How Lassie Is Automating Healthcare Administration

Stein: I never forgot what I saw there. Just like a small business owner that like is the number one rated doctor on Yelp spending 200 hours a month on paperwork and busy work. So submitting claims by hand and he had to stick around himself because he couldn't find people to like build the patients... I thought that this was a solved problem cuz in the 70s my mom worked in hospital and that's what she did. She brought backs of cash to the bank and then processed payments by hand. Uh but it wasn't a solved problem here.

Frederick: A huge difference between SMBs in general and and enterprises is that in SMBs there's nobody to to use the tools. Like you can you can build a tool, but uh there's nobody sitting there that's going to use it... If you take over a job uh reconciling all the insurance payments, interacting with the patient to kind of like bill um it needs to like work. Um so that was like technically like hard to do. Uh, which also makes this super interesting from a technology perspective because you all of a sudden need to build autonomous systems that run on its own and don't have a human in the loop.

Stein: The end goal here is that uh every small business should run itself, right? And the busy work is done by uh agents... step one is to Alexis's point like there are 160,000 dental practices in the US alone $200,000 in labor that Dr. Sloop and others can't find. So like um serving that market first. You're looking at a $1 billion in like a recurring revenue as a market um so we're that's like step one and then uh likely like we will pick another doctor office type... and then the last uh part there is I think uh we've then trained AI agents uh to like run the small business and all small businesses at an abstract level like have a system of record they need to read and write into... We're just the best in you know building AI agents that uh salt of the earth people or people in Iowa and Paduka Kentucky and hopefully in Amsterdam like down the line where I'm from um and Germany Hamburg where Frederick is from can can start like using as well.

Frederick: The models are trained on so much data and they're so large and yet they actually don't really know how to do any of this work. Like they don't have the workflows encoded in any way... there's also a big amount of um just like human knowledge that is encoded in say these office managers and they just like know how to do this work uh that's weirdly not that accessible on the internet. Um I think we have a big advantage there because we have um all of this like historical data out of their ERPs that we can look at and kind of infer you know some of these workflows from.