 Thank you very much. Thank you very much. Hi, everyone. I'm Tomas. I'm the CEO and co-founder of Ksund. And I'm here to tell you about how we're creating the patient interactions of tomorrow. Imagine you're at home on a Sunday night. All of a sudden, you start to experience a headache you've never had before. What do you do? Can you call your doctor? Do you take a pill, try to sleep it out, jump in the car and drive to the next hospital? The fact is more than 50% of patients lack the basic health literacy to make an appropriate decision in such a situation. And what they often do to fill this knowledge gap is they go online and they consult Dr. Google. Now, if you have done this in the past yourself, you probably know that the quality information you typically receive is rather questionable. I've diagnosed myself several times in the past with a deadly disease. Yet I'm still here living and breathing, so apparently it's not the best way to consult regarding your health. So the question is, why would a patient do that? And the answer is the health care system is not much of a help in such a situation. It's not capable to provide a digital front door for the patient to enter the system appropriately from their home, from the couch in the living room. And that leads to numerous problems across the system. So there must be a better way to take the patients by the hand when they're at home starting to getting sick and lead them to the right point of care. And the good news is there is. If we can build fully automated digital patient interactions, we can take patients and connect them to the right point of care at the right time. And this is what we at Sunda Naval Health Care Companies to do. With our patient interactions suite, we enable health care companies to connect patients to the right point of care in the most efficient way. Let me give you a few examples of how this can look like in real life. An insurance company, for instance, can use our technology to move from the end of the patient journey to the beginning of the patient journey and connect patients to the right point of care that are covered by the insurance efficiently. This is what Generali has been doing with the technology of Sunda over the last years. A pharma company can build direct-to-patient channels to assess them, for instance, for comorbidities. This is what we're working on with Rosh for the last few months. And a hospital can build a digital front door so that people are assessed in the waiting room. Their data is collected, structured, and paid into the hospital information system to improve medical outcomes. This is what we're working on, for instance, with the Semmelweis University Hospital. But instead of talking about how this can look like, let me show it in action. And I think we have a video starting. Yes. So the showcase I'm going to show you shows the integration of our technology in a number of different use cases. This is our integration with Doctor24, a health care provider from Hungary. The interaction that I'm showing you here is our symptom assessment. It starts with basic questions about the patient's profile, their biological sex, and their age. And then we move on to the leading symptom that they're faced with. This is the next integration of our API with DoctorBox, an electronic health care provider from Germany. In this case, you see we're talking about a female patient who's facing pain when you're urinating. The algorithm is asking very straightforward, easy-to-understand questions that relate to the symptoms, very similar to like a doctor would do it. And then we move on to the second phase of the integration in a new app. Here, based on the first data point that the algorithm received, the first symptom of the patient, it starts suggesting additional accompanying symptoms, such as fever, et cetera. And with each data point, the algorithm learns more about the patient and can suggest the right next question. You see very intuitive UI. You can select your fever on a scale. And then the algorithm moves on into a second round of questions. We're skipping it here for the sake of time. And then we move on to an overview of the symptoms. This is a safety measure that we've put in place to make sure the data is accurate. And then we move into the third phase where we ask not about symptoms, but about accompanying information about the patient. This is our integration with Generali. Unfortunately, it's only available in German, so I hope some of you can still understand it. At least the patient has been asked whether they have diabetes or not. And then the patient receives the most likely problem based on the data points they have entered. And then they are led to concrete solutions within the ecosystem of the insurance. On the one hand, we show them self-treatment recommendations, so what they can do immediately to feel better. But we're also giving them the chance to find appropriate health care providers that are covered by their insurance and are located close to them. You can see it here, it's very intuitive. In the next integration that I'm going to show you, we're moving back to Dr. 24, so the chain of hospitals in Hungary. Here, the algorithm is linked directly into the booking platform of the health care provider, so we smarten up the way patients book appointments. Based on the results of the assessment, the patient gets specific doctors suggested that can take the problem most appropriately, and then they can directly book an appointment. Now, I could show you also our illness check, which we use with Roche to scan long COVID patients for signs of COVID heart failure. But instead of that, I'm very pleased to be able to show you a first sneak peak into our soon to be released third medical device, which will be our health check. The health check is moving out of the diagnostic phase and moving into prevention. The goal of it is to calculate the personal risk profile of the patient along 14 organ groups and to get a 360-degree picture about the patient's personal health risks. So you can see here, we can select a cardiovascular health check, a neurological health check. And based on the selected disease areas, the algorithm will start asking questions. The focus here is not on the symptoms of the patients, because the hypothesis is the patient doesn't have symptoms yet. But we're focusing on data such as the lifestyle of the patient, pre-existing conditions of the patient, conditions that have been present in the family of the patient, medication that the patient is taking, et cetera. And based on these data points, we can calculate a personal risk profile for the patient. I'm showing you a few questions here, but for the sake of time, we're skipping a number of those. And in a second, we'll get to the report page. And what the report page tells the patient are three things. First of all, a score about the level of risk that the patient has for each individual disease area. The second, you will see it in a minute when we click on the cardiovascular diseases, is the specific steps that the patient can take in order to feel better soon. So on the one hand, change lifestyle. But on the other hand, also personally recommended appointments for checkups that they can book directly with the health care provider where the API is integrated. I think we can move back to the slides as we're at the end of the video. Do I need to press? Perfect. So our competitive advantage is based on three core areas. The first is our medical accuracy, which is on top of the market. And the good thing is, since we're a class 2A medical device, it's not me saying that. It's a notified body of the European Union actually assessing that we can reach the medical accuracy that we claim in our studies. The second is the flexibility and speed of integration, which is at the top of the industry. You can take our API and build something purely from scratch, or you can take one of our SDKs and integrate it into your solution within one day. And the last is the regulatory quality, where the first have been the first class 2A medical device in Europe, and the only API who has received the class 2A medical device certification in Europe so far. Last but not least, our technology is built on the data-driven analysis of more than 2.8 million medical articles, and today more than 3 and 1 half million patients are already access to the interactions of our various integrations. If you want to learn more or become part of reshaping health care together with us, please reach out via my LinkedIn. Thank you very much.