管理層發言
Ladies and gentlemen, thank you for standing by. Welcome to the Alarum Technologies First Quarter 2026 Earnings Results Conference Call. Operator instructions were provided. This conference is being recorded. I'll now turn the call over to Ehud Helft, Investor Relations at Alarum. Ehud, please go ahead.
Thank you, operator. Good day, everyone, and welcome to Alarum Technologies' conference call to discuss the results of the first quarter ended March 31, 2026. Joining us today are Mr. Shachar Daniel, Chief Executive Officer; Mr. Shai Avnit, Chief Financial Officer. Shachar will begin with an overview of the quarter and recent business developments, followed by Shai, who will review the financial results and guidance. We will then open the call for questions. Before we begin, I would like to remind listeners that today's discussion contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and other federal securities laws. These forward-looking statements involve known and unknown risks and uncertainties that may cause actual results or performance to differ materially from those expressed or implied by such statements. Forward-looking statements include, among other things, statements regarding expected market demand, future growth opportunities, infrastructure investments, profitability trends, customer demand patterns, product expansion, future financial guidance and long-term strategic positioning. For a discussion of these risks and uncertainties, please refer to the company's filings with the SEC, including the company's annual report on Form 20-F and subsequent filings. In addition, during this call, the company will discuss certain non-IFRS financial measures, including adjusted EBITDA and non-IFRS gross margin. Definitions and reconciliation to the most directly comparable IFRS measures are available in the earnings press release issued earlier today. With that, I will turn the call over to Shachar Daniel, Chief Executive Officer of Alarum Technologies. Shachar, please go ahead.
Thank you, Ehud and thank you, everyone, for joining us today. Alarum continued scaling its AI data infrastructure platform during the first quarter of 2026, supported by strong demand from AI and enterprise data workloads. First quarter revenues reached $11.7 million, representing 64% year-over-year growth. We also delivered positive IFRS net income of $0.6 million, adjusted EBITDA of $2.1 million while continuing investing in infrastructure scale and platform expansion. Importantly, we believe the first quarter demonstrated the operating leverage potential of the AI data infrastructure platform we built throughout 2025. At the same time, we continue viewing the current market environment as highly dynamic and still in relatively early stages. The AI infrastructure ecosystem is evolving rapidly. Demand patterns remain volatile at times, and we continue prioritizing long-term infrastructure leadership and strategic positioning over short-term profitability optimizations. As a result, investment levels, infrastructure expansion and profitability may continue fluctuating as we scale the platform and pursue what we believe is a very large long-term opportunity. The AI infrastructure market. Demand for large-scale public web data infrastructure continues to expand rapidly, particularly around AI and agentic training, fine-tuning, retrieval systems, inference optimization and continuous model updating. At the same time, public web environments continue becoming more dynamic and operationally complex, increasing the technological barriers required to reliably collect data at scale. We believe this trend increasingly favors companies with large-scale infrastructure, operational know-how, routing optimization capabilities, global IP scale and the ability to maintain reliability under increasingly sophisticated anti-bot protections. During the first quarter of 2026, our infrastructure handled an average of more than 50 petabytes of monthly data traffic and tens of billions of requests across a global network supported by more than 80 million IP addresses worldwide while maintaining success rates exceeding 85%. This compares with a baseline of approximately only 5 petabytes of monthly traffic at the end of 2024, reflecting the rapid scaling of our infrastructure to support growing AI workloads. We believe this combination of scale, infrastructure depth, operational experience and ongoing investment is becoming an increasingly important competitive differentiator. Platform evolution. Over the past year, Alarum continued evolving from a traditional proxy-focused provider into a broader AI data infrastructure platform. Our platform today includes global proxy infrastructure, Website Unblocker, search solutions, AI-ready data sets and planning agentic workflow capabilities, which we expect to gradually introduce to customers during the second half of 2026. This broader product mix expands our addressable market. And over time, we believe it should support stronger customer relationships, improved unit economics and stronger long-term platform economics. We are also seeing encouraging diversification trends across both customers and verticals. While AI-related workloads remain a major growth driver, we continue expanding across additional enterprise use cases, including e-commerce, sales intelligence, digital monitoring, data enrichment and broader enterprise workloads. Operating leverage and infrastructure. Throughout 2025, we invested heavily in infrastructure, network expansion, platform capabilities and organizational scaling. In the first quarter of 2026, we began seeing encouraging early benefits from those investments through improved infrastructure utilization, routing efficiency, efficiency improvements from infrastructure scale, operating leverage and an improved product mix. However, we do not currently manage the business for short-term margin maximization. We continue prioritizing infrastructure scale, strategic positioning, customer expansion and long-term market leadership during what we believe remains an early phase of the AI infrastructure build-out scale. We believe the AI data infrastructure market is still in relatively early stages and we expect customer demand patterns and deployment scales to continue evolving rapidly. Market dynamics. The AI infrastructure market remains dynamic and at times volatile. Large AI customers may adjust consumption patterns based on training cycles, model releases, data set refreshes, inference optimization or internal infrastructure decisions. As a result, quarter-to-quarter variability may continue. At the same time, we believe the long-term secular trend remains very strong. Importantly, as our platform broadens across products, workloads, customers and enterprise verticals, we believe the business should gradually become more diversified and resilient over time. Looking ahead, we remain focused on scaling infrastructure, improving operational efficiency, expanding higher-value products, deepening enterprise customer relationships and strengthening our long-term leadership position in the AI data infrastructure. We believe we are still in the early stage of a very large market opportunity. And with that, I will turn the call over to Shai for the financial review and guidance. Shai?
Thank you, Shachar, and hello, everyone. I will briefly review our financial performance for the first quarter of 2026. Unless otherwise stated, all comparisons are against the same period last year. Revenue: Revenues for the first quarter of 2026 were $11.7 million compared with $7.1 million in the first quarter of 2025, representing growth of approximately 64% year-over-year. The increase was primarily driven by continued demand from large-scale AI-related customers alongside growth across additional enterprise workloads and products. Gross profit and margins: Gross margin for the first quarter of 2026 was 61.7% compared with 67.5% in the first quarter of 2025 and 53.8% in the prior quarter. The sequential improvement reflects improved infrastructure utilization, operating leverage and continued efficiency initiatives implemented throughout the business. This improvement is even more notable given the depreciation of the U.S. dollar against the NIS during the quarter, while most of our operating expenses are NIS denominated, creating an additional foreign exchange headwind. The operating expenses in the first quarter of 2026 were $6.4 million compared with $4.5 million in the first quarter of 2025. The increase resulted mainly from payroll and other employee-related costs, primarily research and development. This increase is a key part of Alarum's strategy to invest in innovation and improve the quality of its infrastructure and capacity. At the same time, we remain disciplined regarding operational efficiency and capital allocation. Net income and EBITDA: IFRS net income for the first quarter of 2026 was approximately $0.6 million compared with $0.4 million in the first quarter of 2025 and $0.2 million in the prior quarter. Adjusted EBITDA for the quarter was approximately $2.1 million compared with $1.3 million in the first quarter of 2025 and $1 million in the prior quarter. These results demonstrate improving operating leverage characteristics as the platform continues to scale. Balance sheet: We ended the quarter with a strong balance sheet and no financial debt. Cash, cash equivalents and debt investments as of March 31, 2026, totaled $24.2 million compared with $22.5 million as of December 31, 2025. Shareholders' equity increased to $33.4 million as of March 31, 2026, compared with $32.1 million as of December 31, 2025, primarily reflecting the company's net profit for the quarter. Outstanding ordinary share count as of March 31, 2026, was approximately 72.6 million shares, representing 7.3 million NASDAQ-listed ADSs. Our financial position continues to support ongoing investment in infrastructure, platform development and long-term growth opportunities. Guidance: For the second quarter of 2026, based on current visibility, we currently expect revenues of approximately $12.2 million, plus or minus 5%, representing approximately 39% year-over-year growth at the midpoint, and adjusted EBITDA of approximately $1.8 million, plus or minus $0.5 million. Our guidance reflects current visibility based on customer activity, existing workloads and current consumption patterns. At the same time, we continue prioritizing long-term infrastructure leadership and strategic positioning within the AI data infrastructure market. We remain focused on maintaining operational discipline while continuing to invest strategically in infrastructure, platform capabilities and long-term positioning within the AI data infrastructure market. I will now turn the call back to the operator for questions.
Before operator, Shai, I think you are a little bit cut off. Please repeat again the projection for the adjusted EBITDA and the plus/minus, okay?
Okay. So, the total guidance for the second quarter of 2026, based on current visibility, we currently expect revenues of approximately $12.2 million, plus or minus 5%, that represents approximately 39% year-over-year growth at the midpoint and adjusted EBITDA of approximately $1.8 million, plus or minus $0.5 million.
Thank you very much. Operator?
分析師問答
Operator instructions were provided. Our first question comes from the line of Kingsley Crane with Canaccord Genuity.
Congrats on a nice quarter. A couple for me. Just wanted to dive in a little bit more into the agentic workflow product that is coming online in the back half of the year. Just want to hear more about the vision, the monetization model and then what kind of—like what you're hearing from customers and what they want out of that product? And then just how quickly that could affect the revenue model?
Okay. So first of all, hi Kingsley, nice to hear from you, and thanks for joining us and for your questions. Regarding the product, you will forgive me in advance, but from a commercial aspect, I cannot expose too much because I prefer not to. But at a high level, all the world is moving basically to the agentic mode, meaning a customer—the customer that is hitting our platform—needs to take his own decisions. For example, which products he needs, which geographic regions, what's the main domains that he is going to hit, and exactly the data and how he needs the data in which structure. The agentic approach means that he will come in and it will be much simpler. As a customer, you can just, for example, indicate your use case and your need, and the model can take you directly to the relevant product, relevant geographic region, relevant subproduct. We have—for example—we have the IP proxy, but IP proxy is relatively under this title. There are many subproducts related to it: it can be ISPs, it can be others, it can be specific geographies, it can be sticky or not sticky. Many elements that basically will provide you the best optimum result. So the agentic layer is just a layer above the product in order to make the life of our customers much simpler. And of course, for us, it's an opportunity for upsell or attracting new customers, etc. But it's not supposed to be by itself a product that will generate its own revenues. It's a layer that is wrapping all our products.
Okay. Yes, that's helpful and looking forward to seeing that rollout. Just another—I just want to take a step back on the vision around scraping. I know that web environments are increasingly dynamic and difficult to access and that is a big reason why you have a moat there because you're more able to successfully circumvent those blockages. But they also have things like cloud defenses, robots.txt enforcement, and they're doing their best to fight fire with fire. So I'm curious about your renewed thoughts on the moat there and the challenges you're facing on the scraping side.
Okay. So, basically, as I mentioned also in my prepared remarks, as time goes on, it becomes more and more challenging to collect data at scale due to the reasons that you mentioned and due to many other reasons that make the life of those that want to collect data more challenging. To answer your question, nothing changed significantly. We have been in this game for years, and it's a game where we need to find the best way; of course, everything related to public data must be according to all policies. We need to find the way and it's all around the size, if you ask our opinion here. So it starts from the size of your network. As you have larger network size, you will have diversified IPs, more geographies, and a bigger amount of endpoints and IPs of all kinds. In this way, you can demonstrate better the experience our customers need and increase the success rate. In special cases, we have the Unblocker and our very successful scraper, which is called SERP API, that knows how to bypass this kind of anti-bot or other protections. They develop their technologies and they are progressing, but we are progressing also. And it looks like if you review our main KPIs—success rate, downtime and of course the size of our network—those went dramatically higher and the KPIs look great. Our customers are basically downloading or collecting petabytes of data on a daily basis.
Okay. I really appreciate that. And then just a couple of quick ones on financials. Gross margins performed really well in the quarter. Revenue roughly flat from Q4, better than expected, but COGS down about $1 million. Could you just help us unpack what's going on underneath there? And then expectations for COGS or gross margins through the rest of the year?
So, okay. I talked about it in general, but I want to be more specific now. As I mentioned, our main purpose now and in previous quarters—and likely in the coming quarters—is penetration: to become more significant and lead part of this AI revolution. The data collection is a layer in this funnel. This is our main purpose. If we need to invest more or to decrease our margins in order to penetrate additional customers or verticals, we will do it. In this quarter, as I mentioned, it's a demonstration of our capabilities and the leverage we can get from our platform because we invested more in the previous quarter in our infrastructure. In this quarter, we reaped fruits from that. Most of the verticals and the use cases were not new for us, so we didn't need to build something new or use a new third party in order to win the opportunity. It's a combination of our improvement over time. I can tell you that our R&D—major part of these KPIs and day-to-day work—is to adjust and improve the efficiency of our IP, the routing, everything behind, which translates to money at the end of the day. So this, and the current use cases that we improved ourselves because we learned in the previous two quarters, made this quarter better. The purpose is to be as efficient as we can. If things go according to plan—like this quarter, from verticals and no unexpected surprises—we can be here and even better. If we decide to invest to penetrate new customers or the market changes and brings new use cases, we will allow ourselves to step back on margins to drive penetration, because as you can see, the penetration we did in the third quarter of 2025 had greater ROI in this quarter. Hopefully, that's how we will act in the future.
Okay. And then just last one from me. NRR continues to be a lumpy metric. In some ways, it's not the best way to judge the business in any given quarter. You did call out that the trends in the AI customer segment are more positive. Is there any more quantification to that? And an update on the durability of those customers in that segment. Is it shaping up that customers in the AI and LLM infrastructure-related segment are going to be multiyear customers with significant expansion opportunities? I know they can come in and spend a lot in the first year as well, which can create a tough comp.
Yes. So, first of all, regarding NRR, as you may remember, the way we measure our NRR is based on big data: we're comparing four quarters versus four quarters. That measurement methodology causes a lag when there's a big shift in customer composition. The shift we experienced over the last year—AI training and AI verticals growing from essentially zero in our customer mix—takes NRR a little bit back because we're not measuring quarter versus the previous quarter. That's the way we chose to measure. We can discuss and perhaps show a metric more related to recent quarters to answer your second question about retention of AI customers. In general, data is like fuel for cars: you need it constantly. Data is the major fuel of AI in training and later in production, because everything is related to data, and much of that data comes from the Internet. So, in general, yes, it's here to stay. Over the last three to four quarters, as these AI customers and AI training use cases came in, we see great retention from a logo perspective—very strong retention. From a revenue perspective, it's volatile: one quarter they consume an amazing amount of data, next quarter less, then they hit another use case and consume more. But as a retention metric at this point, it looks very strong.
We have no further questions at this time. Mr. Daniel, I would like to turn the floor back over to you for closing comments.
Okay. So, thank you very much, ladies and gentlemen, and we appreciate your time. We believe the quarter reflects important progress in the evolution of Alarum into the scaled AI data infrastructure platform, and we remain focused on long-term execution, operational discipline and sustainable growth within what we believe remains an early stage of the biggest evolution of the AI infrastructure. We look forward to updating you again next quarter. Thank you very much.
Ladies and gentlemen, this does conclude today's teleconference. You may disconnect your lines at this time. Thank you for your participation and have a wonderful day.