Welcome to Siili's Result Info for 2025. My name is Tomi, and I'm the CEO of Siili. Today we have a few points on the agenda. First, I will talk about the AI market in general and our positioning in the market. Second, a few highlights of 2025. After that, our new CFO, Tuomas, will go through the numbers. And after that, we'll look a bit on how the future of Siili looks like. Our strategy is "Make AI Real." We introduced that strategy shift roughly 18 months ago, and since then we've been focusing very much on AI. And thus, let's first look at how AI is impacting the market. And today I'm particularly focusing on how the AI is impacting the software industry this time, because that's our context. AI is changing the fundamentals of how the software industry works, where the value is, and in the value chain, and what actually scales. For instance, valuations of global software giants have taken a hit in the past month. Their business is mainly licensing standard software, Adobe and Microsoft Word as an example. AI enables mass customization of software with almost zero variation cost. Thus, that weakens the advantage of, let's say, the traditional generic standard software, and then, of course, at the same time creates opportunities for companies like Siili. And in this—no, maybe not process—but in this situation, one key question is how business models will adapt and fit with the AI-native world. Traditionally, our industry and our business particularly has been based on hourly pricing models, and that clearly is not, let's say, the optimal fit for the current AI market. What the models will be, time will show. Traditionally, the hourly-based pricing has been the traditional model, but I'm, let's say, pretty confident that that will change over time because of the AI. Then if we look at the world and the AI through these three different lenses at the moment. First, what we call the AI Ripple Effect, and this is, by the way, something we published a white paper on this topic also. AI lowers the unit costs and the unit effort and speeds up the development significantly. Earlier, most time and effort in the software development project was spent writing the software itself. Now the bottleneck moves from the software development to other parts of the process, meaning defining the process and specs in the software. Organizations are not ready for that. And of course, because the development speed is now so fast that the organizations simply have difficulties to adapt to that change as fast as it would be possible. The second force we see is what we call the Companion Economy. And by that, we mean that the customer interaction is moving away from the applications and features more toward continuous AI-mediated relationships. And this has a significant impact on, I guess, basically on any consumer business as that weakens the power of brands. So at some point, your own consumer agents start to interact directly with retailers. And today, the OpenAI is maybe the first concrete example of this phenomenon, but I'm pretty sure that there will be much more of those in the coming months and years. Now then, the third lens we look at this phenomenon is what we call the Gutenberg Effect of Software. So Gutenberg invented the printing machine in the 15th century, and that industrialized creating information and made information available, not just public, and scaled it. Gutenberg, and what we mean by the Gutenberg Effect on Software, we mean that the same thing is happening to the software industry. So software production can scale basically unlimitedly at the moment, and at the same time, customizing without losing the efficiency is possible. And this is a completely new phenomenon. We have not seen anything like this before. And therefore, when the variation becomes easy, generic kind of one-product-fits-all models lose their edge because the production is not the bottleneck anymore. And the control point moves to whoever owns the production, so the capability to produce software and to produce customized software, and so how the software is built, adapted, and run repeatedly. And this, of course, is an opportunity for a company like Siili, of course. Now, in theory, a client can do that themselves, but in practice, I seriously doubt that they would, simply because being a software factory is not their core business and will not be their core business. And our role in all this is, first of all, to guide our clients through these changes and what value they can create for their own business with AI, and second, to implement those for our clients, including the role of a software production factory. And this is the structural change we are seeing on the market at the moment. Now then, how we see our position in all this. Now, first of all, as said, our role in all this is to guide our clients where AI creates value, and then, second, implement that value for them through AI-native systems. So those are the two kind of games we are playing. So guiding our clients where AI creates value and then implement that through AI-native systems. And then, if I look at us compared to the competition in the market, our competitive advantage is the combination of these two things. So guiding clients when AI creates value and delivering it through an AI-native production system. And this is a unique competence combination in the market at the moment. And we are very good at this. So we are building an AI-native software house, and we are not building AI tools, but the AI-native software house, meaning the whole process in the picture. In practice, this means that we can deliver tailored solutions with industrial efficiency and improve that efficiency over time. The way we improve it is that at the same time, we are building platforms and assets that support us in repeating and scaling the processes and the outcomes that we deliver to our client. The whole thing that, yes, there are bits and pieces that can be copied, but the whole thing is a difficult thing to copy, and that creates a unique position for us in the market. Also, that scales beyond the Finnish market. The platforms and assets are something that we build on top of those, and then based on those, we can create services which we can then also take outside from Finland. A very practical example of that is the AOS, or the AIPO operating system, which we have delivered now to a few clients, and we are getting more traction to that. That's a good example of this thing or phenomenon. Now next, let's look at what all this meant last year and how all this is visible or was visible last year. 2025 was a year for us to build or building our position in the market and as well building the capabilities. It was not yet a year for financial scale for us. On the capability side, we moved from AI being an add-on to AI as a built-in capability on how we operate through all the functions within the company, not just the software development but all the other functions within the company. From the customer perspective, we moved from experiments into production-ready delivery. So earlier, it was typically the proof of concepts, and now we have seen in the market not many cases yet, but some production delivery cases. I would assume and see that that's something that will scale, and we will see more and more of those coming in this year. Our whole work is now organized around this through what we call growth engines. So the AI-powered development being the one and then the AI advisory the second. The AI-powered development is the AI-native delivery, and the AI advisory is, of course, the way how we guide our clients, how they can create value with AI. Also, one important capability point is that the AI capability is no longer dependent on a few individuals. It's now embedded in the processes and how we operate and how the market sees us. A few proof points. So we have now delivered roughly 40+ AI solutions to our clients. More than 80% of our consultants are AI-native, and we have a very high hit rate whenever we reach out to new clients, and the hit rate is because of the reputation we have on the market, that we really know this AI in and out. Now then, 2025 in numbers. Now first, the second half, so on the second half, we made roughly EUR 50 million revenue. That was a slight drop from the previous year. And then EBITDA was EUR 1.5 million, and the share of international revenue was roughly 30%. And the same in kind of full-year numbers. So revenue was EUR 108 million, EBITDA roughly 4%, and 28% of international revenue. On the revenue side, maybe one point is not on the slide, but that although our revenue dropped 3% on an annual basis, still our revenue per employee actually increased 5% per employee. This reflects the change in our business logic and indicates that we start to scale better than linear. Traditionally, this business has been very much hourly based, and now this increase of revenue per employee is reflecting the change in that. Next, I will hand over to Tuomas, and he will go into more details on the numbers. Thank you, Tomi. Hello everybody. My name is Tuomas Toropainen, and I'm the new Group CFO of Siili. I started in the role of CFO back in September 2025, and I have a strong background in the technology sector from companies such as Nordcloud, IBM, Fjord, and Accenture, to name a few. Now let's take a look at the second half and fourth quarter 2025 results. We can hit it off by looking at our top-line revenue performance. So our revenue growth was still impacted by the challenging market conditions, like Tomi mentioned in his slides, in the second half of 2025. So in the table above, we have the second half result compared against the same period from 2024, and in the table below, we have the fourth quarter result compared against the same period from 2024. So in the second half, we were 4.1% down compared to the second half, and in Q4, we were 6.8% down compared to the second half of 2024. So the difference between the total and the organic results can be explained by the Integrations Group acquisition, in case you were wondering. The revenue decline, however, has stabilized, and our 2026 growth ambitions remain fully intact despite those challenging market conditions across the industry. If we then move on to the international revenue share, it has remained steady at around 30% level during 2025. We generated EUR 15 million in the first half, and we generated EUR 15 million in the second half. The trend remains stable. However, if we compare against H2 2024, we are still 5.7% down. Moving on to profitability. In the table above, you can see our adjusted EBITDA margin in H2 2025 compared against H2 2024, which is 0.5 percentage points down at 3.1% compared against the second half of 2024. In the table below, you can see our adjusted EBITDA margin in Q4 2025 compared against Q4 2024, which is also 0.5 percentage points down at 3.7% compared against Q4 2024. So during 2025, actions were taken to improve profitability, and we expect those results of these actions to start showing in full during 2026 while our profitability remains highly sensitive to top-line performance. So if we then look at our capacity and headcount in 2025, so at the year-end, our capacity was 978 employees, out of which 115 are contractors, subcontractors representing the subcontractor pool. So the total capacity in H2 has been reduced to align with current demand. And going forward, our focus remains fully in improving our operational efficiency while maintaining the recruitment activity in our core competence areas like data and AI. So approximately 80% of our consultants are already today capable of leveraging AI solutions in client engagements. Then if we look at our balance sheet and cash position. So despite the profitability challenges, our balance sheet remains strong, and it's supported by low net debt and a healthy equity ratio of approximately 53%. So liquidity remained at a healthy level despite the profitability challenges. And based on the solid balance sheet position, the board is proposing a dividend of EUR 0.07 per share, which is in line with the company's dividend policy. Thank you very much. I'll hand it over back to Tomi. Right. Thank you, Tuomas. And next, if we look a bit on the 2026 priorities. And that is very simple. So looking ahead to 2026, we have two clear priorities. First is scaling up the AI-native growth. So we will focus on the defined growth pockets and replicate the delivery through platforms and assets. And where appropriate, we will continue moving pricing gradually from hours toward outcomes. Our second priority is to improve profitability. And improving profitability comes from scalability and repeatability. And profitability improvement is very much linked to the AI-native scale. So it's, of course, not a separate initiative for us. And a concrete proof point that we are on the right track is our revenue per employee that has increased, as explained earlier. And in the end, that yes, although we are talking about profitability, that in the end is about revenue growth. And that is the key thing for us, is to get back, I mean, on the net revenue growth track. That, yes, the data and AI is growing, but we have challenges in the, let's say, the more traditional part of the software development business, and therefore the net impact is still negative, I mean, on the revenue side. As long as when we get the net growth back to positive again, then that will reflect—no, I guess it's dangerous to say automatically—the profitability, but it's certain that yes, it will impact the profitability as well and positively. Just to keep in mind that the digital transformation is a long-term trend, and the AI, of course, as a part of that. The market cycles are temporary, so our focus is building a company that benefits structurally from this shift over time. Now then, guidance for 2026. So our long-term financial targets remain unchanged, so we have not changed those. Our guidance range depends on, so first, the guidance for this year on revenue side: EUR 102 million-EUR 126 million. That is dependent on two things. One, the uncertainty of the market in the Finnish market and overall economies. Of course, there are, let's say, news every day that makes changes in the market conditions, and that is difficult to forecast, and we have taken that into account. Then, on the other hand, as discussed earlier in this session, we have seen already that our strategy is clearly the right one, and we have also taken the efficiency measures that are now paying off. We believe that this year we will see the AI adoption speed at scale, and our competitive advantages and the capabilities that we have built give us a competitive advantage and put us in a good position in the market, and that we strongly believe in. Thank you. That was all we had. Then questions, comments. We have some online already at this point. Why don't I read these out loud, maybe starting from this one? So how large a share of your billable hours revenue is coming from actual code creation, the task where AI brings the largest productivity gains, and how much the price point in pure code creation or engineering has declined since the peak seen in 2022-2023? [Foreign lanaguage]. I guess that it's difficult to answer that in very specific terms, sure. No, let's say that. No, first of all, there are two things. One is the software development, and that is under, let's say, a transformation in the market. So from the, let's say, traditional coding to AI-powered coding, or writing the software AI-powered. So that's one thing. And then completely another thing is the data and AI as a kind of domain. And the AI will bring efficiency gains on the process, not just coding, but the whole process. So that's very obvious. But then, as we discussed or tried to explain in the beginning, that the other part of the equation is the business models or the pricing models, maybe, to be more exact. And it's not—I mean, the further this transformation goes, then the less relevant the hourly rates will be. And because, simply, it's not a relevant way to measure it or use it as a basis for pricing. Therefore, it's not that simple that we can say that, "Hey, the price point per kind of coding is this and that," because it's simply not the way to look at it. Sorry, not a very clear answer, but that's how I see it. I think this one was also answered pretty much, but reading it out loud. How are you reacting for the AI-driven disruption in hourly-based pricing? [Foreign language]. No, I guess I pretty much explained our view on that just so. And that's not just in our industry. It impacts every single industry where the hourly-based pricing has been the model for a long time, and that is now in a disruption. And it's—I mean, I strongly believe that what I call the kind of software production factory, that it's something that I really don't believe that the clients are willing to take that role and that the clients are willing to invest and capable of investing that. And therefore, it means that our role will be in the future also to act as a software production factory for our clients. And then when we invest on it and it's our business, then, of course, we need to get money from it in some form. And that some form is still kind of finding its way, what the form will be in the longer run. To me, it, let's say, looks quite clear that it will not be hourly-based in the long run, that yes, in the short run, it still is the case. And in many cases, because the clients are, that's the way how clients, I mean, that you have a five-year contract with the public organization, and the whole way how they buy is based on that. And that will be under kind of discussion in the next coming months and years, how that will change. Okay. Then there's a question about demand. Could you give some color how the AI-related demand has developed since your AI-focused strategy launch? [Foreign language]. No, the demand, of course, is increasing. I guess that's pretty obvious that whatever news you read, it's all about AI nowadays. And that wasn't the case, by the way, when that, yes, of course, there was talk about that when we launched the strategy, but now it starts to be a mainstream thing. And then the big question is that, because as in any kind of new thing, first you try with these proof of concepts and all that kind of things. And then the main question is from companies like us's perspective, that when it really scales. And yes, we estimated that it would have done that already earlier, which it didn't, but it doesn't mean that the direction is very clearly that way. And then it's more a question of timing, that when we will see more of these bigger-scale programs. And now, currently, we have seen some, but it is not mainstream yet, but it will be. It's like if you look at any technological, I mean, internet, mobile, cloud, that yes, it takes time that organizations adapt themselves. But I mean, all the companies and all the organizations are now in the cloud. All the organizations, obviously, are using mobile. It's not a debate that, "Hey, are we using it?" It's exactly the same thing, that it's not a debate that does an organization start to use an AI, that yes, of course, it will. It's just a matter of time and speed. That's the big question for us in terms of how fast it will show in our numbers. There's a more specific question about the advisory business and whether it's bringing in money yet at this point, or is it more like a spearhead model helping win new clients? Yes, it's more, I mean, if we are talking about purely the AI advisory, that yes, that's a spearhead, and it will be a spearhead. So maybe a few things there, that, what we use the term AI advisory, that is a small team, and that is clearly the kind of entry point where we get, it's like the, if you think about the, I mean, a long time ago, design had a similar role, that design was the way to enter the client, and then the software development was the bigger part of the project. Then the digital strategy at some point had a similar role, and now the AI advisory is exactly in the same role. So we enter the client with that, and then it will scale up, not in the advisory, but it will scale up in the other parts of the process. So in practice, meaning that implementing the AI-native delivery and the different types of solutions. And it will not replace the, so I believe that it will have this spearhead role also in the future. Then there's a more specific question about the Finnish revenue in Q4 and whether it's because of a single customer, certain client group, or certain competence, the decline, in more detail, which. [Foreign language]. No, I would say that it's more, I mean, if you look at the companies of our size, and we are in, no, not purely in the project business, but let's say project-related business. And therefore, simply, if you lose one case, it has an impact. And another thing that on these, let's say, uncertain times, that when the year-end gets closer, then the clients, and that purely depends on how the market outlook is. So if the market outlook is uncertain for a client's own business, then they simply make budget cuts for the end of the year to reduce their cost base in a short term, and then they get back on that development on January or February. And that's—I mean, nothing to do with AI as such. It's normal client behavior in an uncertain environment, and that has always been the case. And that realized on the last quarter last year for us, and that explains the—so I wouldn't say that it's any particular competence. It's more, let's say, particular clients with a different reasoning for each of the cases. And of course, cannot open here the cases, but anyway, that's the explanation. Then we have a question about, have you seen the relevance of careful and high-quality defining and design, the wanted outcomes increasing? Sorry. Have you seen the relevance? Sorry. I'm sorry. Is that about design, or? Okay. Sorry, Jaakko. Yeah, maybe we come back to that. Don't understand the question. Yeah. Okay. Sorry. Maybe we come back to that because I'm not sure about the question. Anyway, so moving to the next one. You described while the ongoing and upcoming disruption, how long you think it takes before Siili can turn this to growing overall business? So a market-related question. Yes. And that is, of course, a fair and excellent question. And yeah, and very difficult question to answer because it depends on so many things. Like I said, that I have no doubts of the direction. I mean, the strategy, I strongly believe that we have a right strategy. The execution speed, yes, we can speed that up. I mean, the capabilities, etc. And then the kind of another element of this equation is the client demand and how fast they are willing to scale these proof of concepts to real programs. And as I said, we saw that already last year. I mean, now that movement is moving, but it's not moving as a snowball yet. But no, I guess, like I said, that I really cannot see any other future than that it will, and it's only a matter of how fast. And how fast, yes, I understand that that's exactly your question. And answering that is, of course, a difficult thing. What we can do and how we see it, that we are building the capabilities, we are building the reputation on the market, and clearly those are now in place. And then one by one, the market starts to, I mean, that the client, A, did now something, then it's a small market, and then the other clients and CIOs will hear from that company that, "Hey, we have now done this, and we have done it with Siili," and then the next one comes in. And yes. And no, actually, maybe if I take one very concrete example is the modernization of legacy systems. That's a kind of eternal question in the role of CIO in any big company, and it has been that forever. And there the AI actually makes significant, I mean, significant difference on that it's now realistic to do. That is actually an excellent example of that when companies start to do those, then that automatically brings the scale because if and when you start to convert your legacy software base to more modern, and the AI is the tool to do it, and you simply didn't have that tool available before AI, and then those are big and huge projects. And now that is clearly something, it's a new phenomenon on the market that we do not have references yet, but we have a number of discussions with our clients, and that's, again, one concrete example of that yes, this thing will scale up, and it's a matter of time and how fast. But no, a long answer without the exact answer, but sorry, we don't have a kind of that, "Hey, it will happen on the second quarter," or whatever. But step by step, it will happen. Appears to be the last question in the Q&A. All right. Thank you. And by the way, excellent questions. And now we are truly talking about the real—I mean, this is—I mean, the AI and the transformation to AI in a global scale and in all the functions, in all the—this truly is a major thing, and it's a bigger thing that any of us have seen in our working lives. And now I'm very happy that we are now talking about that, not any, let's say, irrelevant topics. But no, anyway, nice to have you here today, and thank you for this session. Thank you very much.