Featured image for “Gen AI in the Enterprise with Shahzad Zafar, CTO at Trualta”

Gen AI in the Enterprise with Shahzad Zafar, CTO at Trualta

Zach welcomes old friend and CTO of Trualta, Shahzad Zafar on the pod today. Shahzad has always been interested in solving hard problems, which is what drew him to computer programming in the first place, and his family’s background in medicine gave him a particular fascination with healthcare. He kicked off his career at Cerner and has been working within the intersection of healthcare and technology ever since.

Today, Zach and Shahzad delve specifically into how Gen AI is transforming how physicians, nurses, and the healthcare team care for patients. Shahzad highlights successful use cases he’s seen as well as areas to take caution in, driving home the importance of error control and risk mitigation. Generative AI has already and will continue to change healthcare for the better going forward.

Key Takeaways:

  • Enhanced Diagnostic Support: Generative AI improves patient care by providing advanced diagnostics, boosting efficiency, and enabling faster decisions.
  • AI-Powered Chatbots: AI chatbots offer quick, accurate answers to patient queries and assist in scheduling, reducing provider workload.
  • Early Detection and Prevention: Generative AI analyzes data for early detection of conditions like sepsis, potentially saving lives by predicting critical health issues.
  • Personalized Caregiver Support: Generative AI offers personalized education and support, helping caregivers access relevant resources and training tailored to patient needs.

View This Episode On:

About The Generative AI In The Enterprise Series:

Welcome to Keyhole Software’s first-ever Podcast Series, Generative AI in the Enterprise. Chief Architect, Zach Gardner, talks with industry leaders, founders, tech evangelists, and GenAI specialists to find out how they utilize Generative AI in their businesses.

And we’re not talking about the surface-level stuff! We dive into how these bleeding-edge revolutionists use GenAI to increase revenue and decrease operational costs. You’ll learn how they have woven GenAI into the very fabric of their business to push themselves to new limits, beating out competition and exceeding expectations.

See All Episodes

Partial Generative AI In The Enterprise Episode Transcript

Note: this transcript section was created using generative AI tools like YouTube automated transcripts and ChatGPT. There may be typos, slight content changes, or character limits for brevity!

Zach Gardner: Ladies and gentlemen, welcome to the Future. My name is Zach Gardner, I’m the Chief Architect at Keyhole Software, and last year, probably around Halloween, I got a little bit of a wild hair. Maybe it was the ghosts that were in the air, maybe it was the candy that was flying around, but no matter where I went, everyone was talking about generative AI, this generative AI that, and frankly, I was upset. Not that everyone was talking about it, but because I felt like I didn’t know enough about it. I, as a Chief Architect, have to know everything about everything, and this was something that really just kind of bothered me.

So what I did is, you know what most people do, I went out and I was able to find a lot of people across the four corners of the worldwide web that were able to give me their insights, their unique perspectives, their take on what are some of the good parts, what are some of the bad parts, and how should we be thinking about generative AI.

And of course, because I’m going to be talking to people that are employed by companies, I always have to do my little disclaimer. The views and opinions expressed in this program are the views and opinions of the participants and do not reflect their employer, not reflect their trade organizations they are affiliated with, they don’t reflect a grocery store that they might have a loyalty card with. This is just me, this is someone else, we’re just talking.

So today, someone that I met actually, I don’t know if you remember, this was about nine years ago, at a Thai restaurant, someone I met a long time ago recently reconnected with, Shahzad Zafar is the CTO at Trualta. Shahzad, how’s it going?

Shahzad Zafar: Pretty good. How are you?

Zach Gardner: I’m doing pretty well. Yeah, I don’t know, do you remember when we had Thai? It was that restaurant off of like 435. I got the Thai hot and every time I tried to talk, I just had like, you know, just like snot coming down.

Shahzad Zafar: I wouldn’t recommend Thai hot. Thai is very hot.

Zach Gardner: Yeah, no, I mean Thai hot can be very painful, so I don’t think I’ve tried it in probably 15 years now.

Shahzad Zafar: Okay, okay. Well, you know, lesson learned. So for those, you know, you’re based in Kansas City as you could probably guess since, you know, we met at a restaurant. For those that, you know, haven’t heard you at, you know, many of your public speaking events, could you give the audience a little bit of your background? You know, how did you get into programming? Where did you go to university? You know, kind of what were some of the jobs that you did getting out of it and how did you get into healthcare? I guess it’s a good place to start.

Shahzad Zafar: Yeah, well, first of all, thank you, Zach, for having me on the podcast. It’s always fun to talk technology, and as you said in your intro, generative AI is a hot button topic where I had to go learn about it a lot myself just to kind of see how we apply it in our products and, uh, just for as a technology nerd, it was fun to learn about it as well. The hot button topic, um, background for me, um, so, uh, I grew up in Pakistan, uh, and kind of throughout I always had an interest in computers, uh, not where I was in deep programming so I did not program through high school or middle school or anything like that. Um, I mean, I remember my first introduction to computers was learning Lotus 123, if you remember, uh, which is the precursor to Excel, uh, and, um, and working with DOS. It was just very interesting, so I worked on the floppy disk era too, if I’m dating myself. Um, but really got into, uh, just it was interest of what computers could do, was always fascinating to me. Um, so I came to University of Michigan in Ann Arbor to do my bachelor’s in Computer Engineering and that’s where I really got deeper into the the knowledge base of computer science and what I could do with it. Um, I think you were asking the first program I wrote, it was like a, like one of those standard, you know, ComSci 101, uh, board game type of thing, uh, which is fascinating. I used to play that game all the time after I wrote that program. Um, but that’s where I really kind of honed in my interest in Computer Engineering and, and, um, always been interested in solving like hard problems, like, uh, thinking what we could achieve with that. And Michigan had a wonderful set of opportunities, including working on the Michigan solar car team, which was, again, like random but like required a lot of programming to understand weather and all the other things, how do they impact performance, so just different applications you could do. Um, graduated from Michigan and my first job out of college was at Cerner, which is, uh, here in Kansas City, uh, now called Oracle Health. So as a software engineer started off there, um, my interest was always in healthcare just, um, dad’s a physician, just kind of from that interest, I was always interested in health, didn’t want to be a physician but was it just a genuine interest of how could we do healthcare and, um, the more I learned about it in the United States, it’s a big, actually everywhere in the world, it’s how do we optimize it, how do we make it better, it’s a huge problem and it’s something very personal. So, uh, for me it was like what technology field I can get into where I’m building cool things, solving tough problems but at the same time, um, you know, something that’s more personal too, more more inspiring for me personally. Um, so that’s how I kind of got into healthcare, uh, from first day out of college and I’ve stayed in healthcare for throughout my career, so now 18-19 years almost, um, it’s all been in healthcare. So at Cerner did a whole bunch of different positions working on the core EMR side, uh, but within that worked on different parts of the EMR, held various roles and it was not like a straight path, like where I was software engineer one, software engineer two or anything. I did software engineering, I did project management, I became an architect then became an engineering manager, just a whole set of different roles and responsibilities, um, kind of helped get Cerner’s first cloud platform off the ground. Um, and then left Cerner in 2018 to join RX Savings Solutions, uh, uh, which is again Kansas City based healthcare startup at that time. Um, joined there as SVP of engineering, leading all the product development operations, uh, doing a, again in a small company you do a little bit of everything, uh, sales engineering, which was new to me and had to learn how to do sales engineering, uh, but it was fun. Uh, that was kind of my first foray into a lot of big data, um, applications in terms of how to do science data analytics. Um, grew that team out, um, from a small team to 300 plus people where in 2020, uh, my years are getting mixed up, 2022 is when RX Savings got acquired by MassMutual. Uh, I was a CTO at that time, so a couple years into RX Savings became the CTO. Um, had a wonderful time, a wonderful team and most people still there are just, uh, awesome. Um, and kind of a year into the acquisition is when Trualta reached out and it was a chance to go back to an early stage company or earlier stage company. Trualta is a caregiver platform, we provide caregiver education and support abilities. Uh, for me again, it’s a very personal thing of like helping people get better and provide the care they need, keep people at home, your patients and your loved ones at home longer and I get to build a technology that enables that. So, so it’s a niche problem, it’s a tough problem, but it’s something we are excited to solve. So I joined Trualta in October of last year and been here for about, uh, six months now and it’s been growing and I’m the CTO at Trualta as well. Uh, and it’s been great working with this team so far.

Zach Gardner: Very cool. That’s funny, I didn’t realize your, your dad was a physician. My mom’s actually an RN and, uh, they have a much harder job than we do, like any day of the week. You know, we, we always complain about dealing with, you know, the business and product owners and developers, like that’s nothing compared to an unhappy patient.

Shahzad Zafar: Absolutely, absolutely. And it’s interesting that, you know, kind of looking into Trualta, I noticed, you know, there’s the education component to it, there’s the support component, both of those have been really common themes that have come up again and again and again when I’ve been talking with people about generative AI. From a support standpoint, being able to have, you know, chatbots, you know, everyone’s always wanted a chatbot, but they’ve always been sort of prohibitively expensive to develop to maintain, but now we have these LLMs that are just lowering the barrier to entry. And then education, being able to use something like retrieval augmented generation or RAG as the kids call it to be able to answer questions based on just huge, huge amounts of information and something that would be impossible for a regular person to do. So I’m curious if you could talk a little bit about how Trualta’s looking at leveraging AI and specifically generative AI to kind of address those two problems.

Shahzad Zafar: Yeah, so, um, it’s a good question, I think that’s something, you know, at Trualta we’re figuring out ourselves, um, and like most companies, you know, you’re trying to get to the value of generative AI in a responsible way and at the same time, you know, how do you quickly leverage it for our use case? Um, and especially for a small company, it’s a little bit harder to take the time out to do that. But for us, you know, if you kind of take a step back, one of the problems that we’re trying to solve is, you know, how do we provide actionable and useful advice to our caregivers in the moment they need? And that often means, like, one, we already provide a rich library of content for caregivers for different scenarios they might face and the number of things that they might face is very broad and it’s tough to say you will cover everything, but we try to cover a whole set of things from behavioral care to ADL skills, um, and a lot of times people also just want, you know, some connections to their community. So if you think of like caregivers, they’re always asking about, like, what resources are available for me, um, how can I deal with this particular situation? I think there was a survey out there that 70% of caregivers said they feel overwhelmed and they often feel overwhelmed because they don’t know how to deal with certain situations. Um, so for us to, like, think about it, like, okay, if we take our library of content and kind of augment it with the generative AI capability, that’s where it becomes really powerful because generative AI in its own is very powerful, but it could also be really random. So, like, for us, it’s like, okay, how do we provide our caregivers the best possible resource that, one, is already vetted and trusted, which is our content, and be able to say, okay, if you’re searching for, like, let’s say, dementia behavior, it gives you a subset of that content. But now, like, if you’re going more nuanced, like you’re saying, okay, my loved one is wandering, what do I do? And you’re asking, like, a chatbot, um, what are some of the techniques? So we can augment that with our trusted content, and now the caregiver can get a response that’s accurate and factual, uh, which is grounded in real content, um, and you can mix and match the generative AI with the specific content for the user in that specific moment of need, and I think that’s where the power of it is. Um, the other thing I think we think about it is, like, you know, more from a support and understanding of it, the caregivers’ actions and, you know, is this helpful for them or not? So again, providing, like, the RAG type of capabilities, you know, where the kids call it that, but, like, it would help, like, find a specific set of, um, articles or content that we already have and be able to present to our users in a much more natural way, um, and at the same time, kind of thinking about how do we incorporate that into the workflow without them feeling overwhelmed by it or without feeling that, oh, they’re talking to a chatbot versus they’re getting, you know, actual value out of it, and I think that’s a balance that you have to be careful of. But those are, like, the two main areas we are thinking about, like, how do we leverage the power of generative AI to give them the right resources and support in the moment? Um, and then also, like, more internal use cases of, like, data analytics and things like that. So, so there’s just a lot of areas you could do, but I think the focus should always be, like, what’s the user need, uh, the customer need that we’re trying to solve and then go from there, rather than saying, oh, let’s just do generative AI and then you can lose your path very quickly.

Zach Gardner: You know, it’s funny that you talk about sort of this need to focus on the problem and then the solution second, because as I’m talking with all these different companies, all these different organizations, everyone’s using it for something different. You know, you have people that are looking at it from a, hey, we’re going to create software and the code’s going to write itself. I don’t really know if I believe that. Uh, I’ve seen people that are using it for transcription of meetings, uh, being able to have an agenda, a timeline and pull out action items, um, and then you also have people using it for content generation. For a company like Trualta, it sounds like you have to have a pretty solid mix between how you’re approaching generative AI because you don’t have the budget to just say, “Well, we are going to implement it everywhere and see what sticks.” What are some of the trade-offs that you’ve had to consider as you’re looking at how to apply generative AI in the best way possible for your product?

Shahzad Zafar: Yeah, I think, you know, as I mentioned, like, for us, it’s very much about where does the value need to be and how do we get that value quickly and make sure it’s useful for our customers. And you’re right, as a small company, you don’t have the luxury to experiment with a lot of different things. So for us, it has been about figuring out the most impactful use case, and I think the trade-off is always like, how much investment do you want to make into a solution that might have a long-term value versus something that might give you a short-term gain. And I think the balance we’re trying to strike is, you know, the short-term gain is like, okay, we can provide better search capabilities with our existing content and augment that with generative AI. But the long-term vision is like, okay, how do we create a more personalized experience for our caregivers and how do we create something that evolves with them and adapts to their needs? And that requires a little bit more investment. So I think the trade-off is always like, you know, do you spend the time and resources on the short-term solution that might give you a quick win, but then you have to think about, okay, how do you scale that and how do you make sure that it’s maintainable in the long run? Versus, you know, focusing on the long-term vision and making sure that you have a roadmap that kind of balances both. So for us, it’s been a lot of, you know, discussions internally, like what’s the best approach, and I think the consensus has been, you know, start small, start with something that’s impactful, but also keep an eye on the long-term vision and make sure that we’re not losing sight of that. And I think that’s where the balance is, is always tough, but I think that’s the best way to approach it, at least in our case.

Zach Gardner: Yeah, that makes a lot of sense. So, looking forward, what do you see as the next big challenge for Trualta? Not just in terms of generative AI, but just in general, what’s the next big hurdle that you guys are looking to overcome?

Shahzad Zafar: Yeah, I think for us, you know, the next big challenge is really about scaling and making sure that we are able to provide a consistent and valuable experience to our users as we grow. You know, we’ve seen a lot of interest and a lot of uptake in our platform, but as you scale, you know, the challenges become about, you know, maintaining that quality, maintaining that level of support, and making sure that, you know, we are able to adapt to the needs of a larger user base. So I think for us, it’s really about, you know, how do we scale effectively, how do we make sure that we are able to provide the same level of care and support to a larger number of users, and how do we continue to innovate and provide new features and new capabilities without losing sight of the core value that we provide. So I think that’s the next big challenge for us, and it’s something that we’re, you know, actively working on and thinking about every day.

Zach Gardner: Awesome. Well, Shahzad, thank you so much for taking the time to chat with me today. It’s been really enlightening to hear about how Trualta is leveraging generative AI and what you guys are doing to support caregivers. I think it’s a really important and valuable mission, and I’m excited to see where you guys go from here.

Shahzad Zafar: Thank you, Zach. It was a pleasure talking to you, and I appreciate the opportunity to share our story.

Zach Gardner: Absolutely. And for our listeners, thank you for tuning in to this episode of GenAI in the Enterprise. We’ll be back soon with more insights and discussions on how generative AI is shaping the future of business. Until next time, take care and stay curious.