GoKawiilThe market for AI notetaking devices has exploded in the U.S., with the category generating over $600 million in revenue last year, according to a Menlo Ventures report. And as startups like Heidi Health and Freed, have shown, there’s decent demand for this tech in healthcare, where doctors and clinics see the potential for an AI assistant that can help them keep track of patient conversations, surface health records, and lower their administrative burdens.
But those apps don’t do much for patients, which is why Kin Health is building a notetaker that can transcribe your visits to doctors, parse medical advice, and surface next steps when required. To that end, the startup has raised $9 million in a seed funding round led by Maveron.
The app is similar to a meeting notetaker: you can record doctor visits, and it will return an AI summary of the meeting, with the next steps, all of which you share with family and friends if you want to. It also lets you note down questions that you might want to ask during your next visit.
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Kin Health says it encrypts all patient data, and that summaries are kept private by default. The tool is not HIPAA-certified, as it is a patient-facing one, but it adheres to the same privacy standards, the company said.
The free app is built by physicians Arpan and Amit Parikh, along with Kyle Alwyn, who previously built online prescription service HeyDoctor and sold it to health platform GoodRx. Doug Hirsch and Trevor Bezdek, co-founders of GoodRx, are founding partners and executive chairmen at the company.
Co-Founders Arpan Parikh, Amit Parikh, and Kyle Alwyn Image Credits: Kin Health Image Credits:Kin Health
“We have a lot of these storage cabinets where our health data can live, but we don’t have a way to convert that into a utility that we can use to drive our behavioral change. Our goal is to create this health graph where we can store your information from multiple different sources,” Alwyn told TechCrunch over a call.
Kin Health says that its summaries are provided after a few stages of processing. After transcribing the visit, an algorithm turns the transcription into a clinical narrative, which gets crunched into a user-facing summary with action items. The company says it is leaning on specialized medical models to power the transcription, and that it evaluates and observes outputs at different stages to ensure answers are accurate.
But AI in healthcare is being received with a measure of caution and apprehension. Privacy experts and researchers have raised concerns over data security, accuracy of AI, consent mechanisms, the quality of generated notes, and their effectiveness.
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