The Future of Vet Care: AI, Efficiency, and the Human-Animal Bond

This episode is sponsored by Scribenote.

After spending time with his sister who is a practicing veterinarian, Ryan Gallagher, chief executive officer and co-founder of Scribenote, wanted to help find a way to save her time when she was doing her medical records at the end of the day, resulting in the creation of Scribenote. On this episode, our host Adam Christman, DVM, MBA, and Gallagher discuss Scribenote and how it works, plus why it was important for the company to emphasize the importance of the human-animal bond in the company's mission.

Below is a partial transcript, edited lightly for clarity

Adam Christman, DVM, MBA: if you could walk us through just a little bit on, you know how AI listens to the appointments and turns those conversations into usable medical records, that would be useful to some to those of you listening, I know you probably well, how does that? How does that really work? So, can you walk us through just a little bit of that?

Sean Gallagher: Yeah, so, I mean, it's, it's just a couple steps. The first step is to take the audio from the exam room and save that in the cloud. The actual first thing that we do is save it to your device, first, in case you're like, offline, or your you know, Wi Fi connection is not strong, but once that syncs with the cloud, we take that audio and we transcribe it using models tailored more to like veterinary lingo. So you know, you can count on Scribenote not to just transcribe your conversation accurately regardless of accents actually, including regardless of languages. Scribenote supports multiple different languages being transcribed, but then to be sort of accurate and capturing your veterinary verbiage at the same time.

And then we take that transcript audio, which you can access later. And it's also worth noting that you can always access the audio later as well, so you have sort of 2 layers of fallback to your medical record of extra sort of memory and then we take that audio, and then we've run that through large language models, so the same kind of technology that powers popular AI tools like chatgpt, and we then take those large language models and we make them sort of tuned towards spitting out a medical record of highly accurate, highly relevant and. Sort of tuned to you, medical record structure.