 Hi everyone, my name is Johanna Varria and I'm the Chief Marketing Officer at Alvin1. So we're facing a little bit of a challenge here. Our health care costs are growing faster than our GDP and we're spending about 10% of our GDP in Europe on health care. At the same time, type 2 diabetes and other lifestyle-related illnesses are soaring. This is not just a government problem, it's not just a problem for the individuals, but it's a problem for the employers who are paying the price for lost productivity. But I have good news too, 75% of the money we're spending on health care is estimated to be spent on conditions that we could actually treat, that we could prevent beforehand. And that's where Alvin1 comes in. Odom, the company behind Alvin1, has been around for 30 years in the field of preventive health care. We've been able to collect the data from 200,000 Finnish people and our database size reached 9 million data points last year. With our long-term partner, VTT, the Technical Research Center of Finland, we were able to develop a machine learning algorithm that can actually predict future illness. Alvin1 was launched in April 2017 and it looks like this. For the employee, Alvin1 is a personal health coach. For the employer, HR and management, it's an intelligent way to optimize employee performance through improving their health. It creates an ecosystem of well-being that connects the work community with the information and services that the work community needs in order to improve their own health. The global mobile health market is expected to reach over 25 billion US dollars in 2017. Our target market share is 10% of employees in large multinational companies and with this market share, we expect to reach 175 million euros in revenue by the end of 2019 in the Nordics, Germany and China. Our business model is a user-based license fee. We're currently in the go-to-market phase and we have some clients in the Nordics. Our investment need at the moment is 1.5 million, which will be used to accelerate our growth in the market areas mentioned before. By the end of 2020, our vision is to be a strategic partner worldwide for organizations and well-being. The people behind Alvin1 consist of medical professionals, researchers, programmers, designers and sales professionals. We all share our passion for pursuing well-being through knowledge. Thank you all so much for being here. I hope to see you around during the next two days. Thank you. You didn't tell about traction. How much you have already customers in those countries that you are talking to? We've gotten our first sales within the past month or so. It's all very new. We have in Finland and Sweden, we have a few hundred users with this product. Our previous generation product, which you maybe saw on the timeline, has thousands of users, and that's how we've been able to collect the data. This is a new improved product that only has a few hundred users in the Nordics now, and then we have some negotiations going on in the Netherlands and Estonia. We're doing the market research for China right now and really interested in the market and meeting with some Chinese partners, possible partners here as well. From the employer perspective, how are you linking the services to employee benefits or insurance? I wasn't entirely sure what the benefit for the employer was or what the services looked like. Yeah, that's a good question. We have to do it localized in a local way in every area that we go to because everybody has a different insurance system, a different healthcare service provider, so we have to do it locally. We also are looking for digital services that we could connect to our product that would work in several countries, but otherwise it's local services. You said that your service was able to predict future illnesses. I didn't get, or maybe you didn't say, but how good is it at predicting? I mean, do you have any kind of measurement or estimate on that because just saying that it predicts future illnesses is rather broad. And also based on what data it predicts that? Yep, good questions. So it's based on self-assessments. It's a mobile app, a new feed and data, and right now we're up to 83% sensitivity on the prediction. When doctors make a diagnosis, it's around 80%, so 83 is pretty good. So just to understand, so is this like triage? So you do this when you're sick or you do this like a few times every year? It's like a yearly checkup or? Yeah, basically. It could be a yearly checkup. You can do the prediction more often at its own automatic reminders based on your last results on when you should do your next one. Just like lifestyle factors and it's not like, ah, I'm feeling a sore in my throat. It's more like I'm smoking and I'm overweight. Yeah, it's more about chronic illnesses that we can prevent with lifestyle changes. Okay, cool. Thank you. I also am more curious since you're in the AI batch, what kind of AI are you then actually implementing on this one and who in your team is responsible for the AI part? The AI part is in the prediction, so it's a machine learning algorithm that can actually predict based on very few factors. It calculates from 5.5 million different scenarios, the AI, if you're going to get sick or not. In our team, Mark Van Gills, he's a professor at VTT, the Technical Research Center of Finland. He's the one who is responsible for that and can answer more technical questions regarding that. So in terms of the actual benefits from the employer side, like how are you pitching to the employers that they onboard their employees on your platform? Is it, you know, savings on their employee benefits and healthcare plans? That's why they want to onboard on this platform. I'm not entirely sure what it is. Yeah, it's savings. That's the most simple way to explain it. They save money if their employees are at work and they're being productive and they're healthy and happy. So you're introducing them to healthcare insurance providers? Like how are you working from the employers? Can you put your mic a bit closer? I can. Yeah, so how are you? The time is up. Okay, I'm sorry. Okay, time is up. Let's give a big hand for the first piece of the day.