 Welcome to today's session of theCUBE's presentation of the AWS Startup Showcase. I'm your host, Natalie Erlich. Today we're going to feature Olive in the Life Sciences track. And of course, this is part of the future of AI, security and life sciences. Here we're joined by our very special guest, Rohan Dasisa, the Chief Product Officer of Olive. Thank you very much for being with us. Of course, we're going to talk today about building the Internet of Healthcare. Do appreciate you joining the show. Thanks, Natalie. My pleasure to be here, I'm excited. Yeah, likewise. Well, tell us about AI and how it's revolutionizing health systems across America. Yeah, I mean, we're clearly living around, living at this time of a lot of hype with AI and there's a tremendous amount of excitement. Unfortunately for us or, you know, depending on if you're an optimist or a pessimist, we had to wait for a global pandemic for people to realize that technology is here to really come into the aid of assisting everybody in healthcare, not just on the consumer side, but on the industry side and on the enterprise side of delivering better care. And it's a truly an exciting time, but there's a lot of buzz and we play an important role in trying to define that a little bit better because you can't go too far today and hear about the term AI being used slash misused in healthcare. Definitely. And also, I'd love to hear about how Olive is fitting into this and its contributions to AI and health systems. Yeah, so at its core we, the industry thinks of us very much as an automation player. We are, we've historically been in the trenches of healthcare, mostly on the provider side of the house in leveraging technology to automate a lot of the high velocity, low variability items. Our founding and our DNA is in this idea of, we think it's unfair that healthcare relies on humans as being routers. And we have looked to solve the problem of technology not talking to each other by using humans. And so we set out to really going into the trenches of healthcare and bring about core automation technology. And you might be sitting there wondering, well, why are we talking about automation under the umbrella of AI? And that's because we are challenging the very status quo of siloed based automation and we're building what we say is the internet of healthcare. And more importantly, what we've done is we've brought in a human, very empathetic approach to automation and we're leveraging technology by saying when one olive learns, all olives learn so that we can take advantage of the network effect of a single olive worker in the trenches of healthcare sharing that knowledge and wisdom, both with our human counterparts but also with her AI worker counterparts that are showing up to work every single day in some of the most complex health systems in this country. Right, well, when you think about AI and computer technology, you don't exactly think of humanizing kind of potential. So how are you seeking to make AI really humanistic and empathetic potentially? Well, most importantly, the way we're starting with that is where we are treating olive just like we would any single human counterpart. We don't wanna think of this as just purely a technology player. Most importantly, healthcare is deeply rooted in this idea of investing in outcomes and not necessarily investing in core technology, right? So we have learned that from the early days of us doing some really robust integrated AI based solutions but we've humanized it, right? Take for example, we treat olive just like any other human worker would. She shows up to work, she's onboarded. She has an obligation to her customers and to her human worker counterparts and we care very deeply about the cost of the false positive that exists in healthcare, right? So, and we do this through various different ways. Most importantly, we do it in extremely transparent and interpretable way. By transparent, I mean, olive provides deep insights back to her human counterparts in the form of reporting and status reports and we even have a term internally that we call as a sick day. So when olive calls in sick, we don't just tell our customers, all of it's not working today. We tell our customers that olive is taking a sick day because a human worker that might require or might need to stay home and recover. In our case, we just happen to have to rewire a certain portal integration because a portal just went through a massive change and olive has to take a sick day in order to make that fix, right? So, and this is just helping our customers understand or feel like they can achieve success with AI-based deployments and not sort of this like robot hanging over them where we're waiting for a Skynet to come in into place and truly humanizing the aspects of AI in healthcare. All right, well, that's really interesting. How would you describe olive's personality? I mean, could you attribute a personality? Yeah, she's unbiased, data-driven, extremely transparent in her approach. She's empathetic. There are certain days where she is direct and there are uncertain ways where she could be quirky in the way she shares stuff. Most importantly, she's incredibly knowledgeable and we really want to bring that knowledge that she has gained over the years of working in the trenches of healthcare to her customers. That sounds really fascinating and I love hearing about the human side of olive. Can you tell us about how this AI though is actually improving efficiencies in healthcare systems right now? Yeah, not too many people know that about a third of every single US dollar is spent in the administrative burden of delivering care. It's really, really unfortunate in the capitalistic world of just us as a system of healthcare in the United States. There is a lot of tail wagging the dog that ends up happening. Most importantly, I don't know the last time if you've been through a process where you have to go and get an MRI or a CT scan and your provider tells you that we first have to wait for the insurance company in order to give us permission to perform this particular task. And when you think about that, one, there's the tail wagging the dog scenario but two, the administrative burden to actually seek the approval for that test that your provider is telling you that you need to perform, right? And what we've done is as humans or as sort of systems, we have just put humans in this supply chain of connecting the left side to the right side. So what we're doing is we're taking advantage of massive distributing cloud computing platforms. I mean, we're fully built on the AWS stack. We take advantage of things that we can very quickly stand up and spin up and we're leveraging core capabilities in our computer vision, our natural language processing to do a lot of the tasks that unfortunately we have relegated humans to do. And our goal is can we allow humans to function at the top of their license, irrespective of what the license is, right? It could be a provider, it could be somebody working in the trenches of revenue cycle management or it could be somebody in a call center talking to a very anxious patient that just learned that he or she might need to take a test in order to rule out something catastrophic, like a very adverse diagnosis. Yeah, really fascinating. I mean, do you think that this is just like the tip of the iceberg? I mean, how much more potential does AI have for healthcare? Yeah, I think we're very much in the early, early, early days of AI being applied in a production and practical sense. AI has been talked about for many, many, many years in the trenches of healthcare. It has found its place very much in challenging status quotes and research. It has struggled to find its way in the trenches of just the practicality on the application of AI. And that's partly because we, going back to the point that I raised earlier the cost of the false positive in healthcare is really high. It can't just be, I bought a pair of shoes online and it recommended that I bought it by a pair of socks and I happened to get the socks and I returned them back because I realized that they're really ugly and hideous and I don't want them. In healthcare, you can't do that, right? In healthcare, you can't tell a patient or somebody else, oops, I really screwed up. I should not have told you that. So what that's meant for us in the trenches of delivery of AI-based applications is we've been through a cycle of continuous pilots and proof of concepts. Now though, with AI starting to take center stage where a lot of what has been hardened in the research world can be applied towards the practicality to avoid the burnout and the sheer cost that the system is under. We're starting to see this real upwards take of people implementing AI-based solutions, whether it's for decision-making, whether it's for administrative tasks, drug discovery, it's just, it is an amazing, amazing time to be at the intersection of practical application of AI and really, really good healthcare delivery for all of us. Yeah, I mean, that's really, really fascinating, especially your point on practicality. Now, how do you foresee AI being able to be more commercial in its appeal? I think you have to have a couple of key wins under your belt is number one, number two, the standard sort of outcomes-based publications that is required. Two, I think we need real champions on the inside of systems to support the narrative that us as vendors are pushing heavily on the AI-driven world or the AI-approachable world and we're starting to see that right now. It took a really, really long time for providers first here in the United States, but now internationally on this adoption and move away from paper-based records to electronic medical records. You still hear a lot of pain from people saying, oh my God, I use an EMR, but try to take the EMR away from them for a day or two and you'll very quickly realize that life without an EMR is extremely hard right now. AI is starting to get to that point where for us, we always say that Olive needs to pass the Turing test, so where you clearly get this sort of feeling that I can trust my AI counterpart, my AI worker to go and perform these tasks because I realized that as long as it's unbiased, as long as it's data driven, as long as it's interpretable and something that I can understand, I'm willing to try this out in a routine basis, but we really, really need those champions on the internal side to promote the use of this safe application. Yeah, well, just another thought here is, looking at your website, you really focus on some of the broken systems and healthcare and how Olive is uniquely prepared to shine the light on that where others aren't. Can you just give us an insight onto that? Yeah, you know, the shine the light is a play on the fact that there's a tremendous amount of excitement in technology and AI in healthcare applied to the clinical side of the house. And it's the obvious place that most people would wanna invest in, right? It's like, can I bring an AI based technology to the clinical side of the house? Like decision support tools, drug discovery, clinical NLP, et cetera, et cetera. But going back to what I said, 30% of what happens today in healthcare is on the administrative side. And so what we call is the really sort of the dark side of healthcare where it's not the most exciting place to do true innovation because you're controlled very much by some big players in the house. And that's why we provide sort of this insight on saying we can shine a light on a place that has typically been very dark in healthcare. It's around this mundane aspects of traditional operational and financial performance that doesn't get a lot of love from the tech community. Well, thank you, Rohan, for this fascinating conversation on how AI is revolutionizing health systems across the country and also the unique role that Olive is now playing in driving those efficiencies that we really need. Really looking forward to our next conversation with you. And that was Rohan D'Souza, the Chief Product Officer of Olive. And I'm Natalie Erlich, your host for the AWS startup showcase on theCUBE. Thank you very much for joining us and look forward for you to join us on the next session.