Nightingale Health Oyj (NHLTY) Earnings Call Transcript & Summary

Good afternoon, and welcome to Nightingale webcast for the full-year results. So today, our agenda is that I will start by talking about our technology and products. Then we move to the business targets of the past fiscal year. Then we will have a look at the key achievements. Then we have financial review. And then Tuukka Paavola, our CFO, will join me on stage for that part. Then we have business targets for the ongoing fiscal year. Then we have the financial calendar and AGM. Then I will be talking about some significant events after the end of the period. And then in the end, we have Q&A. Our Chief Operating Officer, Janna Ranta, will join us on stage for the Q&A. Please post your questions. My name is Teemu Suna. I'm CEO and Founder of Nightingale Health. So let's start. So why Nightingale exists? We exist to build better health care for everyone. And now when I say everyone, I mean everyone. I mean citizens, I mean health care professionals, I mean institutions, I mean taxpayers, I mean everyone. And this is all about solving health care's biggest challenge. So why do we need to solve health care challenges? Well, if you look at health care, the big picture, the cost of health care are up to 18% of gross domestic product. And to give a bit of context, this is around 4x more than military spending. And this applies the top line percentage is different in different countries, but the ratio is pretty much the same. It's also not only about money. So the way how health care is organized today also causes suffering. So we live longer than ever, yet we are sicker than ever. So if you look at this in a bit more detail, 75% of all deaths globally are caused by preventable chronic diseases. The chronic diseases, they cost tens of trillions of dollars globally. And then if we look to the future, it's not getting better. So in 2030, it's been estimated that the total cost will rise to $47 trillion. So when I'm talking about that health care has a big problem, the problem is massive. So why do we have this problem? Well, the current health care logic, there are 2 key elements that are very challenging. So health care is not health care. It's actually sick care. Health care system today is specialized in treating the sick, which is, of course, very important, but it's not trying to prevent the disease progression. It's kind of a system that was people to get sick and then tries to solve the problem. Then another major challenge is that in health care, there is a huge conflict of interest. This conflict of interest is that the more there is sickness, the more there is money. And this applies to public sector. So public sector will need to allocate more money, the more there are sick people. This also applies, of course, in private sector. So the more there are sick people, the more there is business. So the current health care logic is broken. So how do we fix it? The only way that I think is very well acknowledged, the only way to fix it is by preventing diseases at scale because the problem is so huge that the only way to change the game is to have less sick people. How can you have less sick people, you need to be able to prevent the disease progression, and you need to be able to do it at scale. So let's simplify what this means, what prevention means. So here, we have a very simple graph describing that when people get older, there are more sick people in the population. When we prevent diseases, when we have a systemic prevention for diseases, we move the line. So what this means is that the disease progression is slower because of that, we have less sick people. When we have less sick people, we have lower costs and less suffering. So I feel many times when talking about health care around the world, the issues are many times, people feel that they are like extremely complicated. I think it's not complicated, but it's about the focus to the right thing. This is what we need to solve. We need to change the logic in health care to be more preventable, to have less sick people. This is a real solution. This is actually changing the key challenges in health care. So let's have a look like -- so I say that health care -- the logic of health care is broken. So let's have a look how the logic actually should work. And now the important point is that this will not get solved by an amazing lifestyle improvement app. That is also needed, but this problem is not solved with an app. It's a kind of a single-point solution. This will not get solved by advantages in genomics or any other like next-generation omics technology. We need them, but this is not a solution. This is a systemic problem. It needs a systemic solution. And this is something that is many times not understood properly. So you need to be able to build a complete feedback loop that encourages the system or incentivizes the system, the healthcare system to reduce the risks in population level. So it all starts by introducing a good, scalable, reliable, repeatable way to detect risks in the population. So this is not health care that is targeted for the sick. This is health care that is targeted for everyone because in order to do prevention, you need to find from the population, the ones who have high risks, and they are mostly healthy. So you need a risk detection technology that scales to the entire population without burdening the health care system. This is extremely difficult specification for the technology. But once you have that, you can detect the risks in the population level in a repeatable and objective way. I will come back to this objective way later in the presentation. Then once you find the ones who are at risk, you do the preventative actions in a targeted manner to the ones who actually need them. Here, the key thing is that it's not enough just to detect the risk. You need to be able to also communicate the risk to people who are at high risk to motivate them to change the behaviors or adhere with their medications. So you need a tool that you can actually motivate the individuals at high risk to make the change. So you need first the detection in a population scale, then you need a tool to motivate people to the preventative actions. And then once you have applied the interventions, you need to be able to track how well these interventions have worked. How do you do this? Well, you need to have a technology that can detect the risk again in a repeatable, objective manner. So first, you detect the risk, then you apply the interventions to the people at high risk, and then you measure again. And then you track the change in the risk level. If the risk goes down, it means that the intervention -- the applied intervention had good efficacy. Now in order to do this, the risk detection method needs to be very repeatable and very objective. And just to give an example, the current tools in health care cannot do this because they many times are based on questionnaires or subjective clinical measurements such as blood pressure. It depends who takes the blood pressure. It depends on the situation when it's taken. It depends if the person is nervous in the situation or not nervous or there is a lot of -- I'm not saying that blood pressure is not a good thing to measure. It is a good thing to measure. But to build a preventative health care system, it does not work very well because it's not repeatable. So you need something that can actually repeat the risk assessment in an objective way again to understand what is the efficacy of the preventative actions. When you have these 3 things, then this starts to work. But you need all the 3. And then what you do when you have this, you build a funding mechanism that actually gives money for risk-reducing interventions. This is how we change. This is how we can change health care to get better results. This is how we can reduce the costs. This is how we can reduce the suffering, but it needs to be built in a systemic level to make it work, and it needs to be like a full end-to-end solution. So I mentioned that the current tools in health care have limitations. Let's talk about a bit more detail about the risk detection. So the risk detection is already being done. Every health care system does this. So they try to figure out the risk for people and then take some actions based on the risk. So the current clinical standards are these clinical risk calculators. So we have the Framingham score. We have SCORE , we have QRISK. We have different methods for cardiovascular disease. We have a FID risk for type 2 diabetes. So we have these calculators. They do the risk detection pretty well, but they are very manual. They need a lot of questionnaires. They need clinical measurements such as blood pressure, BMI, et cetera. So they need healthcare professionals' time. They -- because of the subjectivity of the data, I said that the risk detection is good, but there is a clear compromise because of the subjectivity of the data. Then we have -- everybody talks about AI. So I think I also need to talk about AI. We have different AI risk models. The benefit of AI is that they can be very, very automated. But the reliability, now I encourage everyone to think back of the feedback loop that I described. If you put an AI model and you try to track the difference in risk before and after the intervention. The data consistency in health care is just not good enough. And the AI model is as good as the data that is used for the input. So this is not feasible solution to do it in a systemic level. But they are good tools, the AI tools, very good tools when used in the right place. So this is what we do very well. This is where we are the best in the world. So we can do the risk detection with high reliability, high repeatability and in a very automated fashion. We don't use the subjective data. We have no questionnaires. We have no subjective clinical measurements. We use molecular medicine to detect the risks for multiple chronic disease risks at the same time. Because we only use blood, we don't need healthcare professionals' time. I mean risk detection, it's just get one blood sample, and that's it. And because of this, it can be super automated. And because of this, it has very high repeatability. And because of this, the Nightingale technology can actually be the foundation of a preventative health care system. So I want to talk a bit about -- so how do we do this and take this in a bit more detailed level. So as I said, only a single blood sample is needed. Why this is important? I mean there are many like exciting things from the technological point of view, like how can we do it? And I think it's -- I also think it's very exciting. But the real reason why this is interesting is that this enables not to use health care professionals' time for the risk detection because blood, you can get blood samples in a very high throughput with a very, very low cost level. So I think that's the exciting part. So it means that you can take it to national level. You can offer this technology to everyone. And it's not only that the technology allows it, we also have a price point that allows it. You can run this for everyone. And when you do it for everyone, you are actually then moving the health care system towards preventative health care. So what do you get when you run this single -- when we run this single blood sample. So you get -- here we have our clinical report. So our clinical report, it does -- routine risk assessment for common chronic diseases. And I will walk through the different parts of the report. And we will zoom in a bit to the specific parts of the report to explain how this technology actually enables the full feedback loop in preventative health care. So let's start from the detection, from the risk detection. So again, one blood sample, Nightingale's technology, and we get routine risk detection for multiple diseases. We have heart attack, stroke, type 2 diabetes, chronic kidney disease, fatty liver disease. Every time from every sample, and we provide the information about the risk in a very visual and easy-to-understand way. This is kind of the clinical summary. And now think about this from the clinical use point of view. So if you would be a clinician using the traditional methods to evaluate risk for heart attack stroke, type 2 diabetes, chronic kidney disease, fatty liver disease. It takes significant amount of your time. You need to be -- do questionnaires, you need to do clinical measurements, you need to do blood testing. So you need a lot of work. We are talking about this takes easily to do all of that. You spend an hour or you spend more than an hour to get it done. And then you have to manually use different calculators to input the data and then evaluate everything separately. It's not feasible. Nobody does it. Would it be important to do? Oh, yes, this is the way how we -- if we want to bring it a preventative health care system, you definitely want to do this. I think everyone agrees that you want to detect the risks. Now with Nightingale, it takes 30 seconds from clinician to see the risk situation of a patient. 30 seconds, I think it's quite cool. And then what you can do it kind of in addition for kind of supporting the clinician, you can use this to steer the whole health care system. So for example, if you have people who have all red balloons, so every disease is with high risk, you can automatically steer that person to a treatment workflow that is specialized to that situation. You can split automatically the risks depending if there is a person with a risk for type 2 diabetes, you can also put the person to a specialist who is specialized in that disease. So you can do disease-specific automatic steering of people to the right experts. Automation is a key word here because now when I'm talking about like building a preventative health care system, it has to be automated. But with this, you can automate it. And again, you can do it because the data is objective data. It doesn't have subjectivity bias. Blood doesn't know the molecules in the blood doesn't know, they cannot answer wrong to a questionnaire because you don't -- it's just -- it's the molecules. So it's objective. Okay. So we detect the risk, and then we provide for each of these diseases a more detailed page that describes the risk. And now this page is the tool for the clinician and the patient to make sure that the clinician can communicate the risk situation to the patient very clearly. So this is the motivation part. And I will walk you through and pretend to be a clinician to explain the report base. So dear patient, your current risk for heart attack in this case is 18%. So I know that 18% is not maybe very easy to understand. But if you look at the number below 18%, you see a number 6%, which is the average risk for men at 60. So the patient here is also male, 60 years old. Now you see that the average risk is 6%, and you have 18%. So it means that your risk is very high because your risk is actually 3x higher than average. And now it's very important that we take actions to reduce your risk because if we don't do anything, in 15 years, if you read the graph towards the right corner, you see that at 75 years old, your risk is 49%. Every other person will have a heart attack. And then below the 49%, you'll see the average risk, which is 17%. So one big problem in this risk detection is, is how to communicate the risk in an understandable way because this is the clinical way of showing the risk, which is using percentages, et cetera. But with this approach, it's much easier to understand the risk situation than any of the calculators currently used. You can go and have a look at the calculators. They are many of them publicly available. So this communicates the risk situation in a way that it's easier to understand for the patient. And with this, it motivates to either adhere with the medication or to the lifestyle changes or both. Okay. Now we do the prevention. We have a tool for -- to do the prevention. We help the clinicians to do it efficiently, quickly, explain the situation to the patient. Now if we follow, so if you think about the feedback loop I was talking about, the first page in the report was detection. Now we talk about prevention. And the next part is, of course, to measure the change. So after the clinician prescribes the intervention for the individual, for the patient, the doctor says, come back in 3 months, come back in 6 months. We take another blood sample. We measure the risks again, and we show how the risk has changed. And now there are many use cases for this. One is there is globally a rather significant problem with the medication adherence, so people not taking their prescribed medications. One reason is that when you take the medication, you don't feel anything. With this, we can show how the actual risk situation changes and everything reflects back to all of the reports. So it's a tool to track the efficacy of the interventions. It's very important, of course, for the patient and the clinician, but let's take a bit of a bigger picture. This is important for the healthcare service provider. Health care today does not understand very well what is the performance of the healthcare system. Why? Because there are no tools that you can actually repeat the measurement and track the progress. And again, we can do it because we don't have in our data, it's objective data. We can repeat the measurement in a reliable way. So then the health care provider can compare different intervention pathways and figure out which out of those are actually working well. For example, someone says we have an amazing lifestyle improvement app. These diseases we are looking at, they are all lifestyle diseases. 80% of the risk is defined by lifestyle in these diseases. So how does the health care provider know if the app is actually working? Well, the traditional way to do this is that you send questionnaires to the app users and you ask how happy they are. So you use a lot of subjective data to evaluate the performance, which is, I think it's fine to do. But this is a different level, what I'm talking about here. This looks from the molecules if the risk to develop the outcomes for the diseases has actually changed. And now let's take a bit of a bigger picture here. Let's take a nation. So now if you aggregate the data of the individual follow-up measurements, you can actually start tracking the entire health care system. So if a country makes a change in health policy introduces a sugar tax, so you make sugar-based products more expensive for people to buy. How do you know if that health policy change is working? You wait 15 years. With this, if you run this in your -- as a part of your routine health care risk assessment, you see the indication in a year or 2 because you all the time repeat the testing and you can connect the change in the risk, you can connect that back to the changes that the government does, the health care provider does or the individual clinician does. This is the ability to track the performance of health care. This is a novel thing. I'm not aware of any other tool that you can do it in a reliable way. So to build a preventative health care system, we need a systemic solution to do it. We need to be able to detect the risks at scale. We need to be able to prevent the diseases in a targeted manner. We need to be able to measure the change in risk, and then we can connect the funding mechanisms to encourage to the risk-lowering actions. This is what Nightingale does. This is why we exist. This is -- I believe this technology will change how health care is done worldwide because this just makes more sense. And everything starts from a single blood sample. This is what I mean when I'm saying we are building better health care for everyone. All right. So we will move to the next segment and talk about the business targets of the past fiscal year. We had 3 targets to win large international deals to increase revenue and to improve efficiency. The idea here with these targets is to have a clear commercial focus, so increasing the commercial focus all the time while managing the investment so that we don't overinvest because the situation is that building what I just shared with you, it takes time. It's like a massive change in health care. It can be done, but it's not something that you can just like -- you just implement. It's not kind of a thing you go to a store and buy a new iPhone. It's a bit more complicated to change how the system works. So that's why we are putting a lot of effort to also manage the efficiency to have the kind of the flexibility with the runway. Where did we land? So with the first target, we have very successfully built the funnel with exciting new projects in health care. So a lot of negotiations ongoing. A very big win for the past fiscal year was the agreement signed with the public sector in Finland. And this is exactly what I described just earlier, what we want to do in Finland. I think Finland is -- has a very progressive way of thinking about preventative health care and implementing that kind of a full end-to-end solution. I think we are now taking the first and very strong steps in that area in national public health care scope. Increasing revenue, we managed to increase the revenue by 7.7%. Our revenue increase, I think it was a rather good achievement given how much things we are still building and how many things we are ramping up. And then because the U.S. market, a lot of uncertainty in the U.S. market, it had a significant effect to our revenue in last financial year. And then the efficiency, the EBITDA decreased by around 15%. We need to invest to move things forward. It's very important to acknowledge that Nightingale is a truly global company. So we run our operations in Japan, Singapore, U.K., Finland, U.S. So it's quite a lot to manage. And I think the team is working with these different global locations with extremely good efficiency. But of course, it requires some investments. I want to highlight a couple of things that took place in the past fiscal year. Here, we have the global locations. I will be giving like short descriptions from Finland, Singapore and the U.S. In Finland, the win with the public health care for the first time, I think it's very significant. This is a very, very -- this has been a very long-term ambition for Nightingale. And it takes approximately 10 years to get something -- to get a new technology in primary care and public health care. It's extremely complicated. It requires a massive amount of validation and evidence to get there. So because of that, this is a huge milestone for us. And I strongly believe that this is the direction that every health care system in the world are going to. What other options are there than going to preventative health care. What other options? Just keep on increasing the costs. I think it's not possible. It not only cost, but also suffering. I think there is very -- it's very clear that something needs to be done. And this initiative in Finland, I think it's globally leading the way how we can build better primary health care system. In Singapore, we have also made very strong progress. I think it's a very strong indication for our global mission that we can complete the very strict regulatory requirements. Singapore has a very strict, very, very demanding baseline for health care. And we have passed all of the required steps in there. And now we are building up the commercial part of the business, but it needs to be done in an iterative way. So again, this is not something that you have one product and then you go like you go all over the world and you say, okay, get this, start implementing, get this. Health care does not work like that. So you have to go to the -- you have to build up the regulation, you have to build up the capability to deliver the product. Then you need to start building it with your KOLs, your first customers, ensuring that the products you are offering has, for example, the right tone of voice. Clinicians, the way -- the problem is same everywhere, but the way how clinicians work, it's different in different countries. And it needs an iterative process to adapt into that, and then you can scale it, scale it out. But in Singapore, we are getting now very close to the moment when the -- also the commercial scale-up will take place. In the United States, we have -- we opened a new laboratory in Long Island City, New York. And now it's open for research -- medical research customers, but there have been some uncertainties in the U.S. market about the funding with the research institutions that have had an impact also to us. But I think the most important thing is that we are building the local capability there. It's -- there are several complexities around it that are kind of outside of Nightingale, but I think we are making very good progress also to navigate in the environment and because we have strong customer case, very strong names in the U.S. already, I'm expecting that this fiscal year, we can make very strong progress also in the U.S. So step-by-step, getting also to a much stronger position in the U.S. Then in the spring, we moved from the First North list to the main list in Nasdaq Helsinki. At the same time, we also implemented an ADR mechanism and made the stock available in OTCQX market in the U.S. This is part of the strategy that we are a global company, and we also need to take different steps to also connect with the international capital markets better and better. So that with the OTCQX, that was the first step in that journey. And of course, that is connected to our project in setting up the new laboratory in the U.S. So these things goes hand in hand. All right. So that was the review of the milestones in the previous fiscal year. Now it's time to look at the numbers. So Tuukka, welcome on stage. Tuukka will talk to you about the numbers of the past fiscal year.

Thank you, Teemu. Great to be here again, and good afternoon, everybody, watching the stream. So let's -- without further ado, let's jump into the exciting world of numbers. Let's start from the funding side of things. So our liquid funds, i.e., cash and current investments, was at EUR 51 million at the end of June, i.e., at the end of the financial year. The change in liquid funds was roughly EUR 15 million, which is actually about the same as in the previous financial year, which I think underlines the financial prudency with which we have been executing our global growth strategy since the EUR 15 million includes, for instance, certain CapEx investments we have done in setting up laboratories. Now that we have the laboratory setup basically up and running, like Teemu mentioned, 5 laboratories in 5 countries, basically capturing all the key geographies in the world. We can actually now focus on increasing our revenue and focusing on the sales side of things without much pressure to actually increase our operational expenses, which then means that all the sales growth we get, much of that will actually flow to the bottom line, i.e., improve our profitability. So entering this ongoing financial year, we have a really strong financial position with the EUR 51 million of liquid funds, giving us with multiple years of runway to actually do what Teemu just fantastically described to actually change the health care system in the world for the better. On the revenue side of things, the full-year revenue was plus 8% year-over-year. And the second half revenue was actually quite nicely in line with the first half. So rather stable 2 halves. The good thing is that we -- the health care revenue side of things is becoming or growing more and more. We get it currently from Finland, Japan and Singapore. And that is more stable in nature, which then balancing the more volatile research business like we know during the last fiscal, so in the U.S. There are things that are happening in the environment that we can't actually have an influence on. If we look at our sales pipeline, it's really strong. And also the current -- a couple of cases we just announced after the financial year ended are contributing to the strong sales pipeline. So we expect that we are able to reach the financial year target of at least 50% growth in revenue. Wrapping up the financial year. So the revenue landed at EUR 4.7 million roughly, which was this plus 8% year-over-year growth. The profitability was slightly lower, mostly due to the investments in the international expansion. But also there were some one-off expenses such as the cost from the main list transfer in Nasdaq Helsinki. We continued financial efficiency. So the change in liquid funds and also the change in net cash was in line with the previous financial year. And we have a really solid, strong financial position with multiple years of runway remaining. And basically, we don't have any debt. So that's also a possibility to -- a possible lever in the future if need be. Then the business targets for this ongoing financial year. Here, short is sweet. We have one target, increase our revenue by at least 50% compared to the previous financial year, which means we will be truly focusing on sales, continuing our growth, continuing our commercial efforts. So that's where we will be focusing really much this financial year. Then the midterm and the long-term targets actually remain the same. Furthermore, continue our global growth, become profitable in terms of EBITDA first and then, of course, down the line also like net profit-wise to actually reach our long-term targets of generating EUR 500 million in revenue. Finally, a few words about the financial calendar. So we will publish our annual report from the financial year that ended on the 30th of June '25 during the week 40, so in a few weeks. There will be AGM on the 6th of November. And then the half-year report will be published on the 5th of March '26. And like usual, all the reports are available from our company's website. So those were the truly amazing numbers. And then a few words from Teemu regarding some great news that have just recently happened.

Thank you, Tuukka. So we announced that we've been selected as a multiomics provider for EUR 2.4 million research project. I wanted to provide a bit of more color into this and answer the questions of why Nightingale? So the competitive advantage that we have in the research market when it comes to these like multi-omics offerings is that our technology, when we measure the sample and provide the Nightingale data, it's nondestructive for the sample. So we measure the sample, it comes out from the machine kind of undestroyed. You can still use the same sample to run some other assays. For example, in this case, proteomics. Now this maybe doesn't sound so special for the ones who are not familiar with the medical research. But if we put it this way, when the research projects, when they start to recruit volunteers to provide their blood samples and then they put the blood samples to freezer and then they keep them in the freezer for like 10 years, 20 years, et cetera, the amount of blood in the freezer is usually very little. But everybody understands that you cannot -- if you have a volunteer for your project and you say, well, I want to take a bucket of blood, you don't get a lot of volunteers for that kind of approach. So you usually try to take as little blood as possible to get a lot of people into your cohort. So this makes the blood in the freezer extremely valuable, calculate the cost of getting the sample, calculate the cost over 10 years to collect all the follow-up data and everything. It's massively expensive. And now most of the technologies and methods used to analyze the blood, they actually destroy the sample when they analyze the sample. So you cannot use it to anything else. Our technology, it does not destroy the sample. It provides very interesting data because this data also in research is kind of a link to the healthcare use. So you have actually a bridge that you can use to translate the findings to health care use because Nightingale's technology, the only omics technology in the world that is actually already implemented in large-scale primary care applications. So you get that data. And then you also get proteomics data in this case from the same sample. And because we are the only one who can offer this kind of a package, we believe that we have very strong market position. Why this happens now? This -- some of the new omics technologies such as proteomics is now increasing all the time. So this is a very new thing. This is kind of a state-of-the-art in medical research, and we have a very strong position to support and help scientific projects around the world to get very strong data sets from a single sample kind of preserving as much sample material as possible. And because we provide it also from one kind of -- from one company, we can also -- regarding the price point, we can be rather competitive. So it's a big opening around multi-omics, and we believe we are in a strong position also when moving forward in this segment as well. All right. Now let's move to the last part. So we have Q&A. So Janna, welcome on stage. Let's have a look at what kind of questions we have today.

Yes. Good afternoon, viewers online, and good afternoon, Teemu and Tuukka. It's good to be back here. You talked for so long. So let's jump right into the questions. But thank you. It was very exciting to hear about the previous fiscal year and also a very exciting start for this fiscal year. So let's start with a question that Teemu, could you summarize last fiscal year? What were the main accomplishments and what could have gone better?

Yes. So I think last -- past fiscal year, there was still a lot of -- we put a lot more commercial focus in everything we do. But then when looking at like ramping up a new lab in New York, we had in Singapore, a lot of -- we work a lot with regulation. So there's been a lot of this kind of commercial activities that has a very strong development angle. We also build up the kind of a new way of communicating the results. So we need to do a lot of development. But I think the very nice thing is that this commercial focus, everything is now connected very clearly to commercial projects. Whereas earlier, it was more we needed to do like R&D, just you need to do R&D. So this -- I think it was a very strong transformation towards the commercial operations, and it has created a very solid foundation for the fiscal year to put more and more effort to ramp up the commercial side of things.

Okay. What could have gone better? Do you have any comments on that? What you will improve this fiscal year?

Yes. So what we will improve is that we have done a lot of like when we are coming from a company that has a lot of focus in science and R&D and development, the iteration cycle in those things, it's longer than it is with the more commercial projects. So we are in this transformation to have like more shorter iterations and more speed. So of course, I always think that more speed would be good. So that's something we could have done even better. But then on the other hand, I'm thinking like now when we have managed to do it over the past months, and we have got a lot more speed, maybe it was a necessary learning process, but now thinking like looking behind, maybe that could have gone better.

Okay. Thank you. So then a question about revenue, Tuukka, for you. Revenue stayed on the same track with a small improvement, but with a lower profitability. Can you explain what caused this?

Yes, sure. So of course, if we talk about profitability, you have 2 sides. On the one hand, you have the revenue and then the other side is the costs, which then translates into profitability. I think on the cost side, we executed our plan. We set up the laboratories. Of course, there are some costs involved. We are increasing our lab footprint, so that is also increasing our operational expenses. But all that was basically in line with the plan. So no surprises there. Then on the revenue side, I think, again, 2 factors affecting that. One is the -- in a way, the long sales cycles that we have spoken about earlier, also on the research side, but especially on the clinical side. So it takes a long time to get from start of negotiations to starting a pilot to actually getting revenue. And again, since fiscal year ends on a certain date, that's in a way hard stop. And then like now was it 1 week after our end of fiscal year, we got this [ Moisony ] deal. So had that happened the month before, things would have looked quite different. So it's always timing is unexpected. And then the other thing on the revenue is what has now happened in the U.S. So it is the biggest research market in the world. And then the new government new regime, they basically kind of shut down all the funding for the project. So that did have an impact on our revenue, unfortunately.

Okay. Thank you. A lot of questions about our partnerships, especially in Singapore and with Pathology Asia and in the U.S. with Boston Heart. Could you give us a status update what's happening there?

Yes. So I maybe open a bit about the kind of the staging of these kind of projects. So first, you establish the partnership, then you build up the technical capability to actually deliver. Then you engage with the KOLs and like a small group of customers because you want to make sure that the product and the kind of small differences. I'm talking about very small differences that really matters. So clinicians, because they are in such a hurry usually when they need to do their job, it's very important that the information is positioned and placed in a way that's very easily -- easy for them to understand. And then once you have done that, then you go to the broader market because if you just shoot to the broader market immediately when you can and you kind of ruin the -- you have something small that is not appropriate. You don't -- you cannot go back like, oh, okay, we do it different. So the learning process needs to be a very -- I think it's quite delicate how to do it. Now with Boston and with Singapore, particularly with Singapore, we are in a situation now that is -- we have been working with a small group of customers, talking with many KOLs. And we are making very good progress now to get the kind of the, let's say, the launch version of the of the report and these small things adjusted. So I believe this fiscal year will be -- we get into the stage where we -- when we start building the full commercial ramp-up.

Okay. Thank you. So let's come back to Finland and South Savo. Can you give a brief overview about the pilot here in Finland with the South Savo well-being service county? And how important is that for Nightingale?

Yes. Well, it's a huge win. And I remember when starting this company, that was one of the things that I said in the -- to the first investors and when talking about Nightingale, what we want to do, saying like, okay, we want to bring this technology to public health care. Now 10 years later, now it's there. And I think we have managed to do many things in an extremely rapid way because many people may think like, well, how can it take so long time? But give it a go. It's quite difficult. But now when we are there, what I was talking about this feedback loop for preventative health care, there are many elements in that project we will actually build in that project. I'm also having many conversations with many governments where we talk about there's usually Treasury and Ministry of Health because it's such a big problem, something needs to be done. And I think Nightingale Solutions, we get very, very strong feedback that this is kind of a -- it's kind of like a building a house. So this is the foundation for your prevention. And then when you can have the risk baseline well understood, then you can add other things. So this is like complementary. You can add your apps, you can add your kind of other kind of tools to the system, but we just have to build the foundation first. Otherwise, the house will collapse.

That's true. So gentlemen, we're running out of time, but would you still like to have a few questions?

Yes.

Yes. So thank you for your patience, viewers online. We are still asking a few. So multi-omics, as you just announced some very exciting news, how has this expansion in your service offering been received by the market? And will there be other cases like the Albori case coming in the near term?

Yes, yes. So I think that's been very well received. And I think the market very much appreciates the ability to preserve sample material. And then because it's like one -- we are like one shop that does it all, it has certain like cost advantages as well that we can give kind of for the benefit of the customer, which makes us very competitive in these different situations. So now this is something that, of course, we've been talking with many customers for a long time. The sales cycle is long. But now I think definitely, this is a new offering that we will bring to our research portfolio. And at least for now, it looks very, very positive, and our position is strong.

That sounds good. I think we will end this question because everyone is always asking about the -- or in this Q&A with a question about revenue and near-term revenue. This is a question for both of you. So how does the near-term growth in terms of revenue look like? And how does the sales funnel look like? And how has it developed during the past fiscal year?

Go ahead, start.

Yes. So maybe kind of just a little bit repeating myself. So I think the sales funnel looks really positive, and it looks positive in many different ways. It's strong in both research and the clinical side, is strong in many geographies. It's strong with different kind of organizations. A lot of interesting discussions are ongoing. And we are confident that the target we set of at least 50% growth in revenue, we believe that it's achievable, definitely. So it's full focus on revenue, full focus on sales. But also, of course, as CFO, I want to emphasize that we don't focus on sales only. Of course, cost side is also truly important. So we will keep kind of financial prudence. We will only do extra investments where necessarily needed. And by that, we, of course, hope kind of also what I said that the increased revenue will actually then start improving our profitability, and we will be having a good pathway towards our midterm target of becoming EBITDA positive.

Great. And Teemu, if you could comment on that where will this revenue come from? Is it mainly research or also from the health care side?

Yes. So I think the research will still continue driving the revenue. This is partly because also with these -- especially big health care projects, the kind of the time it takes to build it up and get it production and get it scaling up. It just takes a long time. So it's still the balance is there. But as Tuukka also said that the health care is building up all the time. So it's getting also stronger in the upside. And I think like if you think about the competitive advantages of Nightingale now this like an end-to-end loop in preventative health care. We know it's difficult to get there. But when we get there, I think no one as we are not aware that there's anyone else who can actually do it. And then it opens for us like a very strong market. And in the meanwhile, also the other offerings, we can take a much stronger position in medical research that we have had before because of the advantages of the technology. So I think in all fronts, we are making very strong progress. The question about the pipeline, the pipeline, if I compare 12 months ago, it's fundamentally different and fundamentally better. So I think all of these activities are kind of providing a very solid outlook at the moment, and we are very confident of the target we have set and continue building the commercial traction in this fiscal year.

Okay. I think this is a great point to end this conversation. Thank you for participating in this Q&A. Do you have any final words for the viewers online before we end this meeting?

Well, no, I think we covered pretty nicely everything here. So it's time to say thank you. Have a nice day, and we will see you in 6 months again.