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Robin Healthcare: Cracking the Code on AI in the Exam Room


    Today we’re pleased to announce that Scale is leading a $50M Series B round in healthcare technology company Robin. We believe Robin has cracked the code on technology enablement inside the medical exam room.

    Robin Healthcare is in the business of medical charting and reimbursement. Their Robin Assistant product is a hardware device with audio and video capabilities paired with a human-in-the-loop AI software platform. The device sits in patient examination rooms and generates transcripts of patient visits for the purpose of simultaneously generating patient records and SOAP notes (what happened during the visit) and tagging all the services provided (what’s billable) with the associated reimbursement codes. Robin aggregates all of the data associated with a patient visit (including even the doctor-patient dialogue) to create documentation that addresses the complexities of insurers, compliance, and liability.

    Big picture, we believe AI can replace services that have typically been performed by business process outsourcing firms (AI eats BPO) and other third parties. Not surprisingly, medical documentation is a major category of BPO spend that is typically manual and human-centric. Robin is pairing automation with trained healthcare staff. It’s analogous to the way Unbabel’s AI translation platform eats the work of outside translation agencies.

    We’re extremely excited about Robin’s approach to all of these things. The company joins several other leading digital healthcare companies that we’ve invested in over the past three years:, Proscia, and OM1. We consider Robin part of a trend-of-trends we call cognitive applications, enterprise technology systems that take advantage of all three of advanced AI, real-world data collection, and interconnectivity between systems (via APIs). We’ve written extensively about why we see all of enterprise software moving towards cognitive applications.

    Doctors Want Their Time Back

    Doctors go into medicine to care for patients, but complex administrative rules often require them to spend more time documenting care than providing it. Many attempts have been made to address this issue with software, including electronic medical records and transcription services, but they’ve all fallen short.

    In a private medical practice consisting of 10 orthopedic surgeons, for example, you’ll have 5 or even 10 different processes for the required notes and coding. Some doctors take notes during a visit and then hand those notes to an employee who specializes in billing codes. Some will make notes and codes themselves each evening after their patient hours. Some try to do everything in real-time to minimize after hours admin time. And so on. Robin recognized this issue as a symptom of a larger problem—one that stems from bad data and siloed systems. And it knew that the cure had to start at the source: the exam room. It also had to offer more accuracy, while not distracting doctors during their time with patients

    Doctors tell us that notes and codes are the sort of administrative work that they would rather not have to do. It’s the “paperwork” that eats so much of their time. So a device and software combo that seamlessly takes over that work is a welcome improvement that allows the individual doctor to focus more on patient care and less on their already overburdened admin time. When a doctor sees their last patient at 6pm, they are not looking to spend another two hours summarizing charts.

    The Robin Assistant

    We like Robin’s product for what it doesn’t try to do. That is, it doesn’t attempt full automation in real-time. The technology to do that well doesn’t yet exist. The company has instead oriented around a human-in-the-loop system where its speech recognition and computer vision systems capture data then a team of experts reviews the information from the visit and packages and structures the data for documentation and medical coding. This approach is highly accurate, with the team behind the scenes providing feedback to improve the AI over time.

    By combining the note generation and coding into one step, Robin prevents the loss of information you see with other similar but less functional tools. This is good for the patient and good for the doctor: higher quality records and higher billing “capture” rates.

    The big question for doctors is, of course, does it work? Is Robin better than the status quo? In our conversations with doctors, the answer is clearly yes. Doctors across the country using Robin are reducing their risk of practicing in today’s complex healthcare system and saving an average of 90 minutes daily for little to no net cost.

    Robin also carefully walks the line between patient privacy protections (there are many) and providing an unassailable “ground truth” record of each and every patient visit. Regulatory audits are a fact of life for medical practices, and having a record of every service provided (and billed for) is an important benefit to customers.

    Robin’s go-to-market strategy involves a compelling pitch to doctors: reliable medical coding and reduced risk to practice…versus what you’re doing now. Plus, we guarantee accuracy if an audit arises. Bottom line: Robin frees up doctors to spend more time caring for patients.

    The Right Team for the Job

    Robin is in the early innings of developing what can be a hugely impactful exam room AI. Today they’re focused on orthopedics practices with more than 10 doctors, a highly complex medical specialty that allows Robin to prove their value, further develop the underlying AI, and set themselves up for additional medical specialties in the future.

    Robin co-founders Emilio Galán, CEO, and Noah Auerhahn, President, are a highly effective pair of executives with medical training and e-commerce experience, respectively, in their CVs. We welcome Emilio, Noah, and the Robin Healthcare team to the Scale portfolio and look forward to their continued success.

    Thanks to my co-author, Scale Principal Jeremy Kaufmann.

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