On Thursday, Alarum Technologies (NASDAQ:ALAR) discussed first-quarter financial results during its earnings call. The full transcript is provided below.
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Summary
Alarum Technologies reported Q1 2026 revenues of $11.7 million, marking a 64% year-over-year increase, driven by strong demand from AI and enterprise workloads.
The company achieved a positive IFRS net income of $0.6 million and an adjusted EBITDA of $2.1 million, highlighting improved operating leverage.
Gross margins improved to 61.7% from the previous quarter, reflecting better infrastructure utilization and efficiency.
Alarum Technologies continues to focus on scaling its AI data infrastructure platform, expanding product offerings, and prioritizing long-term strategic positioning over short-term profitability.
The company handled an average of over 50 petabytes of monthly data traffic, indicating substantial infrastructure scaling.
For Q2 2026, the company guides revenue of approximately $12.2 million with an adjusted EBITDA of around $1.8 million, emphasizing ongoing investment in infrastructure and platform capabilities.
Management highlighted a focus on expanding into AI-related markets and achieving long-term market leadership, despite the dynamic and sometimes volatile market environment.
Full Transcript
Ehud
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. Shaharr Daniel and Chief Executive Officer Mr. Shai Avni. Chief Financial Officer Shahar will begin with an overview of the quarter and recent business development, followed by Shai who will review their financial results and guidance. We will then open the call for the 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 law. These forward looking statements involve known and unknown risks and uncertainty that may cause actual results or performance to differ materially from those expressed or implied by such statement. 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 filing with the SEC, including the company’s annual report on Form 20F and subsequent filing. 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 Shaharr Daniel, Chief Executive Officer of Alarm Technologies. Shahar, please go ahead.
Shahar Daniel (Chief Executive Officer)
Thank you eud and thank you everyone for joining us today. Alarum continued scaling its 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 did throughout 2025. At the same time, we continue viewing the current market environment as highly dynamic and still in relatively early stages. Their 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 agents 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 company 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 the baseline of approximately only 5 petabytes of monthly traffic in 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, alarm continued evolving from a traditional proxy focused provider into a broader AI data infrastructure platform. Our platform today includes global proxy infrastructure, website and broker solutions, AI ready data sets and planning agents workflow capabilities which we expect to gradually introduce to customers during the second half of 2026. This border product mix expands our addressable market and over time we believe it should support stronger customer relationship, 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 and challenges, 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 a 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 buildout 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 pattern based on training cycles, model releases, dataset refreshes, inference optimization or internal infrastructure decisions as a result of quarter to quarter variability may continue. At the same time, we believe 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 customers 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 Avni
Shaharar, thank you Shahar 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 margins 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 US 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 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 ADS 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, an adjusted ebitda of approximately $1.8 million plus or minus $1.5 million. Our guidance reflects currently 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 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 were 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 half a million dollars. Thank you very much
OPERATOR
Operator. Thank you. We will now be conducting a question and answer session. If you would like to ask a question, please press Star one on your telephone keypad. A confirmation tone will indicate Your line is in the question queue. You may press STAR two if you would like to remove your question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. One moment please, while we poll for questions. Thank you. Our first question comes from the line of Kingsley Crane with Canaccord Genuity. Please proceed with your question.
Kingsley Crane (Equity Analyst)
Hi. Congrats on a nice quarter and thanks for taking the questions. A couple from me just wanted to just dive in a little bit more into the agents 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 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.
Shahar Daniel (Chief Executive Officer)
Okay, so first of all, hi Kingsley, nice to hear from you and thanks for joining us and for your questions regarding the product. So you will forgive me in advance because from commercial aspects I cannot expose too much because I prefer not to. But in high level, you know, all the world is moving basically to the agent-based mode, meaning a customer, the customer that is hitting our platform, he needs to take his own decisions, for example, which products he needs, for example, which geographic, what’s the main domains that he’s going to hit and what’s exactly the data and how we need the data and which structure the agenting means that you will come in and it will be much more simple. And then as a customer you can just for example hitting your use case and your need and the model can take you directly to the relevant product, relevant geographic, relevant sub product, you know, for example the IP proxy. But the IP proxy is relatively under this title there are many sub products, you know, related to the it can be ISPs, it can be others, it can be this geographic, it can be sticky or not sticky, many, many elements that basically will provide you the best or the optimum result. So agent-based is just a layer above the product in order to make the life of our customers much more simple. And of course for us it’s an opportunity for upsell or attracting new customers, etc. But it’s not supposed to be buying sales, a product that will generate its own revenues. It’s a layer that is wrapping all our products.
Kingsley Crane (Equity Analyst)
Okay, yeah, that’s helpful and looking forward to seeing that roll out. Just another question, I just want to take a step back on the vision around scraping and 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 you also have things like Cloudflare, paper crawl robots, text enforcement, and just they’re doing their best to fight fire with fire. So just curious on your renewed thoughts on the moat there and the challenges you’re facing on the scraping side.
Shahar Daniel (Chief Executive Officer)
Okay, so basically, as I mentioned also in my part of this call, I say that as time is running, it becomes more and more challenging to collect data in scale due to the reasons that you mentioned and due to many, many other reasons that make the life of those that want to collect data more challenging. To answer your question, nothing changed significantly. You know, we are in this game for years and it’s a game that we need to find the best way. Of course, everything related to public data, everything according to all the policies where we need to find the way and it all around the size, if you ask our opinion here. So it starts from the size of your network, as you will have, let’s say the size of your network, you will have diversified IPs, you will have much more geographics, you will have a bigger amount of endpoints and IPs from all kinds. In this way you can demonstrate better the experience of what our customers did for us. And to increase the success rate in spatial cases, you know, we have done blocker and our very successful scraper which called SERP API that knows how to bypass this kind of anti bots or anti others that the names that you mentioned, not specifically them, but in general, as you know, they develop their technologies and they are progressing, but we are progressing also. And it looks like that if you will review our main KPIs, which is success rate downtime and of course the size of our network went dramatically higher and still the KPIs looks great. And our customers basically downloading or collecting betas of data on a daily basis. Basically.
Kingsley Crane (Equity Analyst)
Okay, really appreciate that. And then just a couple quick ones on financials. So gross margins performed really well in the quarter. I mean revenue roughly flat from Q4, of course better than expected, but cogs down about a million. So could you just help us unpack what’s going on underneath there? And then just expectations for cogs or gross margins through the rest of the year. So okay, so I talked about it
Shahar Daniel (Chief Executive Officer)
in general, but I want to be more specifically known, as I mentioned, and I will say it again, our main purpose now in these days, in the previous quarters, and it looks like that in the coming quarters is the penetration is to become more and more significant and leader part of this AI revolution. And you know it’s very. The data collection is a layer in this funnel. This is our main purpose and if we will need to invest more or to decrease our margins in order to penetrate to additional customer or to additional vertical, we will do it in this quarter. Also I mentioned it. It’s a demonstration for our capabilities for the leverages we can get from our platform because we invested more in the previous quarter in our infrastructure in this quarter. Basically we barefoot from this most of the verticals and the use cases were not new for us. So we didn’t need to build something new or to use a new third party company in order to win the opportunity. So it’s a combination of our improvement over time. I can tell you that our R and D I think the major part of his KPIs and this day to day is to adjust and to improve the efficiency our ip, the routing everything behind which translate to money at the end of the day. So this and the current use cases that we improved ourselves because we just learned them in the previous two quarters make this quarter to be better or great even not comparing to the previous quarter. But and I will answer like this, the purpose is to be as much as efficient as we can and if all goes according to this like this quarter from verticals, from other new, no new surprises. So we can be here and even better if we take a decision to invest or to penetrate new customers or the market will change and we’ll come with new use cases. We will allow ourselves to go back in order to go in order to go back after but to allow ourselves to go back to penetrate. Because as you can see now, the penetration that we did in Q in the third quarter of 2025 as greater our ROI in this quarter and hopefully that’s how we elect in the future.
Kingsley Crane (Equity Analyst)
Okay, and then just last one from me. You know I like 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. So curious if there’s just any more quantification to that and then just an update on the durability of those customers in that segment. I mean just like is it shaping up to be that customers in the AI and LLM infrastructure related segment, you know, are going to be multi year customers and then have significant expansion opportunities. I know they can come in and spend a lot in the first year as well. So that can create a tough comp.
Shahar Daniel (Chief Executive Officer)
Yeah, yeah. So first of all, let’s discuss about the nrr. If you remember, you know we are, you can see it in our document. The way we are measuring our NRL is basically based on big data. Okay. It’s going back. We are measuring 4 times 4 quarters versus 4 quarters. So the shift basically it’s a huge shift of our customers. Just let’s say one year ago the AI training and all these AI verticals were zero from our customers portion. This shift basically takes the NRR a little bit better because we are not measuring quarter versus the previous quarter. That’s the way we chose to measure. We can discuss about it and maybe we will show something that is more related to the last quarter in order to answer your second question about the retention level of the AI customer. So in general, before we talk about our customers, data will be, you know, it’s like, like in cars. Yes, you need fuel or electric, whatever all the time, otherwise you cannot drive. Data is the major, is the fuel of all the AI in this training stage and later on in the production stage because everything is related to data. The data is coming back from the Internet. It’s not. Nobody generates data by themselves. So in general, yes, it’s here to stay forever. As we see in the last three or four quarters as this AI customers, AI training use cases came in, we see that we have a great retention from logo perspective it’s an amazing retention from revenue perspective because that it’s volatile. So you can see quarter they consumed, you know, amazing amount of data and then in the next order they consume less and then they will go to the next use case and they consume more because it’s quite volatile. But as a retention it looks for this point of time it looks a very good retention.
Kingsley Crane (Equity Analyst)
I really appreciate the comments. Thanks again. Congrats. Thank you very much.
OPERATOR
Thank you. We have no further questions at this time. Mr. Daniel, I’d like to turn the floor back over to you for closing comments.
Shahar Daniel (Chief Executive Officer)
Okay, so thank you very much ladies and ladies and gentlemen and we appreciate your time. We believe the quarter reflects important progress in the evolution of alarm into a 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.
Disclaimer: This transcript is provided for informational purposes only. While we strive for accuracy, there may be errors or omissions in this automated transcription. For official company statements and financial information, please refer to the company’s SEC filings and official press releases. Corporate participants’ and analysts’ statements reflect their views as of the date of this call and are subject to change without notice.
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