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The AI guardian angel of critical care | Mudit Dandwate @ Dozee
169 Plays1 year ago
Unlike its counterparts in the health-tech realm, Dozee doesn't just stop at powerful software. Equipped with a novel physical product, Dozee is a special technology that uses smart AI to watch over patient’s vital stats 24/7 without any physical contact. In this episode, Mudeet talks about cracking data collection in a data dark space, innovating using AI, perfecting the product, raising capital and future plans.
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Read more about Dozee:-
1.’Made-in-India Technology Dozee to Elevate Patient Safety Standards with RPM & EWS
2.Dozee bets on India's growing home healthcare market with new solution
3.How Dozee harnesses the power of AI for continuous patient monitoring and early warning system.
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Transcript
US Healthcare Spending
00:00:00
Speaker
Hi, I'm Madhik. I'm founder and CEO of Dulzi. I'm very glad to be here, interacting today with Ashek.
Mudit Dhanvate's Journey
00:00:19
Speaker
Did you know that the US spends almost 16% of its GDP on healthcare, making it one of the biggest sectors in the economy? And while the space of healthcare has seen a lot of disruption in the pharmacy and outpatient side, the core business of running hospitals has not changed as much, which is what makes Dozie one of the most important health tech companies around.
Dozy's Healthcare Innovations
00:00:41
Speaker
In this episode of the Founder Thesis Podcast, your host Akshay Dutt talks to Mudit Dhanvate, the founder of Dozy, about his extraordinary journey of building up Dozy. Unlike many other health tech startups, Dozy is not just building a software stack but also a physical product along with it.
00:00:58
Speaker
They have made it possible for hospitals to get data about patients' vital statistics 24-7 in a non-invasive manner. And this is a game-changer for patient care. Stay tuned and subscribe to the Founder Thesis Podcast on any audio streaming platform for inspiring stories of courage and disruption from India's finest founders.
Mudit's Early Life and Education
00:01:29
Speaker
OK, so where are you from? Which city were you born in? Where did you grow up? Since born and got up in Baliya, Madhya Pradesh. And what did your parents do? So my dad was an engineer in Durbex in Prasad, Harpi, Nakashwami, and so on. So that's where I got very fascinated with engineering. And my mom, for the least, I would say she's a hustler.
00:01:55
Speaker
And then she has done, I would imagine, almost everything from growing mushrooms and selling it to doing stock trading, commodity trading, selling insurance.
00:02:12
Speaker
big influence also comes from her because I think being an entrepreneur I think that I'm in from my mom. Wow amazing. So like did you do an engineering then? What was your chosen career path when you were in school? Always one of my dreams was and I always used to ask my dad was that I want to create my own car.
00:02:36
Speaker
So how do I do that? So my dad basically had a very bad answer right for that. So he was like, if you are doing that, you need to go to one of the best engineering colleges in the country or to aim for IIT or Mumbai. And then you get to create your own car. So that's how I always wanted to and that's how my dream kind of shaped up. And yeah, I started preparing for IIT, I went to IIT Mumbai.
00:03:04
Speaker
mechanical engineering exactly what he told me to do. But the funny part was when, of course, I reached there, there was no cap there. There were only four. So it also shaped further over there after that, because then what I did was I founded a restart team in IIT.
00:03:24
Speaker
So even convinced Dean of R&D that, you know, this is what students should be doing for learning and all that. And we used to create rascals. And I made work world-scale rascals in my state in IIT, Mumbai. And it was amazing. In fact, India's first elected race car was built by R&D. Wow, amazing. So are there like student-run race car events or are you participating in those regular racing events?
00:03:49
Speaker
So it was racing events, but for students. So it's kind of on the same lines of formula or racing, but for students. So we used to go to Silverstone and other parts of the world taking our car along with us and used to racing. So there used to be a full racing season when we used to be out.
Transition to Healthcare
00:04:10
Speaker
There were lots of fun. And I also used to be the driver of the car as well. It was a rocket ship.
00:04:15
Speaker
So it used to do zero to about 103 seconds. So it was an architecture. OK. And this was the EV that you built. It was an EV.
00:04:27
Speaker
So I built both EVs as well as I built all terrain vehicles. So we had two distinct competitions in which we used to go in. So one was all terrain vehicle, which was more for dirt driving and all of that. So that was one sec. We used to jump over the logs and all of that. And the other part was EV. Wow, amazing. Okay.
00:04:50
Speaker
So then what like by the time you finished IIT what did you want to pursue as your career? So the thing that I wanted to pursue after that was again in the similar line. I joined a company which was into mechanical simulations for race cars and all of that all engineering I joined.
00:05:09
Speaker
That's where I learned to use a lot of data analytics engineering to improve optimize vital health performance. But what does Altair do? Tell me about Altair. So Altair is known for creating these mechanical simulation softwares.
00:05:28
Speaker
okay it says software company for automotive industry generally so for CAD design for CAD optimize they say and then multi-body dynamics and so on right so I used to be in multi-body dynamics team which used to cater to the
00:05:46
Speaker
automobile division to help teams, help companies optimize their vehicle performance using data analytics and all that. So, so that's where I got this intense mango, how to use simulation data, how to use sensor data telemetry to improve
Founding Dozy
00:06:03
Speaker
vehicle health and finally transpired that you know why it is restricted to vehicle health why can't we bring it to human health and that's how those we actually take on. So like I mean you were in a job I'm assuming it would have been a well-paying job and you like what made you feel that okay let me quit this well-paying job and become an entrepreneur what was that trigger moment
00:06:29
Speaker
No, actually more than one trigger movement. It was kind of a window for that, which finally led to the decision. So one thing again, I this
00:06:39
Speaker
always wanted to be an entrepreneur, wanted to, you know, decide what I want to do, especially in the high energy period of my life. I wanted to do something in which I can really control the destiny. And like you wanted to recreate that IIT Bombay racecar. I'm assuming you would have been in control of that team and deciding and all of that.
00:07:03
Speaker
a lot of ideas, right? So one was that the second trigger was that what was the difference that I was also making, right? I was working very hard, we were doing things. What can we do? You are probably making few German cards faster, few Japanese cards faster, and so on. And they are already quite fast, right? So they did the really required answer was, maybe.
00:07:27
Speaker
But, and it tilts us all. But actually, the delta difference that you are creating was not really enticing me enough over there. And one of the part is that the growth that I was looking for myself, I was not getting exactly that.
00:07:44
Speaker
So all of these things and then combined with the events that happened in the family, which really exposed, you know, how broken the healthcare system was in India. And that really got me thinking that, you know, why can't we really work on this to fix it, rather than, you know, creating this Delta kind of innovations over there, right? Why can't we just fix? What happened in the family? Like, what were those events?
00:08:12
Speaker
Yeah. So one of them was my diabetes for very long. So both the kidneys failed and he had to go through kidney transplant and so on. I really saw that, you know, how real human health can be. And secondly, right over there, the kind of monitoring, which was available, there were lots of lapses, which happened in his treatment, which prolonged a lot of things.
00:08:36
Speaker
And they were easily avoidable. Only if someone was monitoring it more diligently, only we had better tools to do that. I'm not blaming anyone over there. And everyone was trying their best. But we are just not equipped today in 20%. We are still using a lot of age-old technology, age-old techniques.
00:08:58
Speaker
And the volume of patients that we are catering to, nurses are, let's say, doctors are not that many as well. So it's impossible if we don't adopt technologically, and that's what led to this thought process. What was the plan? What was your zero to one journey? So the zero to one journey, actually, there was no plan to start with. So both me and Gaurav started discussing that there are a lot of gaps.
00:09:27
Speaker
And Gaurav is your IIT bachment. Gaurav and me were Taliks in Altair and he comes from IIT Indore. Same back. So we joined together. So we were working very closely always and I always wanted to bounce off my idea with him because he will always give a very pressed perspective and not just say yes for yes.
00:09:50
Speaker
So, we discussed thoroughly with Gaurav. Gaurav loved it. Like, yes, we should be doing this. And Gaurav was all prepared to go for his master's. Like, check this, we are going to do this. And we both started this. That is how it began.
Dozy's Technical Challenges and Solutions
00:10:06
Speaker
But, you know, as you asked, first we started identifying what are the gaps. So this was a hypothesis that healthcare is broken.
00:10:13
Speaker
What we did was for next two to three months and all of that, we just went down deep in the market, talked to a lot of doctors, talked to a lot of professional owners and so on. Try to understand what are really the gaps and try to also observe over there, not just talking to them what gaps they are feeling, but that might be always an instrumental thing.
00:10:35
Speaker
I don't know what they would ask for. But no, we were looking for something. It was not a data innovation, but a step comes in change. Right. So we observed that, you know, one thing which is common across the entire healthcare segment, especially in inpatient department and so on.
00:10:55
Speaker
is healthcare needs to be data driven that everyone agrees everyone at least wants to believe that we today as well when we go to a doctor it is based on reports it is based on some data some opd also if we go then take temperature from thermometer they'll take sco2 and all of that
00:11:14
Speaker
They'll take your blood work to determine what is exactly the cause. So it is data-driven. Having said that, when we are inside the hospital or even at home while we are recuperating, at that time data goes for a toss. Then there is no data. Then it is just feeling.
00:11:30
Speaker
on the basis of that, you know, medicines are given and all of that, right? We thought that why can't we make this part also more data-driven or more evidence-based and so on. And for that, one of the primary things that we have to do is we have to make the process of data collection super easy.
00:11:50
Speaker
One is that, then once we have cracked data collection, then using this data can we create analytics which can actually improve decision making. And the last part is of course and then can we use AIA to finally improve the patient outcomes. So these were three steps that we determined which can really create a difference.
00:12:11
Speaker
And we started working towards how to make data collection easy, step one towards that. We thought that the place where a person who is recuperating, I don't want to use the word patient person, but person when they are recuperating, when they are recovering and all of that is their bed, home bed or hospital bed, nonetheless they are on their bed.
00:12:33
Speaker
So why can that damn bed itself be so smart that it knows how well are you doing? That basic data collection is done by the bed with zero inclusion. So we had always the idea that for it to be super scalable, it has to be very simple for the end user.
00:12:53
Speaker
and user is patient and motors. So it has to be in style one once and forget it modern, it has to be like zero friction for the user.
00:13:04
Speaker
And that's where we came up with this context-less monitoring piece. What were the things that you wanted to monitor? It's a heart rate, respiration, blood pressure, SPO2, and temperature. These are five things that are called vitals. And these are called vitals because they give a true picture about your health. Over it, I would say, there are a few more parameters, which also are very good indicators about your health, which is your sleep.
00:13:30
Speaker
Right. And now, probably, you know, your sugar levels as well. Right. And that is where we started that, you know, how many of these parameters can be monitored without catching the person as well. Right. And that's how the journey started of making a contactless monitor, just place it under the mattress once.
00:13:52
Speaker
And that's it. The user sleeps on it, the data starts flowing, it is available on the cloud, so that nurses can monitor it remotely. And then AI is also monitoring this data during the frame page analysis, because it is not possible for a human to just keep on staring at a screen.
00:14:10
Speaker
So if a patient's data is changing and is reaching a concerning level, the AI will flag it in early stages, you know, code blue event so that the early signs are developing an exchange, which are very clear based on the data and there are also research on this. This is not something which we have innovated. What we have innovated is how to seamlessly take the data, how to make it available in a place where it can be utilized perfectly.
00:14:37
Speaker
And then giving them the right kind of information so that they can take right kind of interventions. That is what we do. So this sounds like a hard device to build, something which can be discrete enough to not bother your sleep when it goes under the mattress. How did you go about trying to build this? How many iterations did you have to do? How did you figure out the hardware part of it? It was hard, of course. So it took us almost four and a half years to perfect.
00:15:09
Speaker
and because we had to perfect this for that limit that whatever be the mattress it can be an 18 inch mattress doesn't matter whatever is the posture it doesn't really matter but it can be placed under an 18 inch mattress also it can monitor a tiny heart wall movement also is it like a sheet or what is it like yeah it's like a sheet that's it
00:15:34
Speaker
It's like a sheet. You just place it under the mattress. That's it. OK. So it's a sheet which has so many tiny sensors embedded in it. Correct. It has vibration sensors. So in principle, it is monitoring vibrations produced by every heartbeat. Every time your heart is ejecting out blood, every time you're inhaling, exhaling, smallest of body movements, it's capturing the vibration which is produced in blood.
00:15:59
Speaker
and then converting it into electrical signals so that they can be dragged and then using AI to then segregate it into different biomarkers, heart rate, respiration. In fact, even what is left ventricular ejection, how much time your heart is taking to compound blood?
00:16:17
Speaker
That is for left ventricular ejection time, blood pressure. And this is something which is very, very, very unique to dozy, not just in India, but in the world. In fact, arguably, this is world's first contactless blood pressure. For 150 years, you know, we know about that cost based blood pressure of different variations, mercury based digital and so on.
00:16:39
Speaker
But this is placed under the mattress and now the recent study that we have done with a couple of hospitals in Bangalore and we are on the verge of dissipating it as well. We compared it with arterial blood pressure which is a true holding standard which is only used in ICUs which is an invasive way in which a probe is put inside your artery.
00:17:02
Speaker
To measure your blood pressure, when we compare that with Dozy's non-contact mechanism and we compare non-invasive blood pressure by the cuff based method, we are more accurate than cuff based method, which is the current standard of care.
00:17:21
Speaker
So not just making it more convenient, but we are also making it more accurate also. And once you make it like this, now imagine what can happen is instead, you know, what nurses were taking data every four hours to six hours, you are getting every minute you are getting a data.
00:17:39
Speaker
So you are not waiting for a person's health to deteriorate and then act. You already lost four to six hours in life. And generally in cases where it is life-threatening conditions are there, four to six hours is just too much to lose. We can lose people in life.
00:17:55
Speaker
And that's how Dozy saves lives today. But tell me how you did it. What was version 1 that you lost? And you took four and a half years. So was it like four and a half years of no revenue? You spent four and a half years just to build a product? It was four and a half years of no revenue. You are right.
00:18:14
Speaker
And it was even lots of iterations. In fact, yes, I probably went little faster than that. And you had asked me that question. It took us almost 67 iterations, even more than that, actually. Our first iteration which started working was in less than six months, actually. Very easy. The idea went the same, like a sheet with vibration sensors. It was safe. So sensors, we had been in six months.
00:18:40
Speaker
And I'll come to where the complexity actually lies as well. So in six months, we had created a sensor. And to be honest with you, even we had not imagined it to be a contactless sensor. We had imagined it to be a non-introsy sensor, which will be like a sheet, which will be put over the mattress.
00:18:59
Speaker
But one thing happened, and one very interesting incident happened. When we made our first prototype, me and Gaurav thought that it's time to celebrate. So let's go out, have chai or something. And we have a very naughty dog. His name is Five. So he would just tear off everything that will come in his play knife. He was six months old at that time for teething. So he'll just tear it off. Like to save from him, we placed the sensor under the mattress.
00:19:27
Speaker
This guy went and stayed over the mattress, right? And we were actually getting data. And that's how Dozy became contactless, right? So that was the start of, you know, being contactless. It was a very interesting story that way.
00:19:49
Speaker
After that, I think the added complexity added was that it had to work through different types of matrices and all of that. Second thing was, because we always wanted to go in clinical settings, it had to go through clinical trials and all of that. So we worked with labs like NIMHANS, JI DEVA, EANS, where we proved that all the research is context-less, but this is as accurate as ICU grade equipment.
00:20:17
Speaker
Even without and and now we are proving it is even not just about that equipment also. What were the major challenges in making this device like the the sheet? Was it that the hardware of it or taking the signals and converting it into barkers or like?
00:20:36
Speaker
Both had their share of challenges, I would say. When you are making sensors that sensitive, that it can pick up even a tiny hard wall moment placed under the batteries. It is also very sensitive.
00:20:48
Speaker
When it is sensitive, it is also going to pick up a lot of noise and so on. So then creating algorithms, which ensure that no matter what, you know, it is able to also segregate signal from the noise. So making those strong algorithms took as good time training them because it was entirely AI based and all of that data collection.
00:21:10
Speaker
Doing ethics clearance is everything. He had to go through multiple hospitals. Doing clinical trials is also not an easy job in itself. Registering it with bodies like CTRI and all of that. Sometimes things take months when nothing is happening. So all this has its own set of challenges. And the second part is hardware. So in hardware, one of the problems is standardization.
00:21:35
Speaker
You can create one prototype that works, which you can stabilize and so on. But how to make now a replicable process that gives you a standard quality no matter what? How do you make your output quality check that rejects any kind of quality sensors which are being made and so on, so that you don't find it out in the field?
00:21:57
Speaker
So these are very practical challenges, nothing very unique to those, but they do come. And like you intended to manufacture it in-house only? No, no, no. So we even now as well, we don't manufacture it in-house because that's not our core. We are not a hardware manufacturer over there. And as I mentioned, our IP lives, our business lives in collecting data, dissipating it and so on.
00:22:24
Speaker
So manufacturing is done through contract manufacturing. We have two facilities right now with us, one in Bangalore, one in Chennai. But if tomorrow need be, we can open 10 more facilities in no time without having any kind of capital investment or anything like that. So that is why we wanted to keep it flexible, scalable, right at the end of it.
00:22:48
Speaker
Because finally, you know, this thing, if this technology is made, it has not reached masses, you have done nothing. It has to be very scalable every point that we made. So we always ensure that that is the core of it. How did you train the algorithm? Because that needs a lot of data, right? So did you like have it deployed in hospitals where the patient also had a BP machine hooked up or something like that and had the seat and therefore, like something like that
Personal Motivation and Resilience
00:23:16
Speaker
or
00:23:16
Speaker
To start with, it was not even the patient, it was us. I remember me and Gauray spending a lot of nights in labs as well with polysomnography machines. So we worked with Nima's human sleep research lab over there, where polysomnography gives you data from EMG, ECG,
00:23:38
Speaker
EOG you put 32 electrodes on your brain. EOG you put 3 electrodes on your eyes. Then you put electrodes for sensing any kind of snoring which will happen.
00:23:53
Speaker
Then on the chest, there are two bands, right? And there is ECG to monitor your heart. And then there is EMG on other parts of your body as well. And then an II-based camera also can see your body movements and all of that.
00:24:08
Speaker
Yes, and by the way, this is the way a sleep study is done. So when we pitched this, we just really loved it. This is going to change the way we see healthcare because now a person doesn't need to come to sleep a lot to actually do that. We can simply do it at their home.
00:24:24
Speaker
Today, as well, you can do it at home, but that is portable machine, but still it is with variations of a lot of these. But imagine sleeping every day can be a sleep study, right? How your apnea is progressing, how, you know, anything is progressing. Now you can get to this, you're not bother day, just under the mattress, doesn't matter. When we had some about 20 nights of data, we could
00:24:48
Speaker
train algorithms to some extent, we showed that you know, we can do it accurately. Now we needed more data. So that's where then we went to CTRI. Ethics clearance that what is CTRI basically registering your study with the body so that you can do clinical trials and so on.
00:25:06
Speaker
right on other subjects as well. So, in that way, slightly we were lucky that it is because Dozy is something which is non-contact or non emission based device. There are no side effects. It really doesn't harm anyone. So, if someone is going through a state study, putting a Dozy under the bed,
00:25:29
Speaker
It doesn't really make a difference. So then we got it as well. After the results were good, then we started getting the patient's data as well. And that's how we started training it further. Then when we had done it in one hospital, we showed the results to another hospital that now see we have done this. Now we also want to diversify it further, want to also do it on hard patients as well. So that's where Jai Reva came in. That's where now Eames Jodhpur also came in.
00:25:58
Speaker
So essentially these hospitals are your clinical trial partners, like they are running clinical trials along with you. Is this like a paid thing that you pay them to run the clinical trials or like is it part of growing the body of knowledge and improving the ecosystem? So like that is why they participate in it.
00:26:20
Speaker
It depends. Generally, in government institutes, in public institutes, it's not paid. Basically, yes, you pay a part of it, but then you are just for whatever operational costs are there, you are paying for that. Okay, you're just covering the costs.
00:26:38
Speaker
Yes. So government bodies are not supposed to make any money and so on out of this, right? It is for, as you mentioned, for taking the fines further and then doing publications. So once we do publications and all of that, so we are, it is co-occupied and all of that. But, you know, there also comes a time then when, when speed also matters at that time, so you hire
00:27:03
Speaker
and where we are today. Today, when we have to do a trial, we also go to some bodies, and generally, these are private institutions as well, where we have to do. And then data collection, not just in public setting, but in private as well. Because now settings also matter. Now you have to do data collection, not just in India, but in the US as well, for say, FDA. They won't accept Indian data. They also would like US data as well. So at that time, that is great.
00:27:32
Speaker
And I think you have to pay a lot. So yeah. Yeah. Right. Right. Okay. So during this period of R&D, I believe you also had like a personal tragedy.
Funding and Business Strategy
00:27:42
Speaker
Is that something you want to talk about? Well, yes. So during, about when we are building all of this up, I was always very enthusiastic about going outdoors and so on. Right. And my, my brace from my work would be that, you know, I go for a then walk dry outside city.
00:28:02
Speaker
talked to maybe some stressful instinct. I wanted to go out with my dogs for a run. We were running around the lake. In that time, you know, these two dogs went into the lake and they would generally do right. One of them is laughing at dogs. So he is part of water. So whenever he sees water, he has to jump into that.
00:28:23
Speaker
So went quite deep into the lake and I saw that he started panicking about right and seemed to me he was growling. So without thinking much, I jumped into the lake. And when I approached the dog, I saw that actually there was a crocodile he was approaching him. So I came in between the dog and the crocodile. So I saved the dog. I pulled him out as well.
00:28:48
Speaker
But basically, I lost my left arm in the entire process. So I literally had to fight a crocodile to come out at that time. Because he had put weed into the deep water. So I had to, in a way, also break my own arm, which was partly inside the crocodile's jaw.
00:29:09
Speaker
So broke my arm, had that detachment, that's how I came out of the water, went to hospital, informed family. There were people there or you drove yourself? No, no, people were there. I wish it was that heroic. This is pretty heroic on its own.
00:29:34
Speaker
So yeah, so this happened, right? Recovered in some time. It took me about a week or two to recover completely. Came out of hospital. It was in my CUI. Couple of surgeries also after that. This was in like about a year after you had started Dozy. About three years. About two years after that. Two, two and a half years.
00:29:58
Speaker
We were quite in the middle of it. Ben came out and always my approach towards the problem has been that we will solve it through engineering because I actually was left with a shorter term than what generally is required for putting a prosthetic and so on. So many of the companies which have prosthetic arms actually refused to it.
00:30:26
Speaker
that is not possible for this. So I decided to build a prosthetic on my own. And basically it is also controlled by my brain and so on. So I can still, you know, function to a good extent, like the whole thing, things and all of that.
00:30:42
Speaker
by just thinking about it. So yes, so that is also something which both again, me and Gaurav, we did that. So we did the coding part of it while I took care of the hardware. It was kind of a mini weekend project that we had taken outside those years. How does your brain control the prosthetic? How do the signals travel?
00:31:09
Speaker
So exactly how yours also does. So what actually happens in the science behind that is when you are controlling your arm or you wanted to open or close, what is happening is your brain is sending signals to basically the the nerves which also travel on your surface of your skin.
00:31:31
Speaker
and if you can tap those signals and then train EI algorithms that when you think this, when the signals are like this, it means this. When signals are like this, then it means this. So you can do some level of that. It's still not as
00:31:49
Speaker
sophisticated as you are, and then we sometimes, you know, forget to imagine what kind of gifts we have got, and this kind of dexterity, what we have in our mind, I don't think we are going to get there even in the next 20 years as well. But still, you can do something.
00:32:07
Speaker
Wow. And this is like standard, most prosthetic arms have this technology of like some sensors which can read the electric signals. Correct. So prosthetic arms, not most, but the advanced ones, very advanced ones. Okay. So how are you funding this? Like it must have been about 2019 or so by the time you were ready to deploy it. Those four years, how
COVID-19 Impact and Hospital Focus
00:32:35
Speaker
did you fund it?
00:32:35
Speaker
So in the beginning, it was by it was all bootstrap money, what we had saved from our job. And we were saving for a higher education or whatever you wanted to do. So it was partly funded by that to start with then once we had some prototypes and all it was funded by grants.
00:32:55
Speaker
And then lastly, it was, we also raised some engine money and so on as well. But only after we started getting certain kind of connection, we had product ready for the market. We then raised our first institutional down in quickly.
00:33:11
Speaker
through Prime and I think, you know, you have spoken to Sanjay as well, right before me. So Sanjay was one of the early believers in the company. Now, still it has been about three more rounds post that and we have our early back there, 3-1 till date as well. So Prime, Ventures, 3-1 for Capital, your Nest, who came in in 2020 and, you know, continue to be with us even today as well.
00:33:38
Speaker
I think you raised about $18 million in the last two years, right? Like this is post your product market fit getting established in a way. How did you do your go to market? Like essentially you were doing sales to hospitals that the product is for like ICUs or like who's your customer?
00:33:58
Speaker
Should we start? I mean, actually, the thought was to build more for a home kind of scenario. But at that time, one thing which actually has shaped the way healthcare is today is the COVID moment which happened. So COVID really exposed that the healthcare infrastructure that we have is really broken. Therefore, basically, creating faster capacity building was required in terms of critical care and so on.
00:34:26
Speaker
So we started working towards that and started augmenting our home product more towards hospital needs. And then that became the mail product. So today the mail product that we have is the hospital product. Why are they different products? What is different for the hospital product? Because the operations are different, the way it is used is different, the kind of robustness required, the kind of data consumption that happens. So same technology, similar technology, but from a product standpoint, they are very different.
00:34:58
Speaker
So we started working towards that and we launched a hospital product. It became a huge hit. When did you launch it? We launched it in late 2010. And when did you launch the home product? Late 2019. What was the home product price at and what kind of sales did you see for that?
00:35:19
Speaker
The kind of sales that we saw for that was steadily growing. It was getting a decent amount of traction. I would say from Amazon, our own websites and all of that, we even had deals with a few of the mattress companies that wanted to embed the technology into their mattress sales and so on. So it was seeing a decent amount of traction over there.
00:35:41
Speaker
But, you know, during the COVID, the entire market crashed for this entire industry. And that year, we thought that, you know, probably now this, and it was very much needed for even the survival of the company. And so we did that pivot, and it became a huge success.
00:35:58
Speaker
What did you price the home product at? Home product was priced at nearly about $200. So about 15,000 odd rupees. Which is very affordable. For about two years of subscription and so on.
00:36:14
Speaker
So like the subscription is for the data. How did the data get transferred? Was it like using Bluetooth? So it connects using Wi-Fi. So it's like your Google Home Alexa model. It is connected to your internet and use it to transmit the data to the cloud and so on.
00:36:34
Speaker
And for a home user, it's like a sheet you put under the mattress. Okay. Put it under the mattress and you plug it to a power source probably. And then you use your mobile phone and there must be an app to connect it to Wi-Fi. And then that app will start showing you the statistics and you can choose to share those statistics with a doctor if you want to or something like that. You got it.
00:36:58
Speaker
And the hospital product for in hospital, probably you would need to connect to their information system. I guess like hospitals may be using some enterprise grade information system.
00:37:09
Speaker
Not all, not all, but yes, the bigger hospitalates lights up our polos and so on. They do and that's where we have to work with them to do that. One is that. Secondly, the rates of data transmission is much higher because they are the need for the end time information is there. The alert system is very distinct.
00:37:30
Speaker
And then there are reports which are needed by the hospitals. So the consumption of reports, timing of it, escalation matrix. If an alert comes to this, 10 minutes, nothing happens, it goes to this, and so on. It's not making that entire escalation matrix, et cetera, is very much critical. And what is also needed is that it is not just about the parameters that we are giving contactlessly. But say a category of patients
00:37:57
Speaker
may also require something more. So your device also needs to be extensible that way. So imagine there is a patient post cardiac surgery, might also require rhythm monitoring as well, because they might develop certain type of arrhythmias in CABG kind of setups and so on. And now you also need to monitor the rhythm as well. Now that is not possible to do contactless. It doesn't matter. You'll use a patch
00:38:26
Speaker
put it on the patient, it integrates to Dozy, and it gets even that information as well. So that's where that device is also extensively as and when needed. In the future, there is a diabetic patient. So then taking even glucose reading is also important. And just put a glucose maker over there, and that also starts taking the data in the same line. But the clinicians are getting the entire information at one place.
00:38:54
Speaker
in the most seamless way in the easiest possible way which is there and like hospitals typically deploy this across all beds or only ICU beds or like actually not in ICU. ICU they already have monetization they don't require actually require it and then also patient ratio one is to one where it augments is actually outside ICU where the staff is not that highly trained as well
00:39:19
Speaker
At the same time, the monitoring is intermittent. So outside ICU, where there are critical to subcritical kind of patients, right? So these are typically about 10% to 20% of the beds. To start with, it starts from there. But then we have also seen hospitals putting it in every bed as well, right? Once they start seeing that this actually improves their efficiency, this makes the patient outcomes much better than reduces the burden on nursing.
Global Expansion and Data Integration
00:39:47
Speaker
So they adopt it later on a larger set of bikes as well. So that happens. And not just that we have seen, even what we have seen is then outgoing patients also, you know, take the home monitoring piece as well. So that is how our GTM environment works. Okay. So the hospital, it becomes like a B2B2C kind of a sales channel.
00:40:11
Speaker
So I guess the critical thing here is hospital onboarding. So how do you do that? Like you have like a sales team, which is like building relationships with hospitals. And like, how did you figure that out? Like, I mean, getting time from hospitals is like not the easiest thing to do. How did you figure all of that out?
00:40:29
Speaker
So we have a very experienced sales team, which typically has experience of selling medical device and equipment to hospitals already. And yeah, that is how it is done. That is how we do it as well. And how many devices have you sold till date? Like what is the
00:40:49
Speaker
So we have currently about 7500 hospital beds. Okay. And your revenue is one time cost plus a subscription also because for the data and the
00:41:05
Speaker
for hospital setting up your subscription because it's a B2B kind of a model. For home it is what we were saying one time plus subscription. Okay, okay, okay. So why did you decide to change the model for hospitals that not charge them a one time and only subscription? Just to reduce the barriers of entry a bit as in we are fine with even that as well. One way or other he said financing
00:41:33
Speaker
you know, which work out. This works for us. It kind of, you know, also tells a hospital that we have skin in the game as well. Because we are a new company today, we have to approach it differently. When we are taking subscription and that time hospitals knows that we are going to give best quality services.
00:41:55
Speaker
It is not just one time sell and one kind of a method for which we have come over here. We are here to stay, we are here to give the best services and any kind of commitment that is needed as well. What's your headcount? Like how big are you as a company? So today we have about 260, 130. Wow. Okay. And what is the split? Like say about 40 people are in sales, about
00:42:22
Speaker
70 are in technology product development RMD, right? There is a good team for even support functions, right? Both for home and hospital. So there is close to about 70 people that we haven't been done so on for support.
00:42:42
Speaker
and so on, and then there are also functions like HR, finance. So that's where we have to start with people. Okay. So what's the roadmap for Dozy? Like, do you see yourself like say an Apple, which is like devices plus like Apple is like an ecosystem of devices and software and services and all of that. Like, is that what you see Dozy as? You can say that's a good paradigm, but where we would probably differ with Apple,
00:43:12
Speaker
is that we are not restricted to just our devices. We want to create a platform that unifies this entire, the true continuum of care from home to ICU. The entire patient data flow which is there and which is required in the most seamless way we want to build the platform for that.
00:43:35
Speaker
There are certain kind of places where we have reimagined the way data should be collected, like in wards, like at home and so on, where we are going to own it. At the same time, we also understand that not everything we are going to create. That's where we work a lot on the partnerships, we work on integrations as well.
00:43:58
Speaker
to complete the picture as well. It is not just giving some things in the best way, some things in the best way, but as and when needed, being open to more things in that ecosystem as well. Like you could have like a smartwatch integration, someone who's wearing a smartwatch, that data also goes through to the dashboard of the doctor.
00:44:22
Speaker
We are working on that. Exactly. How much of your focus is on India and how much outside India? Like what do you see? Currently, I guess it must be all India, right? The revenues? Currently, it is all India. 100% India. But we are also expecting our ABA 5-10K soon. Okay. 5-10K is like an approval. Okay. Yes. ABA is two kinds. ABA 5-10K and ABA de novo.
00:44:46
Speaker
I think the approval is something that we are awaiting. Once we have that, we are going to launch this outside India as well. And let me have already started. Of course, that is something we are starting right now. Yeah, Africa would be a great market in terms of the opportunities there.
00:45:07
Speaker
So one model, so India is a good mix of two markets that I would say about developing as well as developed market. So the developing market, which we have that, you know, using technology to improve efficiency, give better outcomes, where in low resource settings, that is something which is directly replicable in all of these places, because they have similar sort of issues.
00:45:32
Speaker
The other one, which is the developed market, they have issues of aging and so on. So there, the approach is going to be slightly different. But we have more of a trouble. So amazing. Within India, what is your split between metro cities and tier two, tier three? Like, have you gone beyond metros? Is it largely in metros right now?
00:45:54
Speaker
I won't say it is testing metros. Metros is probably 40% tier one is 40% and then comes tier three as well till where we have hospitals and places like Jamptelpur which I had never heard of as well where they are using this technology as well.
00:46:15
Speaker
So we do have, you know, even tier 3 towns, hospitals also on this, especially in the public settings. In public settings, we have gone beyond the metros and tier 1s.
00:46:31
Speaker
In private, ESGIs are more loaded towards metros because that's where our sales team and everything is. And what do you price it at? Like a subscription for a hospital? What is the monthly permit that they need to pay?
00:46:44
Speaker
But little bit depends upon what is the services that they require. It ranges between about $500 to about $1,000 a year. Got it. OK. So India is launching this initiatives around patient health records and making it interoperable also. Each patient can get a unique health record ID.
00:47:09
Speaker
I'm not fully clear on the mechanics of it, but what you are building, how does that plug into this ecosystem which India is creating?
00:47:18
Speaker
There are a few links to that. In fact, we are working with the India team as well, over there. Right now, it is more focused towards spot checks and telemedicine. But as soon as they are open for more data streaming and so on, we are going to ensure that Aussie is directly available, pluggable to that as well.
00:47:43
Speaker
In fact, that is a great vision which is there and we would like to fully support that aligns completely with those vision, making data more available, more accessible. That's perfect.
00:47:57
Speaker
So what is NDHM? National Digital Health Mission. I think earlier you named it ABDM or something. And so they're supposed to be like private players who will create these patient health record IDs. So are you going to be one of those or are you going to plug into those private players who create like I spoke to Eka Kailh which is in that
00:48:25
Speaker
Yeah, so our role will be different, actually. So patient onboarding, yes, we can also do that bit as well. But our role will be more into data creation piece, that imagine someone has a UH ID, or someone has the MDHM ID, which is there, then they can put their Dozy records into their IDs.
00:48:50
Speaker
So which will be available to any of the hospitals they are consulting and so on. So our role is more into being the data creator part. And then if they have their data available from other sources that Dozy can also be a place where they can also be with and use some advanced analytics. So data consumption and
00:49:14
Speaker
a creation part is something that we come on to Dozy, right? So there are different roles that every player plays. So we will be there. Okay, okay, okay. So the Dozy app would be more focused on stream of information, whereas like this UHID, universal health ID apps will be point of time information. Like on 3rd of January, this was your blood sugar level, for example.
00:49:40
Speaker
But that is also important. So Dozy will also, you know, add on to that data point as well. So you can put it as well. You can export reports which can go into that.
00:49:51
Speaker
Yeah, movement instance can go into that for that matter, right? OK. So I guess an important piece of building this interoperable ecosystem is alliances with other device makers. So what are you doing on that front? I guess there's Ultra Human, which has this, again, real-time monitoring of sugar and so on. So are you building collaborations there to have the data flow?
00:50:16
Speaker
So yes, so for guys, whatever are the kind of communication layers and everything which are needed, we already have those. And then there are certain standards in which, you know, medical devices operate like HL7, FHRR.
00:50:32
Speaker
So we do work in those standards. It was not that difficult actually for us to integrate to something like what they'll integrate with us. I buy the way that is very easy and straightforward. Okay. And are you looking to raise more funds? Yeah, of course. We have to go deeper in India market. It's a demand day market in itself, huge potential.
00:50:58
Speaker
But demanding. At the same time, we are also expanding now outside India as well, especially after India and so on. So yes, we'll be raising funds as well. And that brings us to the end of this conversation. I want to ask you for a favor now. Did you like listening to the show? I'd love to hear your feedback about it. Do you have your own startup ideas? I'd love to hear them.
00:51:18
Speaker
Do you have questions for any of the guests that you heard about in the show? I'd love to get your questions and pass them on to the guests. Write to me at ad at the podium.in. That's ad at t-h-e-p-o-d-i-u-m.in.