Hippocratic AI

I'm so excited we could do this.

Tell us a little bit about Hippocratic AI.

So at Hippocatic AI, what we do is we build clinical voice agents that talk to patients on the phone.

And so we do that for health systems payers and pharma clients.

Yeah, I think certainly we see it as a really incredible opportunity for us in delivering our mission to improve lives, where we can enhance that care connection more with patients, but that in bringing in this agentic voice technology, we really have to think about kind of going slow at the front so that we can scale faster.

We've focused on that similar approach of making sure we're creating systems and understanding the people process technology that are involved and that If we create those systems at the outset, such as the work that we're doing with Hippocratic AI Now and Agentic Voice, we can then essentially go faster if we have that system and the safety and the confidence in that system.

We recognize to your point that these scheduling calls that we started with initially, we knew we had to put a lot of the processes in place in case something clinical were to surface on those calls.

And that each call, while it might have been intended as a scheduling call, could turn into a clinical interaction and that we need to be confident in where we were going and where we were reviewing things.

Today, we're going to talk about beyond the doomerism, what safe healthcare AI looks like in practice.

Joining me for today's conversation is Munjal Shah, co-founder and CEO of Hippocratic AI.

Munjal, thanks for joining me today and being my participant, my guest for this big topic.

Oh, yeah.

And basically, the bigger the model, the better the judgment.

Working off of that story, I mean, so much of the public narrative or commentary or attention right now is really looking at advanced AI as something to fear.

It sounds like from these stories and the work that you've been putting forward at Hippocratic AI, you and your team are just clearly operating from a different premise altogether.

What would you say, Manjal, is the counter case you'd make to that type of doomerism and Maybe more to the point, what are you seeing in live deployments that actually supports optimism?

My guest today is Bill Hudson.

Bill is the chief information officer at Hippocratic AI.

He is a former health system chief information officer with more than twenty-five years of experience using digital and information technology to improve patient outcomes, clinical adoption, consumer engagement, and health systems value.

His work has included large-scale clinical technology implementations, new hospital integrations, community connection programs, and some of the most complex operational transformations in healthcare.

You know, the Hispanic population didn't engage at the same levels that the Black population didn't engage at, and the Asian population.

It was just-- And they all had different communal needs that they needed to have met to understand how the virus was affecting them or how vaccinations worked, and all the-- and it was every group was a little bit different, and being able to access those, those folks at scale was problematic.

So a couple years ago, I had the opportunity to talk to one of the founders here at Hippocratic AI, and he gave me a demo of one of their agents, and I was like, "This technology is pretty cool." And so I ended up, when I started here, I'm like, "This could be really cool." Everyone that, that works in Hippocratic, one of the first things they do, everybody has to build their own agent.

Everybody builds their own agent, and it's a voice agent that goes out and solves a pr-- makes a phone call and solves a problem.