Snowflake Inc (SNOW) 2026 Q2 法說會逐字稿

Good afternoon, thank you for attending the Snowflake Inc. second quarter fiscal year '26 earnings call. My name is Cameron, and I'll be your moderator for today. (Operator Instructions) And I would now like to pass over to your Jimmy Sexton, the Head of Investor Relations.

下午好，感謝您參加 Snowflake Inc. 26 財年第二季財報電話會議。我叫卡梅倫，今天我將擔任主持人。（操作員指示）現在我想把麥克風交給投資人關係主管 Jimmy Sexton。

Good afternoon, and thank you for joining us on Snowflake's Q2 fiscal 2026 earnings call. Joining me on the call today are Sridhar Ramaswamy, our Chief Executive Officer; Mike Scarpelli, our Chief Financial Officer; and Christian Kleinerman, our Executive Vice President of Product, who will participate in the Q&A.

下午好，感謝您參加 Snowflake 2026 財年第二季財報電話會議。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 和我們的產品執行副總裁 Christian Kleinerman，他們將參與問答環節。

During today's call, we will review our financial results for the second-quarter of fiscal 2026 and discuss our guidance for the third quarter and full year fiscal 2026. 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，我們將回顧 2026 財年第二季的財務業績，並討論 2026 財年第三季和全年的指引。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 risks and uncertainties, which could cause them to differ materially from our actual results. Information concerning these risks and uncertainties is available in our earnings press release, our most recent Form 10-K and 10-Q and our other SEC reports.

這些聲明受風險和不確定性的影響，可能導致它們與我們的實際結果有重大差異。有關這些風險和不確定性的資訊可在我們的收益新聞稿、最新的 10-K 和 10-Q 表格以及其他 SEC 報告中找到。

All our statements are made as of today based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During today's call, we will also discuss certain non-GAAP financial measures. See our investor presentation for reconciliation of GAAP to non-GAAP measures and business metric definitions, including adoption.

我們所有的聲明都是根據我們目前掌握的資訊截至今天所做的。除法律要求外，我們不承擔更新任何此類聲明的義務。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。請參閱我們的投資者介紹，以了解 GAAP 與非 GAAP 指標和業務指標定義的對帳情況（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 be posted on the website.

收益新聞稿和投資者簡報可在我們的網站 investors.snowflake.com 上查閱。今日電話會議的重播也將在網站上發布。

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. Thank you all for joining us today. Snowflake has delivered yet another strong quarter. And I'm proud of the incredible work across our team and the deep partnerships with our customers to deliver these renewals. Our core business remains very strong.

謝謝，吉米，大家好。感謝大家今天的參與。Snowflake 又一個季度表現強勁。我為我們團隊的出色工作以及與客戶的深度合作實現這些更新而感到自豪。我們的核心業務依然非常強勁。

And we continue to deliver product innovation to market at a rapid pace while strengthening our go-to-market motion for growth. We're executing with intensity and alignment and continue to see an enormous opportunity ahead. Snowflake remains laser focused on our mission to empower every enterprise to achieve its full potential through data and AI.

我們將持續快速向市場推出產品創新，同時加強我們的市場推廣力度，實現成長。我們正在全力以赴、協調一致地執行，並繼續看到未來巨大的機會。Snowflake 始終專注於我們的使命，透過數據和人工智慧幫助每個企業充分發揮其潛力。

We're delivering our more than 12,000 customers tremendous value throughout their entire data life cycle with an AI data cloud that's designed to enable faster innovation and remote friction from business operations.

我們透過旨在實現更快創新和遠端消除業務營運摩擦的 AI 數據雲，為 12,000 多名客戶的整個數據生命週期提供巨大價值。

We remain disciplined in driving operational rigor across our business, gaining greater efficiency even as we continue to invest aggressively in growth. We continue to execute with urgency and focus to capture the opportunities ahead and sustain durable momentum.

我們始終嚴格執行業務營運的紀律，在持續大力投資成長的同時，也獲得了更高的效率。我們將繼續緊急並集中精力，抓住未來的機會並保持持久的動力。

Product revenue for Q2 was $1.09 billion, up strong 32% year-over-year, demonstrating an acceleration in growth from last quarter. Remaining performance obligations totaled $6.9 billion with year-over-year growth of 33%.

第二季產品營收為 10.9 億美元，較上年強勁成長 32%，較上一季成長加速。剩餘履約義務總額為 69 億美元，年增 33%。

Our net revenue retention rate was a very healthy 125%. Our non-GAAP operating margin increased to 11%, reflecting our focus on efficiency and operational rates. As you can see, we have continued to deliver strong revenue growth and healthy result this quarter.

我們的淨收入保留率達到了非常健康的125%。我們的非公認會計準則營業利潤率成長至 11%，反映出我們對效率和營運率的關注。如您所見，本季度我們繼續實現強勁的收入成長和健康的業績。

And as a result, we are increasing our growth expectations for the year. At Snowflake, we believe the great technologies defined by the experience of making something complex, feel effortless. And we put simplicity at the center of not just our product design, but our entire customer experience. We are committed to delivering a cohesive product with fast time to value and it's a differentiator that leads customers to choose Snowflake again and again.

因此，我們提高了今年的成長預期。在 Snowflake，我們相信，偉大的科技源自於製造複雜事物的經驗，讓人感覺毫不費力。我們不僅將簡潔置於產品設計的核心，也將其置於整個客戶體驗的核心。我們致力於提供具有快速價值實現時間的有凝聚力的產品，這是讓客戶一次又一次選擇 Snowflake 的差異化因素。

It's why enterprise leaders like Booking.com on the Intercontinental Exchange used Snowflake. Our platform is easy to use, connected to enable fluid access to data wherever it sits and trusted by company of all sizes and industries. And global hospitality icon Hyatt Hotel uses Snowflake to simplify data management and ensure unified go.

這就是為什麼洲際交易所的 Booking.com 等企業領導者使用 Snowflake 的原因。我們的平台易於使用，無論數據位於何處，均可流暢地存取數據，並受到各種規模和行業的公司的信賴。全球酒店業巨頭凱悅酒店則使用 Snowflake 來簡化資料管理並確保統一運作。

By consolidating enterprise data into a single environment, it empowers its teams with fast, secure access to information, enabling them to make informed decisions that enhance customer experiences. and drive operational efficiency.

透過將企業數據整合到單一環境中，它使其團隊能夠快速、安全地存取訊息，使他們能夠做出明智的決策，從而增強客戶體驗並提高營運效率。

This quarter, we delivered on our product strategy, introducing incredible new innovations to drive value at each stage of our customers data journey. Of course, AI is front and center. We are continuing to advance our leadership in enterprise AI with Snowflake Intelligence now in public preview.

本季度，我們實施了產品策略，推出了令人難以置信的創新，以在客戶數據旅程的每個階段推動價值。當然，人工智慧是最重要的。我們將繼續提升我們在企業 AI 領域的領導地位，Snowflake Intelligence 現已公開預覽。

This platform enables every user to talk to their enterprise data turning structured and unstructured data into actionable insights through natural language, and it empowers the creation of intelligent agents directly on enterprise data.

該平台使每個用戶都能與他們的企業數據對話，透過自然語言將結構化和非結構化數據轉化為可操作的見解，並支援直接在企業數據上創建智慧代理。

Early adoption is underway with customers like Cambia Health Solutions, which serves 2.6 million members in the Pacific Northwest. They leverage Snowflake's Intelligence to create its first intelligence agent to assist their teams in improving health outcomes for its Medicare members.

目前，Cambia Health Solutions 等客戶正在進行早期採用，該公司為太平洋西北地區的 260 萬名會員提供服務。他們利用 Snowflake 的智慧技術創建了第一個智慧代理，以協助他們的團隊改善醫療保險成員的健康狀況。

This intelligence agent helps [KBM] Medicare teams quickly analyze vast amounts of both point in time and longitudinal data, enabling them to scale their ability to deliver differentiated, personalized health care experiences and ensure members receive the right care at the right time.

此智慧代理可協助 [KBM] 醫療保險團隊快速分析大量時間點和縱向數據，使他們能夠擴展提供差異化、個人化醫療保健體驗的能力，並確保會員在正確的時間獲得正確的護理。

Then there's Duck Creek Technologies, a leader in insurance core systems and analytics, who is leveraging Snowflake to drive innovation with AI and agentic workflow. They're using Snowflake intelligence to power internal teams and increase efficiency across finance, sales and HR, ultimately setting the standard for the insurance industry.

然後是保險核心系統和分析領域的領導者 Duck Creek Technologies，它正在利用 Snowflake 推動人工智慧和代理商工作流程的創新。他們正在利用 Snowflake 智慧為內部團隊提供支持，提高財務、銷售和人力資源方面的效率，最終為保險業樹立標準。

Alongside Snowflake Intelligence, we introduced Cortex AISQL, bringing AI natively into SQL. Customers can now invoke AI models directly within Snowflake, eliminating data movement and unifying analytics and AI in a single step.

除了 Snowflake Intelligence，我們也推出了 Cortex AISQL，將 AI 原生地引入 SQL。客戶現在可以在 Snowflake 中直接呼叫 AI 模型，從而消除資料移動並透過一步統一分析和 AI。

We have also made great strides to deliver faster, more seamless performance with the launch of Gen2 warehouse. Already, they're helping our customers deliver up to 2x faster performance and greater efficiency, automatically optimizing resources to accelerate insights and simplify data management without increasing costs, strengthening the value that our customers see from Snow.

隨著 Gen2 倉庫的推出，我們也取得了巨大進步，提供更快、更無縫的效能。它們已經幫助我們的客戶實現高達 2 倍的效能和更高的效率，自動優化資源以加速洞察並簡化資料管理，而不會增加成本，從而增強了客戶從 Snow 中看到的價值。

Without introduction of Snowflake Postgres, we have reinforced our commitment to developers, enabling our customers with enterprise-grade PostgreSQL to build and run their most critical AI-powered applications on Postgres right, inside the Snowflake AI data clock.

在沒有引入 Snowflake Postgres 的情況下，我們加強了對開發人員的承諾，使我們的客戶能夠使用企業級 PostgreSQL 在 Snowflake AI 資料時脈內在 Postgres 上建置和運行他們最關鍵的 AI 驅動應用程式。

And we have extended our connectivity platform with Snowflake open flow, making it easy to bring in structured, unstructured, batch or streaming data. Built on our acquisition of Datavolo, OpenFlow provides seamless access to all enterprise data and now supports change data capture from our article through strategic partnerships.

我們還透過 Snowflake 開放流擴展了我們的連接平台，從而可以輕鬆引入結構化、非結構化、批量或流資料。OpenFlow 建立在我們對 Datavolo 的收購之上，它提供了對所有企業資料的無縫訪問，現在透過策略合作夥伴關係支援從我們的文章中捕獲變更資料。

When customers already using open floor to unlock new value from their data architectures OpenFlow expand our reach into the $17 billion data integration market. It's also now easier to bring no work close into snowflake with Snowflake Connect Apache Spark now in public preview. This enables our customers to bring our Spark workloads directly into Snowflake, eliminating the burden of managing and tuning separate spark environment.

當客戶已經使用開放式平台從其資料架構中釋放新價值時，OpenFlow 將我們的業務範圍擴展到價值 170 億美元的資料整合市場。現在，使用現已公開預覽的 Snowflake Connect Apache Spark，可以更輕鬆地將 no work close 帶入 snowflake。這使我們的客戶能夠將我們的 Spark 工作負載直接帶入 Snowflake，從而消除了管理和調整單獨的 Spark 環境的負擔。

Customers can now run Spark data frame and Spark SQL natively on Snowflake's high-performance engines, simplifying operations and accelerating time to value. Overall, it was an amazing quarter for product innovation.

客戶現在可以在 Snowflake 的高效能引擎上原生運行 Spark 資料框和 Spark SQL，從而簡化操作並加快價值實現時間。總體而言，這是一個產品創新令人驚嘆的季度。

In the first half of year alone, we launched approximately 250 capabilities to general availability, demonstrating both the pace of our innovation under breadth of our platform expansion. But we are not stopping there as we innovate. We are continuing to strengthen our platform and help our customers do more with their data to deliver great business out.

光是上半年，我們就推出了約 250 項功能，展示了我們平台擴展廣度和創新速度。但我們不會就此止步，我們將繼續創新。我們正在繼續加強我們的平台，並幫助我們的客戶更好地利用他們的數據來開展出色的業務。

As more companies face a challenge of data spread across different places, we are helping them effectively share data and collaborate. As of this quarter, 40% of our customers are now data sharing on Snowflake, driving powerful network effects that strengthen our ecosystem and expand customer value.

隨著越來越多的公司面臨數據分散在不同地方的挑戰，我們正在幫助他們有效地共享數據並進行協作。截至本季度，我們 40% 的客戶正在 Snowflake 上共享數據，從而產生強大的網路效應，加強了我們的生態系統並擴大了客戶價值。

We're continuing to see strong adoption of open data format, especially truly open modern table pharma like Apache Iceberg. We now have over 1,200 accounts using experts ongoing our leadership in bringing truly open standards to the enterprise.

我們繼續看到開放資料格式的廣泛採用，尤其是像 Apache Iceberg 這樣真正開放的現代表格製藥。現在，我們擁有超過 1,200 個帳戶，使用專家繼續發揮我們的領導作用，為企業帶來真正的開放標準。

Our progress with AI has been remarkable. Today, AI is a core reason why customers are choosing Snowflake influencing nearly 50% of new logos won in Q2. And once they are on our platform, AI becomes a cornerstone of their strategy, powering 25% , all-deployed use cases with over [6100] accounts using Snowflakes AI [every week].

我們在人工智慧方面取得了顯著的進步。如今，人工智慧已成為客戶選擇 Snowflake 的核心原因，影響了第二季近 50% 的新標誌。一旦他們加入我們的平台，人工智慧就會成為他們策略的基石，每週使用 Snowflakes AI 為 25% 的已部署用例提供支持，涉及超過 [6100] 個帳戶。

We have embedded AI across the data life cycle to accelerate analytics, transform workflows and even power migration. For example, Snowflake convert AI uses AI-driven automation to speed up large-scale migration, minimize manual recording and reduce risk, helping customers move faster and with greater content. Cortex AI continues to play a foundational role in enterprise AI strategy.

我們在整個資料生命週期中嵌入了人工智慧，以加速分析、轉變工作流程甚至電力遷移。例如，Snowflake Convert AI 使用人工智慧驅動的自動化來加速大規模遷移，最大限度地減少手動記錄並降低風險，幫助客戶更快遷移並獲得更多內容。Cortex AI 持續在企業 AI 策略中發揮基礎作用。

For example, Thomson Reuters is transforming how its business users easily access information by deploying AI-powered agents built on Snowflake Cortex search and LLM observability. This enables real time insight, seamlessly handle drag and text to SQL and significantly reduces time to insight and costs across functions like finance and HR.

例如，湯森路透正在透過部署基於 Snowflake Cortex 搜尋和 LLM 可觀察性的人工智慧代理來改變其商業用戶輕鬆存取資訊的方式。這可以實現即時洞察，無縫處理拖放和文字到 SQL，並顯著減少財務和人力資源等職能部門的洞察時間和成本。

Then there's BlackRock, which is leveraging called Snowflake Cortex AI to help its team serve their clients more effectively and at a much larger scale. Our technology allows them to pull together every piece of information they have on a client, from their past portfolio not from a recent call and get instant insights. It's like a super power that helps them understand exactly what each client needs so they can provide the best possible service.

然後是貝萊德，它正在利用名為 Snowflake Cortex AI 的人工智慧來幫助其團隊更有效、更大規模地為客戶服務。我們的技術使他們能夠匯總有關客戶的每一條信息，這些信息來自客戶過去的投資組合而不是最近的電話，並獲得即時的見解。這就像一種超能力，可以幫助他們準確地了解每個客戶的需求，從而提供最好的服務。

We have furthered our AI leadership by integrating the world's leading model in Cortex, ensuring day one availability of Open AI's new open source as well as advanced GPT-5 model. providing our customers with choice and flexibility to leverage their model of choice for their enterprise AI application.

我們透過在 Cortex 中整合世界領先的模型來進一步鞏固我們在人工智慧領域的領導地位，確保 Open AI 的新開源模型和先進的 GPT-5 模型能夠第一天投入使用，為我們的客戶提供選擇和靈活性，讓他們能夠將自己選擇的模型用於企業人工智慧應用。

Beyond what's possible with AI today, we are also making Snowflake, the destination for building the next generation of cutting-edge applications such as (inaudible) AI, Agentic AI platform, which helps customers automate workflow for tasks like supply chain and regulatory compliance.

除了當今人工智慧所能實現的功能之外，我們還在打造 Snowflake，它是建立下一代尖端應用程式（如（聽不清楚）人工智慧、Agentic AI 平台）的目的地，該平台可幫助客戶實現供應鏈和法規遵循等任務的工作流程自動化。

As we strengthen our platform and introduce new capabilities, we remain limited to scaling efficiently. Our go-to-market teams are demonstrating renewed focus and rigor as evidenced by our healthy retention rate and our addition of 533 customers including 15 Global 2000 companies this quarter.

隨著我們加強平台並引入新功能，我們仍然受限於有效擴展。我們的行銷團隊展現了新的專注力和嚴謹性，這從我們健康的保留率以及本季新增的 533 個客戶（包括 15 家全球 2000 強公司）可以看出。

This year, Snowflake summit was a clear marker of our momentum. The event, our biggest yet, do record numbers of over 22,000 customers, partners and developers from around the world and underscore the scale of our community and the excitement around the AI data. We're also investing in our partnership. Today, more than 12,000 global partners, including leading cloud providers, technology innovators and system integrators are part of our ecosystem.

今年的雪花峰會清楚地表明了我們的發展勢頭。這項活動是我們迄今為止規模最大的一次，來自世界各地的客戶、合作夥伴和開發人員人數超過 22,000 名，創下了歷史新高，凸顯了我們社區的規模以及人們對人工智慧數據的熱情。我們也對我們的合作關係進行了投資。如今，我們的生態系統已擁有超過 12,000 個全球合作夥伴，包括領先的雲端供應商、技術創新者和系統整合商。

We are scaling our go-to-market engine, while tightly aligned across engineering, product, marketing and sales. This collaboration enables us to deliver greater value to existing customers, but also win new ones with speed and precision. It's certainly exciting time at Snowflake, and I'm proud of the discipline, efficiency and innovation we've built across the business.

我們正在擴大我們的市場進入引擎，同時緊密協調工程、產品、行銷和銷售。此次合作使我們能夠為現有客戶提供更大的價值，同時也能快速、精準地贏得新客戶。這對 Snowflake 來說無疑是令人興奮的時刻，我為我們在整個企業中建立的紀律、效率和創新感到自豪。

We've got a strong operational rhythm. We're investing strategically for growth, and we're in the groundwork for continued scale.

我們有很強的營運節奏。我們正在進行策略性投資以實現成長，並為持續擴大規模奠定基礎。

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

麥克，你為什麼不向我們介紹一些財務細節呢？

Thank you, Sridhar. In Q2, product revenue growth accelerated to 32% year-over-year. Product revenue benefited from strength in our core business. At Investor Day, you heard us outline our four key product categories: analytics, data engineering, AI, and applications and collaboration.

謝謝你，Sridhar。第二季度，產品收入成長率年增至32%。產品收入受益於我們核心業務的強勁成長。在投資者日，您聽到我們概述了我們的四個主要產品類別：分析、數據工程、人工智慧以及應用程式和協作。

In Q2, new features across all four product categories outperformed our expectations. With net new customer adds in the quarter, up 21% year-over-year, it is clear that our new customer acquisition motion is yielding positive results.

在第二季度，所有四個產品類別的新功能都超出了我們的預期。本季淨新增客戶年增 21%，顯然我們的新客戶獲取措施正在產生正面成果。

And in the last quarter, 50 customers crossed the $1 million in trailing 12-month revenue, a record for the company, $1 million-plus customers now total 654.

上個季度，有 50 位客戶過去 12 個月的收入突破了 100 萬美元，創下了公司的最高紀錄，目前 100 萬美元以上的客戶總數達到 654 位。

Shifting to margins. Q2 non-GAAP product gross margin was 76.4%. Non-GAAP operating margin was 11%. Operating margin benefited from revenue performance in the quarter. We are focused on delivering margin expansion while investing in our business. In Q2, we added 529 heads including 364 sales and marketing heads.

轉向邊緣。第二季非公認會計準則產品毛利率為76.4%。非公認會計準則營業利益率為11%。營業利潤率受益於本季的收入表現。我們致力於在投資業務的同時擴大利潤率。第二季度，我們新增了 529 名員工，其中包括 364 名銷售和行銷員工。

As a reminder, our sales and marketing hiring is weighted to the first half of the year. In Q2, non-GAAP adjusted free cash flow margin was 6%. As discussed on our prior calls, we expect free cash flow to be weighted to the second half of the year.

提醒一下，我們的銷售和行銷招募主要集中在上半年。第二季度，非公認會計準則調整後的自由現金流利潤率為 6%。正如我們在之前的電話會議上所討論的那樣，我們預計自由現金流將集中在今年下半年。

This expectation is supported by contracted billings, a large renewal base and large deal volume in the pipeline. We did not utilize our [repurchase] program in Q2. We have $1.5 billion remaining on our authorization through March 2027. We ended the quarter with $4.6 billion in cash, cash equivalents, short-term and long-term investments.

這項預期得到了合約帳單、龐大的續約基礎和大量交易量的支持。我們在第二季度沒有使用我們的[回購]計劃。截至 2027 年 3 月，我們的授權金額還剩餘 15 億美元。截至本季末，我們擁有 46 億美元的現金、現金等價物、短期和長期投資。

Moving to our outlook. For Q3, we expect product revenue between $1.125 billion and $1.13 billion, representing 25% to 26% year-over-year growth. We expect non-GAAP operating margin of 9%. We are increasing our product revenue guidance for FY26. We now expect product revenue of $4.395 billion, representing 27% year-over-year growth. We expect non-GAAP product gross margin of 75% and non-GAAP operating margin of 9% and non-GAAP adjusted free cash flow margin of 25%.

轉向我們的展望。對於第三季度，我們預計產品收入在 11.25 億美元至 11.3 億美元之間，年增 25% 至 26%。我們預期非公認會計準則營業利益率為 9%。我們正在提高 26 財年的產品收入預期。我們現在預計產品收入為 43.95 億美元，年增 27%。我們預期非 GAAP 產品毛利率為 75%，非 GAAP 營業利潤率為 9%，非 GAAP 調整後自由現金流利潤率為 25%。

Finally, I'd like to provide an update on our CFO transition. We are making progress on our search and we will make an announcement once we have more firm details to share.

最後，我想提供有關我們財務長過渡的最新情況。我們的搜尋工作正在取得進展，一旦我們有更多確切細節可以分享，我們就會發佈公告。

With that, operator, you can now open up the line for questions.

接線員，現在您可以打開熱線來回答問題了。

(Operator Instructions)

（操作員指示）

Sanjit Singh, Morgan Stanley.

摩根士丹利的 Sanjit Singh。

Yeah, thank you for taking the question, and congrats on the accelerating product revenue growth this quarter. You guys have been executing quite well. And it seems like multiple parts of the equation came to work in Q2. The question for you is that it seems like modernizing the data infrastructure is a real priority among the Fortune 500, the Global 2000.

是的，感謝您的提問，並祝賀本季產品收入加速成長。你們的表現一直都很好。看起來，等式的多個部分在第二季開始發揮作用。您的問題是，對財富 500 強和全球 2000 強企業來說，資料基礎設施的現代化似乎是一個真正的優先事項。

I want to get a sense of like, as we go through this modernization efforts, on the other side of that, do you see kind of durable growth or is this customers addressing their legacy data infrastructure, maybe you guys benefiting from that migration, if you will.

我想了解一下，當我們進行這種現代化努力時，另一方面，你是否看到了持久的成長，或者這些客戶是否正在解決他們遺留的資料基礎設施問題，也許你們會從這種遷移中受益，如果你願意的話。

But what is -- what do you -- how do you feel about the durability of growth on the other side of these data transformation efforts?

但是，您如何看待這些資料轉換工作在另一方面的成長持久性？

Well, I think data modernization is just the beginning of the journey is primarily driven by the fact that legacy systems have trouble scaling, whether it's workloads or our data. And bringing those systems on to Snowflake is step one in value realization.

嗯，我認為資料現代化只是旅程的開始，主要是因為遺留系統難以擴展，無論是工作負載還是我們的資料。將這些系統引入 Snowflake 是價值實現的第一步。

In fact, the feedback that I get from our customers is that this data monetization journey is even more important than before because they realized that AI transformation of workflows of how they interact with their customers is critically dependent on getting their data in a place that's AI ready.

事實上，我從客戶那裡得到的回饋是，這個資料貨幣化之旅比以前更加重要，因為他們意識到，他們與客戶互動的工作流程的人工智慧轉型，關鍵取決於將他們的資料放在一個可以為人工智慧做好準備的地方。

And that's where Snowflake comes in, data that is in Snowflake is increasingly AI ready, both for access by consumptive layers like Cortex analyst or Cortex search but also by agency players like Snowflake Intelligence, where you can both ask nontrivial questions. But we fully foresee things like applications coming on top of that data.

這就是 Snowflake 的用武之地，Snowflake 中的資料越來越適合人工智慧，既可以被 Cortex 分析師或 Cortex 搜尋等消費層訪問，也可以被 Snowflake Intelligence 等代理機構訪問，你們都可以在其中提出非平凡的問題。但我們完全預見到諸如應用程式之類的東西將基於這些數據。

So we feel very good that we are very much in the beginning of the journey, where data indeed does more for our customers.

因此，我們很高興看到我們正處於旅程的開始階段，而數據確實能為我們的客戶提供更多幫助。

Raimo Lenschow, Barclays.

巴克萊銀行的 Raimo Lenschow。

Perfect for me as well. I wanted to focus on the new customer at Obviously, great progress there. I remember last year, the US organization kind of got split into hundreds of farmers and that started to contribute. I think this year you did it for Europe. Is there already a contribution from the European side?

對我來說也很完美。我想把重點放在新客戶身上，顯然，那裡取得了巨大的進步。我記得去年，美國組織分裂成數百個農民，開始做出貢獻。我認為今年你為歐洲做到了這一點。歐洲方面是否已經做出貢獻？

Like can you speak to that kind of momentum that you have there on that part of the business? Thank you.

您能談談您在該業務領域所擁有的這種勢頭嗎？謝謝。

Yeah, what I would say is Europe is still developing, but it's contributing. We are laying the groundwork there. Obviously, we set up this new motion in the US first in the bulk of those new customers are coming from the US where we've been replicating that setup in EMEA as well as APJ. And we think that will yield as well there. But they're performing.

是的，我想說的是歐洲仍在發展，但它正在做出貢獻。我們正在那裡奠定基礎。顯然，我們首先在美國建立了這項新動議，因為大部分新客戶都來自美國，我們一直在 EMEA 以及 APJ 地區複製這種設定。我們認為這也會產生同樣的效果。但他們正在表演。

Karl Keirstead, UBS.

瑞銀的卡爾·基爾斯特德（Karl Keirstead）。

Sridhar, and Mike Scarpelli at Microsoft on the last call went out of his way to highlight an acceleration in Snowflake on Azure. I'm just curious, as I think through what may have driven the outstanding results this quarter, was there anything unique that you did with Microsoft or with customers that are running on Azure worth calling out or did it feel like your outperformance was fairly even across the different cloud providers. Thank you.

Sridhar 和微軟的 Mike Scarpelli 在最後一次電話會議上刻意強調了 Snowflake 在 Azure 上的加速。我只是很好奇，當我思考是什麼推動了本季的出色業績時，您是否對微軟或運行 Azure 的客戶做了一些獨特的事情，值得一提，或者您是否覺得您的表現在不同的雲端供應商中相當均衡。謝謝。

I would say actually, Azure was our fastest-growing cloud. It actually grew 40% year-over-year. Our customers running on Azure. And I would say a lot of that is attributable to better alignment between our field and Microsoft. We've been spending a lot of time in the last six months.

實際上我想說，Azure 是我們成長最快的雲端。它實際上同比增長了 40%。我們的客戶在 Azure 上執行。我想說，這在很大程度上歸功於我們的領域與微軟之間更好的協調。在過去的六個月裡我們花了很多時間。

There, I would also say too that Microsoft is very strong in EMEA, and we're seeing some good uptick in EMEA in our business as well with some large accounts that's contributing to that as well. But clearly, the Azure cloud is the fastest growing, but it's off a lower base. AWS is still the biggest, but Microsoft is moving up.

我還想說，微軟在歐洲、中東和非洲地區 (EMEA) 的表現非常強勁，而且我們的業務在歐洲、中東和非洲地區也出現了良好的成長勢頭，一些大客戶也為此做出了貢獻。但顯然，Azure 雲是成長最快的，但其基數較低。AWS 仍然是最大的，但微軟正在崛起。

The only thing that I'll add on top of that is that, I think we have both depth and breadth of collaboration. We work very closely with the Azure team at an infrastructure level at the level of Snowflake but also at the level of the end user products like Office copilot and RVI and the go-to-market partnerships that Mike referenced just now are an additional exert on top of that. We see these as long-term benefits for both the companies, and you'll see more and more results come out of it in the future.

除此之外，我唯一要補充的是，我認為我們的合作既有深度，也有廣度。我們與 Azure 團隊在 Snowflake 等基礎設施層級以及 Office copilot 和 RVI 等最終用戶產品層面密切合作，而 Mike 剛才提到的上市合作夥伴關係則是在此基礎上的額外努力。我們認為這對兩家公司來說都是長期利益，並且您將來會看到越來越多的成果。

Kirk Materne, Evercore ISI.

柯克·馬特恩（Kirk Materne），Evercore ISI。

Thanks very much, and my congrats on a great quarter. Mike, it sounds like there's a number of drivers of the upside in 2Q, especially around some of the newer products that came to market across those sorts of growth.

非常感謝，並祝賀本季取得優異成績。麥克，聽起來第二季的上漲動力很多，特別是在這些成長過程中上市的一些新產品。

I was just wondering, how did you sort of contemplate some of these newer products in the guide for 3Q? I know you guys tend to want to get a little bit of a trend line going before you want to make any kind of bet on them. So I was just wondering how the kind of how that played out in 2Q and how you're thinking about for 3Q? Thanks.

我只是想知道，您是如何考慮第三季指南中的一些新產品的？我知道你們在對它們進行任何形式的下注之前往往想要了解一點趨勢線。所以我只是想知道第二季的情況如何以及您對第三季有何看法？謝謝。

Well, as I said, they outperformed our expectations. We did have a modest amount in our forecast for those because it didn't just come out this quarter. We talked about it some, but we've been working on these for a while.

嗯，正如我所說，他們的表現超出了我們的預期。我們對這些數字的預測確實比較溫和，因為它不是本季才公佈的。我們對此進行了一些討論，但我們已經為此工作了一段時間。

And when we set our forecast for the next quarter, it's always based on consumption patterns we're seeing today. I would say, yes, Q2 surprised us on the upside, we knew it was going to be a strong quarter, but not as strong as it was, and that's just the nature of a consumption model.

當我們制定下一季的預測時，總是基於我們今天看到的消費模式。我想說，是的，第二季度的表現確實讓我們感到意外，我們知道這將是一個強勁的季度，但並沒有那麼強勁，這只是消費模式的本質。

Alex Zukin, Wolfe Research.

沃爾夫研究公司的亞歷克斯·祖金（Alex Zukin）。

Yeah, thanks for taking the question. I guess to the prior question, maybe if I think about the acceleration and consumption that you guys are now seeing, is this something where this is a normalization of like the demand environment, your customers feeling better about spending again or is there and/or is there something more happening where you're getting increasingly included in these AI initiatives as AI budgets, these new products are unlocking incremental budget spend. And if it's the latter, to what extent is --

是的，感謝您提出這個問題。我想回答前面的問題，也許如果我考慮一下你們現在看到的加速和消費，這是否是需求環境的正常化，你們的客戶對再次消費感覺更好，或者是否存在和/或是否發生了更多的事情，你們越來越多地被納入這些人工智能計劃，因為人工智能預算，這些新產品正在解鎖增量預算支出。如果是後者，那麼--

We were just cut off in the middle of Alex's question.

我們剛才在 Alex 的問題中被打斷了。

(Operator Instructions)

（操作員指示）

Perfect. Alex Zukin, line is now open.

完美的。亞歷克斯·祖金 (Alex Zukin)，線路現已開通。

Hey, sorry, I don't know where I got cut off, but to what extent do you feel as though the outperformance was kind of a normalization of the demand environment? And kind of improved execution from the field versus getting included in more of these AI-centric budgets and seeing some of these products really initiatives come to fruition.

嘿，抱歉，我不知道我在哪裡被打斷了，但是您在多大程度上覺得這種優異表現是需求環境的正常化？並且從現場執行情況的改善，而不是被納入更多以人工智慧為中心的預算，並看到其中一些產品真正取得成果。

And if you think about it more of as the latter, how do we think about that as we progress through the year is starting to drive really meaningful incremental upside on top of previous consumption trends in your customers.

如果你更從後者的角度來考慮，那麼我們如何看待這個趨勢呢？隨著時間的流逝，我們將開始在客戶先前的消費趨勢基礎上推動真正有意義的增量成長。

Mike and I have talked to this before, Alex, which is that our core business in analytics continues to be strong. It's the foundation of the company. And you can see this also in things like NRR, net revenue retention, which was a very solid 125%.

亞歷克斯，麥克和我之前談過這個問題，那就是我們在分析方面的核心業務繼續保持強勁。這是公司的基石。您還可以從 NRR（淨收入保留率）等方面看到這一點，該比率達到了非常穩定的 125%。

What is happening is that there is more and more recognition that the AI components of our data platform can deliver enormous value. And we're seeing budgets get allocated from large customers for AI projects.

實際情況是，人們越來越認識到我們資料平台的人工智慧元件可以帶來巨大的價值。我們看到大客戶為人工智慧專案分配了預算。

And typically, that also happens when the data is on Snowflake because our customers can realize but the things that they love about Snowflake, which is the ease of use, the work that they have put into governance to make sure that only the right people can see the right data, a lot of work that we put in to make sure that AI is trustworthy all of these play into these large customers using us for AI projects.

通常，當數據在 Snowflake 上時也會發生這種情況，因為我們的客戶可以意識到這一點，但他們喜歡 Snowflake 上時也會發生這種情況，因為我們的客戶可以意識到這一點，但他們喜歡 Snowflake 上時也會發生這種情況，因為我們的客戶可以意識到這一點，但他們喜歡 Snowflake 的地方在於它的易用性，他們在治理方面所做的工作以確保只有合適的人才能看到正確的數據，我們為確保人工智能值得信賴而投入的大量工作，所有這些都促使這些大客戶使用我們進行人工智能項目。

And for example, of the use cases that were deployed in Q2, close to [25] close to quarter of them involved AI in some form or the other. So this is definitely a trend that will continue. But again, I'll stress something that Mike has said, which is we forecast as well as we can, meaning that as these workloads become more and more mainstream, our prediction models are going to pick that up and increasingly rolled that into our forecast.

例如，在第二季度部署的用例中，近四分之一以某種形式涉及人工智慧。所以這肯定是會持續下去的趨勢。但我再次強調麥克所說的一點，那就是我們會盡可能地進行預測，這意味著隨著這些工作量變得越來越主流，我們的預測模型將將其納入其中，並將其逐漸納入我們的預測中。

But we feel very good about our ability to create business value with AI and our customers, and that is a trend that we expect to see both continue and accelerate.

但我們對自己利用人工智慧和客戶創造商業價值的能力感到非常滿意，我們預計這一趨勢將會持續並加速。

Kash Rangan, Goldman Sachs.

高盛的卡什·蘭根（Kash Rangan）。

Hi, congratulations. Good to see the re-acceleration and product revenue and also that expansion rate. Sridhar, I have a question for you. We have seen AI in the consumer ramp just get better and better. So I would argue the rate of improvement of these models, appears to have stalled a little bit, which is disputable. But at what point are we going to see the AI magic that has taken over the consumer world make its way into the enterprise?

你好，恭喜你。很高興看到產品收入和擴張率的再次加速。Sridhar，我有一個問題想問你。我們已經看到人工智慧在消費領域變得越來越好。因此我認為這些模型的改進速度似乎有點停滯，這是有爭議的。但是，什麼時候我們才能看到佔領消費世界的人工智慧魔力進入企業領域呢？

I mean, certainly, there seem to be some indicators of that happening at the platform layer. But what gives you the direction today more than perhaps a summit that AI and the enterprise is about to work through tangible business cases.

我的意思是，當然，似乎有一些跡象表明這種情況正在平台層面發生。但是，今天能給你指引方向的或許不只是人工智慧和企業即將透過實際的商業案例展開的峰會。

And also, I was intrigued by your comment on supporting Spark, I mean that confidence in supporting Spark on Snowflake seems to be a new thing that I picked up. Can you talk more about that as well. Thank you so much.

而且，我對您關於支持 Spark 的評論很感興趣，我的意思是，對在 Snowflake 上支持 Spark 的信心似乎是我學到的新東西。能再詳細談談這個嗎？太感謝了。

Yeah, on the first one, I definitely say that AI is emerging and increasingly powerful force. I can speak to it with personal experience. The kind of questions that we can ask of a sales agent that we developed on Snowflake intelligence has become pretty remarkable.

是的，關於第一個問題，我肯定地說人工智慧正在興起並且日益強大。我可以根據親身經歷來談論它。我們利用 Snowflake 智慧技術向銷售代理商提出的問題已經變得非常了不起。

Obviously, I wanted to answer questions like get an update about our customers that I'm about to meet so that my [AE] does not have to write that particular brief forming.

顯然，我想回答一些問題，例如獲取有關我即將會見的客戶的最新情況，這樣我的 [AE] 就不必寫那份特定的簡報。

But being able to do a cross-cutting analysis, for example, of the most popular use cases up trends in use cases, questions that I would normally need to go to an analyst for, Snowflake intelligence can figure out how do I pretty complicated plans for these and deliver this.

但是，能夠進行跨領域分析，例如，對最流行的用例、用例趨勢以及我通常需要向分析師提出的問題進行分析，Snowflake 智慧可以弄清楚如何為這些問題制定相當複雜的計劃並實現這些計劃。

I think that's where you are seeing the magic happen. And thanks for our partnerships with OpenAI. We launched GPT-5, the same day that they launched it. We launched GPT-5 on Snowflake. And similarly, with Anthropic, gives our customers the best of both worlds, the world's best models combined with the data about their business that they have often painstakingly put into Snowflake.

我想這就是你所見證的奇蹟發生的地方。感謝我們與 OpenAI 的合作。我們在他們推出 GPT-5 的同一天推出了它。我們在 Snowflake 上推出了 GPT-5。同樣，Anthropic 為我們的客戶提供了兩全其美的解決方案，將世界上最好的模型與他們經常煞費苦心投入 Snowflake 的業務數據相結合。

And that's where we are seeing massive value get realized. And that's a little bit of an [Aha] moment for us, for our customers. I'm happy to show off, for example, Snowflake intelligence to our customers in every conversation that they have and the -- reaction is that they want such functionality directly on top of their data as well. So Christian, do you want to take the part question, please?

這正是我們所看到的巨大價值得以實現的地方。對於我們和我們的客戶來說，這都是一個令人驚訝的時刻。例如，我很高興在與客戶的每次對話中向他們展示 Snowflake 智能，而他們的反應是，他們也希望在他們的數據上直接擁有這種功能。那麼 Christian，你想回答部分問題嗎？

Certainly. So we've talked about snow part for many years and how it has been performing well for us we outperformed all Spark distributions managed products out there. And what we heard from our customers is they will want to simplify the migration effort or cost to be able to get those benefits from Snowpark. Spark itself has introduced something called Spark Connect. And that is what we've done.

當然。因此，我們已經討論了多年的雪部分以及它如何為我們帶來良好的表現，我們的表現優於所有 Spark 分佈管理產品。我們從客戶那裡聽說，他們希望簡化遷移工作或成本，以便能夠從 Snowpark 獲得這些好處。Spark 本身引進了一種稱為 Spark Connect 的東西。這正是我們所做的。

We've adopted the Spark APIs, but the processing happens by Snowflake, specifically by Snowpark, so now you get the benefit of it is a familiar set of APIs and proven models, but with the performance and cost benefits of Snowpark.

我們採用了 Spark API，但處理由 Snowflake（具體來說是 Snowpark）進行，因此現在您可以獲得它的好處是一組熟悉的 API 和經過驗證的模型，但同時具有 Snowpark 的效能和成本優勢。

Brent Thill, Jefferies.

布倫特·蒂爾（Brent Thill），傑富瑞集團。

Thanks, Mike. You raised the guide more than the beat this quarter. I'm just curious the visibility in what you're seeing in the second half?

謝謝，麥克。本季度，您提高的指導值超過了節拍值。我只是好奇您對下半年的前景有何看法？

I would just say we've consistently been raising by the beat us more for the last six quarters. And that's based upon consumption trends we're seeing through literally today, and consumption is strong within our customers.

我只想說，過去六個季度以來，我們的利潤一直在穩步增長。這是基於我們今天所看到的消費趨勢，而且我們的客戶消費能力很強。

You see that in the net revenue retention, and we're seeing a number of our new products with a lot of uptick in those. And as Sridhar mentioned, we just went GA this year with 250 new features. All these features drive new revenue for Snowflake, and we anticipate continuing to have that type of delivery of new features going into the future.

您可以從淨收入保留中看到這一點，而且我們看到我們的許多新產品都出現了很大的成長。正如 Sridhar 所提到的，我們今年剛推出了 GA 版本，並推出了 250 個新功能。所有這些功能都為 Snowflake 帶來了新的收入，我們預計未來將繼續提供這種類型的新功能。

That's one of the things Sridhar's really focused on the last 1.5 years with engineering and product.

這是 Sridhar 在過去 1.5 年中在工程和產品方面真正關注的事情之一。

Mark Murphy with JPMorgan.

摩根大通的馬克墨菲。

Thank you. The sales and marketing new hires are again just an enormous number for the second consecutive quarter. I think it's the biggest six months of hiring that you've ever had. Can you walk us through the underlying dynamic?

謝謝。連續第二個季度，銷售和行銷部門的新員工數量再次創下紀錄。我認為這是你們有史以來招募人數最多的六個月。您能向我們介紹一下其中的根本動態嗎？

Does that reflect pipeline growth stepping up proportionately? And where is that going to place Snowflake in terms of the growth of your quota-carrying sales capacity by the time all of that ramps in 6 to 12 months or however long it takes?

這是否反映出管道成長正在相應加速？那麼，當所有這些在 6 到 12 個月內或無論需要多長時間時達到高峰時，Snowflake 在配額銷售能力的成長方面將處於什麼位置？

Yeah. I would say we've actually hired more sales and marketing people in the first six months of this year on a net basis than we did in the prior two years combined. But I want to remind you that in Q3 and Q4 of last year, we went through a pretty extensive performance management within our sales organization, in particular, we've pretty much worked through most of that.

是的。我想說，我們今年前六個月僱用的銷售和行銷人員實際上比前兩年僱用的總人數還要多。但我想提醒大家，在去年第三季和第四季度，我們在銷售組織內部進行了相當廣泛的績效管理，特別是，我們已經基本完成了大部分工作。

But we really look at productivity of reps, and we're really focused on getting reps and SEs, by the way, too, we've added a lot more SEs into the organization, we have more specialty sales people within the organization. And we will continue to add as long as we see that we're yielding the productivity.

但我們真正關注的是銷售代表的生產力，我們真正專注於獲得銷售代表和 SE，順便說一下，我們在組織中增加了更多的 SE，我們在組織內擁有更多的專業銷售人員。只要我們發現生產力有所提高，我們就會繼續增加。

And it's not just bookings is also activity and stuff of what they're doing with customers. And that's strong. But we've always anticipated that the first half of the year was going to be a much higher number than the second half.

這不僅僅是預訂，還有他們為客戶所做的活動和事情。這很強大。但我們一直預計上半年的數字將比下半年高出許多。

Thank you.

謝謝。

Brent Bracelin, Piper Sandler.

布倫特布雷斯林、派珀桑德勒。

Thank you. Good afternoon. Mike, I wanted to go back to the drivers of upside the quarter. If I just take a step back, I sequential growth in product revenue 2.5 years. a pretty sharp year-over-year acceleration in a number of million dollar customer adds. How much of the acceleration here in Q2 and surprise was driven by higher consumption in the core versus an incremental uptake on these new products in AI.

謝謝。午安.麥克，我想回到本季上漲的驅動因素。如果我回顧一下，我發現產品收入連續 2.5 年成長。百萬美元客戶數量的同比增長相當快。第二季的加速和意外成長有多少是由核心消費的增加而不是人工智慧新產品的增量所推動的。

Well, we had some large customers that were doing some migrations of new workloads that drove outperformance some very big customers. I would say we saw a little bit of contribution from crunch that acquisition we did with Postgres. But the newer workloads we're seeing meaningful contribution as well, too. But it's really the core of our business is what's driving the significant upside.

嗯，我們有一些大客戶，他們正在進行一些新工作負載的遷移，從而超越了一些非常大的客戶。我想說，我們從 Postgres 的收購中看到了一些貢獻。但我們也看到了較新的工作負載帶來的有意義的貢獻。但真正推動我們業務大幅成長的是其核心。

Tyler Radke, Citi.

花旗銀行的泰勒拉德克（Tyler Radke）。

Yeah, thank you for taking the question. Sridhar, one of the questions we often get from investors just in terms of framing the competitive environment. Obviously, Snowflake, Databricks, hyperscalers, including Microsoft fabric despite your recent partnership Palentir with others.

是的，謝謝你回答這個問題。Sridhar，我們經常從投資者那裡得到的一個問題就是如何建構競爭環境。顯然，儘管您最近與 Palentir 等公司建立了合作夥伴關係，但還有 Snowflake、Databricks、超大規模企業，包括 Microsoft fabric。

I'm just curious if you are having these conversations with an increasing number of million-dollar customers. Just sort of how are they bucketing and thinking about the different swim lanes of these various technologies? And do you think like the there's sort of less confusion maybe among the larger players such as yourself that that's helping sort of unlock higher deal flow and velocity for you?

我只是好奇您是否與越來越多的百萬美元客戶進行過這些對話。他們是如何劃分和思考這些不同技術的不同泳道的？您是否認為，對於像您這樣的大型參與者來說，這是否會減少一些困惑，從而幫助您獲得更高的交易流量和速度？

I think, first of all, Snowflake is the best AI data platform that is -- and this is widely recognized by many of our customers and new customers. And we stand out in that respect and the product quality that we have always strived to create, whether it is ease of use and simplicity our connectedness where we don't let silos develop where data is shared as it should be, autumn being a trustworthy platform.

我認為，首先，Snowflake 是最好的 AI 數據平台——這一點得到了我們許多客戶和新客戶的廣泛認可。我們在這方面脫穎而出，並且我們一直致力於創造產品質量，無論是易用性和簡單性，我們的連通性，我們不會讓孤島發展，數據應該共享，秋天是一個值得信賴的平台。

That we spend a lot of time on making sure that we reduce hallucinations, work with our customers and having the right governance in place. Increasingly, these quality are apparent to our customers. Yeah, there are some areas in which customers might prefer some of the platforms that you mentioned.

我們花費大量時間確保減少幻覺、與客戶合作並實施正確的治理。這些品質對於我們的客戶來說越來越明顯。是的，在某些領域，客戶可能更喜歡您提到的一些平台。

But we feel very good both about our strength in the core, which is around analytics, but increasingly in our ability to bring new products, whether it is our Postgres offering or open flow, which is our cloud injection platform or variance supporting Spark or machine learning or AI.

但是，我們對自己在核心方面的優勢感到非常滿意，這主要體現在分析方面，而且我們推出新產品的能力也越來越強，無論是我們的 Postgres 產品還是開放流程，這是我們的雲端注入平台或支援 Spark 或機器學習或人工智慧的差異。

We feel very good and confident about our position and the value props that we bring resonate in all the customer conversations that we have, and that's the reason why you're seeing acceleration across the board both in new customers, but also in things like consumption from existing customers or how AI is getting adopted.

我們對我們的地位感到非常滿意和自信，我們所帶來的價值主張在我們與所有客戶對話中都引起了共鳴，這就是為什麼你會看到新客戶、現有客戶的消費或人工智慧的採用等方面都在全面加速。

Brad Sills, Bank of America.

美國銀行的布拉德·西爾斯。

Great. Thank you so much. I see that professional services had a real nice ramp this quarter. I think it's up 20% quarter-on-quarter. What's going on there? Is that just an indication of customers looking to select for more consultative kind of strategic deals as you get into all these different types of workloads. We just would love to get your thoughts on what's driving that and what that might mean as a leading indicator for the business? Thank you.

偉大的。太感謝了。我發現本季專業服務取得了非常好的成長。我認為它比上一季增長了 20%。那裡發生什麼事了？這是否僅僅表明，當客戶面臨所有這些不同類型的工作量時，他們希望選擇更具諮詢性的策略交易？我們只是想聽聽您的看法，看看是什麼推動了這一趨勢，以及這作為業務領先指標意味著什麼？謝謝。

Yeah. I just want to remind you that the -- if you look at the total amount of professional services done in the Snowflake ecosystem, we, ourselves, do a very small fraction of most of that is being done by the GSIs. We typically want to be more the expert services to help other partners, do things.

是的。我只是想提醒你——如果你看看 Snowflake 生態系統中完成的專業服務總量，我們自己所做的只是 GSI 所做的大部分服務的一小部分。我們通常希望提供更多的專家服務來幫助其他合作夥伴做事。

And for some customers that insist that we are the ones doing the work. And what drove that upside in the TS this quarter was one large customer where there were some milestones that had to be that we were deferring that revenue that we recognized this quarter because those milestones were hit.

有些客戶堅持認為我們才是做這項工作的人。本季推動 TS 上漲的是一個大客戶，該客戶有一些里程碑，我們推遲了本季確認的收入，因為這些里程碑已經達到。

If you took that out, it was a normal growth quarter for services. But our goal is not to do all the services. Our goal is for our partners to be doing those things.

如果去掉這個數字，那麼對於服務業來說這是一個正常的成長季度。但我們的目標不是提供所有的服務。我們的目標是讓我們的合作夥伴能夠做到這些事情。

Michael Turrin, Wells Fargo.

富國銀行的邁克爾·圖林。

Hey, thanks very much. Appreciate you taking the question. Maybe the expansion rate, good to see the improvement there. I'm curious if you think that metric is at all turning a corner with optimizations, data background and consumption trends improving or anything else you'd add around the improvement we're seeing in Q2 whether that's from here and how maybe some of the newer product traction you're seeing informs your perspective on that metric going forward. Thank you.

嘿，非常感謝。感謝您回答這個問題。也許是擴張率，很高興看到那裡的改善。我很好奇，您是否認為該指標正在隨著優化、數據背景和消費趨勢的改善而出現轉機，或者您是否會補充關於我們在第二季度看到的改進的其他任何信息，無論這些改進是否來自現在，以及您所看到的一些較新產品的吸引力如何影響您對該指標未來的看法。謝謝。

Well, I would say, first of all, we never guide to net revenue retention is really a product of our revenue growth, and we grew -- we outpaced our revenue growth this quarter. So you'd expect that net revenue retention to have ticked back up slightly.

嗯，我想說，首先，我們從來沒有將淨收入保留率作為收入成長的真正產物，而我們的成長——本季我們的營收成長超過了預期。因此，您預計淨收入保留率會略有回升。

What I will say is what's driving that is actually, and I mentioned this a couple of questions, we had a number of our large customers that have been existing customers for a while that migrated new workloads that caused an uptick.

我要說的是，實際上推動這一趨勢的因素是，我提到了幾個問題，我們的許多大客戶已經是現有客戶一段時間了，他們遷移了新的工作負載，從而導致了工作負載的上升。

And as a reminder, when people migrate new workloads. It typically causes an uptick in consumption and then it normalizes thereafter. This has always been the case. And I would say optimizations actually have nothing that caused anything unusual. We've talked about optimizations before.

提醒一下，當人們遷移新的工作負載時。它通常會導致消費量上升，然後恢復正常。情況一直如此。我想說的是，優化實際上並沒有導致任何異常。我們之前討論過優化。

Customers are always optimizing on Snowflake. If anything, we're trying to get in front of these things with customers, so customers don't use Snowflake unwisely so they don't have to deal with optimizations. And I'm not aware of any customer that's not in an unhealthy place right now in terms of their consumption, where a number of years ago, we were well aware of ones.

客戶始終在 Snowflake 上進行最佳化。無論如何，我們都會努力讓客戶了解這些情況，讓客戶不會不明智地使用 Snowflake，也不必處理最佳化問題。我不知道現在有哪位顧客的消費狀況不健康，而幾年前，我們就已經很清楚這一點。

Brad Reback, Stifel.

布拉德·雷巴克（Brad Reback），Stifel。

Great. Mike, just picking up on that migration point. I know last quarter, you talked about having good line of sight into that level of activity. Does it look similar for the second half or maybe even bigger? Thanks.

偉大的。麥克，我剛剛談到了遷移點。我知道上個季度，您談到了對該級別的活動有良好的了解。下半部看起來是否類似，甚至更大？謝謝。

Yeah. We've identified a number of new workload use cases to go into production. And think about this as a number of -- some of these are on-prem migrations. Others are from first-generation cloud infrastructure from raw, S3 or Azure. So yes, we're getting much better than that, I would say, as our SEs, I think, are doing a phenomenal job of really identifying those use case go-lives and migrations.

是的。我們已經確定了一些將投入生產的新工作負載用例。想像一下這些——其中一些是內部遷移。其他來自原始、S3 或 Azure 的第一代雲端基礎設施。是的，我想說，我們正在做得更好，因為我認為我們的 SE 在真正識別這些用例上線和遷移方面做得非常出色。

Patrick Colville, Scotiabank.

加拿大豐業銀行的派崔克‧科爾維爾。

Hi, this is [Joe Vander] on for Patrick Colville. You guys had a nice quarter landing incremental GK customers. Can you talk a bit more about the opportunity that you see in these accounts specifically? And I know you have 654 customers spending over $1 million.

大家好，我是 Patrick Colville 的 [Joe Vander]。你們本季表現不錯，獲得了越來越多的 GK 客戶。您能否具體談談您在這些帳戶中看到的機會？我知道您有 654 位客戶的消費金額超過 100 萬美元。

Have you guys talked about what percentage of those customers are G2K? And then lastly, I guess, how are your sales reps communicating the value proposition to these very large customers to drive spending higher? Thanks.

你們有沒有討論過這些客戶中有多少比例是 G2K 的？最後，我想，您的銷售代表如何向這些大客戶傳達價值主張以推動支出成長？謝謝。

Well, what I would say is a Global 2000 customer, there's no reason why the average Global 2000 customer can't spend $10 million a year on Snowflake, just looking at all the different things, and it can be higher than that. And I would say don't quote me on this, but it gets roughly 50% of those 1 million-plus customers or Global 2000.

嗯，我想說的是，對於全球 2000 強客戶來說，沒有理由平均全球 2000 強客戶不能每年在 Snowflake 上花費 1000 萬美元，只要看看所有不同的東西，它可能會更高。我想說的是，不要引用我的話，但它佔據了 100 多萬個客戶或全球 2000 強客戶中的大約 50%。

Matt Hedberg -- my apologies.

馬特·赫德伯格——我很抱歉。

And you were asking about how do our salespeople articulate the business value. We spend a lot of time with sales enablement and educating these people, and we really wanted to be in a discussion about not as what is the cost of Snowflake, what is the value you're getting. And I would say some reps and teams are very good at it. Others are developing. But that's really the way we go to market is what is the business value you're going to get out of using Snowflake.

您問的是我們的銷售人員如何表達商業價值。我們花費大量時間進行銷售支援和培訓這些人，我們真正想討論的不是 Snowflake 的成本是多少，而是您獲得的價值是什麼。我想說的是，有些代表和團隊在這方面做得非常出色。其他國家正在發展。但這實際上是我們進入市場的方式，即使用 Snowflake 可以獲得什麼商業價值。

Matt Hedberg, RBC.

馬特·赫德伯格（Matt Hedberg），RBC。

Great. Thanks for taking my question, guys. Congrats for me as well. I wanted to circle back on Crunchy. Mike, you noted it contributed a little bit to the quarter. Just kind of curious about how that's progressing. How is that integration working?

偉大的。謝謝你們回答我的問題。我也祝賀你。我想回到 Crunchy 的話題。麥克，你注意到它對本季做出了一點貢獻。只是有點好奇事情進展如何。這種整合是如何進行的？

And when you're thinking about addressing OLTP and OLAP opportunities, where are we in that sort of evolution curve because it feels like it's certainly a long-term opportunity. There's obviously some increased competition there. But just kind of give us an update on kind of how that's progressing.

當您考慮解決 OLTP 和 OLAP 機會時，我們處於這種演變曲線的哪個位置，因為感覺這肯定是一個長期機會。那裡的競爭顯然有所加劇。但請向我們介紹一下事情的進展。

I'll let Christian answer this one.

我讓克里斯蒂安來回答這個問題。

Yeah, the integration from crunchy to what we're calling Snowflake post-progressing extremely well. The part that we highlight are most excited is that it's not just opposed to service, but it is posts with enterprise readiness and enterprise capabilities, customer manage keys, replication, business continuity. All of that is making great progress, and we will be in preview in the next couple of months very soon. And the customer interest that we're seeing is very, very strong.

是的，從 Crunchy 到我們稱為 Snowflake 的後期整合進展非常順利。我們最興奮地強調的部分是它不僅僅針對服務，而且它還具有企業準備和企業能力、客戶管理密鑰、複製、業務連續性等功能。所有這些都取得了巨大的進展，我們很快就會在接下來的幾個月內進行預覽。我們看到客戶的興趣非常非常強烈。

Patrick Walravens, Citizens.

帕特里克·沃爾拉文斯，公民。

Great. Thank you so much. Sridhar, can I have sort of a big picture question here, which is, do you agree with people who are observing that the frontier models are converging in their performance? And if so, what are the implications of that? Like where do those companies -- where do the opens and drops or do they go next? And what are the patients that for Snowflake and where it needs to go now?

偉大的。太感謝了。Sridhar，我可以在這裡問一個比較宏觀的問題嗎？那就是，你是否同意那些觀察到前沿模型在性能上正在趨同的人的觀點？如果是這樣，那意味著什麼？例如這些公司在哪裡——開盤下跌在哪裡，或是下一步會去哪裡？那麼 Snowflake 的患者是誰呢？現在它需要去哪裡？

First of all, I think every prediction that we have made about various kinds of motor has not really turned out to be true, some six months-odd later. So I don't think it's quite the case, not these models have plateaued along every dimension. If you think about the increase in quality that these models have been able to demonstrate, even over the last six months, it's been a pretty remarkable transformation.

首先，我認為，大約六個月後，我們對各種引擎做出的每一個預測實際上並沒有被證明是正確的。所以我不認為情況完全如此，這些模型並不是各個維度都達到了穩定狀態。如果您想想這些模型所展現的品質的提高，即使在過去六個月裡，這也是相當顯著的轉變。

And when it comes to the enterprise, obviously, there's no products that have been adopted at quite the same scale, let's say, a consumer ChatGPT with is nearly 1 billion customers. But these kinds of experiences become useful only the data that matters to the enterprise, all of the PDFs that are sitting in SharePoint are the various other data sources that they are also become accessible to these models.

而當談到企業時，顯然沒有任何產品能夠達到如此大的規模，比如說，消費者 ChatGPT 的客戶數量接近 10 億。但這些經驗只對企業重要的資料有用，SharePoint 中的所有 PDF 都是這些模型可以存取的各種其他資料來源。

And that's what we have created with Snowflake intelligence. So I think there is ample this ample runway. But I think the remarkable progress is also being made in Agentic AI in these models, learning to use tools of different kinds.

這就是我們利用 Snowflake 智能所創造的。所以我認為這條跑道很充足。但我認為這些模型中的 Agentic AI 也正在取得顯著進展，學習使用不同類型的工具。

I dabble a bit in core generation models and their ability to get work done has gone up by a pretty remarkable amount again over the past six months-odd. And I think you're going to see situations in which every complicated as that humans are involved in is going to have Agentic solutions that are assisted, where the model you do some of the work under the humans the model to be able to be a lot more effective.

我對核心生成模型進行了一些涉獵，在過去六個月多的時間裡，它們完成工作的能力再次顯著提高。我認為你會看到，人類所涉及的每一個複雜問題都會有代理解決方案的輔助，在這種模型下，你在人類模型下完成的一些工作能夠更加有效。

So I think from that perspective, it's still very, very early innings. Think of all of that happens in an enterprise, whether it is insurance claims processing our regulatory reporting or anomaly detection of variants or even going through the due diligence process for an M&A or a complicated legal thing that you have to do.

所以我認為從這個角度來看，現在還處於非常非常早期的階段。想想企業中發生的所有事情，無論是保險索賠處理、監管報告還是變體的異常檢測，甚至是併購的盡職調查過程或您必須做的複雜的法律事情。

All of those are areas where application of data and AI is very much in its infancy. So I think honestly, years of work ahead in terms of the value that we can get from the models have advanced so much that I think just effectively using them in all of the workflows that matter to enterprises is going to create enormous value for all of them.

所有這些領域中數據和人工智慧的應用都還處於起步階段。因此，我認為，坦白說，就我們可以從模型中獲得的價值而言，未來多年的工作已經取得了很大進步，我認為只要在企業關心的所有工作流程中有效地使用它們，就會為所有企業創造巨大的價值。

Mike Cikos, Needham.

麥克·西科斯，尼德姆。

Hey, thanks for taking the question, guys. I just wanted to come back the impressive stat that we heard earlier regarding the volume of accounts which are adopting your AI products and features, I think we're going full mid to high teens sequentially here.

嘿，謝謝大家回答這個問題。我只是想回顧一下我們之前聽到的關於採用你們的 AI 產品和功能的帳戶數量的令人印象深刻的統計數據，我認為我們將在這裡連續達到中到高十幾個數量級。

And I just wanted to -- together, so we have the adoption with -- but can you discuss what's the monetization strategy that you're putting in place behind that adoption curve? Is the larger sales effort required on Snowflake's part to ramp the revenue behind that usage? Or how does that play out from your seat? Thank you.

我只是想 - 一起，所以我們有採用 - 但是你能討論一下你在採用曲線背後實施的貨幣化策略是什麼嗎？Snowflake 是否需要加強銷售力度來增加這種使用所帶來的收入？或者從您的角度來看這是如何發生的？謝謝。

Yeah. We were very deliberate about how we brought AI to Snowflake. We wanted it to feel natural to be a natural extension of how people access data. I've talked previously about primates around search and structured data that was the foundation of how we began to introduce AI.

是的。我們非常慎重地考慮如何將 AI 引入 Snowflake。我們希望它感覺自然，成為人們存取資料方式的自然延伸。我之前曾談論過搜尋和結構化資料的靈長類動物，這是我們開始引入人工智慧的基礎。

They, themselves, were useful in that people could create chatbots on structured data or be able to talk to your SQL as it were to get -- to get a structured data. We've then introduced higher-level constructs that sit on top of it, like Snowflake Intelligence.

它們本身很有用，因為人們可以根據結構化資料創建聊天機器人，或者能夠與你的 SQL 對話以獲取結構化資料。然後，我們引入了位於其上的更高層次的構造，例如 Snowflake Intelligence。

But one thing that we were very, very deliberate about was the need for these capabilities, we truly be easy to use and for our customers to be able to get value very quickly from them or at least experiment with them very quickly. And this is what has led to the broad adoption, to be honest, without us investing in a massive sales play.

但有一件事我們非常非常慎重，那就是這些功能的必要性，它們真的很容易使用，而且我們的客戶能夠很快地從中獲得價值，或至少很快地嘗試它們。說實話，這就是廣泛採用的原因，而我們並沒有投入大量的銷售資金。

Yes, we have a specialist team but compared to the size of our regular sales team, it's actually quite small. And so from that perspective, that brand, 6,000-odd number is very active. We are now beginning to see situations in which a product like Snowflake Intelligence is rolled out very, very broadly to the entirety of a workforce.

是的，我們有一個專家團隊，但與我們常規銷售團隊的規模相比，它實際上相當小。因此從這個角度來看，這個品牌（6,000 多個）非常活躍。我們現在開始看到像 Snowflake Intelligence 這樣的產品被廣泛地推廣到整個勞動力隊伍的情況。

For example, with the sales data assistance, I want to make sure that it is rolled out to every salesperson and the beauty of that is all of the permissioning, all of the complexities of making sure the right person has access to the right information is the thing that we make very, very easy to implement. These kinds of use cases are the ones that are going to be driving meaningful revenue for us.

例如，對於銷售數據協助，我希望確保它能夠推廣到每一位銷售人員，而它的美妙之處在於，所有的許可，所有的複雜性，確保正確的人能夠訪問正確的信息，都是我們做得非常非常容易實現的事情。這些用例將會為我們帶來可觀的收入。

And yes, we are having our specialists focused on these use cases because they're going to drive more revenue but this is all part of a very deliberate strategy of creating world-class products, getting very broad adoption and demystifying AI and then working on use cases that generate massive value for our customers. and in turn, revenue for us.

是的，我們讓專家專注於這些用例，因為它們將帶來更多收入，但這都是我們深思熟慮的策略的一部分，即創造世界一流的產品，獲得廣泛的應用並揭開人工智慧的神秘面紗，然後致力於為我們的客戶創造巨大價值的用例，進而為我們帶來收入。

And that's the beauty of the consumption model in that our customers don't have to make some very large commitment to a project that's not yet delivered value. Yes, they have to go implement a project which we make easy but we may be -- like we make revenue only our customers -- when our customers recognize value. So we feel good about where we are. I think this is the right way to have taken AI to the Snowflake data cloud

這就是消費模式的魅力所在，我們的客戶不必對尚未交付價值的項目做出非常大的承諾。是的，他們必須去實施一個我們簡化的項目，但我們可能——就像我們只為客戶創造收入一樣——當我們的客戶認識到價值時。因此我們對目前的狀況感到滿意。我認為這是將 AI 引入 Snowflake 資料雲的正確方法

Gregg Moskowitz, Mizuho.

瑞穗的格雷格·莫斯科維茲。

Great. Thank you. Maybe another question on AI, if I may. We've recently begun to hear, Sridhar, meaningful customer commitments to Cortex AI. In other words, not just some customers exploring it, but a real uptick in usage. I know you called out some interesting wins in your script, but more broadly, is this consistent with what you're seeing? And if so, it would be helpful to hear a bit more on the primary use cases that you're seeing for -- par. Thanks.

偉大的。謝謝。如果可以的話，我想再問一個關於人工智慧的問題。Sridhar，我們最近開始聽到客戶對 Cortex AI 做出有意義的承諾。換句話說，不只是一些客戶在探索它，而且使用量確實有所上升。我知道您在劇本中提到了一些有趣的勝利，但更廣泛地說，這與您所看到的一致嗎？如果是這樣，那麼進一步了解您所看到的主要用例將會很有幫助。謝謝。

The primary use case is inevitably centered around a combination of bringing structured and unstructured information together in a custom repository, for example, as a data agent. I talked about BlackRock in the script, I think, where I said they're creating a little bit of a Customer 360. All of the information that is relevant to our customers available in a single chatbot.

主要用例不可避免地圍繞將結構化和非結構化資訊組合到自訂儲存庫中，例如作為資料代理。我想，我在劇本中談到了貝萊德，我說他們正在創建一個客戶 360 度全景圖。所有與我們的客戶相關的資訊都可以透過一個聊天機器人取得。

And I use this kind of functionality very frequently, but if I'm going to have a meeting with a customer. I want to know everything about them that we know I'm able to get at what kind of relationship we have with them, how much we are spending, what the open use cases are, any other recent notes, Workday information about -- hierarchy here that manages them.

我經常使用這種功能，但如果我要與客戶會面。我想要了解他們的一切，我知道我能夠了解我們與他們的關係是什麼樣的，我們花了多少錢，開放的用例是什麼，任何其他最近的記錄，Workday 資訊——這裡是管理他們的層次結構。

It is that pattern. It is a flexible access to data that repeats itself over and over again. And people just apply that in very different ways. Thomson Reuters uses Cortex to create a set of products for their internal views. They have products for HR teams, finance teams and so on.

就是那種模式。它是一種靈活的、可重複重複的資料存取方式。人們只是以不同的方式應用它。湯森路透使用 Cortex 創建了一套用於其內部觀點的產品。他們有針對人力資源團隊、財務團隊等的產品。

I think that it gets really interesting is now in having -- in being able to take a whole set of actions using Agentic AI, where in addition to getting information that you want, you're also then able to say, okay, and now take -- like do this update, send an e-mail or update a record in sales force or some other actions. I think that's where we are seeing easily get created.

我認為現在真正有趣的是 - 能夠使用 Agentic AI 採取一整套行動，除了獲取您想要的信息之外，您還可以說，好的，現在採取 - 例如進行此更新，發送電子郵件或更新銷售人員的記錄或執行其他操作。我認為這就是我們所看到的容易被創造出來的地方。

John DiFucci, Guggenheim.

古根漢美術館的約翰·迪富奇。

Thanks for taking my question. My question is, I guess it's sort of a high-level question. Listen, these results are really good. Everybody has noted that. And you've been pretty clear that you're focused on AI for the future, but these results are primarily driven by our core data warehouse and analytics business. And then we understand why focused on AI and I guess why everybody is asking lots of questions on AI.

感謝您回答我的問題。我的問題是，我想這是一個高層次的問題。聽著，這些結果真的很好。大家都注意到了這一點。您已經非常清楚地表明，您專注於未來的人工智慧，但這些結果主要由我們的核心資料倉儲和分析業務推動。然後我們明白了為什麼關注人工智慧，我想為什麼每個人都在問很多關於人工智慧的問題。

But I'm more curious about that core market. There's still a huge amount of this market that's still on-premise. And you have the pole position in cloud-based data warehouse, you're the pioneer and people love your products.

但我對核心市場更感興趣。這個市場仍有大量份額處於現場狀態。您在基於雲端的資料倉儲領域佔據領先地位，您是先驅，人們喜愛您的產品。

But can you talk about the sustainability of that market as a growth driver? And are there any other solutions on the horizon that keep you up at night that could disrupt that market, the data warehouse cloud-based data warehouse and analytics market, like you disrupted the massive on-prem data warehouse market.

但是您能談談該市場作為成長動力的可持續性嗎？還有其他解決方案會讓您夜不能寐，從而擾亂資料倉儲市場，即基於雲端的資料倉儲和分析市場嗎，就像您擾亂了龐大的內部部署資料倉儲市場一樣。

I mean, first of all, I should be clear that we have been consistent in saying that it's not an either or -- our core business continues to be very strong, and we have talked to you folks about a number of metrics, including net revenue retention, which is measured over a two year time frame that supports that.

我的意思是，首先，我應該明確表示，我們一直在說這不是非此即彼的問題——我們的核心業務仍然非常強勁，我們已經與你們討論了許多指標，包括淨收入保留率，這是在兩年的時間範圍內衡量的，以支持這一點。

And other things that we are doing, especially in the areas of AI are important because that is where utility is going to be delivered in a massive way, both today and tomorrow. So it's not the case that we can say we should just focus on our core business because people that bet on Snowflake are bidding on Snowflake for the next five years. And we need to invest in both.

我們正在進行的其他工作，特別是在人工智慧領域，非常重要，因為無論是現在還是將來，人工智慧都將大規模地發揮效用。因此，我們不能說我們應該只專注於我們的核心業務，因為押注 Snowflake 的人正在競標未來五年的 Snowflake。我們需要對這兩者進行投資。

But to your point about the sustainability of the core analytics market, 100%. I think there is a lot of business to be had. There are a lot of on-prem systems. And part of what we are figuring out in this moment is AI is going to disrupt potentially everybody, including us. This is the reason why the trust product innovation so much.

但對於您關於核心分析市場永續性的觀點，是 100%。我認為有很多生意可做。有很多內部部署系統。我們目前正在思考的一個問題是，人工智慧可能會顛覆每個人，包括我們自己。這也是信託產品創新如此之多的原因。

This is the reason why, in addition to creating products like Snowflake intelligence, which are cutting edge, we also obsessed about how to make sure that our migration technology is the latest and greatest that there is because being able to migrate legacy systems faster is going to be a -- benefit to Hoover that can do that fast and that would be a final thing.

這就是為什麼除了創造像 Snowflake intelligence 這樣尖端的產品之外，我們還痴迷於如何確保我們的遷移技術是最新和最好的，因為能夠更快地遷移遺留系統將為胡佛帶來好處，因為胡佛可以快速做到這一點，這將是最終的事情。

Yes, there is a big market in legacy systems that are going to be migrating over. all the cloud players, including us, are benefiting from that on-prem to cloud migration. But we do really need to innovate on both fronts to be successful in the long term.

是的，遺留系統遷移的市場很大。包括我們在內的所有雲端運算參與者都將從本地到雲端的遷移中受益。但我們確實需要在兩個方面進行創新才能取得長期成功。

Due to the interest of time, that was our last question. I would now like to pass the conference back over to Sridhar Ramaswamy for closing remarks.

由於時間關係，這是我們的最後一個問題。現在，我想將會議交還給 Sridhar Ramaswamy 並請他致閉幕詞。

Thank you. In closing, Snowflake is at the center of today's enterprise AI revolution, delivering tremendous value throughout the end-to-end data life cycle. Snowflake is EDU, connected for seamless collaboration and trusted by enterprise-grade performance, driving customers to choose and expand with us.

謝謝。最後，Snowflake 是當今企業 AI 革命的中心，在整個端到端資料生命週期中提供巨大的價值。Snowflake 是 EDU，可實現無縫協作，並具有企業級效能的信賴，推動客戶選擇我們並與我們一起擴展。

We continue to execute our scale as evidenced by our product revenue growth and strong outlook for the remainder of fiscal '26. And we see a long runway of durable high growth and continued margin expansion. It's an exciting time for Snowflake, and I look forward to sharing more of our progress in the quarters ahead. Thank you all for joining us.

我們將繼續保持規模效應，這從我們的產品收入成長和 26 財年剩餘時間的強勁前景可以看出。我們看到了長期持續高成長和持續利潤擴張的前景。對於 Snowflake 來說，這是一個令人興奮的時刻，我期待在未來幾季分享更多我們的進展。感謝大家的參與。

That concludes today's call. Thank you for your participation, and enjoy the rest of your day.

今天的電話會議到此結束。感謝您的參與，祝您今天過得愉快。