How a Psychologist Brings Clinical Judgment to AI for Psychiatry with Sophie Klarskov Petersen
How a Psychologist Brings Clinical Judgment to AI for Psychiatry with Sophie Klarskov Petersen
In most of medicine, the data a clinician needs is discrete: a potassium level, an ejection fraction, a blood pressure. In psychiatry and psychology, the most important clinical data is a story, shared in pieces across sessions that can run two hours or longer. Building AI for that world takes a clinician in the room.
In this episode, host Helen Tanner talks with Sophie Klarskov Petersen, a psychologist and the clinical product manager at Aisel Health, a Copenhagen health tech company building an operating system for psychiatric care. After two years as a therapist in a multidisciplinary pain department at Copenhagen’s largest hospital, Sophie moved into product, where she says she uses her psychology training more than ever.
Helen and Sophie talk about what the clinical product manager role actually involves, how a tool can take documentation off a clinician’s plate without taking away clinical judgment, why clinicians tend to jump to solutions before the problem is fully scoped, and what it feels like to be the one who asks whether the team should build something it already knows it can build. Sophie also shares how she answers clinicians’ first question about AI (“Is this safe?”) and why AI does not need to be perfect to be useful.
For any clinician wondering what product work looks like inside an AI company, and especially for behavioral health clinicians, this is a clear, practical look from the inside.
Key Outcomes: What You Will Gain
A clear picture of what a clinical product manager does, and how clinical workflow knowledge becomes product decisions
An understanding of why mental health data needs tools built for narrative, not just discrete values
A way to separate “can we build it” from “should we build it,” and to hold the patient safety line on a team that wants to move fast
Practical language for earning trust from clinicians who are cautious about AI
Reassurance that the product skills clinicians lack at first, like staying in the problem, can be learned on the job
Must-Hear Insights and Key Moments
In psychiatry, the data is a story. A basic scribe pulls short data points from a recording. Psychiatric recordings can run an hour and a half to two hours or more, and the information comes as narrative. Sophie points out that summarizing is only half the job: the data also has to be stored and used afterward. Where does everything a patient said go, and is anyone using it? That is a patient safety question, not only an efficiency one.
The clinician decides the order of the blocks. Sophie uses a Danish image: the tech team has all the Lego blocks, and her job is to tell them whether the blue one or the yellow one comes first. Most of her input is about workflow, not therapy content: would a clinician do this before or after seeing the patient, during the session, and where would they need this tab? She also helps the team skip features that would never bring real value.
Clinicians jump to solutions. Product starts with the problem. Psychologists are trained to help people feel better, which makes them fast to propose solutions. In product, Sophie’s job in the discovery phase is to scope the problem and let design and engineering bring the options. She still catches herself moving into solution mode, and a colleague helps her roll back and stay in the problem a bit longer.
“Technically, it’s possible. But should we do it?” Sophie describes being the voice of the customer and the voice of patient safety, which sometimes means killing ideas she can see the vision behind. The question is not only whether a feature helps the clinician, but whether a patient would rather have a human do it. She finds this hard, and says it is a skill you learn.
Earning clinicians’ trust in AI starts with what AI will not do. Some clinicians find Aisel on their own because they see AI is here to stay. Others start with “Is this safe?” Sophie answers with data protection first (in Europe, practicing GDPR), then shows exactly where the product prompts the clinician for their own assessment. The common misunderstanding is that AI will do all of the work. It replaces tasks a clinician should not spend time on, and it does not need to be perfect, because humans are not perfect either.
Key Questions Helen Asks Rebecca
What does a clinical product manager actually do? Sophie is the clinical part of the product. She brings knowledge of clinical workflows to engineers and designers who know how to build but need to know what shape the product should take. The product team often asks her for scenarios and use cases: would you need this, and when?
How does building for narrative data change the product? Aisel is not using AI to decide what matters. It is building a product shaped specifically for psychiatry, where long recordings and many documents per patient create a huge amount of data. The goal is to remove the mental load of preparing for the real work, so the clinician can make their assessment.
What was it like moving from a hospital pain department into a tech and business setting? The biggest learning curve was thinking in frameworks and processes: knowing which phase the team is in (discovery, scoping, building) and what her task is in each one. She wears many hats, sometimes salesperson, sometimes “techie psychologist,” and had to learn the language that goes with each.
How has the role changed in the first year? The tasks are similar, but she now works far more independently. Early on she kept suggesting ideas the team had already tried. Now she has been part of that history, keeps up with every corner of a product that changes week to week, and the team has learned when in a process it helps to bring her in.
How do you earn the trust of clinicians who are cautious about AI? Start with safety and data protection, then show clinicians where their expertise is still required. Address the belief that AI replaces the clinician, and manage expectations on the other side too, since tech-forward clinicians sometimes expect the tool to be perfect.
Words of Wisdom: Standout Quotes from This Episode
“In psychiatry, the most important clinical data is not a lab value. It’s a story.” - Helen Tanner
“The tech people are having all the blocks, and I’m the one to tell them if you need the blue one first or the yellow one first, and then we shape the product together.” - Sophie Klarskov Petersen
“To be honest, I’ve never used psychology as much as I do right now.” - Sophie Klarskov Petersen
“Technically, it’s possible. But should we do it?” - Sophie Klarskov Petersen
“It will just replace tasks which a clinician shouldn’t spend time on.” - Sophie Klarskov Petersen
“Be open to and adjust to the world you’re entering.” - Sophie Klarskov Petersen
About Sophie Klarskov Petersen
Sophie Klarskov Petersen is a psychologist (cand.psych.) and the Clinical Product Manager at Aisel Health in Copenhagen, Denmark. She began her career in clinical practice, spending two years as a therapist in a multidisciplinary pain department at Copenhagen’s largest hospital, and recently received her authorization as a psychologist in Denmark. Always drawn to developmental work, she also trained in sports psychology and worked with young talent at a football club before moving into health tech, which she sees as her generation’s tool for making care better. At Aisel, she brings clinical workflow knowledge into the product and helps shape where it goes next.
Aisel Health is building an operating system for psychiatry and mental health, designed to take the burden of documentation off clinicians while keeping clinical expertise at the center. The name comes from “æsel,” the Danish word for donkey (a nod to Eeyore from Winnie the Pooh), with “AI” built in.
Mentioned in the episode:
Aisel Health: the Copenhagen health tech company where Sophie is Clinical Product Manager
General Data Protection Regulation (GDPR): the European data protection law Sophie describes as something companies practice, not a certificate they hold
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Episode Transcript:
Note: We use AI transcription so there may be some inaccuracies
Helen Tanner: Welcome to The Early Hires, the podcast for clinicians and startups. I'm your host, Helen Tanner. This is a show for early clinical operators working alongside founders to build the next generation of healthcare companies. Every episode is designed to help you feel more understood in your role, clearer about your influence, and more confident in how you show up inside a growing company. If you're a clinician working inside a startup, The Early Hires is for you.
Before we get started, a thank you to our founding sponsor, Hey Health Tech. If you're a clinician curious about health tech, Hey Health Tech is a newsletter and community helping healthcare professionals understand the industry, discover new career opportunities, and connect with people working in tech. Learn more at https://www.heyhealthtech.com/.
Hi, I'm Helen, your host of The Early Hires. Today's episode is a first for this show in a few ways. First is our first conversation with a psychologist. It is our first with a guest building outside of the US, and it takes us into AI for psychiatry, where the most important clinical data is not a lab value, it's a story.
My guest today is Sophie Klarskov-Petersen. She's a psychologist and she lives in Copenhagen, Denmark, and she's the clinical product manager for a company called Aisel Health. They are building an operating system for psychiatric care with clinicians at the center of how it's designed. Sophie started where many psychologists do in clinical practice. For two years, she worked as a therapist in a multidisciplinary pain department at Copenhagen's largest hospital, which gave her a deep understanding of clinical work and the people behind it. She was always drawn to building and shaping things, and she came to see technology as her generation's tool for making care better.
Psychiatry is facing a real capacity crisis. The need for help keeps growing while capacity stays the same. Sophie saw a huge opportunity to change that by moving into health tech. Now, a year into her work at Aisel Health, she gets to watch the products and company grow week to week and month to month and help shape from the inside where it goes next. I'm so glad she's here to share more about her work and experience.
Welcome, Sophie.
Sophie Klarskov Petersen: Thank you, Helen.
Helen Tanner: So before we get into product work, because that's where I want to spend our time, tell us a little bit about what it takes to become a psychologist in Denmark. Tell us about your earlier years in clinical work.
Sophie Klarskov Petersen: Yeah, sure. So how did we become psychologists in Denmark? I don't know how it functions in the US, but in Denmark at least you get, first of all, a bachelor, which is three years, and then you top it off with a master. Psychologist is a protected title, so you need to have both the bachelor and the master, and you can't really build your own education, you can't really build up the study in your own way. You can, of course, take some pathways in a few directions, but it's not like you can just take this course and then in the next semester you can choose something completely else. It's pretty fixed because otherwise they can't really control what the title contains, so to say. And then you get on the other side and then you're a psychologist. For psychologists it's more, you need this quality stamp, so you need to work in clinic for two years at least. You will get a lot of supervision, you will have to collect a given amount of hours in therapy, where you provide therapy and practice your expertise, and then you'll apply for this stamp, which I call it. It's an organization for patient safety where you apply and they will, of course, review your application and then you can get the stamp. And actually, I just got it. So that's quite new.
Helen Tanner: That's wonderful. Congratulations.
Sophie Klarskov Petersen: Thank you.
Helen Tanner: You described in your writing to me that you feel like technology is your generation's tool for making things better. When did that click for you and what made you move into health tech to accomplish that interest of yours?
Sophie Klarskov Petersen: Well, I've been exploring different ways of using psychology, so I also went into sports psychology at some point, and I was working in a football club with some talents and stuff. And I saw that, okay, this element of developing, it shouldn't necessarily be a pathway for a human, it shouldn't necessarily be a development of a human or a human's talents. could also be something else, but at least it should be something where I saw something good being better compared to having something bad or like sad people to make them good. So bringing good to better compared to bringing bad to good, if that makes sense. So that was kind of my view on it. And ending in technology wasn't written anywhere in the stars. It was actually just me seeing this position in Aisel. And then I thought, well, our generation was schooled with technology. We know how it works and the basics. So why not look into this? We've seen the world develop in technology in so many ways and psychiatry and psychology is just full of traditions. It's so conservative and it's still on a level where, you know, the low hanging fruit, at least how I see it, we didn't get there yet. So there's a lot we can do by doing minimal changes. And I see technology as a low hanging fruit right now with AI and stuff. So that was my way into it.
Helen Tanner: I think that's fascinating. And I know you probably wear a lot of hats, but tell us a little bit about your role at Aisel, what it entails, and also maybe tell us a little bit about ISIL as a company and how your role fits in.
Sophie Klarskov Petersen: To start with, the position I applied for is called clinical product manager. So obviously I'm the clinical part of our product. My clinical perspectives and the way I use psychology in the role is about bringing knowledge about workflows into our product. Because all of the tech people, they know how to build the backend, but they need some inputs on which shape it should be, so they do have all the building blocks. I am sitting in Copenhagen and Denmark and I don't know if you know Lego, you might do. Oh yes. So the tech people are having all the blocks, but I'm the one to tell them if you need the blue one first or the yellow one first, and then we shape the product together. So bringing in a lot of knowledge about workflows, would you do this before or after you saw the patient? Would you do this during this session? Where would you need this tab? So that's mainly how I use it.
Helen Tanner: I love the image that you gave of Lagos. That is very tangible to think about. Tell us a little bit about what Aisel is building.
Sophie Klarskov Petersen: Aisel is building a way to remove the burden of documentation away from the clinician and make the clinician spend the time and the capacity where it really matters with the patient. So what we do is that we build a product that takes all of that documentation path out of the room without compromising clinical expertise. So you still get pronged to put in your opinion. So if I'm the AI, then I will write all of the things. I will give it to you and say, here you go, please review it. What do you think? Here, I need your input. Please provide your input. Otherwise we can't get verbal. So it's a way of taking away the burden of documentation and things a clinician should really spend time on, but they are forced to do it because illegal stuff and things like that. That's what we do. The whole Aisel concept is have roots in a real use case because one of the co-founders had experience with the psychiatry in Denmark and saw the need for bringing up this capacity in the clinical world. She was a part of a treatment where she really saw that the demand is higher than we can follow right now. She came up with Iceland, got the chance to pitch the idea and get some real teammates along the way who helped her to shape this, and then Iceland was born.
Helen Tanner: When we spoke a few weeks ago, you shared something that was really interesting for me to think about because as a clinician practicing in a clinic or hospital setting, there's a lot of discrete data points, you know, so a potassium level, an ejection fraction, And so when we're talking about building AI and utilizing AI for clinicians to make their work easier and more efficient, you know, bring a lot of information all together so that the continuity of care between clinicians can continue. So you can have that summary and then see at the top, okay, here is their last this, this was their last this. And I thought it was really interesting and such a good point that you brought up that in your world, the mental health as psychology, psychiatric world, data a lot of times comes more as a story. You know, a patient shares one aspect of their story this day, and then maybe a month later, it's this aspect. And I thought that was really fascinating is how do you make sure that you're drawing out the most important pieces and what are the most important pieces to keep carrying visit to visit and how do you shape that? I just think that is such an impressive feat and really needed when I think about my psychology colleagues and just even the referring when we are reading notes. So, I'm just curious when you're talking about shaping from a story and maybe less specific discrete data, how does that change the way that you're building the technology for the clinicians? How does context begin to outweigh perhaps certain data points? Can you speak to that a little bit?
Sophie Klarskov Petersen: Yes, we're not using the AI to decide what to pull out. We're building a product which is shaped to psychology and psychiatrists. As you said, with psychology, it is stories. It's not just a blood pressure you need to note down. It's real patient stories and the amount of data coming from narratives like that. It's huge and having a basic scribe or anything is more about, as you said, having data points where it can pull out these short things from a recording, but here you can have recordings of one and a half hour. two hours, we sometimes also see longer than that. So we need a product which is shaped to do this and to store that information. Because one thing is having a scribe which can summarize, and as you said, just print the summary. But what about that data afterwards? We also need to think about, okay, we're about to generate more and more data because it obviously gets easier with AI. But we also need to use that data. It's both a matter of clinical expertise and a profession where you need to meet some demands, but it's also a matter of patient safety. All the things I said, where did it go? What do you use it for? Do you even use it? And looking at 10 documents or how many you might have to review as a human without any tools, that's a lot. And if you need to do it for three or four patients a day, then it's even more. So having a tool which is taking away that mental load you get from actually preparing your real work, which is making your assessment based on something, is just optimizing in the right way. So that's how, at least for ICE's sake, we shape a product which is made for psychiatry and using clinicians to do it.
Helen Tanner: So you mentioned earlier that you feel like you use your psychology degree and your clinical psychology skills more now than ever. Can you give us an example?
Sophie Klarskov Petersen: So we just developed a feature from medical documents where you can write clinical documents, declarations for job centers or other organizations which are requesting something. And here you get asked about, okay, which type of declarations do you get in what kind of formatting? Do you get it? Do you get it on an email? Cause then we need to have a way to integrate that email into our product. Do you get it from here? Cause then we need to do it this way. So it's a matter of workflows. So they're just asking me, how do you do it? And not really what I'm doing. So the content of it, that doesn't matter, or at least most of the time it doesn't. So do you write this journal this way or this way? Yeah, it's more about the things going forward to what you really do. So. Acting as a clinician is not really something I do anymore. It's more a matter of saying what's the work you do before doing what you should do as a psychologist. It's also making me reflect a lot about what am I doing as a clinician? How can I do it even better? Would I need anything here that would help me in this workflow? It's also really pushing me to be creative and think in scenarios. The product team often ask me, which scenario would you do this? Do you have any use cases where this could be a scenario? And then they suggest something because they know from the tech side, this is possible, but do you need it? And then I just confirm or say. That doesn't matter anyways, and then we can also make sure that we don't spend a lot of time on developing stuff, which will never bring any values anyway.
Helen Tanner: Take us back to when you first started thinking about your work cross collaboratively with other teams. And all of a sudden you're no longer in that pain management hospital setting. You're now in a very heavy like business tech building. How did that feel? What were some of your early takeaways and how did you start to develop skills needed to work in that setting?
Sophie Klarskov Petersen: Well, startup is an area where you get forced to develop skills because otherwise you cannot follow the flow. You said that I might wear a lot of hats during a day or during a week, and that's totally true. I do. Sometimes I'm a salesperson and sometimes I'm a psychologist in a system where I need to learn some tricky words. So in the beginning, it was definitely a huge task for me to learn to think in frameworks and processes because something was about to be developed. It wasn't just about using my expertise as a psychologist. I also need to put it into a context where things were developed. So there's different kind of phases, like here we're in discovery phase. Now we're just scoping out the problem. I think by also the person I am, but it's also natural when you're a psychologist that you will fast go on to the solution. So I move into solution mode way before it's intended, at least in the ideal world of how we work. We would much rather have me to scope out the problem because I'm the psychologist. And then it's up to the design team and the, which are also kind of a part of, but also the tech team to say, okay, you have this problem and this use case. We can solve it in this way, this way or this way. What do you prefer? And then we will figure it out together. But finding out what's my task in this and not just jumping straight to the solution, that was a big challenge for me and I still struggle with it from time to time. But my colleague is good at pointing it out and say, let's just roll back and then stay a bit more in this phase and then move on to the next one afterwards. When you're used to solving problems and want someone to feel better, then you're also used to finding the solutions, right? So that's been a challenge for me.
Helen Tanner: That is very true because you're trained that way as a psychologist, but also startups can be so iterative and they change so much that one solution, one week you try it out, it may not be the right solution the next week and you have to change again. But what a great skill that you built and are continuing to build. Are you doing similar things when you started as you're doing now or has your scope very much expanded?
Sophie Klarskov Petersen: I would say it's pretty much the same. Of course, I've developed in my tasks. So now I'm also much more in control of what I do. Because in the beginning, my colleague, he told me what to do when I was on board. Then we moved on and I get to learn the system. I get to learn the frameworks, the way we worked and stuff like that. And then you're moving to a phase where you get told what to do, but it's up to you to find a solution for it, or at least figure out what's the best way of doing this. I would say I do the same things, but I'm much more on my own. I'm also at a point where when you're doing something a lot, you also get deeper into it. You get more insights and being a part of a startup. forces you to follow along week for week and be able to also turn in on what's going on right now, what's the product looking like right now. I know we had this last week, but now it looks totally different. So I need to be update it all the time. I need to be aware of every single corner of the product. And you can't be that when you start in your first month or your first two months. You don't really know what's the story of this feature. I kept suggesting things and they just said, yeah, we tried that, didn't work. So now I know what we tried because I was a part of it. I can much better see the product as a new product if that makes sense. It's growing fast and just having a summer holiday. does force you to catch up either during the free weeks I at least had, or a really deep dive the first day you get back, because a lot is happening. And the same with my role. We get a lot of learnings and we adjust all the time that, okay, it didn't make sense to bring in Sophie in this part of the process. Let's wait a little bit. We need psychologists to say before this process, because otherwise we'll develop something. which we won't need anyways, or need to change and stuff. So it's a question about learnings and adjusting all the time.
Helen Tanner: Yeah, and you mentioned when people are like, when to bring Sophie in, when to bring the psychology and the clinical perspective in. How do you balance a healthy friction between the non-clinical side is pulling, we should do it this way, but you clearly see like, oh, that wouldn't really work in real life or that's not going to help the psychologist and the clinician work in real life in an effective way. You know, have you learned how to cautiously push back to get people to think about different perspectives and shape a product in that way?
Sophie Klarskov Petersen: Yeah, I think I'm the voice of the customers also. So I'm a part of the product and I want to develop a product which is useful and which people like and where I can also get caught up in, oh, this is nice because we can do this on the tech side. But then I also need to remind myself. but is it useful on the clinical side? And there's also a question about moral and should we do this with AI? Yeah, we can obviously do it. Technical, it's possible, but should we do it? And that's the ongoing discussion, which I find quite hard because I do see that there's a vision behind it and I do see that the product could look really good with this feature or that we can do more by having some kind of feature. But if it's on the border of moral or stuff like that, then I'm the voice of patient safety as well. And that's the hat I need to wear sometimes and also kill some ideas. And I do find that quite hard. It's something you need to learn also, because when you're with a team with a dream, then you also want to like meet them in their ideas and just get out there with a product which is bringing value. But also one thing is bringing value to a clinician which is doing their work. But there's also a thing in bringing value to the patients, being in that room with that person or being the one receiving some kind of questionnaire or anything where a human maybe could do it instead. But we decided with this feature that an AI should do it. But would the patient rather see a human? That's also something we need to take into account. So that's a discussion which we have ongoing.
Helen Tanner: So psychiatrists and psychologists can be thoughtfully cautious about AI. What have you learned about earning clinicians' trust and getting a tool in front of them that they actually want to use?
Sophie Klarskov Petersen: Yeah, we see different kinds of approaches. Sometimes people are so curious and so keen on it and they found Aisel themselves. We didn't reach out. They just saw this trend moving and then some of them also saw that AI is here to stay, so we better learn it and we better jump on the train before it's gone. That's one part of the clinicians. And then there's the other one. The first question they ask is, is this safe, obviously? And of course, we always meet them with, yeah, otherwise we wouldn't have a product. We have something called GDPR in Denmark and you can't really get a certification in that, but you can live up to the demands. It's more like a practice that you practice GDPR. And yeah, obviously we wouldn't have a product if we didn't. Then the next step is to say, we won't take over all of your work. I think a misunderstanding about AI is that it will do all of your work. that it will replace the clinician, but that's not the case. It will just replace tasks which a clinician shouldn't spend time on. I think that's the barrier I will try to talk to them about, saying that we still need your expertise. And then I go into our product and show them that here the AI won't say anything. It will tell you that it needs you to take action. AI is misunderstood in a way where it's taking for something that will do everything. And I also see clinicians having a lot of expectations for what it can do for them. Because for those who are techie and really want to implement some kind of technology in their practice, they're like, But why didn't they do like this? They see it as something perfect. Just as we see with cars, you know, there's these intelligent cars which can drive themselves. And we're so afraid of them because what if they harm someone? And I think the discussion is so funny because what if a human will harm someone? Because we're also making mistakes all the time and maybe a bit more than machines can because we don't have any code or anything to follow. We're just humans and we can't get distracted. And we're not perfect either, so I think we need to understand before we're open enough to totally adopt to AI that AI isn't perfect just as humans, but it can take the part which we shouldn't spend time on. So I think that's a start at least.
Helen Tanner: I agree with that. I think the initial data out there for the self-driving cars is that their safety rating is higher than a human behind the wheel. So that's a great point to make. And just to clarify, GDPR is the General Data Protection Regulation. Is that right?
Sophie Klarskov Petersen: Yeah, exactly.
Helen Tanner: Well, as we start to wrap up, if you could hand a team member or a colleague who's joining a team building mental health AI, what is one recommendation or something you might say to kind of give them a piece of advice while they're doing this?
Sophie Klarskov Petersen: I would say from what I've been doing myself is to be open to the world you enter and try to at least somehow adapt the way they're working because it's so different from what you're used to. We're schooled in, you know, having conversations, doing our work in specific ways. But so are the ones we are entering the world to. So for example, 10 people or these strategic business people, which our co-founders is from a business school. And I really see that they shape the task by using different frameworks to be as efficient as possible and to make sure that you're actually building something in an efficient way. Whereas what I come from is more using psychology into the way I've learned to use it, but now I should use it in another setting, in another context to solve the task I'm asked to solve. And I think that's rule number one, be open to it and adjust to the world you're entering. That's at least something I've learned myself and it's been really useful.
Helen Tanner: Well, and I want to say congratulations. I saw that Aisel just completed their pre-seed round of funding. One of the things that you told me about ISIL that I just love and I feel like people would love to know is the meaning behind the name. Do you want to share that with us?
Sophie Klarskov Petersen: Yeah, of course, because I also love to tell it. As we've been talking about, Aisel is a product in mental health. And when our co-founder was shaping the product and the whole vision and the story of AISL, she was trying to find a name which was also reflecting what the product is really about. So AISL in Danish is really close to the pronunciation of donkey, which is AISL. And then we just, because we're about AI, then we chose to, or they chose to use AI in the name. And Donkey is a reference to the donkey in Winnie the Pooh, which had a depression. And he's always really sad. And I think he reminds people of being sad. Since we're in mental health and trying to solve the crisis or at least help people out there. It was a great name for a company.
Helen Tanner: That's a great name because like I was telling you, we refer to that donkey as Eeyore. So I know I use that sometimes with my kids or you seem like a little bit of an Eeyore today, you know, so feeling a little bit down in the dumps and whatnot. So I love knowing that that's the meaning behind the name.
Sophie Klarskov Petersen: Yeah, it's a cute story. I love it. So thank you for asking because then I got the chance to tell it again.
Helen Tanner: Yes, yes. Is there anything in particular that you'd like to share that Aisel is working on or looking for or just anything that the listeners should know about?
Sophie Klarskov Petersen: Well, right now we are deep diving into what comes after transcribing and generating a huge amount of data. Because as I said in the beginning, we are seeing a lot of scribes out there and we need to remember that this data, which is generated from the scribes, also should be used in a clever manner. Also, you know, It's your own data as a patient, you want to make sure that it's used in the best possible way. So right now we are looking into medical documents, so clinical documents, how do we aggregate all of the information from the data we generated and assemble it in one big document to give that data to whoever requested it to do any further assessments. So that's what we are aiming for right now, to find the best possible way to use data which we generate.
Helen Tanner: Oh, excellent. Well, I'll make sure to put the information in the show notes so that people can look up and contact you or Aisel and just kind of follow along with what you're doing. I just want to tell you again, thank you so much for your time today. And I really appreciate you sharing about your experience and it just sounds extremely exciting and I can't wait to see what continues to happen.
Sophie Klarskov Petersen: Helen.
Helen Tanner: Thanks for listening to The Early Hires. These conversations exist because clinicians like you are doing hard, important work inside growing companies. If this episode resonated, please share it with a colleague and take a moment to rate the podcast so more clinicians can find The Early Hires. And if you'd like more, visit https://www.theearlyhires.com/ for the latest news, resources, and updates for clinicians and startups.
I'm Helen Tanner. Thank you for the work you're doing and the voice you bring to it..
