Teton.AI bags €4.8M to help nurses tackle burnout using AI; here’s how

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Copenhagen-based Teton.ai, a health tech startup building an AI companion for nurses, announced on Wednesday that it has secured $5.3M (approximately €4.8M) in funding led by Plural. 

Strategic angel investor Finn Murphy, formerly at Frontline Ventures, also participated in the round.

Fund utilisation

Teton.ai says it intends to use the funds to expand its engineering and commercial teams to help roll out the product in Denmark. 

The company also plans to utilise the capital to expand to the rest of the Nordics, Germany, the UK, and the US.  

Founded by Mikkel Wad Thorseen (CEO) and Esben Klint Thorius (CTO), Teton.ai is building an AI companion for nurses to help monitor patients and optimise workflows. 

Silicon Canals had the opportunity to interview Mikkel Wad Thorseen, the CEO of Teton.ai. During the interview, we had the chance to learn more about the company’s technology, its approach to addressing the nursing shortage problem, its success stories, and more. 

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Battline nurse shortage

The shortage of nurses in the healthcare industry is a pressing issue that has persisted for years and is predicted to reach up to 13M by 2030. 

Last year, the International College of Nurses called the lack of available nurses in the workforce a new “global health crisis”

Nurses face physically demanding shifts of up to 12 hours, and patient care now encompasses mounting admin work. 

With nurses suffering from exhaustion and burnout, a lack of support on the ward can lead to lapses in patient care, and in the worst cases, serious issues can be missed.

To address this issue, Thorseen founded Teton.ai, which leverages AI and computer vision to give nurses tools that can help monitor patients in real time and keep on top of paperwork.

With a professional background in product design and computer science, Thorseen has always been interested in healthcare and wanted to build something in this space.

“It made sense to start with nursing – it’s a neglected part of healthcare as it’s not seen as prestigious or glamorous. But the bread-and-butter work is the most important for keeping the healthcare system afloat,” says Thorseen.  

“When we started exploring this idea we spoke to nurses across the healthcare field to understand their needs and pretty quickly understood how much of their time was spent on non-patient-related work, such as admin, and how much that affected their job satisfaction. It helped us lay the groundwork for Teton.ai,” he adds. 

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Image credits: Teton.ai

Helped reduce night shift workload by 25% 

According to Thorseen, Teton.ai’s technology has helped reduce night shift workload by 25 per cent in care homes, giving caregivers more control over their workload, reducing exhaustion, and allowing them to dedicate more time to caring for residents. 

“This could have major knock-on effects such as helping to reduce burnout and the time spent focused on administrative tasks which are driving nurses and caregivers away from the sector,” adds Thorseen. 

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Image credits: Teton.ai

Nurses’ extra eyes and ears

Currently, Teton.ai’s product provides a comprehensive and anonymised overview of the ward. The AI assistant acts as an extra pair of eyes and ears so nurses can focus on delivering high-quality care. 

“This enables nurses and caregivers to understand the state of the ward and care home in a second. Because the companion has visibility over every room, it can help alert staff about unintended events, capture relevant data, and even assist in reporting on those events, all with the permission of the nurse of course,” says Thorseen.

Teton’s AI was trained using hospital data sets and feedback from nurses to provide support for clinicians facing high volumes of work.

Smart cameras, which leverage computer vision, are installed on wards and can scan the room for updates and patient activity, which are then fed back into a web app to alert nurses when care is needed.

“The companion also assists the staff in tracking things like sleep or mobilisation to prevent unnecessary disturbances. The companion also monitors patient falls and if a patient is attempting to get in and out of bed to help staff avoid falls altogether,” Thorseen shares. 

Borrowed the whole hospital….!

In Denmark, Teton.ai is currently working with Nykøbing Falster Hospital and Næstved Hospital, among others. 

“We worked early on extremely close with nurses at Nykøbing-Falster Hospital as they allowed us to essentially “move in” to the ward. We trained it using real data, with the permission of hospitals and their patients to enable it to become a really helpful tool and a major asset for nurses,” reveals Thorseen. 

“Some feedback we’ve had includes that Teton.ai has ‘saved’ nurses during difficult shifts and that they ‘appreciate the system’.” 

“To get ahead on data collection, we even borrowed a whole hospital wing and hired 25 actors and a whole class of nursing students to enact edge cases so we could train our AI to improve its reaction and notifications during difficult situations,” adds Thorseen.

End goal

“The general idea behind Teton.ai is that AI will permeate all of healthcare, not only diagnostics but also the nursing fields. We feel well-positioned to bring AI innovations to the nursing field and will continue to do so,” says Thorseen.

“The end mission is to create a full virtual nurse companion that supports the staff in every way possible, one that has eyes and ears in every room and can provide real-time guidance and insights and take care of all the paperwork, enabling nurses to instead focus 100% of their energy on delivering the best care to the patient,” concludes Mikkel.

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Vigneshwar Ravichandran

Vigneshwar has been a News Reporter at Silicon Canals since 2018. A seasoned technology journalist with almost a decade of experience, he covers the European startup ecosystem, from AI and Web3 to clean energy and health tech. Previously, he was a content producer and consumer product reviewer for leading Indian digital media, including NDTV, GizBot, and FoneArena. He graduated with a Bachelor's degree in Electronics and Instrumentation in Chennai and a Diploma in Broadcasting Journalism in New Delhi.

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