Latest / Seth Farbman on Podcast - From Startup to Stock Exchange / How AI Is Revolutionizing Healthcare | Pavani Munjuluri | CEO of CognitiveHealth Technologies

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How AI Is Revolutionizing Healthcare | Pavani Munjuluri | CEO of CognitiveHealth Technologies · Seth Farbman on Podcast - From Startup to Stock Exchange

• 0:00
  Speaker 1: I pulled out my phone, ChatGPT, and I said, this is the car I drive. My sensor is on. Blah, blah, blah. How do I reset it?
• 0:08
  Speaker 2: It's in my blood. Because that's what I trained as an engineer as an 18, 19-year-old person in college campus.
• 0:14
  Speaker 1: Is there any other message that you think that our audience would like to hear? Good afternoon and welcome to the podcast. I'm very excited for our guest today, because in today's world of capital markets, we hear a lot of different buzzwords. At some point, it was esports, and then it was electric vehicles. And I think that there's no question that in today's environment, everybody with an upside opportunity is talking about AI. But what makes Pavani different? And I'm excited to have her as our guest today. She's the CEO of cognitive Health technologies, is from all of my conversations with her, it's always fascinating, for me, at least, and I think our listeners will enjoy it, to see, well, how can AI be used on a practical basis? What type of companies are actually executing on the different technologies available to them?
• 1:19
  Speaker 1: And most importantly, how does it demonstrate as a measurable return on investment for the companies that can utilize it the right way? So, with that, with no further ado, I should say, pavani, welcome to the podcast, and thank you for taking the time to be with us today.
• 1:36
  Speaker 2: Thanks for inviting me. Seth and I go by Pavani. I'm just saying, I don't wanna hear my name said incorrectly. And at the end of this end of the session, I would say the right way. And you would say, why didn't you correct me at the beginning?
• 1:48
  Speaker 1: No, no. Listen, we're family here, so that's totally fine. I appreciate that. So why don't we jump right into it, if you could, before we look backwards at the journey of how you landed as the CEO, tell us a little bit about cognitive health technologies, what it is that you do, what's the market that you're going after? And most importantly, I think, for our users and our audience, what is the pain point that you are plugging up?
• 2:18
  Speaker 2: Absolutely. Thanks for the opportunity to share, you know, another fascinating story of AI, Seth. I think so. We have the ChatGPT world post Covid kind of got AI into the limelight and forefront. Everybody from the schools to the teachers to, like, you know, everybody in the corporate world, even individuals, and I've heard and read stories of how people can go on to ChatGPT with some of their medical symptoms and kind of give the, take the responses to their positions and doctors to kind of triangulate in a different way. So it's phenomenal what we have the opportunity to use AI and chat. GPT has brought that to the front center.
• 3:03
  Speaker 2: But if you look at where we are, like as organizations, as company, post industrial revolution, post Internet folks whom I work with and whom we have, this wave of AI is almost a third or the fourth wave. It may be surprising to some. But if you look at how your Google is taking you from place a to place b, or tells you what restaurants on the way or what coffee shops are on the way, that's AI working in the background. Then Google and Maps launched it kind of eliminated Garmin industries, if anyone knows. And that's like dating.
• 3:39
  Speaker 1: I'm old enough to know what that is, and I was very excited to get one, but yeah, exactly.
• 3:46
  Speaker 2: So the whole industry was wiped out because of this technology. And there's already so called artificial intelligence or augmented intelligence, or, you know, all kinds of names out there. So this has been there for a period of time. And we are excited to kind of bring that to healthcare specifically. So as you ask, as a background, I did engineering with specialization in architecture. That means I used to buildings, not just buildings, but I think for me, the big thing is the big words right now, where we have design thinking, it's in my blood, because that's what I trained as an engineer, as an 1819 year old person in college campus doing this day in and out for like five years. And when people talk about design thinking, we need to go to the problem for slate whiteboard. What are we solving?
• 4:37
  Speaker 2: And I'm thinking in my head, isn't that the way the world is? Because apparently is not. So we have a lot of books and, you know, PhDs and everything else on design thinking. But I got lucky to have been exposed to this very early on being in this space. And when the y two k happened again, another dated conversation.
• 4:56
  Speaker 1: A lot of architectural projects interrupt you. It's so funny because my 18 year old said to me the other day, he's like, can you believe it's going to be 2025? And immediately what comes up in my mind is that night before, you know, the turn of 2000, when we all thought that everything was to shut down. So in a blink of an eye, it's 25. Exactly, but go ahead.
• 5:19
  Speaker 2: Surprisingly, it had a not so great impact on architecture and buildings at that time. A lot of buildings stayed empty. And so a lot of projects I was working on didn't take off. And I kind of pivoted to doing and getting an MBA at that time, and then did my masters in business management and administration, and went back to a large corporate construction building real estate company, where I then helped people bring their dreams to reality in terms of building designs, both for corporates and residences, switched gears to moving from architecture to network architecture, because that's how life happens.
• 6:01
  Speaker 2: And learned about Cisco systems and sun systems and everything else, and worked with a lot of different kind of companies back in the day, and ended up working with a company which was doing the so called back office outsourcing way back when the whole labor arbitrage was a thing. So you're trying to take out the low hanging, mundane manual tasks and move that to low labor cost locations like India, Philippines, all of those places. So my first exposure to us healthcare and the whole nuances of, you know, I should be quoted again, I guess the insurance mafia, as we call it here, back in the day. And that's when I started working on the healthcare space.
• 6:46
  Speaker 2: And since then, I've done a lot of work in the data, in technology, in consulting, and most recently, which is, again, five, six years ago, the story, the reason why we have cognitive, or how I'm involved in cognitive, is working for a company which is looking at real world based, evidence based data to handle and do treatment pathways for oncology and diabetes. What it needed was it needed two willing parties to come to the table, which is the providers and the payers, to look at the data and exchange data. And what's working for my patients, what's working, what's not working? And how do you create reimbursement models around that so that they get paid appropriately by the payers? Because the providers cannot just go ahead and say, I'm going to do this, and not get paid.
• 7:35
  Speaker 2: So there were two willing parties at the table to do this, but they could not do it because their systems wouldn't talk to each other. There was no data flow happening between the two. You needed to throw in a lot of bodies. It was always the last on the list of the priority list of the people working on the project because there were so many other things to do. So that's when the banking and the financial industry was already ahead of healthcare in terms of leveraging the bar technology and said, hey, can we not bring the bot technology here so you're not throwing bodies and people at this problem of data exchange and getting this to work. Why don't we use the RPA or the bot technology back then? That was the phase where I got involved into building this product for cognitive.
• 8:21
  Speaker 2: So cognitive. Since then, it has evolved so much that the bot technology on its own, standalone, doesn't work, as they call RPA is dead again. Count me on that. I didn't, I'm not quoting this. It was, it's been, it's all over. What helps AI in the so called, always dynamic, changing landscape of healthcare is AI. RPA standalone doesn't cannot automate workflows. It doesn't give as much results. It has, it has its own benefits. It has its own place. But if you're looking to really automate and get the ROI, what you talked about, Seth, earlier, you need to look at the AI technology. So cognitive health built the AI platform, Icann. It's integrated cognitive automation agent network for us to be able to automate end to end back office administrative functions for healthcare providers.
• 9:17
  Speaker 1: Interesting. So many, you know, at least for myself, you know, many times when you hear about healthcare and all the companies that have the opportunity to contribute to the growing industry, you think of it more on the medical side. But to your credit, you are focusing on the back end and the administrative. So tell us then, who is the ideal customer? Who are some of your clients? And on a day to day basis, what is the problem that this ICANN technology is really solving for sure?
• 9:51
  Speaker 2: Seth Post Covid and it's, there's a world pre Covid and the world post Covid. I think we need to come up with like the BC. BC terms of c and post C kind of thing. The biggest, you know, healthcare is one of the largest employers in the country, right? There's one of the top employers of the country. I think almost in every state you have healthcare as one of the top employers, or one of the top two, at least, if not the top one. Post Covid, the whole remote working. And so much of pressures and everything else has put so much pressure on this staffing industry that in the staffing for healthcare, there was a lot of pressure to get things done in the right way. So both from the clinicians and the clinical side to the back end of administrative functions.
• 10:45
  Speaker 2: So that one of the biggest thing is how do we work through this whole staffing challenge? You know, you're not able to hire the right people at the right time. There's an aging population who's retiring, and you're finding it difficult to backfill. And the costs, staffing costs have increased significantly without necessarily the payment terms or anything else. So there are so many staffing challenges that is one of the key areas and drivers for us to look at and say, can we somehow enable the staff to do and focus on something more meaningful and I productive and take away the mundane, the redundant, the clicks and the keypads and the keyboards kind of away from the staff. And again, this is my personal story. I've always this Star wars fan here, okay?
• 11:32
  Speaker 2: And I always believe that, hey, why are there only two, three people who have so called Jedi mindset of the Jedi? I think each and every one of us is capable of doing more than what we think we do in the nine to five corporate job or whichever jobs we are doing, both physical and mental. And I feel like if you're able to help and aid us ourselves and take away the routine and the mundane, like, I don't have to answer my emails unless it's the top three things where I have to create something, I don't have to do the excel and move the data. I just want to type in my question and the system to be able to answer my question in a more meaningful and intelligent way.
• 12:10
  Speaker 2: I don't want to spend time taking intake forms and keying from system to system. I want to spend that time in person, face to face, looking at the other person, you know, who the person is, how do we interact with that? So the systems and technology should enable us to live more human and take away the non human parts of it. And that's what we hope that I can, agents are doing right now and will be doing more in the healthcare space right now.
• 12:41
  Speaker 1: Can I just interrupt you for a second? I think what you're saying is so important in terms of, you know, us, you know, enabling each one of us to be able to do more ourselves. I'll tell you just a 32nd example yesterday, which I was even fascinated about. So I had a tire issue, right? I don't drive an old clunky car. I have a Range Rover. And I had some tire issues. And I got the tire fixed. And then as I was pulling away, the light sensor was still on that I had a tire issue. So I went back to the tire guy and I said, the light sensor is still on.
• 13:18
  Speaker 1: He said, as I was pulling away, he's like, either it'll go away in a minute or two or read the handbook and the manual and reset the tire sensor, and I pulled away. So after like 20 minutes, a half hour, I was far enough away from the tire guy and it wasn't resetting. And then I'm thinking to myself, what does that mean? He wants me to read the entire, like, I looked in the glove compartment and the manual is like 400 pages, and to start sitting there. So I promise you, here's what I did. I pulled out my phone, ChatGPT, and I said, this is the car I drive, my sensor is on, blah, blah. How do I reset it and instantly push this, touch that, do this, done. I was just like, that just saved me hours of looking at a manual.
• 14:02
  Speaker 1: And to your point, the fact that you guys are focused on not just the benefits to the company, but just the human element of that extra time and utilizing them, I think is fantastic. So what type of company then is, or what type of, is it a hospital? Is it a facility? Is it a nursing home? What's the ideal target for you?
• 14:28
  Speaker 2: So, right now? So the vision for cognitive and ICANN is to sit between the provider and the payer space set. I think we want to be in the middle. We want to enable the workflows between the provider and the payer in such a seamless manner that you probably would, the AI on the provider's side of the firewall would talk to the AI on the payer side of the firewall and execute the whole function. That's where our dream and our vision is. But right now, we are focused. Our client base, where we are building and developing, is mostly on the provider side.
• 14:58
  Speaker 2: So anyone who's dealing with staffing challenges, so the typical hospital health systems, academic medical centers, regional hospitals, physician groups, specialty providers, behavioral health, dermatology, orthopedics, any of these groups, nursing homes, any provider group which is struggling with staffing challenges and or wants to scale and, you know, expand their business with the same amount of staff, is an ideal customer for us. And I think the ICANN can help them multiply their productivity of their staff, or if not having staffing challenges, we take away the manual errors and all the pain which you get from having staff to do certain tasks which, you know, you're not essentially supposed to be even letting them do. Like, we invented Excel to like, take away a lot of stuff. Instead, we created excel exports around that.
• 15:54
  Speaker 1: So, you know, that's a great point.
• 15:57
  Speaker 2: Yeah, we've always tried to be innovative about it.
• 16:01
  Speaker 1: I think you had mentioned, I forget if it was your website or one of the articles or some of our prior discussions, that 33% of the healthcare centers operate at negative margins. So tell me, how is it that what you guys are trying to accomplish? How does that help bring those margins to a healthier place?
• 16:20
  Speaker 2: So, great question. I think one of the things we have observed and recorded for some of the cloud customers where we have the implementation up and running for a period of time, is that our tool is, our platform is able to eliminate up to 80% of the manual tasks within that workflow, which means that you're able to leverage your staff in a different place. You're able to, no need to hire back people or whoever is retired or even bring back temp staff during the seasonal high peaks, et cetera. So we've seen 80% of reduction in the staffing needs for a specific workflow. That is one variable in driver. The second important thing is AI does what AI does. Irrespective of the Sunday or having a bad day, there's a good day, it doesn't matter.
• 17:13
  Speaker 2: It does the same exact thing over and over with the same predictability, if you will. So you're avoiding lot of manual errors, which is one of another reason or cause for a lot of rework denials and frustrations from the front end team to the mid office, the back office. You're avoiding a lot of those reworks and manual errors. And third, most important, the large language models and getting a little technical here, but the data, the capability for AI to read, review and process such vast, large amounts of data in a very short period of time and draw insights which are not human driven insights, but the models are learning as they, as we call it, those help these companies to not leave money on the table.
• 18:01
  Speaker 2: There are a lot of places where the money is left on the table because you haven't been able to handle the denial on time. You haven't had the proper work closing upfront for proper registration, so your eligibilities are not done. So you're getting denied, which there's nothing you can do about. So there are a lot of workflow related, data related insights you're leveraging from AI, which is enabling you to not leave money on the table. So it not only helps with the bottom line for your I staffing costs, but also helps with your top line, if used well, to be able to push your top line up too. So those are the reasons why we think this can have a meaningful impact on the industry right now.
• 18:41
  Speaker 1: That's interesting. And let me ask you like a CEO type question here, and I think that a lot of the listeners either have pivoted careers in their lives. I certainly know that when I graduated law school, I didn't expect to be doing stock transfer or LinkedIn or half the things that I've done sitting where you are right now, did you ever expect that you would make that transition from the real estate world to the AI world? Did you find that to be a seamless transition? And then I guess part two of my question is, when we talk about aih, I feel like it changes by the minute, right. The technology. So how do you and your team keep up with everything so that everything is current?
• 19:35
  Speaker 2: Thanks for that question. I don't have, I don't think I ever thought of AI was even a thing. I think I learned how to code back in the day, as I mentioned, when architecture, when I was in my final years of architecture and doing my thesis, you know, all our senior folks who are in the market industry are like, oh, everything is slowing down. You guys need better do something else, like have a plan b. So I learned coding and did a bunch of cool things of how the program I created was able to work on the lights and turn on and off the lights in the house. But there was just one project. And then for that, it needs to be connected to something for it to control that, you know, so the whole electric wiring had to be changed.
• 20:18
  Speaker 2: So it was like a non starter for my parents house. But. So I was always fascinated by technology, and I've always dipped toes and stayed in touch, but I never thought I would do something related to AI, but what I always knew I would want to do is build something on my own. So I think that was something from very early age. My grandfather and I used to play sharp. I was the doctor, and he was the one who's managing my whole setup. So I always wanted to be my own boss from a very early age. So I think I, in every role, in every area, every time I pivoted, I think it was always towards, what can I do? What can I build? How can I improve on what I'm doing? So what do we build, essentially?
• 21:04
  Speaker 2: So I think the AI happened at the right time for me personally, and we are still at the very early stage of AI. I feel for us to have real use case and case studies where no one is actually questioning, is there an ROi versus how strong is your AI? Is your AI, you know, how, what are you doing about all the biases in AI? And, like, what, you know, there are other nuances of AI. I think for us to get there, we'll say it will take some time, but it's a very early stage for AI, and I'm glad to be at this stage for off my career in this space set. I know enough on the brick and mortar industry that, you know, I can fall back on. At the same time, I don't think.
• 21:47
  Speaker 1: I don't think you're going to need to at this point.
• 21:48
  Speaker 2: I know, but I know what AI I can do. So I'm at a happy place to say that we've seen that and now this will help us go to the next level is what I feel.
• 21:58
  Speaker 1: And I think that's just to digress for a second. I think it's such an important message. I have a 22 year old daughter and she is at that point figuring out what do I want to do career wise. And I think that when in theory, somebody like my daughter sees somebody like yourself who always knew that they wanted to build something or have something on their own and now sits in that CEO chair, it's extremely motivating and a great message. So back to in terms of the healthcare industry, I think that I speak for a lot of people, that when that concept comes to mind, we often think about prior authorizations as some sort of tremendous bottleneck in the industry. Can you touch on how cognitive uses AI to help with that process, if at all?
• 22:47
  Speaker 2: Yes, sure. Seth. I think so. We kind of took a backseat for the prior authorization problem. That's like the hard topic in the industry right now for a couple of years. I think it's one, it's a very complicated, it has become a very complicated and very financially burdensome process for both providers and payers. And it's a direct negative impact if not done well on the patient. So it's a very hard topic because if you're not your prior authorization or not done before the patient has procedure, surgery, et cetera, there's a negative impact on financials for everybody involved. And if you're not getting that in the right time, you have to reschedule the whole procedure. There's a whole lot going on in that space.
• 23:36
  Speaker 2: And all the vested bodies and associations are putting pressure and getting the right way to get some of the regulations changed and moved in the right direction. From a government and a federal perspective, that kind of helps with the streamlining of the process. So cognitive health, when we started, there were already some large companies that deep pockets were in this space. So we haven't really done a lot in the prior authorization space to specialize ourselves in this space. But what we do is we do work on the prior authorization as a part of our workflow. So if you, what cognitive agents do is if we are working on any denial project, we are working on work queue for denials as a part of that process.
• 24:22
  Speaker 2: And as a part of that, if we need to qualify or verify the prior authorizations, help the team do the prior authorization. Before this procedural surgery or appointment is set up, our agents are able to go to different payer sites and check whether the priority is required or not, and then go ahead and initiate a prior authorization. But there are companies out there who are focused, laser focused on this very specific thing. The way cognitive is looking at this is we are looking at a more broader picture and multiple use cases within revenue cycle. So you're not tied in with one solo use case or one solo use. We are able to traverse the entire lifecycle from the time the patient comes into the time the money is in the bank and you reconciled and sent the report to the CFO.
• 25:16
  Speaker 2: Cognitive agents can work through all of.
• 25:18
  Speaker 1: This continuum well, and I guess that's one of the benefits when we do talk about the topic of AI in healthcare, there's so many different areas to be able to focus on and for cognitive to really decide, okay, what's going to provide the most value to the bottom line and what's going to use your strength. And I'm sure that's part of the challenge of figuring out where do we want to focus our efforts, because there's so much to offer. I had a personal question in that very often when people hear about entrepreneurs and CEO's, they read online about, oh, well, this person gets up at 04:00 a.m. And they start working, or this person sleeps till 11: 00 and this person works till two or three in the morning. What does an average day look like for you?
• 26:05
  Speaker 1: Because I would imagine that you are pulled in a million different directions, both in terms of technology, managing your team, bringing in the revenue. What is an average? Is there an average day and what does it look like?
• 26:20
  Speaker 2: There is no average. That is true. And I also have read those articles before when this happened and when I became a CEO for cognitive from founding member CEO. And then I've read all this and I work very closely with my previous company, CEO's different stage of the company, both the startup stage, the growth stage, as well as an IPO company. And I've seen them work and I was like, I am not like that. And I'm not like any of the things I read. And no one talks about dropping their kids to school while on the call. No one talks about walking a dog while they're doing something yet. So my life is different. Can I even do this? It's always been the case, but I think I have my rhythm.
• 27:03
  Speaker 2: My typical day is all over the day when people talk about work life balance, the way I talk about is it's just, I think my mental health is more important than anything else at that moment in time. I think it's just life in general. I think, I don't separate, I think being a CEO of a startup and this is a company, I don't separate between work and non work. I think everything is growth, everything is positive, and everything is, there's an output associated with it and everything has an expectation. So am I, are we, am I setting the right expectations for my team? When I'm talking to my team, this is what we need to do. Am I setting the right expectations with my kid, with my dog? This is what is happening. So I have to balance all of that.
• 27:53
  Speaker 2: So it kind of spreads. Some days I have lot much more during the daytime and then my evenings are, you know, my workout or whatever else. The other times it kind of flips. I have something late night. We are talking to someone in a different time zone, so it kind of switches.
• 28:08
  Speaker 1: So yeah, that's a great point.
• 28:11
  Speaker 2: I remember doing an investor call from a different, in a different part of the time zone at 02:00 a.m. 02: 30 a.m. Our eastern time, talking to an investor in a different time zone. And I was equally motivated, excited, like.
• 28:32
  Speaker 1: Especially on the investor side. Like when we're raising money and there's an opportunity, we do what we do. And likewise, I'm on occasion speaking to people in Singapore, Malaysia, and ideally for them it's 11:00 p.m. 11: 30 p.m. And we need to, well, listen, I want to be cognizant of your time. So is there any other message that you think that our audience would like to hear? And I would imagine, well, let's start with that. Is there any other messages that our audience might appreciate either in terms of where the company is at or where you think that the company together with AI is going to be, say, six months from now?
• 29:16
  Speaker 2: Absolutely. I think one of the things I also wanted to mention, you know, as you're talking, especially of prior auth and things like that, I think one of the areas where we are seeing a lot of interest and traction is this entire document management and correspondence of the payers are one of the things where I feel like money leaving on the table is a very, this is a very typical example of that. There are denial letters coming in, there are response to appeal letters coming in, someone has to manually look at that letter, route it to the right team for them to take an action, whether it's a phone call, whether it's like responding back and going to the patient's medical records and doing something more with it.
• 29:55
  Speaker 2: AI is doing all of this, our AI agents are doing all of this and helping our customers and providers to be on top of their correspondence, be on top of their response times, and be on top of their posting all the cash and reconciling. So the CFO's have the money. There is no 30 day, 15 day, two day delay, nothing. It's like, right real time at any given point of time. So that's like, I'm very proud of our team to be able to do that. That was one of the things we have done during COVID We couldn't really do a lot of marketing and outreach. We've honed on this product. We've spent a lot of hours and hours of retraining, training the models, etcetera. So that's something which, and as you were saying, AI kind of traverses throughout the continuum.
• 30:39
  Speaker 2: So your data taking in from, you know, at point a can be transferred to point n without doing too much of work or anything else. So that kind of helps. So once AI has all of this data, from a correspondence and the document management perspective world is there's no limit to what you can let AI do for your denials, for your ar, for your registrations, etc. So that's one thing which I wanted to mention. And I think in general, where we are, as you, I think one of the things which I didn't answer is, how do we as a team, keep up with what's happening?
• 31:15
  Speaker 1: Yeah, because every day you think, this is the new ChatGPT, and this is the new AI, and this is the new. Every day is the new for somebody that is at the core of it, like you are. How do you keep up with it all?
• 31:27
  Speaker 2: I think one of the things just my two cent said, being in this space for a period of time, there's a lot of shiny objects out there. Easy for individuals like you and I to just take a login for ChatGPT and do it. But when you're trying to bring in patient data, when you're trying to bring in company corporate data, et cetera, you can just do that. There are so many regulations, compliance, so there are certain bodies like NIST, and we follow all of that. So every innovation there is a financial give and take. Like, is it worth the juice? Like, is it, how much will I spend? I can do a trial for like $100 or whatever, but I want to scale it to a million records. What would this be? So there is always.
• 32:10
  Speaker 2: And then, and once you do that, if I'm a company with deep pockets or I have a lot of investment money, I might say, oh, let's go ahead and do it. But then how do you transfer that as a value to our end customer? At the end of the day, if the provider customer, whoever, if it is you get, you guys are too expensive for them to even afford you, then the whole innovation, I think, is a zero sum game. I think the innovation has to be affordable for the person who's there without essentially, you know, it's not like I'm taking money from the investors and giving those freebies to the providers. Like, what's the balance? How do we, how do we run a balanced profit?
• 32:47
  Speaker 2: And, you know, company which is making the margins on the product, you don't necessarily make profits from day one, but how do you make your margins right on the product? So that's where the ROI is. So you're not spending millions on your product and charging hundreds of vice versa. Right. So that's where I think, from an innovation point of view, I think I'm constantly looking at how much are we spending? Where are we bringing this innovation from? So that translates into meaningful use on the product which the providers can afford to pay. That's my goal.
• 33:21
  Speaker 2: And in terms of innovation, we have a team, we have an R and D team, research team focused specifically on working on these new things which they hear in the market, whatever is coming up, but then they bring it to us and then we look at the real deal, like, what's the value of this? How much does it cost and what are the regulations do we tied in? So slow and steady. So there are so much out there. But we pick and choose what is making financial sense as well as stays within the regulations of providing a meaningful output and to our providers, provider clients right now. So that's how we work on that.
• 34:00
  Speaker 1: I got to tell you, it's all very exciting. I mean, and I don't know how you balance everything because like you just said, that's another element of it, because you're in the healthcare industry, you're dealing with regulation, which is a big part of it. Well, I appreciate all this insight, and I hope you'll come back in a couple months and give us an update with how things are going and where things are at. In the meantime, I know you have a fantastic LinkedIn presence, so anybody that's looking to get in touch with you can reach out to you there. Can you also give us the company website? And then this way anybody, and I encourage anybody in the healthcare space, tech space, AI, take a look at what's going on and try to keep up with this amazing opportunity.
• 34:45
  Speaker 1: What's the website where people can learn more from?
• 34:47
  Speaker 2: It's cognitivehealthit.com is our website, and I'm doing a webinar on Wednesday for our community at the aah am on demystifying AI for healthcare. So do listen in if that's of interest.
• 35:05
  Speaker 1: That's a great topic. That's a great topic.
• 35:07
  Speaker 2: Yes. Yes.
• 35:08
  Speaker 1: Well, you've definitely helped demystify a lot of things today, so thank you for your time. I appreciate it, and we look forward to being in touch soon. Thanks for coming on.
• 35:17
  Speaker 2: Thank you so much, seb. Be well. Talk soon.
• 35:20
  Speaker 1: Bye.