Replay available
Alarum Technologies (TASE:ALAR) Q1 2026 Earnings Call
Alarum Technologies (TASE:ALAR) Q1 2026 earnings call, held 2026-05-28. Watch the replay and read the transcript on 6ix.

- Company
- Alarum Technologies Ltd (TASE:ALAR)
- Period
- Q1 2026 earnings call
- Date
- Thu, May 28, 2026, 9:00 AM ET
- Replay
- Watch the replay on this page · 29 min
On 6ix: 6ix.com/event/alarum-technologies-ltd-alar-q1-2026-earnings-call
Replay
Transcript
Automated transcript · Written by software from the replay's audio. It can mishear names and figures; the replay is the record.
0:00 Ladies and gentlemen, thank you for standing by. Welcome to the Alarum Technologies First Quarter twenty twenty six Earnings Results Conference Call. During today's presentation, all parties will be in a listen only mode. Following management's presentation, the conference will be open to questions. If you have a question, please press the star followed by the number one on your touch tone phone. If you would like to withdraw your question, please press the star followed by the number two. If you're using a speaker, please lift the handset before making your selections. This conference is being recorded. I'll now turn the call over to Ahud Helft, Investor Relations at Alarum. Ehud, please go ahead.
0:46 Thank you, operator. Good day, everyone, and welcome to Alarum Technologies conference call to discuss the results of the first quarter ended 03/31/2026. Joining us today are Mr. Shahar Daniel, Chief Executive Officer and Mr. Shay Avnit, Chief Financial Officer. Shahar will begin with an overview of the quarter and recent business developments, followed by Shay, who will review the 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 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.
1:37 Forward looking statements include, among other things, statements regarding expected market demand, future growth opportunities, infrastructure investments, profitability trends, customer demand patterns, product expansions, 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 Shahar Denha, Chief Executive Officer of Alarum Technologies.
2:27 Shahar, please go ahead. Thank you, Ehud, and thank you, everyone, for joining us today. Alarum continued scaling its data infrastructure platform during the first quarter of twenty twenty six, supported by strong demand from AI and enterprise data workloads. Third quarter revenues reached $11,700,000 representing 64% year over year growth. We also delivered positive IFRS net income of $600,000 adjusted EBITDA of $2,100,000 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 bid throughout 2025.
3:17 At the same time, we continue viewing the current market environment as highly dynamic and still in relatively early stages. Data 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.
4:16 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 twenty twenty six, our infrastructure ended 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 80,000,000 IP addresses worldwide while maintaining success rates exceeding 85.
5:12 This compares with a baseline of approximately only five petabytes of monthly traffic in the end of twenty twenty four, 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 and broker self solutions, AI ready datasets, and planning agentic workflow capabilities, which we expect to gradually introduce to customers during the second half of twenty twenty six.
6:08 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 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.
7:00 In the first quarter of twenty twenty six, 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 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.
7:53 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, dataset refreshes, inference optimization, or internal infrastructure decisions. As a result, 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.
8:54 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 Shay for the financial review and guidance. Shay? Thank you, Shahram, and hello, everyone. I will briefly review our financial performance for the first quarter of twenty twenty six. Unless otherwise stated, all comparisons are against the same period last year. Revenues for the first quarter of twenty twenty six were $11,700,000 compared with $7,100,000 in the first quarter of twenty twenty five, 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.
9:52 Gross profit and margins. Gross margin for the first quarter of twenty twenty six was 61.7% compared with 67.5% in the first quarter of twenty twenty five and fifty three point eight percent 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.
10:42 The operating expenses in the first quarter of twenty twenty six were $6,400,000 compared with $4,500,000 in the first quarter of twenty twenty five. 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 twenty twenty six was approximately $600,000 compared with $400,000 in the first quarter of twenty twenty five and $200,000 in the prior quarter.
11:35 Adjusted EBITDA for the quarter was approximately $2,100,000 compared with $1,300,000 in the first quarter of twenty twenty five and $1,000,000 in the prior quarter. These results demonstrate improving operating leverage characteristics as the platform continues scaling. Balance sheet. We ended the quarter with a strong balance sheet and no financial debt. Cash, cash equivalents and debt investments as of 03/31/2026, totaled $24,200,000 compared with $22,500,000 as of 12/31/2025.
12:23 Shareholders' equity increased to $33,400,000 as of 03/31/2026, compared with $32,100,000 as of 12/30/2025, primarily reflecting the company's net profit for the quarter. Outstanding ordinary share count as of 03/31/2026 was approximately 72,600,000 shares, representing 7,300,000 NASDAQ listed ADSs. Our financial position continues to support ongoing investment in infrastructure, platform development, and long term growth opportunities.
13:10 Guidance. For the second quarter of twenty twenty six, based on current visibility, we currently expect revenues of approximately $12,200,000 plus or minus 5%, representing approximately 39% year over year growth at the midpoint and adjusted EBITDA of approximately $1,800,000 plus or minus $1,500,000 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 AI data infrastructure market.
14:05 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 a little bit cut. Please repeat again the projection for the adjusted EBITDA and the plusminus. Okay? Okay. So, the total guidance for the second quarter of twenty twenty six, based on current visibility, we currently expect revenues of approximately $12,200,000 plusminus 5%. That represents approximately 39% year over year growth at the midpoint, and adjusted EBITDA of approximately $1,800,000 plus or minus $05,000,000 Thank you very much.
15:07 Operator? Thank you. We will now be conducting a question and answer session. Thank you. Our first question comes from the line of Kingsley Crane with Canaccord Genuity. Please proceed with your question. Hi. Congrats on a nice quarter, and thanks for taking the questions. Thank you very much. A couple from me.
15:52 Just wanted to just dive in a little bit more into the AgenTic workflow product that is coming online in the back half of the year. Just wanna 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, you know, how quickly that could affect the 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, 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 diegetic 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, 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.
17:10 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, where, for example, we have 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 dysgeographic, it can be sticky or not sticky many, many elements that basically will provide you the best or the optimum result.
17:57 So diegetic 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, etcetera. But it's not supposed to be buying sales a product that will generate its own revenues. It's a layer that is wrapping wrapping all our products. 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 division around scraping and, you know, 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 know, you're more able to successfully circumvent those Yeah. Those blockages. But and you also have, like, things like Cloudflare, paper crawl, robots dot text enforcement, and just, you know, they're they're doing their best to to 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.
19:11 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. 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.
20:05 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 geographic. 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 need for us and to increase the success rate. In special cases, we have done Blocker and our very successful script, which is Serp API, that knows how to bypass this kind of anti bots or anti others, 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.
21:01 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 data of on a monthly on a daily basis, basically. Okay. I really appreciate that. And then just a couple quick ones on financials. So, gross margins performed really well in the quarter. I mean, 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?
21:54 So, okay, so I talked about it in general, but I want to be more specifically now. As I mentioned, 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 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's a demonstration for our capabilities, the leverages we can get from our platform.
22:51 Because in this, we invested more in the previous quarter in our infrastructure. In this quarter, basically, bear fruit 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 these KPIs in this day to day is to adjust and to improve the efficiency of our IP, the routing, everything behind, which translates to money at the end of the day. So this and current use cases that we improved ourselves because we just learned them in the previous two quarters, make this quarter to be better or or or 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 it goes according to this, like, this quarter from verticals, from from other new no no new surprises, so we we can be here and even and and and better. If we take a decision to invest or to penetrate new customers, oh, the market will change and we come with new use cases, we will allow ourselves to go back in
24:22 order 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 twenty twenty five, it's greater ROI in this quarter, and hopefully, that's how we will act in the future. Okay. And then just last one from me. 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.
25:09 I mean, like the the shaping up to be that customers in the AI and LLM infrastructure related segment are gonna be multi year customers and 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. Yeah. Yeah, so first of all, let's discuss about the NRL. If you remember, you we are you can see it in our documents. The way we are measuring our NRL is basically based on big data. Okay, it's going back fourwe are measuring four times, four quarters versus four quarters. So, the shift, basically, it's a huge shift we of our customers that just, let's say, one year ago, the AI training and all these AI verticals were zero in our from our customers' portion.
26:09 This shift basically takes the NRR a little bit back 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 the you know, it's like in cars, yes, you need fuel or electric, whatever, all the time, otherwise you cannot drive. Data is the fuel of all the AI in the 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.
27:10 So in general, yes, it's here to stay forever. As we see in the last three or four quarters, as these 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 they consumed, you know, amazing amount of data. And then in the next quarter, they consume less, and then they will go to the next use case and they will consume more because it's quite volatile. But as a retention, it looks for this point of time, it looks a very good retention. I really appreciate the comments. Thanks again. Congrats.
27:57 Thank you very much. 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. Okay. So thank you very much, ladies and gentlemen, we appreciate your time. We believe the quarter reflects important progress in the evolution of Alarum into the scale 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.
28:47 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.
Follow Alarum Technologies Ltd into a list and get an email when it puts out news.
Latest news releases
- TASE:ALAR — Alarum Technologies Provides Further Update Regarding Recent Developments · Mon, Jul 13, 2026
- TASE:ALAR — Alarum Technologies Announces Temporary Operational Pause of Certain Network Services · Sat, Jul 4, 2026
Companies on this call
More from Alarum Technologies Ltd
- May 28, 2026 Alarum Technologies (TASE:ALAR) Q1 2026 Earnings Call
- Mar 19, 2026 Alarum Technologies (TASE:ALAR) Q4 2025 Earnings Call
- Nov 26, 2025 Alarum Technologies (TASE:ALAR) Q3 2025 Earnings Call
- Aug 28, 2025 Alarum Technologies (TASE:ALAR) Q2 2025 Earnings Call
- May 29, 2025 Alarum Technologies (TASE:ALAR) Q1 2025 Earnings Call
- Mar 20, 2025 Alarum Technologies (TASE:ALAR) Q4 2024 Earnings Call