How AI Agents Are Giving Clinicians Time Back - Zyter TruCare CEO

So for example like triage documentation you know prior authorization which is a very kind of written process with a lot of business process that can all be reimagined with agents very very quickly and it's happening now we delivering some of that but it extends this possibility without having to do a lot of modernization but now more than ever you don't need to invest in tons of money to modernize your systems to get the value you can start embedding AI and be in a thoughtful way start to scale the process is end to end. >> Hi, my name is Demetri Bonichi and I'm a content creator, agency owner, and AI enthusiast. You're listening to the AI agents podcast brought to you by Jot Form and featuring our very own CEO and founder, Idkin Tank. This is the show where artificial intelligence meets innovation, productivity, and the

tools shaping the future of work. Enjoy the show. Hello and welcome back to another episode of the AI Agents podcast. In this episode, we are interviewing the CEO of Zider True Care, Sundar. How are you doing today, Sudar? >> Great to be here. Thanks for having me. Doing really well. >> Awesome. Well, I appreciate you um for making the time on the show. Would love to hear a little bit just to kind of get started um kind of how you got into the world of AI. >> Sure. World of AI. So [clears throat] I would say way back when donkey years I started I was really good in math and uh luck would have it I got into a group uh that was doing uh computational modeling in MIT in you know physics and material science and so that's how I got in uh to

really thinking about uh how do you have an hypothesis how do you really model that and how do you do simulate how do you simulate real world results else and then you know either through the models or digital twins and um you know you either prove your theory right or wrong and it has led me to a deep belief in like what is what is explainable. You could luck into a lot of different results but unless you really had a basis to prove your theory very clear way it uh you know it was not uh useful right so my earliest exposure in AI was really you know uh exposure to uh explanability if the simulation couldn't explain its reasoning it wasn't useful and um and and then lot of different business experiences since then um so I got into consulting And uh you know during

co uh I've done a lot of work in healthcare and we were building behavioral and epidemiological models to simulate covid progressions using digital twins of you know US population but also um you know the science of the models and again the repeated lesson was you know how do you it's not really there's a lot of issues with data there's a lot of issues with um you know how do you really simulate the problem but most of it uh in order to get adoption was an explanability problem. We didn't have a data problem. I'm going to explain the lesson really stayed with me and um you know and then I've done a lot of consulting for Fortune 500s and digital transformation and um you know the crux of how do you draw business value from any technology not just AI because when you look at it

Dimitri there's a lot of massive tech spend that goes on right now it's the wave of AI but the last 20 years there's a lot of uh tech spend and you you know ERP, CRM, RPA but you know while it's a it's not while you can't dispute that consumer B2C technology evaluation has really helped right like we use iPhones we our ways of life are very convenient but on the business side it's quite not the same right there's not as much value that's arrived on the business processes and so it led me to have a deep kind of belief that how do you solve a business process is dead and how do you solve for broken workflows and uh not just from how do you embed AI doesn't fix broken workflows it magnifies them so that's what led me to get to where I am

which like um the most complex of industries healthcare and zider and zider trueare services clinicians as they hope to achieve their mission in serving their patients right consumers us so we are an AI company that um is really our mission is to drive outcomes not just features and functions uh or just point solutions. >> Yeah. No, I think that's a very fair comment about the you know workflows and how you know if they're bad they do cause problems uh practically they don't just um get fixed with AI. Can you kind of dive into that a little bit more? uh especially with what you guys are doing and and maybe how um your solution coincides with that issue. >> Yeah, absolutely. So I think there are few things before we get into our solutions even like one of the things look I mean it's undisputable that

AI is going to is kind of the technology of our life right and it's going to be one of those shifts that's very profound but if you see in the past for something that's happened quite the scale of this and the lessons from history repeat itself right if take away the buzzwords and all that when you look at it like let's go back in time for a little bit so we understand how this problem originates now how we can solve it like take electricity for instance right so you know when electricity came about I and I went research for three decades for three decades the productivity improvement didn't happen so there was a big bus 30 years plus nothing changed nothing changed Oh shoot. >> I'm not saying it's going to take three decades for the AI value to arrive. >> No, but that is

a crazy thing. Yeah. >> So, but why did that happen? And uh you know, I think that this is the productivity paradox. A lot of people have studied it. But the way I internalize in my brain in a more simplistic way is you know what happened is that these early factories that were set up to you know for steam engines and all that they just swapped it for motors with local power distribution is the kind of the gist of how they laid out the factory flows and so when electricity arrived they didn't redo the process end to end they just put electricity into the same flow layout right and what happens when you do that of course there are no gains in productivity. You just flowed electricity through a bad process, right? And um it takes hard work to reimagine the process. And it took

Toyota to arrive a lot of years later to introduce really reimagined workflows which distributed cells and flow and human machine collaboration and real you know versus this assembly line thinking. And so transformation didn't occur from adding power. It comes from rearchitecting the workflow, right? Just to anchor the point I was trying to make. And I think we are in a very similar moment here, right? We are all everybody's waking up thinking about like how do I add AI to my workflows? That's the wrong question to ask. It's like how do I really think about solving for my outcomes given what AI could accomplish? Right? If people had asked that question in electricity until Toyota did, nobody did. And then you could have gotten to different productivities that that lesson repeats itself, right? Personal computing, you know, PCs existed honestly before Apple, but it weren't really

accessible, right? Apple designed it for humans. So it's more intuitive and visual and more personal and so then adoption happens, right? So you have to reimagine the workflows. You have to really plan for humans working with the technology to you know so it's working for you not the other way around right and um and then you have to create trust right I think cloud we've seen a lot of spend go through the cloud in the last few years but cloud existed but enterprise didn't trust cloud and you know I think AWS came along and built a trust layer through security compliance transparency and all that right so that you know technology could shift So my point about AI is like electricity you have to redo the reimagine the work whatever fancy terms we use most people say transformation embedding AI work on use cases all

the stuff but they are not fundamentally asking how to redo the work it's hard right because these have been built up over decades and um like PCs you got to figure out how do you deliver on a more humanentric kind of adoption and then you know how do you make it trusted. So I think back to how do we see um see that play out with our solution. So first of all a little bit about Zider we are uh we serve 45 million members in healthcare. Our core platforms um you know provide utilization management, care management, population health management. So anything to do with managing the cost of health care where clinicians and nurses are trying to manage a population help um people direct care etc. our popular our platform can do that and with deep expertise in clinical workflows. But what symfony which is

our agentic AI and our um sort of AI workflows do is the same thing principles I was talking about from the age of electricity which is how do you create a modular orchestrated system of AI agents that are not just solving one-off use cases right if you take a current process and embed hey I can do just document summarization here I can do some automation here I can do a chatbot here it's not going to help. It's only going to add to the tech debt and the business process data end to end right maybe at best someone gets a bigger bathroom break but it's not transitive right and I think you know AI can be helpful it improves some user experiences and gives a little bit more productivity that's not fundamentally anything different and it would be the story of electricity and no productivity gain

and so what we doing is more multi- aent systems that orchestrate so that's what Symphfony is it It looks at the end to end workflow and how stakeholders are participating. How do you really do that and how do you really keep humans in the loop and uh you know so the decisions are trust. Yeah, that's um I really like that story. I thought it was I thought it was pretty intriguing. So thanks for that. I I'm going to keep that one in the back pocket in regards to the the adoption uh stuff because I feel like a big topic right now with AI is, you know, AI exists. You know, there was that whole article this summer that dropped that was talking about how >> I don't know was it like 90% of companies that were implementing AI. Yeah. >> Not >> Yeah. >> Yeah.

The value gap's big right now. So um how did you I guess personally um find this your way into this like intersection of AI and healthcare and like what motivated you to want to tackle these complexities of the healthcare sector specifically? >> Yeah, it's a great question. See there are um you know what is it Maslo's hierarchy of needs you know food shelter whatever like fundamentally you know as people get more sophisticated you can get to consumer industry to get different kind of goods or products uh in B2C you can have luxury industries that cater to different things but everyone everyone has got to is you know have a better experience in healthcare right everybody wants wants to live longer and live a h happy and healthy life. And unfortunately though given this like complex way here we are right we've arrived at a situation

and a system that's very siloed that has a lot of siloed in the sense of data sharing is not quite wide right people have trapped data unstructured data in different enterprises regulations and privacy concerns are foremost which is very understandable right But um and and and and modernization of these old technologies and the digital codes are going to be very significant investments that uh people don't have the money to make. And we are here postco at a enormous affordability crisis. I mean incredible affordability crisis. If you project any of these projections, we cannot afford the way that the healthcare spend expendes growing right and so then what do you do? And consumers are not having fun or [laughter] great experiences. So somehow we've arrived at this but everyone is unhappy with it but I do think we was bad idea ex not ideal but exactly

so but um so how did I arrive at AI and healthcare like I talked about like you know I've been in healthcare um uh for last 25 years and what strikes me is this first is like the problem statement I stated on 90% plus value gap I'll start there and get into healthare Okay, that that's a problem statement that is quite wide even beyond industries that the technology spend doesn't really rearchitect the business process is my fundamental kind of way of internalizing why the value hasn't arrived. We haven't been able to reimagine the business processes contemporary to what the technology could do. So it's not the technology that's the issue, it's the human imagination and adoption that's the issue right at hand. And um and then you go deeper into healthcare, it does arrive with this kind of regulation complexity of the current state systems

etc. And so past technologies have uh solved problems in use cases, right? Like I I I've worked on use cases where you go do collect data, you show the causality, explainability to solve a specific problems and then the real world hits and it's a very small problem in a very complex ecosystem. So you don't have any meaningful impact, right? Like it's very small and micro scale. And so fundamentally then if we were to say okay forget about this let's look at something that's more end to end in healthcare and how could this work um somehow then you know it it the answer is not like complex to understand it's um it's really how do you get the best of data to understand what's the predictive next step and how do you get AI agents to you know help humans take these actions in a very

timely and meaningful way that if you model that kind of a system it'll be probably you know we've done different kind of scenarios it'll be probably you know 1/5if the cost of what we're doing and much better customer experiences etc then the question is how do you get that how do you really what's the future where agentic AI offers that you can get there and I think I'm very excited about something that's very distinctly different about this current AI movement which is you know this power of cognition that can be embedded in every node, right? So it's not like you have to define all the business rules in every step of the process. So when you start to rethink this process end to end, the cognition you can place in different nodes through the agents and agent AI and the multi- aents coming in, it

can solve problems within kind of defined boundaries more autonomously. And so then the question is how do we um so so so for example like triage documentation you know prior authorization which is a very kind of written process with a lot of business process that can all be reimagined with agents very very quickly and is happening now we delivering some of that but it extends this possibility without having to do a lot of modernization. There is still a lot of burden on like how do you make sure your data is ready? How do you make sure you have the right architecture for safety? But now more than ever, you don't need to invest in tons of money to modernize your systems to get the value. You can start embedding AI and be in a thoughtful way start to scale the processes end to end. And

I think that's exciting for healthcare because uh there's tremendous amount of value to be unlocked from that. >> No. Um absolutely. And uh I I definitely think there's there's a definite need as you mentioned Maslo's hierarchy. There's a definite need for something uh like this. there's a definite need for AI to to help out people um in the healthcare industry because practically speaking, I mean, I I I' I've heard, you know, I'm sure you've heard I've heard there's just a lot of people struggling with kind of the costs and everything. I I run my own business. The premiums aren't crazy cuz I'm younger, but like as I, you know, get older and have uh and have kids, like it's going to be wild. Um so, everyone's struggling with the care, the cost, etc. So, I think it's a very good place and I' I've interviewed

a couple different people and I do think this is where the intersection of AI could be really valuable um industrywide um that I don't think a lot of people have necessarily um considered in the general day-to-day conversations about things, right? I think most people are focused on and rightly so like general business applications and you know emailing back and forth and like task management and like content output and stuff. That's kind of the main things that you notice. But I think healthcare is really really where it could uh make some universally good waves for people. So just to kind of further that thought a little bit more, what are you guys practically doing um to helping out in this just to get to dive deeper into like your product and what you guys do so that everyone get more of an idea. >> Yeah, great

question. Absolutely agree. So let's take an example to bring this to life, right? So um you know the the industry has a very common process called utilization management or prior authorization today right. So what happens today is to the extent that you know the available information is there when when a when a member goes to a provider or a doctor and it can be approved it can get approved but many times what happens is that the there's a lot of back and forth between the insurer or the risk bearing entity and the health system or provider or the doctor's office and for getting an approval before the service could be performed. Right? So what happens is they send either fax or sometimes electronic but many times fax is still that's reviewed by a clinician or an medical director and uh they they have to match

eligibility requirements. They have to understand if the benefit is covered. Then they have to look at medical necessity to apply guidelines the evidence-based guidelines to see if this is actually necessary care because a lot of times the care that's being administered is unnecessary and it creates more complication more spend and so so they have to go through the decisioning on that and then when you go through that there may be information from the medical record that's missing right that is required to then they reach out to the provers's office and many times there's not like sometimes maybe there's connectivity with EHR that you and message them electronically otherwise somebody has to call the doctor's office and the doctor's office they're not they're in the middle of looking at somebody else so they're not able to answer them so they have to return the call then

you get the missing information you have to go through the process to redo the workflow so it takes time it adds administrative burden and meanwhile the patient or the member is waiting for all this look at now what AI can do right it's not just these kind of like very straightrough scenarios all these complex scenar scenarios with peer reviews and data going back and forth and reviews that need to happen at when you look at this end to end process. What we are able to show is that bringing in 40 agents, not one or two, 40 agents working on behalf of one clinician, they can streamline all of this, right? And when they do this, when the when the AI is working in tandem with the human with a lot of responsible AI layers built in, the human is still getting so they're reading the

document surfacing the first summary. They're saying whether it's eligible or not. They're saying whether it's benefits covered or not. They're already applying the clinical criteria guideline to suggest what might be the they're saying is the missing information. They're actually fetching the missing information from the EHR and doing the redetermination on the fly. They're notifying the pro. It's end to end, right? So all these edge scenarios when 40 agents can work on behalf of a clinician it gives an enormous lift to the clinicians right so it's the question is not about um how do you really um replace the clinicians the question is about how do you give relief to the clinicians right and with all this administrative work that's happening so they can actually apply it to either counseling or looking at care guidelines and accepting and and practice at the highest of their license.

Right? So that is that is dimmetry that workflow I just described is 80 to 90% more efficient and the turnaround times improve by like multiffold and the patient gets what they need right away. That's the important that >> I think that's really important to call out. um that percentage one crazy very good um two what does it kind of give clinicians like time back for because I' I've heard different things on this would love just to kind of hear more context on that perspective from you >> so here's the thing if we if in this first of all uh I think we you know if we step back clinician capacity is a pretty significant issue in the industry right we need more clinicians and we need more clinicians focused focused on helping members stay stay healthy, not just overwhelmed at taking the volume for an

event that comes in, right? So, um there is not enough um care management, population health management going on. So, if you know that this needs to be done anyway and we are able to get it automated and the clinician agrees and get it done right away, right, which is what right now the system is dragged down on, right? the system is set up for just, you know, being compliant. All the resources take up the time to just do that. When you automate all that, you're going to be having a lot more compliance. But then now you can really engage with the members or the patients with the care management programs. that was always being the intent on and you could actually think about how do you really help them stay healthy and the incentives will be also aligned because then you'll spend less the insurers

makes more and the provider systems make more right so because they're spending time with that right I'll give you a very real example like my personal example um you know I have intermittent back spasms right so I go try to you know and when that happens s I'm kind of like shocked, right? I can't do anything. It it affects my productivity quite a bit and to get the approval go get to see the PT, I have to drive somewhere, do all this, right? And then it's one session and then I have to be compliant with that session which you know like with daily life etc. I get a but now I actually am using a digital therapist. It's fantastic. it basic there is a there's a care team in which an AI digital therapist part of this there's a tablet that comes with that right

and and the and there is a phys physical therapy therapist also as part of that care team that um she messages with me back and forth right but I mean in this whole interaction over the last two months probably she spent 15 to 30 minutes with me because all the other work is being done by the digital therapist that's part of that care team and with the tablet so it it is monitoring it's keeping me compliant right I'm doing set of exercises every day and it's looking at my posture giving feedback it's taking my feedback preparing care plans giving it to the physical therapist and she's redesigning the program based on these inputs that we we're having and look at how many such patients that physical therapist probably able to support because the tablet and the digital therapist giving an you know um leverage for

that physical therapist right so that's the mindset we need to get in. I'll give you a more simpler example to kind of nail this down. You know, we used to go to um you know what our checkout lines and we used to stand in checkout lines. It used to be a time we used to stand check for a physically a person to do the checkout. Right now the philosophy is there are self-service checkouts but there's still a human in the loop. Most of these self-service checkouts when you see there's a person that's watching if there's an issue. If there's an issue with the system they'll come in. So this is the mindset we need to go with care teams right. So it becomes a team AI agents are part of the team and nurses clinicians are part of that team many times. So, so the

patient or the member, the caregiver or the nurse or clinician and AI agents are part of one team. And in this team construct, many times the AI agents might be in the front communicating with the member with the nurse being informed or watching it. The human nurse or clinician being informed or watching it. Sometimes it might be a live interaction that the human person is having with the member with AI enabling that. So it's an it's this kind of mindset we need to go to and then but every but they're always looking at each other and we're all watching right. So I think that's a very highly leveraged model and then you know going back to master's hierarchy of needs then how many patients can be like you know I like how many folks are having physical pain that can get this kind of support

right I think that's the way to untap the potential of the clinicians to its fullest needs aligned to members goals >> yeah I mean truly uh I feel like this would maybe make the adjustment uh for the clinicians to feel like they're giving healthcare more like more than health catching up. Um cuz I I don't know you know any doctors or nurses personally. Um that's what it feels like they're always trying to do is just play catchup on different things from an administrative perspective most of the time. >> Absolutely. They are trying to stay ahead with the cues and just play catchup and the extraordinary administrative burden that we place on these humans is just enormous right and so it's not just a cost perspective it's a burden that actually comes off their shoulders so they're actually supported is the way I look at AI

>> yeah they feel like they can do their job rather than do things that enable them to be able to do their job it's a very interesting like catch22 they kind of get put in when they become come a become a clinician. I will I will say something that does it's not a concerning thing to me but it is a curious thing to me. How is the market uh kind of adjusted um and uh handled things in regards to like compliance with this right like how does how does that all chestnut going to go? >> It's a great question. It's a great question. So first of all trust is not um so we did a study on this as well. I'll talk about it in a little bit. So look, I think what clinicians f first of all it has to be set up in

a way that the human is in the loop. Um because otherwise we did a consumer survey and study as well and we did a study of clinicians as well. What consumers are telling us is not that they'll reject the AI. They're saying they need the explanability and they need a human in the loop. then they're willing to accept the benefits of an AIdriven system and from an um from a clinician perspective for this to be compliant with you know just not just regulations with privacy etc which has to be very highly secure safety data sharing is utmost uh concern and all of that you know the infrastructure exists to do that but then more than that even when a human is in the loop for the clinicians to trust the recommendation from on the AI there are three things that matter. This is what the

study showed right. one of our um you know PhD data scientists along with some um health system collaborators did this study and the study was simply looking at clinicians using AI and what drives overrides right so you know low confidence predictions get overridden 99% of the time and when you show the explainability so transparently how the AI came to that conclusion in a very simple way and show why the result is to be a high confidence one the overridden went down to overrides went down to 1.7%. 99% to 1.7%. So, so completely different picture on overrides, right? Yeah. It's published study. And so, what it was saying is that doctors and clinicians weren't rejecting AI, they were rejecting uncertainty. And so, the way to solve this problem is first put clinicians always in the loop. Human in the loop. So, AI is not autonomously deciding.

It's recommending for the clinicians and making the administrative burden last for the clinicians. then you have to work on um really explainability which is the I started with that right in anything from research to anywhere if it's totally a black box nobody's going to trust it no matter how good it is not going to be trust so better systems that shows the rationale and the reasoning for the decisioning and what's the evidence base against that decisioning and rendering that in a very simple human experience so they don't have to go digging and doing our own research to find the explanability very prominent explanability. And the third is how do you get the confidence factor of the recommendation very high by showing that multiple models converging to the same recommendation and that it's a groundability that it's repeatedly asking with different prompts the same question leads

to the same answers. When you show those three things, the clinicians override go down, the compliance is very high and and you know they can do their job. So I think that's the key in making making sure we're creating very trusted systems that can be effective in you know doing what it does. >> Yeah. No that that that makes a lot of sense. I do think transparency is key um in any context let alone this one. I think that made that that to me is is perfectly fair. Um you know since your platform is already using AI to automate workflows where do you kind of see AI agents heading in the next few years? Right. Obviously, AI agents right now are doing really valuable things um for companies that are effectively using them. Um regardless of what that stat says, I know for me they're

doing a lot. Um granted, I'm in a bubble. I run a tech podcast about how AI AI agents work, so I get it a little bit more, but the, you know, practical implications of where AI agents are going in the next few years. What are your thoughts on that? I think we are in the cusp of a pretty significant singularity or dislocation from an AI agent perspective. Honestly, um I'll get back to healthcare in a second. There's an article that a few researchers from MIT Exor did about the what they call it as a coalition singularity. I'll simplify it. Essentially, you know, businesses have a lot of processes and workflows because of friction or coordination or decisions that need to be taken, right? That's the fun fundamental reason it exists. and the cognitive skills of these AI agents and how fast it's progressing means that

the cost of this kind of friction and coordination is going to go to go very quickly to zero. What I mean by that is and we're seeing this the the point I was making on looking at that end to end process and prior and looking at it as like it can be 80% 90% efficient um in making the same decisions more much more instantaneously. Think about it like extrapolating that to all these complex processes we've created uh in all these businesses with agentic AI and the kind of cognition that's coming in is going to take those processes to be much more like closer to a cost of zero and all these workflows going to get reimagined very very fast. So the orchestration of work is going to happen very fast through agentic AI and even even if I assume there's going to be no progression

of cognitive and reasoning skills from where it is today which is an extraordinarily modest assumption because every 3 weeks something comes out that beats something else. Even if you assumed it still is going to happen because it because something fundamental has happened which is that you don't have to define everything up priority in terms of business rules for these agents to understand and this reinforcement learning from human feedback is going to progress in a scale that we've never seen before and these processes are going to get to closer to cost of zero. So businesses that really adopt on this reimagination journey are going to create some extraordinary value props for consumers and uh you know I think they're going to see either very low price points and different products coming out or extraordinarily you know significant uh value proposition that consumers haven't seen or businesses

haven't seen come about when these kinds of processes take hold that are that can be autonomously executed at a cost of zero. Yeah, I think that's um that's a fair point. You know what uh I mean just to speak to it, the flagship models that exist, right? So software engineering is a big thing obviously in this whole component right now. Um >> Gemini 3 Pro was released recently, but then uh you know, we all knew Opus was going to be the flagship the second it released an update and then a week later it releases an update. I don't know if you saw they reduced their pricing significantly. >> Yeah. um on the new flagship model. Um and I think it kind of funny timing that you mentioned that, but it it seems very apparent to me things are going to continue to get cheaper. Um

things are going to continue to get better and it's like only a matter of time uh like you're saying. >> Yeah, you you brought up a great point there. So so like even you know the more on on just that problem of coding, right? and taking that kind of use case in a problem set and what has been like I think geminy 3 and this tool anti-gravity for as a coding base and you know but even there are other tools uh that are out there I think this con even in the last 9 months 12 months the concept has been this kind of idea of a co-pilot that's helping or a chatbot that's helping people code right that that what that was the concept but that concept itself is getting broken because these newer tools and these advances coming in, you can define of course

it's initially prompt driven in the sense that you give it a problem statement but then it's able to solve like pretty it you know recursively and create products against that problem statement versus this kind of logic of just a co-pilot kind of helping some human create. So I think this level of autonomous kind of decision- making you know of course it has to be done in a way that it's responsible and managed and the end output is uh stress tested but that kind of productivity gain that's very real even from the last two weeks announcement is just extraordinary. >> Yeah it is. Where do you think um your company's uh vision um is right now to kind of end up uh like what's the final or not final goal but like what's what is the the goal for the next 5 years to accomplish uh

and with the ethos of of your company? >> Look, I mean we are very committed to uh single point which is we want to help businesses be part of this reimagination of the workflows. We want to help create the Toyotas that took advantage of electricity, right? Not the ones that kept their processes the same and did some, you know, just poured poured electricity through their current layouts. And I think that is going to fundamentally drive a pretty significant revolution on the global economy. And the way we do that is through Symfony and the sandbox and a tool that we provide for businesses to be able to really help reimagine that what they do in in a way that they can learn with us. The platform provides the ability to learn, create your own agents, create your own different kinds of workflows and get to the

best outcome possible, right? And that's a continuous journey. And that's the continuous journey we are with our clients on and healthcare is a fantastic place that we started but it's not just in healthcare that we um we have the aspirations on we are already helping clients with like anything regulated anything that's you know very complex anything that has multiple stakeholders anything that has a lot of friction which is a lot of play lot of where uh the global economy and the dollars are tapped they're going to get reimagined and we are providing the platform to create multi-agent workflows and it could be that there are mult multiple advances in AI that takes even generative AI to this next stage and it could be world models it could be whatever right but it's undisputable that the learning curve of AI is going up very fast and

we are providing the platform to keep up businesses to keep up to reimagine their work using how you bring in the AI to really drive outcomes and that's kind of our vision and that's going to stay and we're going to learn it's a very you know we we keeping up with what are the advances that coming up and very quickly figuring out how do you get that from the labs to the real world processes in a very responsible way, right? How do you give the sandbox for clients to build their own agents and really redo their workflows? >> Yeah, makes a lot of sense. One last question kind of to make it a more fun one because I do like to ask this question kind of as we get towards the end of episodes. What is your personal favorite tool um when it comes to

just general AI use for yourself? >> Um I like chubby a lot. I have to tell you it understands me a lot. >> I must admit I like it. It's it's the it's cal it's everybody says like I mean I'm sure there's a lot of it's very tight and a lot of usage goes but like what I'm amazed at I use all kinds of tools but the level of personalization that's happening on chat GPT um I'm always very excited and you know I'm like you know I'm a f father for two daughters and so my I have a newsletter called student of life so it's all about AI leadership but also parenting how do I mix these things you Now, it's like, you know, bedtime stories to parenting advice to it's it's gotten into a level of personalization that's very very, you know, it's very

shocking and I think um it's a fantastic tool. >> It is. No, it absolutely is. So, with that being said, just to kind of close that out for everybody here, um, please let everyone know where they can find what you guys are doing over there at Zider. And, um, any other final plugs you'd like to end the show? >> First of all, thank you for having me. Fantastic discussion and kudos to what you're doing because we need more more of this out there so people can understand what and learn from each other. And it's not just a it's not like you can get it from a reading a paper or something, right? This is a whole movement that's very amorphous and we have to learn from each other. So, thanks for doing this. I'm a big fan and um yeah, I think two one quick

message. I mean AI won't transform your business because you bought the right tool, right? It will transform your business because you've learned to redesign the system around it. And that's the primary message we are aspiring to help businesses with. You can find more about what we're doing at zida.com and uh you can find a lot more about our product called Zido Symphony which is a platform that uh can you know integrate with existing digital tools and help people reimagine the process end to end and uh agentify your workflows and thank you for having me. >> Absolutely. Well, I appreciate you for spending the time here today as well as I appreciate everyone else who had the chance to watch. If you like this episode, make sure to hit that like button, um, subscribe, and also to both you here, Sunder, and everyone else listening, make

sure to leave a review on Apple Podcast and Spotify to help the, um, algorithm boost everything they're doing over here for healthcare um, at Zider. That is zyt.com. That's zider.com. Thank you so much. We'll see you in the next one. >> Thank you. Take care.