲明呢？

I was just wondering if you guys could comment on that.

我只是想知道你們是否可以對此發表評論。

And then, Mike, really quickly for you.

然後，麥克，我們很快就為你講講。

Just any adjustments to the sales comp model that we should be aware of this year?

今年我們應該注意銷售補償模型的任何調整嗎？

Why don't you go first, Mike?

麥克，你為何不先走呢？

Yes, on the comp model, probably the biggest change is taking a little bit of a step back in terms of allocation.

是的，在補償模型上，可能最大的變化是在分配方面稍微退後一步。

We're still principally paying people on their variable comp on revenue.

我們主要還是根據員工收入的浮動薪酬來支付報酬。

But we do think it's important that reps also have a total contract bookings number as well to.

但我們確實認為，銷售代表也應該擁有合約預訂總量，這一點很重要。

And so there's going to be a quota as well on bookings, but the bulk of their earnings will come from consumption revenue.

因此預訂量也會有配額，但他們的大部分收入將來自消費收入。

Great.

偉大的。

And going back to the first question, we call ourselves the AI data cloud for a good reason.

回到第一個問題，我們稱自己為 AI 資料雲是有充分理由的。

This is because most customers see us as the best place to get value from data, especially analytic and predictive value from data.

這是因為大多數客戶都將我們視為從數據中獲取價值的最佳場所，尤其是從數據中獲取分析價值和預測價值。

At Snowflake itself, for example, we have connectors that bring in data from Salesforce, from ServiceNow, from GitHub and the list sort of goes on and on.

例如，在 Snowflake 本身，我們有從 Salesforce、ServiceNow、GitHub 等引入資料的連接器，而且這個清單還在增加。

And I think what's obviously been very interesting for all of us, even prior to the AI revolution, is being able to look at this data, say Workday data as well as Snowflake data along with Salesforce data all in the same pain.

我認為，對我們所有人來說，顯然非常有趣的是，即使在人工智慧革命之前，我們也能以同樣痛苦的方式查看這些數據，例如 Workday 數據、Snowflake 數據以及 Salesforce 數據。

All of us have access to reports that can switch these kinds of data together.

我們所有人都可以存取可以將這些類型的資料交換在一起的報告。

And so we have done a number of partnerships with many companies, some of our best ones are with folks like ServiceNow and Salesforce.

因此，我們與許多公司建立了合作夥伴關係，其中一些最好的合作對像是 ServiceNow 和 Salesforce 等公司。

We have bidirectional integrations with them, where a lot of customers bring data from those applications into Snowflake.

我們與他們進行了雙向集成，許多客戶將這些應用程式中的資料帶入 Snowflake。

It works very, very smoothly.

它運行得非常非常順暢。

I think what is unique in the world of Agentic AI is the time to value from data can become exceptionally quick because you're not in the process of building painful integrations, painful new applications.

我認為 Agentic AI 世界的獨特之處在於，從資料中獲取價值的時間可以變得異常快，因為你不必建立痛苦的整合和痛苦的新應用程式。

And some of the things we ourselves, again, have been able to build with Snowflake intelligence have been pretty remarkable.

而且，我們自己已經能夠利用 Snowflake 智慧建構出一些東西，這些東西已經相當了不起了。

We do expect this trend to continue.

我們確實預計這一趨勢將會持續下去。

Of course, players like ServiceNow or Salesforce , they're going to have a class of applications, which can benefit from data that is coming from outside.

當然，像 ServiceNow 或 Salesforce 這樣的參與者將擁有一類應用程序，可以從來自外部的資料中受益。

And hence, we do bidirectional partnership.

因此，我們建立雙向合作關係。

The larger theme that I would find to in both of this is that of giving customers choice.

我發現這兩者中更大的主題是給予顧客選擇。

Customers should have the right to decide where it is that their data should be.

客戶應該有權決定他們的資料應該存放在何處。

And as far as we are concerned, I think we are very uniquely positioned as a central and very efficient repository of data for most companies.

就我們而言，我認為我們作為大多數公司的中央和非常高效的資料儲存庫，具有非常獨特的優勢。

And yes, some of our customers will take data over to one of the folks that I mentioned.

是的，我們的一些客戶會將資料交給我提到的某個人。

SAP, in particular, Christian will give us an update.

SAP，特別是 Christian 將為我們提供最新消息。

Yeah.

是的。

So as Sridhar said, we've always done bidirectional type of sharing and data movement with a number of partners.

正如 Sridhar 所說，我們一直與許多合作夥伴進行雙向共享和資料移動。

While we don't have a specific announcement to share at SAP today, I can tell you that we are working with SAP.

雖然我們今天在 SAP 沒有具體的公告可以分享，但我可以告訴你們，我們正在與 SAP 合作。

We like what they're doing with the business data cloud products.

我們喜歡他們在商業數據雲端產品所做的努力。

And we have a common commitment to foster an open data environment and hope to share more with all of you soon.

我們有著共同的承諾，致力於營造開放的數據環境，並希望很快能與大家分享更多。

Raimo Lenschow, Barclays.

巴克萊銀行的 Raimo Lenschow。

Congrats from my end for the quarter and for Mike as well as in a working with you over the last few years.

我個人對本季的表現以及 Mike 的表現表示祝賀，也對過去幾年與你的合作表示祝賀。

Two questions.

兩個問題。

One for Sridhar and one for Mike.

一份給 Sridhar，一份給 Mike。

Sridhar, how do we think about adjacencies for your offering that you kind of might want to consider?

Sridhar，我們如何看待您可能想要考慮的與您提供的服務相鄰的內容？

Or how do you think about them?

或者您對它們有什麼看法？

Like, for example, this quarter, there was a big debate about streaming and how that might fit into you.

例如，本季度，關於串流媒體以及它如何適合您展開了一場激烈的爭論。

So maybe can you kind of talk about like how you see the product evolving from your perspective?

那麼您可以從您的角度談談您如何看待產品的發展嗎？

And then, Mike, for you on guidance, how conservative are the assumptions this year in the guidance versus kind of what you -- for example, did last year when you had the CEO change, obviously, how did the economy also play into the guidance for this year?

然後，麥克，對於您的指引，今年的指引中的假設與去年執行長變動時的假設相比有多保守？

Great.

偉大的。

I'll take -- sorry, can you repeat the first question?

我會——抱歉，您能重複第一個問題嗎？

I want to make sure I get it right.

我想確保我做對了。

It's just more -- if you think about adjacencies for where you want to play versus where you want partner and there think about streaming, for example, as one of the kind of areas?

這只是更多——如果您考慮您想要玩的地方與您想要合作的地方的相鄰性，並考慮串流媒體，例如，作為其中一種領域？

Yes.

是的。

Like overall, we work with a number of partners, the data space is a very large space. we try to be open and clear with our partners about what our big areas of investment are.

就像整體一樣，我們與許多合作夥伴合作，資料空間是一個非常大的空間。我們努力向合作夥伴公開、清楚地說明我們的主要投資領域。

And absolutely, we work with a number of folks in streaming.

當然，我們與串流媒體領域的許多人士合作。

But both streaming and infection are areas where we think it is important for us to have a good offering in place.

但我們認為，在串流媒體和感染這兩個領域，提供良好的服務非常重要。

And while it looks simple, streaming comes in many shapes and sizes that are on-prem solutions that are great, that are more native sort of solutions and the same goes for connectors.

儘管看起來很簡單，但串流媒體有多種形式和規模，有些是出色的內部部署解決方案，有些是更原生的解決方案，連接器也是如此。

We will have a robust ingestion offering, and we continue to work with partners.

我們將提供強大的攝取服務，並繼續與合作夥伴合作。

We do continue -- we do think of streaming as a critical area for Snowflake.

我們確實會繼續下去——我們確實認為串流媒體是 Snowflake 的關鍵領域。

Just like we think of Snowflake Intelligence, which begins to merge the line between what one would think of as BI and a new class of application, it's literally -- it's a new thing.

就像我們所想到的雪花智慧 (Snowflake Intelligence)，它開始融合人們所認為的 BI 與一類新應用程式之間的界限，它實際上是 - 一個新事物。

We think it's important for us to have a presence there.

我們認為在那裡設立辦事處對我們來說非常重要。

Christian, any thoughts to add?

克里斯蒂安，還有什麼想法可以補充嗎？

No.

不。

We, at the same time, partner with a number of players.

同時，我們也和許多玩家建立了合作關係。

We continue to be very good partners.

我們將繼續保持非常好的合作夥伴。

We have lots of customers that uses alongside other technologies.

我們有很多客戶同時使用其他技術。

You may be alluding to Redpanda also companies like conferred partners, and we will continue to do that.

您可能暗指 Redpanda 也是授予合作夥伴的公司，我們將繼續這樣做。

And then, Raimo, on your question of guidance, I'm just going to say the guidance, I feel is appropriate.

然後，雷莫，關於你關於指導的問題，我只想說我覺得合適的指導。

We've always tried to get meaningful guidance.

我們一直在努力獲得有意義的指導。

And given the scale we're at right now, we think a 3% beat is -- should be considered a big beat.

考慮到我們目前的規模，我們認為 3% 的超出預期應該被視為一個巨大的超出預期。

And I feel good about the guidance that we've set for the quarter and the year.

我對我們為本季和全年設定的指導感到滿意。

And by the way, everyone makes it sound like this is my last call.

順便說一句，每個人都讓這聽起來像是我的最後一通電話。

I think I'll be here for a little while longer.

我想我會在這裡多待一段時間。

Brad Zelnick, Deutsche Bank.

德意志銀行的布拉德‧澤爾尼克 (Brad Zelnick)。

Great.

偉大的。

Maybe first for Sridhar, with Cortex agents announced for agent orchestration, can you talk a little bit more about what differentiates your offering versus many other agent offerings out there and maybe where the product vision came from?

首先對於 Sridhar 來說，隨著 Cortex 代理商宣布用於代理商編排，您能否再談談您的產品與其他眾多代理商產品的區別，以及產品願景的來源？

Was this something customers were asking for?

這是顧客要求的嗎？

And are there any early adopters maybe that you're working with out there?

您是否正在與任何早期採用者合作？

It's a good question.

這是個好問題。

I think the best answer to that goes back to something that I talked about earlier in the context of the data cloud.

我認為對此最好的回答可以追溯到我之前在數據雲背景下談論的內容。

I think we are rapidly approaching a world in which data is even more central than before.

我認為我們正在快速進入一個數據比以前更重要的世界。

Previously, if you had data sets and wanted to stitch them together and/or build an application, you had to painfully engineer semantics, figure out how to do it, build an application and then figure out how to write, for example, how to use an API to write back data what, for example, Cloud does incredibly well is it can produce pretty professional-grade UI with instructions in English, which was just like unthinkable AI couple of years ago.

以前，如果您有數據集並想將它們拼接在一起或構建應用程序，您必須痛苦地設計語義，弄清楚如何去做，構建一個應用程序，然後弄清楚如何編寫，例如，如何使用 API 來寫回數據，例如，雲做得非常好，它可以用英文說明生成非常專業級的 UI，這就像幾年前不可想像的人工智能一樣。

I think it is the centrality of data that plays into how we think about agent flows.

我認為資料的中心性影響了我們如何思考代理流。

Then other software vendors talk about agent applications, they are generally limited to the context of the particular function that they serve.

然後其他軟體供應商談論代理應用程序，它們通常僅限於它們所服務的特定功能的上下文。

So for example, if you have a customer service offering, then you will naturally offer a customer service agent that can automate parts of the work that agent is going to do.

舉例來說，如果您提供客戶服務，那麼您自然會提供一個客戶服務代理，該代理可以自動執行該代理將要做的部分工作。

We are uniquely positioned in that we are a horizontal platform.

我們的獨特優勢在於我們是一個水平平台。

Customers store all different kinds of data with us.

客戶在我們這裡儲存各種不同類型的資料。

And that makes it possible to create pretty interesting new applications.

這使得創建非常有趣的新應用程式成為可能。

It's too early for me to speak in public about customers and use cases just yet.

對我來說，現在公開談論客戶和用例還為時過早。

But I can give you lots of examples even within Snowflake, where the ability to look at data that is sitting in sales force, which is where all our meeting data lives are the -- and simultaneously look at all of our enablement material or notes from each of the use cases.

但我可以給你很多例子，即使在 Snowflake 內部，也可以查看銷售人員的數據，也就是我們所有會議數據所在的地方——並且可以同時查看每個用例的所有支援材料或說明。

And then using that to update some stores, update the status of things.

然後使用它來更新一些商店，更新事物的狀態。

This is an application that we're super excited about.

這是一個讓我們非常興奮的應用程式。

It is this combination of structured data, unstructured data, tool calling that are the basic ingredients.

這種結構化資料、非結構化資料和工具呼叫的組合就是基本要素。

And we can also scale these very effectively with a number of partners that we have, companies like Elementum build on top of Snowflake and they're going to use the core infrastructure that we provide to drive these kinds of agent applications.

我們還可以與許多合作夥伴一起非常有效地擴展這些功能，像 Elementum 這樣的公司在 Snowflake 之上構建，他們將使用我們提供的核心基礎設施來驅動這些類型的代理應用程式。

That's really helpful.

這真的很有幫助。

And Mike, just for you, with Q4 being such a bonanza bookings quarter, where you do a lot of big deals with large customers.

麥克，我想問您，第四季是預訂量大豐收的季度，您與大客戶做了很多大交易。

Can you talk more about the trends you're seeing with your largest customers, maybe the momentum and expansion rates and the services that they're embracing and plan to consume this year?

您能否詳細談談您從最大客戶看到的趨勢，例如發展勢頭和擴張率，以及他們今年所接受和計劃消費的服務？

Yes.

是的。

I'll just say the momentum continues with their large customers.

我只想說，他們的大客戶繼續保持這種勢頭。

They continue to grow and consume like any quarter, some overachieve our forecast.

它們像任何季度一樣繼續成長和消費，有些甚至超出了我們的預測。

Some are under.

有些在下面。

There was nothing usual there.

那裡沒有什麼不尋常的。

But large customers really are the ones that drive our revenue growth.

但大客戶才是真正推動我們營收成長的動力。

I was very pleased with the number of million dollar plus customers growing in the number of $5 million and $10 million as well, too.

我很高興看到百萬美元以上的客戶數量也增長到了 500 萬美元和 1000 萬美元。

So I'm very pleased there.

所以我很高興。

And I think our sales organization has really built up a lot of muscle too.

而且我認為我們的銷售組織也確實增強了許多實力。

This year to really identify new workload opportunities and go live.

今年要真正發現新的工作量機會並開始實施。

I think our professional services and our partners are getting better at migrations and handling a number of these things as well, too.

我認為我們的專業服務和合作夥伴在遷移和處理這些事情方面也做得越來越好。

I think our SE organization has really stepped up and is going to really help drive a lot of those new workloads next year in Snowflake.

我認為我們的 SE 組織確實已經進步了，並且將真正幫助推動 Snowflake 明年的大量新工作量。

So I'm very pleased with what I'm seeing right now.

我對目前看到的情況非常滿意。

Brent Bracelin, Piper Sandler.

布倫特·布雷斯林，派珀·桑德勒。

Mike, happy to learn you're not leaving anytime soon here.

麥克，很高興得知你不會很快離開這裡。

We'll save the current graphs.

我們將保存當前圖表。

But I did want to ask you a question around product growth.

但我確實想問您一個有關產品成長的問題。

The guide implies an acceleration for the first time into the second half in 3.5 years. what's driving the optimism on acceleration?

該指南暗示，3.5 年來下半年經濟將首次加速成長。是什麼推動了人們對加速發展的樂觀？

Is it all new products?

都是新產品嗎？

Or are you feeling better about consumption activity across the base?

或者您對整個基礎的消費活動感覺更好嗎？

It's both.

兩者都有。

The core of our business is very strong, coupled with the new products that we see that will be going into production.

我們的業務核心非常強大，再加上我們看到的即將投入生產的新產品。

Also on top of, I'm pleased with the muscle we've been building on new customer acquisitions, and that's going to start to kick in in the second half of the year.

此外，我對我們在吸引新客戶方面所取得的進展感到滿意，這將在今年下半年開始發揮作用。

We do get a lot of visibility into our existing customers with planned migrations that they have.

我們確實對現有客戶的遷移計劃有了深入的了解。

And I think that is looking very good for the second half of the year.

我認為今年下半年的情況會非常好。

And remember, our guidance for Q1 seems low, but that is because of that we miss one business because of leap year, and that's a fair chunk of revenue that comes out of that when you're looking at that growth rate just in Q1.

請記住，我們對第一季的預期似乎很低，但這是由於我們因閏年而錯過了一項業務，如果僅從第一季的成長率來看，這將產生相當大的收入。

Helpful color there.

那裡有有用的顏色。

And then Sridhar, just as you think about growth levers to the business, one area you flagged with this idea of Snowflake role in AI-powered advertising.

然後 Sridhar，正如您在思考業務成長槓桿時，您提到了一個領域，即 Snowflake 在人工智慧廣告中扮演的角色。

You clearly know the advertising market well.

您顯然非常了解廣告市場。

I never really thought of the large ad market as a as a meaningful opportunity for Snowflake.

我從未真正想過大型廣告市場對 Snowflake 來說是一個有意義的機會。

Can you just double click into when you think about the AI-powered ad market, is there an unlock that you see there for Snowflake in that kind of new workload scenario?

當您考慮人工智慧廣告市場時，您是否看到 Snowflake 在這種新的工作負載場景中可以解鎖什麼機會？

We've actually been in the area of marketing and advertising for a fairly long time.

事實上，我們從事行銷和廣告領域已經相當長時間了。

There are tons of CDP, start-ups, others that custom CDP that people build customer data platforms on top of Snowflake.

有大量的 CDP、新創公司和其他客製化 CDP 的公司，人們在 Snowflake 之上建立客戶資料平台。

In fact, we acquired a company called because data clean rooms are a really powerful enabling technology for things like conversion lift.

事實上，我們收購了一家名為 的公司，因為資料清理室對於實現轉換提升等目標而言是一項非常強大的支援技術。

And part of what we facilitate in this role as a -- like a ecosystem player is automating even more operations.

作為生態系統參與者，我們在這角色中所扮演的角色之一就是實現更多操作的自動化。

We talked last time about this idea called AI SQL, which is what are the primitives you can put into SQL such as that image analysis, video analysis can be done very easily by analysts, so you can ask questions like putting a Christmas tree into the ad, increase the click-through or the conversion rate of an ad that you show over the holidays.

我們上次談到了一個名為 AI SQL 的想法，也就是你可以放入 SQL 中的原語，比如圖像分析、視頻分析，這些都可以由分析師輕鬆完成，因此你可以提出諸如在廣告中放入一棵聖誕樹之類的問題，提高在假期展示的廣告的點擊率或轉換率。

And so I think like as we introduce multimodal capabilities into Cortex, I think the lens of what is achievable with Snowflake will continue to expand.

因此，我認為，隨著我們將多模式功能引入 Cortex，Snowflake 可以實現的功能範圍將會不斷擴大。

And of course, with language models, with AI models in general, the generative applications, how can you generate creative.

當然，有了語言模型、一般的人工智慧模型和生成應用程序，你如何產生創造力。

How can you generate copy for creators.

如何為創作者產生副本。

Those are also areas that become easier and easier to do.

這些領域也變得越來越容易實現。

And so that's our broad role.

這就是我們的廣泛職責。

It's an important vertical, both marketing and advertising for Snowflake.

對 Snowflake 來說，行銷和廣告都是一個重要的垂直領域。

But I think the arc is moving more from measurement and privacy-preserving technology to also generative technologies that can power more automated testing, and like things like auto AI measurement using Snowflake.

但我認為，這個方向正從測量和隱私保護技術轉向能夠支援更多自動化測試的生成技術，以及使用 Snowflake 進行自動 AI 測量等技術。

Alex Zukin, Wolfe Research.

沃爾夫研究公司的亞歷克斯祖金 (Alex Zukin)

Mike, I look forward to our banter for at least a few more quarters.

麥克，我期待我們至少在接下來的幾個季度繼續交流。

Yes, we'll have it.

是的，我們會有的。

Sridhar, maybe just on looking at the spend intensity in your market, it seems like something has changed to the positive over the past six months.

Sridhar，也許僅從您所在市場的支出強度來看，過去六個月似乎出現了一些積極的變化。

It seems like it's gotten better.

好像已經好起來了。

You've been meeting with a lot of customers.

您已經和許多客戶見面了。

Mike mentioned the tech and financial services verticals outperforming.

麥克提到科技和金融服務垂直產業表現優異。

But maybe can you talk to how much of this is a broader demand environment versus sales execution improvements versus confidence in kind of like better product innovation velocity, releasing of new products?

但也許您能否談談，這在多大程度上是更廣泛的需求環境、銷售執行改進還是對更好的產品創新速度、新產品發布的信心？

Anything you can do there I think it would be helpful.

我認為您在那裡所做的任何事情都會有所幫助。

Well, you know how this works.

嗯，你知道這是如何運作的。

Positive feedback cycles like feed on themselves.

正回饋循環就像自我回饋一樣。

And so -- but I would say, in my mind, the pretty substantial changes that we've made in how we operate as a company, absolutely.

所以 — — 但我想說，在我看來，我們在公司運作方式上確實做出了相當大的改變。

First is around product velocity.

首先是產品速度。

I think if you look at the pace, of how we've been able to get AI products out to market, I think it's been remarkable.

我認為，如果你看看我們將人工智慧產品推向市場的速度，我認為這是相當了不起的。

But there's a lot more innovation that is happening.

但還有更多的創新正在發生。

We have a big effort around AI-powered migrations that you will hear more about.

我們在人工智慧遷移方面做出了巨大努力，您將會了解更多相關資訊。

We have invested heavily in data collaboration and sharing with release of things like an internal marketplace for our data.

我們在數據協作和共享方面投入了大量資金，並發布了諸如數據內部市場之類的東西。

Lots of new products in the data engineering space, including Iceberg.

數據工程領域有許多新產品，包括 Iceberg。

So from that perspective, I think we are just feeling more confident about who we are and obviously expanding the approach of what is possible.

因此從這個角度來看，我認為我們對自己是誰更有信心，並且顯然正在擴展可能的方法。

Previously, it used to be that people would have to bring their data into Snowflake to get something done.

以前，人們必須將他們的數據帶入 Snowflake 才能完成某些事情。

But the things like iceberg, we can take care of that right off the bat without any need for movement.

但對於像冰山這樣的問題，我們可以立即處理，而不需要採取任何行動。

I think product velocity is one part.

我認為產品速度是其中一部分。

But to what Mike was talking about, I think there is an awareness of the use case life cycle of the discipline needed to understand where we can create value for our customers, map it out in a thoughtful way and then engage in a fairly I would say, constant or constant conversation about what are the best places our account teams and our customers can come to a shared understanding of the projects that we should be working on.

但對於 Mike 所說的內容，我認為我們需要對該學科的用例生命週期有一定的認識，以便了解我們可以在何處為客戶創造價值，以深思熟慮的方式將其規劃出來，然後進行公平、持續的對話，討論我們的客戶團隊和客戶在何處能夠就我們應該開展的項目達成共識。

Anything that area is becoming more and more of a science where we are able to what the best people and the team do and have more folks to be more like them.

該領域的任何事情都越來越像一門科學，我們能夠了解最優秀的人才和團隊所做的事情，並讓更多的人更像他們。

I think there's just a maturity when it comes to use case prosecution.

我認為用例起訴已經成熟。

I think the third piece which is what gives us confidence about new products is then how all of these come together in how things are multiplexed over from the product team to the sales team.

我認為第三點讓我們對新產品充滿信心，那就是所有這些如何結合在一起，如何從產品團隊到銷售團隊進行多路復用。

I mean at the end of the day, it's unreasonable for Christian RI to expect that one salesperson is going to know about the 400 things that we launched last year is just not a thing.

我的意思是，歸根結底，Christian RI 期望一個銷售人員了解我們去年推出的 400 種產品是不合理的。

And so we increasingly have specialist teams that know what it is to take, for example, clean rooms to the two dozen most important customers that they must reach this year, say, compared to pretty much all of our customers who we think can benefit from key data engineering features our key AI features.

因此，我們越來越多地擁有專業團隊，他們知道如何做，例如，將潔淨室提供給他們今年必須接觸的二十幾個最重要的客戶，相比之下，我們認為幾乎所有客戶都可以從關鍵數據工程功能、我們的關鍵 AI 功能中受益。

I think it is that maturity and the ability to take the right feature to the right customer to create value that I think positions us overall better.

我認為，正是這種成熟度和將正確的功能提供給正確的客戶以創造價值的能力，使我們整體上處於更有利的地位。

And the final thing that I'll add on here is that we've also cleaned up how we work with partners, definitely ISVs, but also system integrators.

我最後要補充的是，我們也理清了與合作夥伴（肯定是 ISV，當然還有系統整合商）的合作方式。

And I think you will see more progress on that side as well.

我認為你也會看到這方面的更多進展。

So we are very proud that our ISV partners like Relational AI or Kumo or, of course, Blue Yonder, with whom we have a fairly deep partnership or succeeding along with Snowflake.

因此，我們非常自豪我們的 ISV 合作夥伴，例如 Relational AI 或 Kumo，當然還有 Blue Yonder，我們與他們建立了相當深厚的合作關係，並與 Snowflake 一起取得成功。

So it's a multi-faceted effort, but they build on the same core perimeters great product, a sales team that knows how to execute at scale and ability to totally overlay new things that we should be doing on what is a very large sales force.

因此，這是一項多方面的努力，但他們建立在同一核心基礎上：優秀的產品、一支懂得如何大規模執行的銷售團隊，以及在非常龐大的銷售隊伍中完全覆蓋我們應該做的新事物的能力。

Super helpful and really clear.

非常有幫助，而且非常清楚。

Mike, maybe one for you, while we still have you.

麥克，趁我們還有你，也許可以給你一個。

The guide for next year, it does seem like it's starting.

明年的指南看起來確實才剛開始。

I think you've gotten this question in a few different ways.

我認為您已經通過幾種不同的方式提出了這個問題。

It's starting at a stronger place than if I look at a year ago.

與一年前相比，它的開局更加強勁。

If we look a year ago, when you were incorporating maybe some iceberg risk.

如果我們回顧一年前，當時您可能正在考慮一些冰山風險。

So to the extent that you can put finer point on that confidence that you have to put that guide out there, again, implying some acceleration.

因此，如果您能更準確地指出這種信心，那麼您必須將該指南放在那裡，這再次暗示了一定的加速。

You mentioned some -- Sridhar mentioned some new products potentially ramping in the second half from a contribution standpoint.

您提到了一些——從貢獻的角度來看，Sridhar 提到了一些新產品可能會在下半年增加。

How do we think about iceberg as a tailwind or a headwind in that guide?

在該指南中，我們如何看待冰山是順風還是逆風？

How do we think about NRR stabilization at 126% in the context of that guide.

在該指南的背景下，我們如何看待 NRR 穩定在 126%。

Any finer point you put on it?

您對此還有什麼更詳細的說明嗎？

Yes.

是的。

First of all, I think NRR is pretty stable.

首先，我認為 NRR 相當穩定。

I'm not saying it's not going to go to 125% or 124%, but I don't really see it.

我並不是說它不會達到 125％ 或 124％，但我確實沒有看到它。

It's going to be in the mid-120s is what we are predicting.

我們預測它將達到 120 年代中期。

In terms of Iceberg, we're really now seeing Iceberg as more of a tailwind than a headwind as it's opening up so much more data for us.

就 Iceberg 而言，我們現在認為 Iceberg 更像是一種順風而不是逆風，因為它為我們提供了更多的數據。

We've yet to see massive amounts of data move out of Snowflake.

我們還沒有看到大量資料從 Snowflake 中移出。

Yes, there has been some, but stroke remains at roughly 11% of our revenue.

是的，有一些，但中風仍然占我們收入的約 11%。

And we are seeing workloads that otherwise wouldn't have been accessible to Snowflake.

我們看到了一些 Snowflake 原本無法存取的工作負載。

So I think that's good.

所以我認為這很好。

And our guide is based upon the strength of what we're seeing with customer commitments.

我們的指導是基於我們所看到的客戶承諾的力度。

And as I said before, we've done a really good job this year.

正如我之前所說，我們今年做得非常好。

There's still room for improvement always and there will always be room for improvement.

總是有改進的空間，並且永遠會有改進的空間。

But I think we're getting much better at working with customers to identify new workloads that will go into production that gives us that confidence.

但我認為我們在與客戶合作以確定將投入生產的新工作負載方面做得更好了，這給了我們信心。

Just to add on what Mike said, which is -- I've said this before, the Iceberg story is one that Snowflake can write.

我只是想補充一下麥克所說的話——我之前說過，冰山的故事是雪花可以寫的。

We've made all the right investments in the pharma, how broadly it is getting adopted.

我們在製藥領域做出了所有正確的投資，並且其應用範圍十分廣泛。

And yes, while there will be some customers who might want to move data that is instantly over to Iceberg.

是的，有些客戶可能希望將資料立即轉移到 Iceberg。

There is vastly more opportunity for us to take Snowflake to where the data is.

我們有更多的機會將 Snowflake 帶到資料所在的地方。

And that's what I mean when I say this is our history to write.

這就是我說這是我們要書寫的歷史的意思。

And that's what we are in the process of doing.

這正是我們正在做的事情。

We have had success with a number of data engineering use cases.

我們在許多資料工程用例中都取得了成功。

We think that there are a lot of data analytics use cases to also go after, and that's the exciting opportunity that has opened up for us.

我們認為還有很多數據分析用例值得探索，這是為我們帶來的令人興奮的機會。

And I'll add that I think on Iceberg, we've shifted from theoretical to actual consumption, actual revenue coming already materializing to us.

我還要補充一點，我認為在冰山一角，我們已經從理論轉向實際消費，實際收入已經開始實現。

Mark Murphy, JPMorgan.

摩根大通的馬克墨菲。

This is Sona on for Mark Murphy, and congrats.

這是 Sona 為 Mark Murphy 表演的，恭喜。

Sridhar, curious to get your take on a couple of the major recent industry developments, one being DeepSeek models and the other being the large-scale data center build-outs with Stargate of $100 billion to $500 billion, and now Meta announcing the $200 billion project.

Sridhar，我很好奇，想聽聽您對最近幾個重大行業發展的看法，一個是 DeepSeek 模型，另一個是星際之門 (Stargate) 的大規模數據中心建設，其投資額為 1000 億至 5000 億美元，現在 Meta 又宣布了 2000 億美元的項目。

How would you think through the direct and kind of indirect opportunities for Snowflake with that much data in motion?

在如此大量的資料傳輸下，您如何看待 Snowflake 的直接和間接機會？

For instance, DeepSeek usage in Cortex or some of the broader data management or data integration needs as you're customers start to tap into those services?

例如，當您的客戶開始使用這些服務時，Cortex 中的 DeepSeek 的使用情況或一些更廣泛的資料管理或資料整合需求？

This is a pretty dynamic space, which seems to change pretty dramatically every three months.

這是一個相當活躍的領域，似乎每三個月就會發生巨大的變化。

But in as much as DeepSeek is interesting, I think the work that XAI is doing and Grace and what it is capable of is equally interesting.

不過，儘管 DeepSeek 很有趣，但我認為 XAI 所做的工作以及 Grace 及其功能同樣有趣。

I think we are definitely headed to a world in which there are now several players.

我認為我們肯定會走向一個擁有多個參與者的世界。

It's not to any longer that are leading the charge when it comes to the world's innovation with AI.

在全球人工智慧創新領域，美國不再處於領先地位。

And the fact that it is a healthy combination of Opes models as well as proprietary model, we think is a good thing.

事實上，它是 Opes 模型和專有模型的健康組合，我們認為這是一件好事。

As I said, our value comes from our customers being able to bring all of their data together into one place and drive more and more value with it.

正如我所說，我們的價值來自於我們的客戶能夠將他們的所有資料集中到一個地方，並以此創造越來越多的價值。

And what our partnerships with the leading model makers of the world indicates is an implicit acknowledgment that we have a big role to play in this world of AI.

我們與世界領先的模型製造商的合作表明，我們預設我們在人工智慧世界中發揮著重要作用。

And so what we are doing is building the best products that can take advantage of the data gravity that we have and access to the biggest, best models that are on the planet.

因此，我們正在做的是打造最好的產品，利用我們擁有的數據引力，並且可以使用地球上最大、最好的模型。

Absolutely, I think there is a belief on the part of many, especially the ones that can afford it that there are more breakthroughs to be had by investing hundreds of millions of dollars.

當然，我認為很多人，特別是那些有能力的人，都相信投資數億美元可以取得更多突破。

I mean, sadly or not.

我的意思是，無論是否悲傷。

That's not us, but I feel very happy about our ability to work with these folks and create value for our customers.

這不是我們，但我對我們能夠與這些人合作並為我們的客戶創造價值感到非常高興。

Kash Rangan, Goldman Sachs.

高盛的卡什·蘭根 (Kash Rangan)。

This is Matt Martino on for Kash Rangan.

這是 Kash Rangan 的 Matt Martino。

Sridhar, one for you.

Sridhar，給你一個。

I know Snowflake is recently coming off their sales kickoff.

我知道 Snowflake 最近剛開始銷售。

So it would just be great to get some of your takeaways from the event and kind of what the key message was to the sales force, whether it's around prosecuting new use cases or pushing some of the newer products Snowflake is bringing to market?

所以，如果您能從這次活動中得到一些收穫，並且對銷售人員來說，關鍵訊息是什麼，無論是圍繞新的用例還是推銷 Snowflake 推向市場的一些新產品，那就太好了？

As you folks know, sales kickoff is about unifying around a common message, a common team a sense of purpose.

大家知道，銷售啟動是為了圍繞著一個共同的訊息、一個共同的團隊目標感來團結大家。

I think I found the enthusiasm among the folks to be infection.

我想我發現人們的熱情具有感染力。

I think it was very good.

我認為這非常好。

I can't obviously attend like all of the meetings.

我顯然不能參加所有的會議。

They're all in parallel.

它們都是並行的。

I looked at some of the material.

我看了一些材料。

I think the level of sophistication that our leaders are bringing to how they take care of business where they find out what do exemplary ESCs to and how do we hold them as a role model for others and how we thoughtfully add on new products.

我認為，我們的領導者在處理業務時表現出的成熟度​​水平，他們會發現模範 ESC 的作用是什麼，我們如何將他們作為他人的榜樣，以及如何周到地添加新產品。

As I said, we are at a place where it's pretty unreasonable for anyone to expect that they're not going to know everything that Snowflake does.

正如我所說的，我們現在所處的境地，任何人期望自己不知道 Snowflake 所做的一切都是非常不合理的。

So we've introduced things like colleges.

因此我們引入了諸如大學之類的事物。

These are essentially constructs within Snowflake cross specialization in different areas, so that somebody that wants to become an expert in machine learning within a particular pod can sign up, become that expert and serve as a point of contact for that particular pad.

這些本質上是 Snowflake 在不同領域交叉專業化的構造，以便想要成為特定領域機器學習專家的人可以註冊，成為該專家並作為該特定領域的聯絡人。

So what I would say I saw was this sort of sophistication and confidence in being able to take our product to market.

所以我想說，我看到了這種將我們的產品推向市場的成熟度和信心。

And of course, there's a lot of how do we do right by the customer, what creates value for them, how do we work with them, that was also front-end center.

當然，我們還有很多事情要做，例如如何為客戶做好事，如何為他們創造價值，如何與他們合作，這些也是前端中心。

But these folks are also there.

但這些人也在那裡。

Anything else to add, Mike, Christian?

還有什麼要補充的嗎，麥克，克里斯蒂安？

Out of excitement for our product lineup on what's coming, we'll share more at Summit.

出於對即將推出的產品陣容的興奮，我們將在峰會上分享更多消息。

Yes.

是的。

Joel Fishbein, Truist Securities.

Truist Securities 的 Joel Fishbein。

I guess it's a two-part.

我猜它是由兩個部分組成的。

One for Sridhar and one for Mike, but same topic.

一個是給 Sridhar 的，另一個是給 Mike 的，但主題相同。

Mike, you had an expansion with your partnership with Microsoft and relates to Open AI.

麥克，你與微軟的合作已經擴展，並且與 Open AI 相關。

I would love to just get a little more granular about what that means for you guys for Snowflake?

我很想更詳細地了解這對 Snowflake 來說意味著什麼？

And Mike, if you can potentially quantify what that could mean from a revenue standpoint in the future?

麥克，您是否可以從未來的收入角度量化這意味著什麼？

I'll start, and Christian should add.

我先開始，然後克里斯蒂安補充。

We have a broad and deep partnership with Microsoft at the level of data, but also at the level of products where things that we create come out in Microsoft Copilot, come out in Teams.

我們與微軟在資料層面有著廣泛而深入的合作關係，在產品層面也是如此，我們創造的東西出現在 Microsoft Copilot 和 Teams 中。

And so I'm very happy with that partnership.

我對這段合作關係感到非常高興。

We are increasingly going to market together in a number of situations.

我們在許多情況下都會越來越多地進行聯合行銷。

And so I think that is all hugely positive.

所以我認為這一切都是非常正面的。

The specifics of this partnership means is that open AI models that effectively accessible within snowflake security perimeter.

此次合作的具體內容意味著開放的人工智慧模型可以在雪花安全邊界內有效存取。

And that's a highly technical definition.

這是一個非常技術性的定義。

It is basically the guarantee that we make to our customers that their data is fully under our control.

這基本上是我們向客戶做出的保證：他們的數據完全在我們的控制之下。

It's a big deal for our customers.

這對我們的客戶來說是一件大事。

I think what this means in practice is that every product that we make starting with simply having the model available in a model garden that we have, I use Anthropic all the time in one of our internal instances, that ability to have access to these world-class models to then build different kinds of chatbot, different kinds of Agentic applications.

我認為這在實踐中意味著，我們製造的每一種產品都是從我們擁有的模型園中可用的模型開始的，我一直在我們的一個內部實例中使用 Anthropic，這種能力可以訪問這些世界一流的模型，然後構建不同類型的聊天機器人、不同類型的 Agentic 應用程式。

And so what this enables is for us and our customers is to be able to build world-class applications without having to have data go anywhere else without special licenses that are needed.

因此，這使我們能夠和我們的客戶建立世界一流的應用程序，而無需將資料傳輸到其他任何地方，也不需要特殊的許可證。

It just means that like open AI models are available out of the box just like Anthropic models are available on AWS out of the box.

這只是意味著開放的 AI 模型可以開箱即用，就像 Anthropic 模型在 AWS 上可以開箱即用一樣。

So I think this is a pretty big deal for a lot of our customers.

所以我認為這對我們的許多客戶來說都是一件大事。

Cover on the overall partnership -- okay.

涵蓋整體合作關係－好的。

So we're leveraging for our own products on top.

因此，我們正在充分利用我們自己的產品。

So it's good for our customers use directly but also for ourselves.

因此，這對我們的客戶直接使用和我們自己都有好處。

Yes.

是的。

And I'll just say, Joel, what is that impact going to be on our business?

我只想說，喬爾，這會對我們的業務產生什麼影響？

Obviously, we wouldn't do it if we didn't think it could be impactful to our business, but it's too early to say.

顯然，如果我們認為這不會對我們的業務產生影響，我們就不會這樣做，但現在說還為時過早。

And I would say that would be upside in our revenue once we see traction with that.

我想說，一旦我們看到這項進展，我們的收入就會增加。

But it's going to take some time before we get this rolled out to customers.

但我們還需要一些時間才能推廣到客戶。

There are no additional questions waiting at this time.

目前沒有其他問題需要回答。

So I'll pass the call back to Sridhar for any closing remarks.

因此，我將把電話轉回給 Sridhar，請他做最後發言。

Thank you.

謝謝。

In closing, think Snowflake stands to benefit enormously from the data and AI revolution that is sweeping the enterprise market.

最後，我認為 Snowflake 將從席捲企業市場的數據和人工智慧革命中受益匪淺。

Our philosophy of an easy-to-use, fast to value efficient product makes us uniquely differentiated and much loved by our customers.

我們的理念是生產易於使用、快速實現價值高效的產品，這使我們獨樹一幟並深受客戶喜愛。

30% product revenue growth in fiscal '25, combined with our strong initial outlook for fiscal '26 think demonstrates our ability to execute that scale.

25財年產品營收成長30%，加上我們對26財年的強勁初步前景，證明了我們實現這一規模的能力。

And so we are going to continue our strategy of driving high growth and efficiency.

因此，我們將繼續推行高成長、高效率的策略。

Our ability to release products and take them to market quickly is what enables high growth, simultaneously generating more than $1 billion of adjusted free cash flow, expanding operating margin and increasing SBC efficiency -- demonstrate the strength of the business.

我們快速發布產品並將它們推向市場的能力是我們實現高成長的關鍵，同時產生了超過 10 億美元的調整後自由現金流、擴大了營業利潤率並提高了 SBC 效率——展示了業務的實力。

I think the long-term profile of Snowflake is one that showcases durable growth and continued margin expansion, which I think is very unique.

我認為 Snowflake 的長期表現是持久的成長和持續的利潤率擴大，我認為這非常獨特。

And this is really exciting, and I look forward to sharing more and more of our progress with all of you along the way.

這確實令人興奮，我期待與大家分享我們在這過程中取得的更多進展。

Thank you all for joining us.

感謝大家加入我們。

That concludes the conference call.

電話會議到此結束。

Thank you for your participation.

感謝您的參與。

You may now disconnect your lines.

現在您可以斷開線路了。