AvePoint Inc (AVPT) 2024 Q1 法說會逐字稿

Good day and welcome to the AvePoint Inc Q1 2024 earnings call. (Operator Instructions) Please note this event is being recorded.

美好的一天，歡迎參加 AvePoint Inc 2024 年第一季財報電話會議。（操作員說明）請注意此事件正在被記錄。

I would now like to turn the conference over to your host today, Jamie Arestia, Vice President, Investor Relations. Please go ahead.

現在我想將會議交給今天的東道主，投資者關係副總裁 Jamie Arestia。請繼續。

Thank you, operator. Good afternoon and welcome to AvePoint's first quarter 2024 earnings call. With me on the call this afternoon is Dr. TJ Jiang, Chief Executive Officer, and Jim Caci, Chief Financial Officer. After preliminary remarks, we will open the call for a question-and-answer session.

謝謝你，接線生。下午好，歡迎參加 AvePoint 2024 年第一季財報電話會議。今天下午與我一起參加電話會議的是執行長 TJ Jiang 博士和財務長 Jim Caci。初步發言後，我們將開始問答環節。

Please note that this call will include forward-looking statements that involve risks and uncertainties that could cause actual results to differ materially from management's current expectations.

請注意，本次電話會議將包括前瞻性陳述，這些陳述涉及可能導致實際結果與管理階層目前預期有重大差異的風險和不確定性。

We encourage you to review the safe harbor statements contained in our press release for a more complete description. All material in the webcast is the sole property and copyright of AvePoint with all rights reserved.

我們鼓勵您查看我們新聞稿中包含的安全港聲明，以獲得更完整的描述。網路廣播中的所有資料均為 AvePoint 的專有財產和版權，保留所有權利。

Please note this presentation describes certain non-GAAP measures, including non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating income and non-GAAP operating margin, which are not measured, prepared in accordance with US GAAP.

請注意，本簡報描述了某些非 GAAP 指標，包括非 GAAP 毛利、非 GAAP 毛利率、非 GAAP 營業收入和非 GAAP 營業利潤率，這些指標均未根據美國 GAAP 進行衡量。

The non-GAAP measures are presented in this presentation as we believe they provide investors with a means of understanding how management evaluates the company's operating performance. These non-GAAP measures should not be considered in isolation from as substitutes for or superior to financial measures prepared in accordance with US GAAP.

本簡報中介紹了非公認會計準則衡量標準，因為我們相信它們為投資者提供了一種了解管理階層如何評估公司經營績效的方法。這些非公認會計原則措施不應孤立地視為替代或優於根據美國公認會計原則制定的財務措施。

A reconciliation of these measures to the most directly comparable GAAP financial measures is available in our first quarter 2024 earnings press release, as well as our updated investor presentation and financial tables, all of which are available on our Investor Relations website.

這些指標與最直接可比較的 GAAP 財務指標的調整可在我們的 2024 年第一季度收益新聞稿以及更新的投資者演示和財務表格中找到，所有這些都可以在我們的投資者關係網站上找到。

With that, let me turn the call over to TJ. Thank you.

接下來，讓我把電話轉給 TJ。謝謝。

Thank you, Jamie, and thank you to everyone joining us on the call today. Our Q1 was a very strong start to the year as we outperformed our guidance for total revenue and non-GAAP operating margin while delivering strong growth in total and net new ARR. Our performance was again driven by the robust capabilities of our platform as well as a growing recognition among customers and partners of a need.

謝謝傑米，也感謝今天加入我們電話會議的所有人。我們的第一季是今年的一個非常強勁的開端，因為我們的總收入和非公認會計原則營運利潤率超出了我們的指導，同時實現了總新 ARR 和淨新 ARR 的強勁增長。我們的業績再次受到平台強大功能以及客戶和合作夥伴對需求日益認可的推動。

Now more important than ever to build a strong data foundation. Doing so will empower them to covering their mission critical information assets, optimize operational costs, boost workplace efficiency and foster more insightful, data-driven decision-making. While these goals have always been top of mind, they're now more critical than ever as organizations around the world seek to leverage generative AI to unlock business value and gain a competitive advantage.

現在，建立強大的數據基礎比以往任何時候都更加重要。這樣做將使他們能夠覆蓋其關鍵任務資訊資產、優化營運成本、提高工作場所效率並促進更有洞察力、數據驅動的決策。雖然這些目標一直是首要考慮因素，但隨著世界各地的組織尋求利用生成式人工智慧來釋放業務價值並獲得競爭優勢，現在它們比以往任何時候都更加重要。

At this dynamic, I would like to discuss today with two areas of focus. First, the challenges and obstacles organizations face in adopting AI, primarily due to data security issues that prevent a comprehensive strategy to manage our data estate.

有鑑於此，我今天想重點討論兩個領域。首先，組織在採用人工智慧時面臨的挑戰和障礙，主要是由於資料安全問題阻礙了管理資料資產的全面策略。

And second, the customer demand for AI to improve productivity and the overall employee experience. Along the way, I'll highlight some key customer wins in Q1 that demonstrate how we solve these challenges and close by touching on our ongoing investments to innovate in this dynamic business environment. I will then turn it over to Jim to discuss our Q1 results and updated financial guidance.

其次，客戶對人工智慧提高生產力和整體員工體驗的需求。在此過程中，我將重點介紹第一季的一些關鍵客戶勝利，這些客戶展示了我們如何解決這些挑戰，並最後介紹了我們在這個充滿活力的商業環境中進行創新的持續投資。然後我會將其交給吉姆討論我們的第一季業績和更新的財務指導。

So let's jump in. It's no surprise, companies everywhere wanting incorporate AI into their businesses. I recently had the privilege to keynote the SkillsFuture SG training and Adult Education Conference in Singapore. In speaking with many CXOs in attendance, it was clear, the ambition to use AI to transform upskilling is probable, but the elephant in the room is the concern that their data is not ready for AI.

那麼就讓我們開始吧。毫不奇怪，世界各地的公司都希望將人工智慧融入他們的業務中。最近，我有幸在新加坡的 SkillsFuture SG 培訓和成人教育會議上發表主題演講。在與許多出席的 CXO 交談時，很明顯，利用人工智慧來提高技能的雄心壯志是可能的，但房間裡的大像是擔心他們的數據還沒有為人工智慧做好準備。

These conversations align with the findings in our inaugural AI and information management report, which we published a few weeks ago. Our report surveyed nearly 800 organizations globally and find that 83% plan to increase their AI spending this year with 60% intending to allocate at least a quarter of their technology budget to AI in the next five years.

這些對話與我們幾週前發布的首份人工智慧和資訊管理報告中的發現一致。我們的報告調查了全球近 800 個組織，發現 83% 的組織計劃今年增加人工智慧支出，其中 60% 的組織打算在未來五年內將至少四分之一的技術預算分配給人工智慧。

However, our survey also confirmed a significant delta between these ambitious plans and the reality facing these organizations. Simply put, they are not ready to deploy effective AI strategy because their data estates

然而，我們的調查也證實了這些雄心勃勃的計畫與這些組織面臨的現實之間存在著顯著的差異。簡而言之，他們還沒有準備好部署有效的人工智慧策略，因為他們的數據資產

are not in good order.

秩序不佳。

Business where our competence platform comes into play by bolstering organizations' data security postures, providing robust cyber security measures, offering comprehensive control and visibility across the digital workplace and delivering intelligent data insights through automation.

我們的能力平台透過增強組織的資料安全態勢、提供強大的網路安全措施、提供跨數位工作場所的全面控制和可見性以及透過自動化提供智慧資料洞察來發揮作用。

By leveraging all our platform has to offer, customers can realize a secure and compliant digital environment that also improves the employee experience and then build on this foundation with a meaningful AI strategy. But without taking these steps to solidify their data estates, the challenges business face are amplified when incorporating AI, particularly around data security and data governance.

透過利用我們提供的所有平台，客戶可以實現安全、合規的數位環境，同時改善員工體驗，然後在此基礎上製定有意義的人工智慧策略。但如果不採取這些步驟來鞏固資料資產，企業在整合人工智慧時面臨的挑戰就會放大，特別是在資料安全和資料治理方面。

According to recent research from Gartner, 72% of organizations believe over sharing and exposing sensitive information is the biggest risk when deploying generative AI applications, such as Copilot from Microsoft 365. The AvePoint confidence platform can mitigate these risks by helping companies understand the quality of the data AI relies on controlling permissions and rapidly setting up proper access controls.

根據 Gartner 的最新研究，72% 的組織認為過度分享和暴露敏感資訊是部署生成式 AI 應用程式（例如 Microsoft 365 的 Copilot）時的最大風險。AvePoint 置信平台可以幫助公司了解 AI 所依賴的資料品質控制權限並快速設定適當的存取控制，從而降低這些風險。

In the health and life sciences industry for example, we worked with a leading US based medical technology company in the quarter to ensure its data was ready for AI as they prepare to deploy Copilot for Microsoft 365.

例如，在健康和生命科學行業，我們在本季度與一家領先的美國醫療技術公司合作，確保其數據為 AI 做好準備，因為他們準備為 Microsoft 365 部署 Copilot。

With Avepoint policies, AvePoint cloud governance and AvePoint MyHub, the company is drastically reducing the risk of exposing sensitive information, streamlining their workspace policies and securing data access so the company's 15,000 employees can utilize Copilot.

借助 Avepoint 策略、AvePoint 雲端治理和 AvePoint MyHub，該公司大大降低了暴露敏感資訊的風險，簡化了工作區策略並保護資料訪問，以便公司的 15,000 名員工可以使用 Copilot。

Our study also found that before implementing AI, 71% organizations were concerned about data privacy and security and 61% were worried about the quality and categorization of their internal data. But despite these concerns, many forge ahead in the flawed belief that their existing information management strategy was suffice. Specifically, our report find nearly half of the organizations lack basic measures such as archiving and retention policies and just 29% of organizations use automation.

我們的研究還發現，在實施人工智慧之前，71% 的組織擔心資料隱私和安全，61% 擔心內部資料的品質和分類。但儘管有這些擔憂，許多人仍然錯誤地相信他們現有的資訊管理策略就足夠了。具體來說，我們的報告發現近一半的組織缺乏歸檔和保留策略等基本措施，並且只有 29% 的組織使用自動化。

These shortcomings are even more glaring when compared to the size and volume of data our customers need to secure, driven by the relentless growth of data for many years, more than 40% of the companies today manage at least 500 petabytes of data, and they're seeing that growth accelerate due to AI, addressing the challenges related to data growth and sprawl has always been a key use case for AvePoint and led to a new customer win in Q1 with a Germany-based real estate firm with over 130,000 tenants and 1,500 employees.

與我們的客戶需要保護的資料大小和數量相比，這些缺點更加明顯，在資料多年來不斷增長的推動下，當今超過 40% 的公司管理著至少 500 PB 的數據，並且看到人工智慧帶來的成長加速，解決與資料成長和蔓延相關的挑戰一直是AvePoint 的關鍵用例，並在第一季度贏得了一家總部位於德國的房地產公司的新客戶，該公司擁有超過130,000 名租戶， 1,500 名員工。

The firm turned to AvePoint secure backup solution to protect its growing data across Microsoft 365, Entra ID, Power Platform and to rapidly identify crucial data sprawl and storage optimization challenges with AvePoint Opus. With these critical AvePoint solutions, the customer can now quickly and intelligently archive its data, enhance its data governance and cyber resilience posture.

該公司採用 AvePoint 安全備份解決方案來保護 Microsoft 365、Entra ID、Power Platform 中不斷增長的數據，並利用 AvePoint Opus 快速識別關鍵的數據蔓延和儲存優化挑戰。借助這些關鍵的 AvePoint 解決方案，客戶現在可以快速、智慧地歸檔其數據，增強其數據治理和網路彈性狀態。

As noted in our report, we believe the most effective approach for all companies is to establish a robust information management strategy from the outset because organizations with mature information management strategies are [1.5 times] more likely to realize benefits from AI than those with less mature strategies.

正如我們的報告中所指出的，我們認為對所有公司來說最有效的方法是從一開始就建立強大的資訊管理策略，因為具有成熟資訊管理策略的組織比那些不太成熟的組織從人工智慧中實現收益的可能性高[1.5 倍]策略。

For example, let's take a look at the CPG industry where nearly half of companies are facing challenges collecting and integrating the volume data needed for successful AI adoption. This is largely due to data fragmentation across a large number of SKUs, expansive supply chain and warehousing networks and complex product categories.

例如，讓我們來看看 CPG 行業，其中近一半的公司面臨著收集和整合成功採用人工智慧所需的大量數據的挑戰。這主要是由於大量 SKU、廣泛的供應鏈和倉儲網路以及複雜的產品類別中的資料碎片。

In Q1, we expanded our relationship with one of the largest CPG companies in the world to streamline its information management approach with the purchase of AvePoint Opus. Already a existing customer with a number of AvePoint solutions and a growing data estate. Opus will streamline data management policies for their 123,000 users, providing better visibility into data utilization, improved data quality and lower the risk of breaches.

第一季度，我們透過購買 AvePoint Opus 擴大了與世界上最大的 CPG 公司之一的關係，以簡化其資訊管理方法。已經是擁有許多 AvePoint 解決方案和不斷增長的數據資產的現有客戶。Opus 將簡化 123,000 名用戶的資料管理策略，提供更好的資料利用率可見度、提高資料品質並降低外洩風險。

We know a healthy data state is essential to effective a strategy and effective a strategy, obviously makes good business sense in creating a more secure organization, reducing costs and addressing macro challenges. But one additional benefit of effective AI strategy is the improvement of the overall employee experience, for example, Gartner finds AI can drive productivity gains by up to 20%.

我們知道，健康的數據狀態對於有效的策略至關重要，而有效的策略顯然對於創建更安全的組織、降低成本和應對宏觀挑戰具有良好的商業意義。但有效的人工智慧策略的另一個好處是改善整體員工體驗，例如，Gartner 發現人工智慧可以將生產力提高高達 20%。

Why does that matter? Research show that more than 60% of a typical workday is lost to repetitive and mundane tasks that knowledge workers spent 25% of their time searching for information, and they use an average of six to eight apps to complete a single process.

為什麼這很重要？研究表明，典型工作日 60% 以上的時間都浪費在重複性和平凡的任務上，知識型員工花費 25% 的時間搜索信息，並且他們平均使用六到八個應用程序來完成單一流程。

If AI can successfully mitigate these employee frustrations, companies can retain talent and reduce turnover, further strengthening the organization Our best-in-class abilities to solve these problems for many years have established a strong competitive moat, and it's why we continue to innovate and invest in further enhancements for our customers and for the AvePoint team.

如果人工智慧能夠成功緩解這些員工的挫敗感，公司就可以留住人才並減少人員流動，從而進一步增強組織實力。創新和發展的原因。

Our AvePoint AI program aimed at integrating AI into everything we do continues to progress with internal and external applications of AI. One example is our tyGraph product, where we recently introduced new advanced analytics capabilities for Copilot from Microsoft 365.

我們的 AvePoint AI 計畫旨在將 AI 融入我們所做的一切中，並隨著 AI 的內部和外部應用程式不斷取得進展。我們的 tyGraph 產品就是一個例子，我們最近為 Microsoft 365 的 Copilot 引進了新的進階分析功能。

We're proud to be first to market with this offering to support Copilot, which enables companies to identify areas of high collaboration to better prepare for Copilot readiness. This is just the latest of our AI readiness solutions for organizations to prepare, secure and optimize data, which collectively will enable them to fully take advantage of AI in the workplace.

我們很自豪能夠率先向市場推出這項支援 Copilot 的產品，使公司能夠識別高度協作的領域，以便更好地為 Copilot 做好準備。這只是我們為組織準備、保護和優化資料而提供的最新人工智慧就緒解決方案，這些解決方案共同將使他們能夠在工作場所充分利用人工智慧。

In closing, successful AI deployments require strong and healthy data states, which in turn mandates a robust data management strategy. As companies become increasingly aware of this, we have a massive opportunity to drive AI adoption in the years to come, underpinned by our platform technology and our experience solving the most urgent challenges facing organizations around the world.

最後，成功的人工智慧部署需要強大且健康的數據狀態，這反過來又需要強大的數據管理策略。隨著公司越來越意識到這一點，在我們的平台技術和解決世界各地組織面臨的最緊迫挑戰的經驗的支持下，我們在未來幾年有巨大的機會推動人工智慧的採用。

I'm excited for the years ahead, and I want to thank the entire AvePoint team for their tireless efforts and dedication. Our Q1 results are another strong step forward, and we are laser focused on continued execution and capitalizing on the growing demand for our platform.

我對未來的歲月感到興奮，我要感謝整個 AvePoint 團隊的不懈努力和奉獻精神。我們第一季的業績是又向前邁出了一大步，我們專注於持續執行並利用對我們平台不斷增長的需求。

With that, let me turn the call over to Jim.

接下來，讓我把電話轉給吉姆。

Thanks, TJ, and good afternoon, everyone. Thanks for joining us today. As we review our strong first quarter results today, let me remind you that unless otherwise noted, I'll be referring to non-GAAP metrics.

謝謝，TJ，大家下午好。感謝您今天加入我們。當我們今天回顧第一季的強勁業績時，請允許我提醒您，除非另有說明，否則我將指的是非 GAAP 指標。

For the first quarter ended March 31, 2024. Total revenues were $74.5 million, up 25% year-over-year and above the high-end of our guidance. Within total revenue, first quarter SaaS revenue was $51.3 million and grew 44% year over year.

截至 2024 年 3 月 31 日的第一季。總收入為 7,450 萬美元，年成長 25%，高於我們指導的上限。在總收入中，第一季 SaaS 收入為 5,130 萬美元，年增 44%。

And in Q1, SaaS comprised 69% of total revenues compared to 60% a year ago. SaaS continues to be our fastest growing revenue segment with 44% year-over-year growth, representing our highest in eight quarters. In addition, our other revenue lines continued to perform in line with our expectations and commentary.

第一季度，SaaS 佔總營收的 69%，而去年同期為 60%。SaaS 仍然是我們成長最快的營收領域，年增 44%，是八個季度以來的最高水準。此外，我們的其他收入線繼續表現符合我們的預期和評論。

Term license and support as well as maintenance revenue declined year over year, both in dollars and as a percentage of total revenue. At the same time, services revenues grew 8% year over year, but declined as a percentage of revenue to 14% for Q1. And because services represents our only nonrecurring business, 86% of our total Q1 revenues were recurring, our highest ever percentage.

定期許可和支援以及維護收入同比下降，無論是美元還是佔總收入的百分比。同時，第一季服務收入年增 8%，但佔營收的比例下降至 14%。由於服務是我們唯一的非經常性業務，因此我們第一季總收入的 86% 是經常性業務，這是我們有史以來最高的比例。

Our strong SaaS performance is also evident as we look at our results from a regional perspective where SaaS revenue growth was above 40% in every region.

從區域角度來看，我們強勁的 SaaS 表現也很明顯，每個區域的 SaaS 收入成長均超過 40%。

In North America, SaaS revenues grew 42% year over year and represented 77% of total North America revenues, which in turn grew 22% year over year. In EMEA, SaaS revenues grew 46% year over year and represented 81% of total media revenues, which in turn grew 17% year over year. And in APAC, SaaS revenues grew 47% year over year and represented 45% of total APAC revenues, which in turn grew 40% year over year.

在北美，SaaS 營收年增 42%，佔北美總營收的 77%，而北美總營收年增 22%。在歐洲、中東和非洲地區，SaaS 營收年增 46%，佔媒體總收入的 81%，而媒體總收入則較去年同期成長 17%。在亞太地區，SaaS 營收年增 47%，佔亞太地區總收入的 45%，而亞太地區總收入則較去年同期成長 40%。

Last quarter, we began disclosing our regional ARR performance as these growth rates provide a better view of the underlying momentum of the business everywhere we operate. We were again pleased with the year-over-year growth we saw in Q1. As North America, ARR grew 22%. EMEA ARR grew 27% and APAC ARR grew 27%.

上個季度，我們開始揭露我們的區域 ARR 業績，因為這些成長率可以更好地了解我們經營所在地的業務的潛在勢頭。我們再次對第一季的年成長感到滿意。北美地區的 ARR 成長了 22%。歐洲、中東和非洲地區 ARR 成長 27%，亞太地區 ARR 成長 27%。

Once again, each region was a strong contributor to our overall performance with their respective ARR growth rates in line with the total ARR growth we reported on a consolidated basis, continuing now with total ARR and other key metrics we regularly assess.

每個地區再次對我們的整體業績做出了重要貢獻，其各自的ARR 成長率與我們在合併基礎上報告的總ARR 成長率一致，現在繼續與總ARR 和我們定期評估的其他關鍵指標保持一致。

As of March 31, 2024, total ARR was $274.5 million, representing year-over-year growth of 23%. As a result, net new ARR in Q1 was $10 million and grew 29% year-over-year. Additionally, we ended the first quarter with 560 customers with ARR of over $100,000, an increase of 20% from the prior year.

截至 2024 年 3 月 31 日，總 ARR 為 2.745 億美元，年增 23%。結果，第一季淨新 ARR 為 1000 萬美元，年增 29%。此外，第一季末，我們有 560 名客戶的 ARR 超過 10 萬美元，比去年增加了 20%。

As of the end of Q1, 51% of total ARR came through the channel compared to 48% a year ago. And for Q1, specifically, 62% of our incremental ARR came through the channel compared to 65% for Q4 of '23 and 56% in Q1 of 2023. As we discussed, the channel contribution to our incremental ARR will fluctuate from quarter to quarter, but we expect the channel contribution to total ARR to continue increasing each quarter.

截至第一季末，總 ARR 的 51% 來自該通路，而一年前為 48%。具體而言，對於第一季度，我們增量 ARR 的 62% 來自該管道，而 23 年第四季為 65%，2023 年第一季為 56%。正如我們所討論的，通路對增量 ARR 的貢獻將隨季度波動，但我們預計通路對總 ARR 的貢獻將繼續每季增加。

Turning now to our customer retention rates, where we continue to make progress toward our medium-term goals, which to remind you are 90%-plus for GRR and 110% to 115% for NRR. Adjusted for the impact of FX, our trailing 12 month gross retention rate for the first quarter was 87%, consistent with our performance in 2023.

現在談談我們的客戶保留率，我們繼續在實現中期目標方面取得進展，提醒您，GRR 為 90% 以上，NRR 為 110% 至 115%。根據外匯影響進行調整後，第一季過去 12 個月的毛保留率為 87%，與 2023 年的表現一致。

And we are pleased that our FX-adjusted net retention rate for the first quarter was 110% compared to 106% a year ago and to 109% in Q4 of 2023. On a reported basis, Q1 GRR was 86%, in line with the 86% we reported in Q4 2023. Q1 NRR was 110% compared to 108% in Q4 of 2023.

我們很高興看到，第一季經匯率調整後的淨保留率為 110%，而去年同期為 106%，2023 年第四季為 109%。根據報告，第一季的 GRR 為 86%，與我們在 2023 年第四季報告的 86% 一致。第一季的 NRR 為 110%，而 2023 年第四季為 108%。

Turning back to the income statement, gross profit for Q1 was $55.2 million, representing a gross margin of 74.1% compared to 71.5% in Q1 of 2023. The improvement in our gross margin is a result of improved SaaS margins as well as our product mix as we had more SaaS revenue and less low-margin services revenue as a percentage of our overall revenue this quarter versus a year ago.

回到損益表，第一季的毛利為 5,520 萬美元，毛利率為 74.1%，而 2023 年第一季的毛利率為 71.5%。我們毛利率的提高是由於 SaaS 利潤率以及我們的產品組合的改善，因為與去年同期相比，本季 SaaS 收入占我們總收入的比例增加，低利潤服務收入減少。

Moving down the income statement. Operating expenses for Q1 totaled $48.6 million or 65% of revenue, compared to $42.9 million or 72% of revenues a year ago. As a result, Q1 operating income was $6.6 million or an operating margin of 8.9%.

將損益表向下移動。第一季的營運支出總計 4,860 萬美元，佔營收的 65%，而一年前為 4,290 萬美元，佔營收的 72%。結果，第一季營業收入為 660 萬美元，營業利潤率為 8.9%。

While Q1 non-GAAP operating income was well ahead of our guidance, I would point out that approximately $1.5 million of expenses we had expected for Q1 shifted to Q2 and the second half of the year and this is reflected in our updated guidance, which I will cover shortly.

雖然第一季非GAAP 營業收入遠高於我們的指導，但我要指出的是，我們預計第一季的約150 萬美元費用轉移到了第二季和今年下半年，這反映在我們更新的指導中，我將其很快就會涵蓋。

But even after adjusting for this, Q1 operating income would have come in comfortably above the high-end of our guidance as our commitment to profitable growth and our sustained focus on expense management, again allowed us to realize more of the substantial embedded leverage in our business.

但即使在對此進行調整後，第一季營業收入仍將輕鬆高於我們指導的上限，因為我們對盈利增長的承諾和對費用管理的持續關注，再次使我們能夠實現更多的實質性嵌入槓桿商業。

Turning to the balance sheet and cash flow statement. We ended the first quarter with $219.3 million in cash and short-term investments. For the three months ended March 31, 2024, cash generated from operations was $7.8 million, while free cash flow was $7.3 million. This compared to cash generated from operations of $1.3 million in free cash flow of $1 million in the first quarter of 2023.

轉向資產負債表和現金流量表。第一季結束時，我們的現金和短期投資為 2.193 億美元。截至 2024 年 3 月 31 日的三個月，營運產生的現金為 780 萬美元，自由現金流為 730 萬美元。相較之下，2023 年第一季營運產生的現金為 130 萬美元，自由現金流為 100 萬美元。

During the three months ended March 31, we repurchased 1.8 million shares for a total cost of approximately $13.7 million.

截至 3 月 31 日的三個月內，我們回購了 180 萬股股票，總成本約為 1,370 萬美元。

I would now like to turn to our financial outlook, where for the full year, we are pleased to raise our expectations for total ARR, total revenue and non-GAAP operating income. For the second quarter, we expect total revenues of $73.8 million to $75.8 million or approximately 15% year-over-year growth at the midpoint. We expect non-GAAP operating income of $3.6 million to $4.6 million.

我現在想談談我們的財務展望，對於全年，我們很高興提高對總 ARR、總收入和非 GAAP 營業收入的預期。我們預計第二季總營收為 7,380 萬美元至 7,580 萬美元，中間值年增約 15%。我們預計非 GAAP 營業收入為 360 萬美元至 460 萬美元。

For the full year, we now expect total ARR of $316.8 million to $321.8 million or approximately 21% year-over-year growth at the midpoint. We now expect total revenues of $314.3 million to $320.3 million or approximately 17% year-over-year growth at the midpoint.

對於全年，我們目前預計總 ARR 為 3.168 億美元至 3.218 億美元，中間值年增約 21%。我們目前預計總收入為 3.143 億美元至 3.203 億美元，中間值年增約 17%。

And lastly, we now expect full year non-GAAP operating income of $30 million to $32 million or an operating margin of 9.5% to 10%. And on a Rule of 40 basis, which for AvePoint is the sum of our ARR growth and non-GAAP operating margin, our updated guidance reflects a [31%] compared to the [29%] that we initially guided for the year in February, with each component contributing equally to the increase.

最後，我們現在預計全年非 GAAP 營業收入為 3,000 萬美元至 3,200 萬美元，營業利潤率為 9.5% 至 10%。在40 規則的基礎上，對於AvePoint 來說，這是我們的ARR 成長和非GAAP 營業利潤率的總和，我們更新後的指導反映了[31%]，而我們2 月份最初指導的年度指導為[ 29%] ，每個組成部分對成長的貢獻相等。

In summary, Q1 was a strong start to 2024, and we are excited for another year of continued execution and capitalizing on the substantial long-term opportunity ahead of us. Thanks for joining us today.

總而言之，第一季是 2024 年的良好開端，我們對又一年的持續執行和利用擺在我們面前的大量長期機會感到興奮。感謝您今天加入我們。

And with that, we'll be happy to take your questions. Operator?

因此，我們很樂意回答您的問題。操作員？

(Operator Instructions) Derrick Wood, TD Cowen.

（操作員說明）Derrick Wood，TD Cowen。

Great, thanks and congrats on a strong quarter. TJ, I'll start with you. You're talking about the rollout of the Copilot analytics offering within tyGraph, when it was just made available, what's the feedback from customers?

太棒了，感謝並祝賀這個季度的強勁表現。TJ，我就從你開始吧。您談論的是在 tyGraph 中推出 Copilot 分析產品，當它剛推出時，客戶的回饋是什麼？

And I imagine dollars tied to this will start small, but I'd be curious if marketing this kind of tool could draw incremental interest for some of your core offerings, whether it's cross selling the base or generating new customers?

我想與此相關的資金一開始會很小，但我很好奇行銷這種工具是否可以為您的一些核心產品吸引更多的興趣，無論是交叉銷售基礎還是產生新客戶？

Yeah, great question. The rule for tyGraph or Office 365 Copilot is the first such solution in the market where we actually help our customers the zoning in onto the high-density collaboration areas and data estates to focus the effort around Copilot readiness.

是的，很好的問題。tyGraph 或 Office 365 Copilot 的規則是市場上第一個此類解決方案，我們實際上幫助客戶劃分高密度協作區域和資料資產，以集中精力圍繞 Copilot 準備情況。

Around the world, we have seen tremendous activities of companies across the board to actually experiment with Gen AI and traditional AI capabilities. And Microsoft has done a fantastic job in commoditizing and democratizing AI approach, especially offering Copilot to well over 500 million users and 365. So a ton of experimentation.

在世界各地，我們看到各公司進行了大量活動來實際試驗 Gen AI 和傳統 AI 功能。微軟在人工智慧方法的商品化和民主化方面做得非常出色，特別是為超過 5 億用戶和 365 家提供了 Copilot。所以進行了大量的實驗。

We haven't seen massive enterprise wide deployment yet. So this is why the solution like a tyGraph for Copilot from AvePoint that's released just this quarter is the way to zoom in onto the specific areas of collaboration and user groups. So this allow them to in pilot mode and in a century, POC mode in small group settings to really experiment and take advantage of the power of Gen AI.

我們還沒有看到大規模的企業範圍部署。因此，這就是為什麼本季剛發布的 AvePoint 的 tyGraph for Copilot 解決方案是放大特定協作領域和使用者群組的方法。因此，這使他們能夠在試點模式和一個世紀的 POC 模式下，在小組環境中真正進行實驗並利用 Gen AI 的力量。

And as we mentioned in our prepared remarks, very important aspect of making sure that your AI deployment strategy works is to have a very confident and solid trust in your data estate. So a lot of that preparation work goes into preparing, making sure that you have the right privilege for access to information management, lifecycle or life control as well as removing much of the redundant out-of-date trivial data.

正如我們在準備好的演講中所提到的，確保您的人工智慧部署策略有效的一個非常重要的方面是對您的資料資產有非常自信和堅定的信任。因此，大量的準備工作都用於準備，確保您擁有存取資訊管理、生命週期或壽命控制的正確權限，以及刪除許多冗餘過時的瑣碎資料。

And for tyGraph, what Copilot does is actually allow you to not just look at their entire data estate, which could well be over 500 petabytes for a lot of customers, zooming into the specific areas and user groups that you start with and to get the bigger ROI right away. So it's a very unique product sets. And you're right, we see robust pipeline building from all these information management requirements.

對於 tyGraph，Copilot 所做的實際上是讓您不僅可以查看他們的整個數據資產（對於許多客戶來說可能超過 500 PB），還可以放大到您開始的特定區域和用戶組，並獲得立即獲得更大的投資報酬率。所以這是一套非常獨特的產品。您是對的，我們從所有這些資訊管理需求中看到了強大的管道建置。

Very interesting, thanks. And one for Jim, 44% SaaS growth, really impressive. And even as I look at sequential growth, it was double digits. We haven't seen that since the first half '21. Can you talk about what's driving that inflection in SaaS?

非常有趣，謝謝。Jim 的 SaaS 成長了 44%，確實令人印象深刻。即使我觀察連續成長，也是兩位數的成長。自 21 年上半年以來，我們還沒有看到過這種情況。您能談談是什麼推動了 SaaS 的發展嗎？

Is there been a pickup in on-prem migrations? Or are there other factors like more cross-selling, new customer generation, et cetera? And then how do we triangulate that strength with your guide in Q2 of, I guess, relatively flat or sequential growth on total revenue?

本地遷移是否增加？或者是否還有其他因素，例如更多的交叉銷售、新客戶的產生等？然後，我們如何根據您在第二季度的指導來對這種優勢進行三角測量，我猜，總收入相對平穩或連續增長？

Yeah. Hi, Derrick, thanks for the questions. So maybe the first part of that question, I think we're seeing actually a couple of different factors, right? We are seeing nice growth from new customers, but specifically in Q1, we saw some nice real expansion with our existing customer base, sort of touch on your point and getting to that 110% of NRR. That was a nice driver and also drove some of that SaaS expansion as well.

是的。嗨，德里克，謝謝你的提問。所以也許這個問題的第一部分，我認為我們實際上看到了幾個不同的因素，對吧？我們看到新客戶的良好成長，但特別是在第一季度，我們看到現有客戶群出現了一些真正的擴張，有點觸及您的觀點並達到了 110% 的 NRR。這是一個很好的驅動力，也推動了 SaaS 的一些擴展。

So I think we're seeing it really across the platform. I wouldn't say it's just coming from one particular product or even migration, as you suggested, it's really across the spectrum, which is nice. And again, both new customers and then again, seeing nice growth from the existing customer base, which is nice that expansion.

所以我認為我們確實在整個平台上看到了這一點。我不會說它只是來自一種特定的產品，甚至是遷移，正如您所建議的，它確實是跨範圍的，這很好。再次，新客戶和現有客戶群都看到了良好的成長，這是很好的擴張。

And then I think when we think about Q2 in terms of where we ended Q1 and what we're thinking about for Q2, I think we're really pleased with the guidance that we have out there. And in terms of really setting the stage for the full year raise that we put out, we feel comfortable about that. We went from really revenue forecasts about 15% year-over-year growth to 17%.

然後我認為，當我們根據第一季的結束情況以及我們對第二季度的想法來考慮第二季度時，我認為我們對現有的指導感到非常滿意。就真正為我們推出的全年加薪奠定基礎而言，我們對此感到放心。我們將實際收入預測從年增約 15% 調整為 17%。

We're increasing the ARR growth from actually 20% to 21%. So we feel good about the guidance that we put out there. We also -- we've talked about this before. We do have this flux between SaaS and term and the impact that has on revenue. We did see in Q1 that there was a significant amount of SaaS and that can fluctuate from quarter to quarter.

我們將 ARR 成長率從實際的 20% 提高到 21%。因此，我們對我們在那裡發布的指導感到滿意。我們之前也討論過這個問題。我們確實存在 SaaS 和術語之間的這種變化以及對收入的影響。我們確實在第一季看到有大量的 SaaS，並且可能會隨著季度的變化而波動。

So we're mindful of that as we think about setting guidance specifically for Q2, but even thinking about the full year. So again, we're excited. We've got -- we think the guidance that we put out there is good, and we feel very comfortable about that achievement.

因此，當我們考慮專門為第二季度製定指導方針時，我們會注意到這一點，甚至考慮全年。我們再次感到興奮。我們認為我們提供的指導很好，我們對這項成就感到非常滿意。

Well done. Thank you.

做得好。謝謝。

Brett Knoblauch, Cantor Fitzgerald.

布雷特·諾布勞赫，坎托·菲茨杰拉德。

Hi, guys. This is Tommy Shinske on for Brett. Congrats on another solid quarter. I guess last quarter, we talked a little bit about the MSP approach to that to the SMB sector and how that's kind of shielded you from a lot of the headwinds that in the SaaS industry is kind of seeing as we head into 2024.

嗨，大家好。我是湯米·辛斯克 (Tommy Shinske) 替補布雷特 (Brett)。恭喜又一個穩定的季度。我想上個季度，我們討論了針對中小型企業領域的 MSP 方法，以及這種方法如何幫助您免受 SaaS 行業在進入 2024 年時會遇到的許多不利因素的影響。

I guess, is there any update, if you're seeing any SMB weakness or maybe even some budget constraints from the MSPs themselves?

我想，如果您發現中小型企業的弱點，或者甚至是 MSP 本身的一些預算限制，是否有任何更新？

Yeah, that's great question. So MSPs segmentation, as our approach to SMB segment for Microsoft SMB segment, it's well over 40% of their total revenue. So for us today is just under 20% of our total recurring. It's still the fastest growing segment for us. We see a level of abstraction.

是的，這是一個很好的問題。因此，MSP 細分，作為我們對 Microsoft SMB 細分市場的 SMB 細分的方法，它遠遠超過其總收入的 40%。所以對我們來說，今天的佔比略低於我們總經常性的 20%。它仍然是我們成長最快的部分。我們看到了某種程度的抽象。

So we don't -- because what we do is we offer essentially a management platform for these managed service providers to enable their businesses to scale to manage hundreds if not thousands of Microsoft Cloud tenants behind the scenes. So from that perspective, it's a different layer.

所以我們不這樣做，因為我們所做的本質上是為這些託管服務提供者提供一個管理平台，使他們的業務能夠擴展，以在幕後管理數百甚至數千個 Microsoft 雲端租用戶。所以從這個角度來看，這是一個不同的層次。

And from there, we actually continue to see very strong demand. We do have a very differentiated platform approach in the Microsoft Cloud play with information management, and we continue to see very strong demand from MSPs.

從那時起，我們實際上繼續看到非常強勁的需求。我們在微軟雲端資訊管理方面確實有一個非常差異化的平台方法，並且我們繼續看到來自 MSP 的非常強勁的需求。

Before it was really focused around data protection, data integration and control. And now very, very hot topic, of course, is Microsoft Copilot readiness, policy insight of the product and Opus are these products here are skews now among the MSP community.

在此之前，它真正關注的是資料保護、資料整合和控制。當然，現在非常非常熱門的話題是 Microsoft Copilot 準備、產品的策略洞察和 Opus，這些產品現在在 MSP 社群中存在偏差。

So yeah, we actually don't see much softness in that segmentation. Perhaps as I indicated before, is because we're really targeting enabling MSP business to grow. And for us SMB, the small medium business segment is still just 20% recurring, while the overall market is at least 40% of total market. So still a tremendous headwind and headroom and a green space bar to grow into. Thank you.

所以，是的，我們實際上在該細分中沒有看到太多的軟性。也許正如我之前指出的，是因為我們真正的目標是促進 MSP 業務的成長。對於我們中小企業來說，中小型企業細分市場的重複率仍然只有 20%，而整體市場至少佔總市場的 40%。因此，仍然存在著巨大的逆風和空間，以及可以成長的綠色空間酒吧。謝謝。

Awesome. Thanks, and congrats again guys.

驚人的。謝謝，再次恭喜大家。

Nehal Chokshi, Northland Capital Markets.

Nehal Chokshi，北國資本市場。

Thanks. Congrats on the strong quarter, strong raise. Your net new ARR was up 29% from the March quarter. How are you thinking about the net new ARR year-over-year growth as we move through the remainder of the year here?

謝謝。祝賀強勁的季度，強勁的成長。與 3 月季度相比，您的淨新 ARR 成長了 29%。當我們進入今年剩餘時間時，您如何看待新 ARR 的年淨增長？

Yes. So I think our guidance now that we just put out implies [$55 million] of net new ARR comp for the year, and that will be up about 10% over for the full year year-over-year. So I think when we think about it over the course of the year on the net new, that's kind of how we're expecting the full year shakeout.

是的。因此，我認為我們剛剛發布的指導意味著今年淨新 ARR 補償為 [5500 萬美元]，全年將同比增長約 10%。所以我認為，當我們在新的一年中思考這一點時，這就是我們對全年大洗牌的預期。

Right. I guess what I'm trying to drive at is that I think that adds up to about $46 million net new ARR for the remainder three quarters compared to $42 million in the comparable year-ago period. So that's up about 10% year over year. Is that you just hit the 30%. And so your question here is that what's behind what appears to be a deceleration in the net new ARR that you're expecting?

正確的。我想我想要推動的是，我認為剩餘三個季度的淨新 ARR 總計約為 4,600 萬美元，而去年同期的淨新 ARR 為 4,200 萬美元。所以年增了約 10%。是不是你剛剛達到了30%。因此，您的問題是，您預期的淨新 ARR 似乎出現減速，背後的原因是什麼？

Well, I think there's a couple of factors. I wouldn't say it's deceleration. But if you think about Q1 last year, when we were we were sitting here, we had a relatively low Q1 last year, definitely the weakest part of last year and definitely a comp that we're comparing against. So we're pleased with the growth at 29%, but it's also coming off a weak Q2 one in particular.

嗯，我認為有幾個因素。我不會說這是減速。但如果你想想去年的第一季度，當我們坐在這裡時，我們去年的第一季度相對較低，絕對是去年最弱的部分，也絕對是我們正在比較的一個比較。因此，我們對 29% 的成長感到滿意，但尤其是在第二季表現疲軟的情況下。

So again, we're pleased with the guidance that we have out there. I wouldn't call it a deceleration. We had strong performance in Q2 through Q4 of last year. And again, I think on that net incremental ARR, we feel good about that. And that gets us to our annual target of that 21%, which again, for the year, we're focused on achieving that growth rate and feel good about that guidance we have out there.

再說一遍，我們對現有的指導感到滿意。我不會稱之為減速。去年第二季到第四季我們表現強勁。再說一遍，我認為就淨增量 ARR 而言，我們對此感覺良好。這讓我們達到了 21% 的年度目標，今年我們再次專注於實現這一成長率，並對我們現有的指導感到滿意。

Great. And by the way, I mean, 10% incremental ARR growth for remainder years. Nothing required about, that's very good by itself anyhow.

偉大的。順便說一句，我的意思是，剩餘年份的 ARR 增量為 10%。沒什麼要求，無論如何，這本身就很好。

TJ, thanks for the customer examples and especially the concrete example around how Opus is helping customers be get their data Gen AI ready. Can you give us a sense of so what is the ARPU add as customers look at leveraging AvePoint's capabilities with respect to getting their data Gen AI ready?

TJ，感謝您提供的客戶範例，尤其是有關 Opus 如何協助客戶準備好資料 Gen AI 的具體範例。您能否讓我們了解一下，當客戶考慮利用 AvePoint 的功能來準備資料 Gen AI 時，ARPU 值會增加多少？

I know that's a great question. As we mentioned earlier, there's still a ton of experimentation happening. I think you probably also hear from other hyperscalers, the expectation for our real revenue evidence monetization will really happen probably in 2025. This year it's really because a lot of -- I was just recently at the Microsoft Redmond headquarters around executive for the briefing.

我知道這是一個很好的問題。正如我們之前提到的，仍然有大量的實驗正在進行。我想您可能也從其他超大規模供應商那裡聽說，我們對實際收入證據貨幣化的預期可能會在 2025 年真正發生。今年確實是因為很多 - 我最近剛在微軟雷蒙德總部與高管一起參加簡報會。

A lot of that challenge with AI deployment is actually change management. It has to drive from business owners, business sea levels versus just the IT conversation. So still a ton of experimentation and making sure that there is solid concrete business ROI before folks are willing to really deploy this enterprise-wide really deploy massive amount of budget towards it.

人工智慧部署的許多挑戰實際上是變革管理。它必須由企業主、業務海平面和 IT 對話來推動。因此，在人們願意在整個企業範圍內真正部署這個專案之前，仍然需要進行大量的實驗並確保有堅實的具體業務投資回報率，並為此部署大量預算。

So it's experimentation phase, we see a ton of that, and we see that as obviously to the number of increases conversations and opportunities in the pipeline. I would say that real dollar value, we won't see it most likely into next year.

所以現在是實驗階段，我們看到了很多這樣的情況，我們看到這明顯增加了管道中的對話和機會的數量。我想說，真正的美元價值，我們很可能不會在明年看到它。

That's great. Thank you.

那太棒了。謝謝。

Jason Ader, William Blair.

傑森·阿德，威廉·布萊爾。

Yeah, thank you. Good afternoon, guys. I wanted to ask about multiproduct, multisuite customers. I know that you've talked a little bit about that. I don't know if you have specific metrics for us, but maybe you can just talk to any momentum there.

是的，謝謝。下午好，夥計們。我想問有關多產品、多套件客戶的問題。我知道你已經談過一些了。我不知道你是否對我們有具體的衡量標準，但也許你可以談談那裡的任何動力。

And then beyond that, if you could build upon that, just maybe talk about the relative growth rates of each of your three suites? And any color commentary on what is happening within each of those product suites?

除此之外，如果您可以在此基礎上，談談您的三套房中每一套房的相對增長率？對每個產品套件中發生的事情有什麼顏色評論嗎？

Yeah. So maybe the first part of that question. I think we provide the suites and the multiple products and multiple suites within the customer. I think with that metric we're providing annually. But I will say that, Jason, in terms of what we saw in Q2, we did see some -- again, very nice growth from the existing customer base.

是的。所以也許是這個問題的第一部分。我認為我們為客戶提供套件以及多種產品和多種套件。我認為我們每年都會提供這個指標。但我要說的是，傑森，就我們在第二季度看到的情況而言，我們確實看到了現有客戶群的一些非常好的成長。

Most of the upselling that we see or the sales to existing customers is not so much more of the same product, but it is cross-sell motion. So we had a very strong quarter in Q2 in terms of where that landed.

我們看到的大多數追加銷售或對現有客戶的銷售並不是更多相同的產品，而是交叉銷售運動。因此，我們在第二季的表現非常強勁。

In terms of our annual disclosure around products, we've got about 50% of our customers that are on two or more products and about 24% that are [four-plus] products. And then when we talk about suites, it's roughly about 25% of our customers on [two-plus] suites.

就我們關於產品的年度揭露而言，我們大約 50% 的客戶使用兩種或兩種以上產品，大約 24% 的客戶使用[四種以上]產品。當我們談論套房時，大約有 25% 的客戶入住[兩間以上]套房。

And that's that annual metric that we're providing. We'll again provide that next year. But again, we saw a nice progression and upsells in Q1, and that led to that NRR of [110%] which was again, a very strong quarter for us.

這就是我們提供的年度指標。明年我們將再次提供這項服務。但我們再次看到第一季的良好進展和追加銷售，這導致 NRR 達到 [110%]，這對我們來說又是一個非常強勁的季度。

And then just the rank order of the growth rates by suite and then color commentary, maybe love to hear TJ talk to the on just the kind of dynamics in each of those three suites and what's going really well?

然後是按套房的成長率排名順序，然後是彩色評論，也許喜歡聽 TJ 談論這三個套房中每一個的動態以及進展如何？

So overall, the upsell, we're very pleased with that. We saw 25% increase upsell deals in Q1 compared to this time last year and also deals over [$100,000], we saw a 40% increase compared to this time last year.

總的來說，我們對追加銷售感到非常滿意。與去年同期相比，我們看到第一季的追加銷售交易增加了 25%，而且交易金額也超過 [10 萬美元]，與去年同期相比增加了 40%。

Now in terms of suites, as I mentioned earlier, it's really the control suite that that really focus on information management and access control that's the most active. Again, in terms of dollar value, though we are seeing again, smaller deployments because we do buy subscription and seat count is mirroring that of Microsoft's license model for their cloud.

現在就套件而言，正如我之前提到的，真正專注於資訊管理和存取控制的控制套件是最活躍的。同樣，就美元價值而言，儘管我們再次看到規模較小的部署，因為我們確實購買了訂閱，而且席位數量也反映了微軟雲端的授權模式。

So because of that experimentation across accounts are still focused on our smaller focus groups, business leaders to roll out our Gen AI capabilities. So there's definitely that happening and we do have a plan. And we have a set playbook for Copilot readiness, it actually leverages all three suites because people need to prepare, secure and optimize their data estates.

因此，由於跨帳戶的實驗仍然集中在我們較小的焦點群體、業務領導者上，以推出我們的 Gen AI 功能。所以肯定會發生這種情況，我們確實有一個計劃。我們為 Copilot 準備工作制定了一套劇本，它實際上利用了所有三個套件，因為人們需要準備、保護和優化他們的資料資產。

So step one is preparing to centralize enhanced data integration and integrity and step two secure that as identify and also enforce content policies. And last that optimize is to go forward with our governance and automation. You have to do both at the input of AI model as well as the outputs because now almost 10% of our data generated been done by Gen AI.

因此，第一步是準備集中增強的資料整合和完整性，第二步是確保識別和執行內容策略。最後的優化是推進我們的治理和自動化。你必須同時處理 AI 模型的輸入和輸出，因為現在我們產生的資料中近 10% 是由 Gen AI 完成的。

So the output also need to be very much controlled and filtered and moderated because we all know with large language models that you have inherent about 10% hover around that of a hallucination that's happening. So because output oftentimes is also used as inputs of data models to capture and model concept drift as the business environment evolves for large enterprises.

因此，輸出也需要受到嚴格的控制、過濾和調節，因為我們都知道，對於大型語言模型，你固有的大約 10% 徘徊在正在發生的幻覺周圍。因為輸出通常也用作資料模型的輸入，以隨著大型企業的業務環境的發展來捕獲和建模概念漂移。

So you never -- you always have to have that new century software of governance and then in the middle type of approach to ensure that this continuous feedback to the model is managed and measured and optimized. So in fact, it's actually driving all have three of our product suites.

因此，您永遠必須擁有新世紀的治理軟體，然後採用中間類型的方法，以確保對模型的持續回饋得到管理、衡量和最佳化。所以事實上，它實際上推動了我們所有的三個產品套件。

Thanks, guys. Good luck.

多謝你們。祝你好運。

Gabriela Borges, Goldman Sachs.

加布里埃拉·博爾赫斯，高盛。

Good afternoon. Thank you. TJ, AvePoint has this unique advantage playing in two ways. One is the savings that you enable for your customers when they think through things like storage optimization and the other is the projects that you have visibility into from an AI deployment standpoint.

午安.謝謝。TJ、AvePoint 在兩方面都有著獨特的優勢。一是當客戶考慮儲存優化等問題時，您為他們節省的成本；二是您從人工智慧部署的角度可以了解的項目。

So my question for you is how is that push towards cost optimization trending in some of your larger customers relative to last year? And the second part of the question is, where is the budget for some of these projects coming from and can AvePoint maybe connect the two pieces where you're enabling savings in one area of the business, but then go towards funding a project from another area of the business.

因此，我向您提出的問題是，與去年相比，您的一些較大客戶的成本優化趨勢如何？問題的第二部分是，其中一些專案的預算來自哪裡，AvePoint 是否可以將這兩個部分連接起來，在其中您可以在業務的一個領域實現節省，然後為另一個領域的專案提供資金業務領域。

That's a great question, Gabriela. So we continue to see consolidation on place from customers where they like platform vendors, they like less singular products and less vendor and it decreases risks and allow them to focus on the high-quality platform providers. So that economics focus and platform approach continues into this year.

這是一個很好的問題，加布里埃拉。因此，我們繼續看到客戶在喜歡平台供應商的地方進行整合，他們喜歡不那麼單一的產品和更少的供應商，這降低了風險，使他們能夠專注於高品質的平台提供者。因此，經濟重點和平台方法將持續到今年。

So we do, as you mentioned, give customers significant savings. One of the important value we provide in the Microsoft Cloud ecosystem is to help our customers maximize their ROI return on investment on their existing cloud investments.

因此，正如您所提到的，我們確實為客戶節省了大量費用。我們在 Microsoft 雲端生態系統中提供的重要價值之一是幫助我們的客戶最大限度地提高現有雲端投資的 ROI。

So we ourselves actually consume about $100 million of Azure over a three-year period, and that's growing very rapidly. And from that kind of economic of scale, we're able to drive a further savings for our customers. So storage optimization is just one such savings.

因此，我們自己在三年內實際上消耗了約 1 億美元的 Azure，而且成長速度非常快。透過這種規模經濟，我們能夠為客戶進一步節省成本。因此，儲存最佳化只是其中之一。

The others are also be able to provide consistent data management capabilities across different license type tiers as well as multi-cloud. I can't emphasize enough that today's world customers are not only on one hyperscalers.

其他人還能夠跨不同許可證類型層以及多雲提供一致的資料管理功能。我必須強調的是，當今世界的客戶不僅僅使用一台超大規模伺服器。

In fact, most enterprise customers, including government agencies, have a mandate to business continuity reasons. So they actually intentionally have multiple clouds vendors, just ensure that they have a business resiliency.

事實上，大多數企業客戶，包括政府機構，都有業務連續性原因的授權。所以他們實際上故意擁有多個雲端供應商，只是確保他們具有業務彈性。

And the second part of your question is that budget bucket. It is true increasingly the conversations are shifting towards the business budget versus the IT budget. If you only look at pure IT budget, it's very hard to say, hey, I'm going to spend an extra $30 per user per month just on Gen AI capabilities.

你問題的第二部分是預算範圍。確實，人們的討論越來越多地轉向業務預算與 IT 預算。如果你只看純粹的 IT 預算，那麼很難說，嘿，我將在 Gen AI 功能上每月為每個用戶額外花費 30 美元。

From an IT infrastructure planning perspective considering that that's equivalent to what more than most customers pay for entirety of home office we have out today with teams, with office, with e-mail with one terabyte of OneDrive, et cetera combined.

從 IT 基礎設施規劃的角度來看，這相當於大多數客戶為我們今天擁有的團隊、辦公室、電子郵件和 1 TB OneDrive 等的整個家庭辦公室支付的費用。

However, when you take it into a business context when you're driving business outcomes that is a much easier and different conversation. And this is what we're seeing very, very aggressive and active experimentation across the board to drive that business ROIs.

然而，當您將其帶入業務環境並推動業務成果時，這是一個更容易且不同的對話。這就是我們所看到的非常非常積極和積極的全面實驗，以提高業務投資回報率。

So yes, while the Copilot experimentation happening are limited to smaller footprints within the overall user population in companies. But those user population today are your power effectively power users among business community, your head of sales, Head of Marketing, Head of HR, CFOs.

所以是的，雖然 Copilot 實驗的發生僅限於公司整體用戶群中較小的足跡。但今天的這些用戶群是您在商業界、銷售主管、行銷主管、人力資源主管、財務長中的有效權力用戶。

So when you have that kind of conversation, it's a very different conversation than just pure IT, CIO level conversation. So yes, it is actually a very different budget conversation altogether.

因此，當您進行此類對話時，這與純粹的 IT、CIO 層級的對話非常不同。所以，是的，這實際上是一次完全不同的預算對話。

That makes sense. And then given some of the dynamics you were just walking through and the newer products that AvePoint has in its portfolio, talk to us about how the go-to-market is evolving, both from a cross-sell standpoint and then from a customer education standpoint as well.

這就說得通了。然後考慮到您剛剛經歷的一些動態以及 AvePoint 產品組合中的新產品，從交叉銷售的角度和客戶教育的角度與我們談談進入市場是如何演變的的立場也是如此。

How do you intersect some of the problems that you're solving with what the customers are planning for 2024? How does that conversation get catalyzed?

您如何將您正在解決的一些問題與客戶 2024 年的計劃結合？這種對話是如何被催化的？

Yeah, that's a great question. So what's really interesting is AvePoint has been in the business of information management, data management for the last 20-plus years. And it's a very easy conversation with a highly regulated industry customers because that just a policy and regulations demanded.

是的，這是一個很好的問題。真正有趣的是，AvePoint 在過去 20 多年裡一直從事資訊管理、資料管理業務。與受到嚴格監管的行業客戶進行對話非常容易，因為這只是政策和法規的要求。

But now with Gen AI rollout and everyone wants to take advantage of AI capabilities and disruptions to enhance and innovate on a business. The market educating them very, very quickly, the need for very solid and clean data estate. So otherwise, it's a trash and treasury issue because it's just not magic, right?

但現在隨著人工智慧的推出，每個人都希望利用人工智慧的功能和顛覆來增強和創新業務。市場非常非常快速地教育他們需要非常可靠和乾淨的數據資產。否則，這就是一個垃圾和財政問題，因為它不是魔法，對吧？

So AI models are heavily rely on your corporate data estates when you do fine tunings on existing large language models to take advantage of these new technology and your existing domain-specific industry data so that you're AI capabilities not just a summer intern had the knowledge base, but rather 20-year decades worth of industry knowledge in your specific company and domain.

因此，當你對現有的大型語言模型進行微調以利用這些新技術和現有的特定領域的行業數據時，人工智慧模型在很大程度上依賴你的公司數據資產，這樣你的人工智慧能力就不僅僅是一個暑期實習生擁有的知識庫，而是您特定公司和領域 20 年數十年的行業知識。

So with that, the awareness of data and information management and governance becomes the forefront across our industries. So that's really the sea change that we see before we have to educate customer the need for data management and governance and security. And today, they're actually coming to us to ask for that.

因此，數據和資訊管理和治理的意識成為我們行業的前沿。因此，在我們必須教育客戶了解資料管理、治理和安全性的需求之前，這確實是我們看到的巨大變化。今天，他們實際上來找我們要求這個。

And as I mentioned with our playbook around what we call oftentimes work with regional partners and Microsoft Azure teams around Copilot readiness is that a three-step process of prepare, secure and optimize and continually optimize and monitor your ongoing data usage to train and refine your models that actually brings forth all of our product sets and our platform.

正如我在我們的手冊中提到的，我們經常與區域合作夥伴和Microsoft Azure 團隊圍繞Copilot 準備工作進行合作，這是一個三步驟流程，包括準備、保護和優化，以及持續優化和監控您的持續資料使用情況，以訓練和完善您的資料使用情況。

And that also further highlights the need for our platform is you can no longer just offer of point products that's just in one aspect of the information management lifecycle or just only focus on data protection. You have to really consider the entire lifecycle and data management and continuous governance cycle to be successful. So it elevates the importance of our platform even more.

這也進一步凸顯了對我們平台的需求，即您不能再僅僅提供僅涉及資訊管理生命週期某一方面的單點產品或僅關注資料保護。您必須真正考慮整個生命週期、資料管理和持續治理週期才能取得成功。因此，它進一步提升了我們平台的重要性。

Very interesting. Thank you.

很有意思。謝謝。

Thank you. That concludes our question-and-answer session. I would like to turn the call back over to CEO, TJ Jiang for any closing.

謝謝。我們的問答環節到此結束。我想將電話轉回給執行長 TJ Jiang 進行結束。

Thank you. The rate of innovation always switch in our sector is gaining even more momentum powered by the rise of AI. The energy was tangible during my recent visit with fellow Microsoft IGM partners at executive briefing center in Bremen, as I mentioned earlier. It was a inspiring experience to be part of such a massive technology ecosystem as we embrace the AI transformation wave together.

謝謝。在人工智慧的崛起的推動下，我們行業的創新速度不斷變化，並獲得了更大的動力。正如我之前提到的，當我最近造訪不來梅執行簡報中心的微軟 IGM 合作夥伴時，這種活力是顯而易見的。當我們共同擁抱人工智慧轉型浪潮時，成為如此龐大的技術生態系統的一部分是鼓舞人心的經歷。

At AvePoint, we're excited by the transformational potential of AI, and we're equally aware of the challenges it poses to organizations around the world. We're ready to capture the many opportunities ahead of us and we look forward to a strong 2024.

在 AvePoint，我們對人工智慧的變革潛力感到興奮，我們也意識到它對世界各地的組織帶來的挑戰。我們已準備好抓住眼前的眾多機遇，並期待 2024 年的強勁發展。

Thank you again for joining us today, and we look forward to speaking with you more this quarter.

再次感謝您今天加入我們，我們期待本季與您進行更多交流。

Thank you. The AvePoint conference has now concluded. Thank you for attending today's presentation. You may now disconnect.

謝謝。AvePoint 會議現已結束。感謝您參加今天的演講。您現在可以斷開連線。