Or Offer
Analyst · Barclays
Thank you, Rami. Welcome, everyone, joining the call today, and a special welcome to Ran, who joined us as our new CFO in December 2025. I will begin with our Q4 and full year 2025 highlights, then cover our strategy and the progress we made in 2025, rolling out our innovative solution and conclude with our 2026 priorities and goals. Now let's look at our Q4 2025 performance on Slide 5. Revenue grew 11% year-over-year to $72.8 million. This was below our guidance, mostly due to the timing of 2 large LLM data training contracts that did not close yet, but remain active in our pipeline. Given the size and complexity of those AI contracts, sales cycles can take longer to complete. That said, once closed, we expect them to represent a very big multiyear revenue opportunities with strong expansion potential. We are working hard to close those deals. In addition, and despite the delay of those deals, we slightly exceeded the midpoint of our non-GAAP operating profit targets for the quarter through disciplined cost management. Despite the low topline performance, we delivered our ninth consecutive quarter of positive free cash flow and achieved our second consecutive year of positive operating profit. We generated approximately $13 million in free cash flow for the year, reinforcing our commitment to profitable and durable growth. Net revenue retention for all clients was 98% and 103% for clients above $100,000. We are focused on driving improvement in these metrics in 2026 by executing our customer expansion playbook. Later on, I will expand on the drivers behind that optimism and the action we are taking. Finally, customer demand for our AI offering continued to expand. AI-related revenue reached 11% of sales in the fourth quarter, up from 8% at the end of the second quarter of 2025, driven by our portfolio rated AI solution which we also will cover later in the presentation. Turning to Slide 6 and our key messages. First, 2025 was a build deal. We build the platform to win in the AI era, while the market was dynamic we lean into the opportunity forming around AI. We accelerated product innovation and launched new offerings such as App Intelligence, which was the fastest-growing product we had in 2025. We introduced an ad intelligence, Gen AI intelligence, AI agent and MCP integrations, which is a new industry standard for AI systems to access our data. Most recently, we launched an AI studio which is an AI-powered chatbot interface that make it easier for more users to access our data and actionable insights and recommendations. These are commercial products already gaining traction. As said, in Q4, 11% of our revenue came from AI-related use case. We see AI as magnificat [indiscernible] tailwind going forward. Second, we demonstrated the strength and durability of our model with AI revenue free ex year-over-year and achieved our second consecutive year of positive operating profit and free cash flow. One important highlights is that 60% of ARR is now multiyear, up from 49% a year ago. This is an important metric as it reflects deeper customer relationship stronger alignment with our value proposition and greater revenue visibility. Most importantly, it shows that our customers are choosing to commit to our data and products for a longer period of time, which is a strong vote of confidence in the value we deliver. In addition, 63% of ARR comes from customers generating over $100,000 annually enforcing how embedded we are in mission-critical use case in the enterprise segment. Third, our data mode matters more than ever. AI models and systems are only as strong as the data behind them. Our proprietary digital data now powers enterprises, LLM and AI agents, the quality of our data has been validated by both third parties and customers. For example, we expanded our integration within the Bloomberg terminal. This positions similar well as a premium alternative data provider for institutional investors and provide another proof point or the quality of the data we provide. And finally, 2026 is transformation here. We are moving from building to scaling as AI become embedded into workflow and trusted digital data become a strategic asset. We believe similar web is well positioned to power the next generation of digital intelligence. Let me walk you through how we are executing our strategy to build an AI-driven data powerhouse on Slide 7. Our strategy is built on 3 pillars: strengthening our data not deepening enterprise relationship and third, scaling AI first integrated solution. So let's start with the first one, durable data mode. We are a leader in the digital market data. For more than a decade, we invest hundreds of millions of dollars in developing and deeping our data mode, building deep expertise in collecting and estimating digital behavior at global scale. We continue to invest in R&D to enhance the quality, accuracy and the breadth of the data sets that power our digital intelligence. We continue to expand coverage, accuracy and freshness across web, app, search ads and now chat-based channels staying at the front wherever digital traffic is shifting. This is a hard to replace assets with compounding advantage and significant long-term commercial potential. AI depends on it. It's not replacing it. Second, we are powering leading enterprise with our trusted digital data. Many of the world's largest and most sophisticated companies are already our customers. We see significant opportunity to scale those relationships by applying our proven expansion playbook. -- increasing multiproduct adoption over time and driving higher no. We already have 2 large tax customers generating over $10 million in ARR, those are broad multiuse case relationship across multiple teams and function. Both have expanded into a data agreement that powered the LLMs, positioning similar as a critical building block within the Reintec. Enterprise expansion will be a key focus area for us in 2026 and beyond. Third, we are doubling down on AI-first integrated solution. And we will continue to expand our AI portfolio to establish ourselves as a winner in the AI transformation. Our data sets are uniquely positioned to power both enterprise users and AI systems, a dual strategy built for people and for agents. Through ecosystem partnerships like [indiscernible] data is embedded directly into AI-native workflows especially for research-driven use case, just as financial data become essential for research platforms, chatbots, we believe that digital market data can play a similar role across all platforms. we expect it become a meaningful commercial growth driver. As we execute on our 3 pillars, we remain fully committed to operational excellence to drive durable, profitable and cash generated growth. As you can see on Slide 8, we made significant steps forward on our strategy in 2025. As we build similar web for the next stage in our journey. Starting with the data note. In 2025, we launched multiple new data sets to further extend our 360-degree visibility across the digital world and establish our leadership in digital data. We significantly expanded our coverage across app data, ad spend data, chatbot activity data and Gen AI visibility. These data sets are very unique -- and we believe we are uniquely positioned to provide a comprehensive view across web, app, search, e-commerce, advertising and emerging AI-driven channels and covering the full digital journey across touch points. Moving to the enterprise pillar. We delivered a solid performance in 2025. Our $100,000 customers grew 12% year-over-year and now represent 53% of ARR. Revenue for multiyear contracts increased significantly to 60% of ARR from 49% in 2024. Lastly, on our AI-first solution. We launched our innovative offering, AI Studio, AI Agent embedded across our business solution to accelerate time to insight, Gen AI intelligence model which help brands measure their visibility and sentiment across generative AI platforms and a new chatbot MCP integration, including partnerships like Manus, which opened an exciting new distribution and monetization channel. Our partnership with Manus extends our data sets into agent-driven workflow, where autonomous AI agents capable of performing complex tax activities execute marketing analysis, competitive assessment and strategic planning. Manus, which was recently acquired by Meta is one of the fastest scaling start-up in history. And this is collaboration offer us revenue opportunities to scale with it. Furthermore, Manus provides access to a much broader set of potential end users beyond our core subscriber space, expanding our term by empowering millions of users with our data. This milestone partnership reinforced our value proposition as a central data layer for the next generation of agenetic tools and serves as a strategic blueprint for more integration to come. Those are some of the steps we took to strengthen our data mode, deepen enterprise relationship and position SimilarWeb to win in the AI era. Slide 9 captures our AI data and product strategy, how we power the ecosystem, build AI First solution and expand its tradition and scale. First, we are powering LLM and AI agents. We are seeing strong traction, licensing our data directly to leading LLM companies for both pre and post training use case. This is a strategic priority for us, and we expect it to become increasingly strong revenue stream for us over time. At the same time, autonomous agents require trusted structured digital intelligence to operate efficiently that's exactly what we provide. Our data is built for both human and agent and we see accelerating demand from both. Second, we are building our own AI native solution. With Gen AI intelligence, we are helping brands to improve their Gan AI visibility and sentiment. We are seeing strong market validation on this front, including the recognition of our leadership by G2Crowd and we have recently launched it in a self-serve with adoption from hundreds of customers. We believe our data provides an important competitive advantage in this new market, and we are on a journey to become a market leader in this category as well. We are also transforming our traditional software into an agent first model launching workflow-specific AI agents across marketing and sales use case. This move customers from insights to action with a faster time to value and stronger ROI. This effort is helping us to get to many more users, grow adoption and [indiscernible]. We are very excited about the potential of our own agentic strategy. Third, we are expanding distribution at scale. Our partnership with leading LLM and agent platform such as Manus and for MCP integration, we embedding similar web directly into AI ecosystem. Our MCP is already available in cloud and will soon be integrated into ChatGPT, enabling AI systems to seamlessly access our data, so users can consume similar web insights directly within the workflows. Those ecosystems partnership unlock new customers, expand our TAM and position our digital data as a critical ingredient for AI-driven research and decision-making. We believe we are well positioned to be an AI winner with multiple commercial opportunities across data products and partnerships, and we are excited about the potential. I would like to spend a moment on the AI Studio on Slide 10 because this is more than just a new product launch. AI Studio represents a huge shift in how users interact with similar web data. Historically, our platform delivered a powerful data-driven insight, but often requires technical expertise to express value. AI Studio changed that with an AI-powered interface, user can ask a business question in plain language and in all languages and [indiscernible] receive actionable insights what used to take time and specialized skill can now happen quickly and easily. This is a major step in the [indiscernible] access to our data across teams and workflows. AI Studio expand the number of users who can average similar web, increases engagement enables faster and more seamless insight generation and unlock new monetization opportunities. The early feedback both from better customers and since launch has been amazing. We see AI Studio as a core part of our product strategy, an important driver of future growth. I encourage you to watch the demo video after the call via the link on the slide to see it in action. Let me close by reflecting back on 2025 and how it's set up for 2026 on Slide 11. 2026 was a pivotal year, we made real progress, as I said, AI revenue grew 3x and now represent 11% of Q4 revenue. That is a meaningful traction and globalization that AI is already contributing to the business. We also strengthened our durability of the model. $100,000 customer grew 12% and [ 60% ] of ARR is now multiyear, up from 49% a year ago. They give us better visibility and enforce the depth of our enterprise relationship. At the same time, we acknowledge that 2025 was not within challenge. Overall, NRR stabilized at 98%, and we are not satisfied with that level. Well, NRR our $100,000 customers was at 103%, we know we can execute better across the border base. We have taken action while sharpening our go-to-market strategy, upgrading talent, refining processes and building scalable playbook to drive cross-sell and expansion. We see a clear opportunity to convert onetime AI evaluation deals into recurring revenues and to accelerate the adoption of our newer solution across the installed base. That's why we have a strong conviction in 2026. We are well positioned to capture long-term AI spend. Our AI First portfolio is scaling, ecosystem [indiscernible] are expanding, and we are targeting high-growth segments like LLM companies, large big tech players and OEM with our own dedicated go-to-market team and focus. With Ran joining as a CFO, will also strengthen our financial discipline and public market execution. So 2025 at this stage, 2026 is of our disciplined execution and acceleration. With that, I will hand it over to Ran.