 Yeah, so good afternoon. Just a small introduction about myself. So I am a serial entrepreneur. I am also an angel investor. I have invested in companies in Silicon Valley and India. I am also part of some of the early stage funds in India and also funds like Boundary Capital in UK which invest in Medtech early stage funds. So it has been an interesting entrepreneurial journey. Today the session is on lean startup. So I would be talking about, you know, how we have imbibed lean startup philosophies and agile and design thinking in what business we are doing and how we are implementing them. We had very good sessions on lean startup. So I think the basic fundamentals are of course all known to you. What I would like to talk about is how lean startup is an agile and others are applied not just to software development but also to, you know, developing products and developing business models and running businesses. So I think it has relevance to all businesses, large and small. Let's start from, you know, talking about learning from failure. I think Silicon Valley and Bangalore are two cities in the world where we can proudly talk about failures and, you know, it is in fact fashionable to talk about failures. So my first startup in 2013 was Adventure Labs. Before I started that, you know, because I do some, I was getting into doing angel investing and all. So I had read about lean startup, about design thinking and I was quite aware of what is going on. And but not surprisingly, we made all the classical mistakes that one could make, you know, and not follow. So, you know, theoretical understanding of lean startup is very different from actually imbibing it and actually being able to, you know, basically implement it in your business. And that is the story that I'm wanting to talk about. So this startup that we started in 2013 in edtech was about online tutoring for mental math through gamification. It's a large enough market, a billion dollar opportunity. It's a global market, abacus, humon, mental math. And so we were not in a wrong industry. This is one of the slides that I picked out from 2013 when we had made that presentation. So our vision was that every kid can calculate faster than a calculator and that kids would not be afraid of numbers. So it was a tall vision. Again, this slide is from 2013. I just highlighted the last portion where we said in five years we will do a turnover of $6.53 million and we would be operationally profitable in first year. For two years, we had a great team. We built a breakthrough product that was hailed as one of the best edtech products at that time by experts from Stanford to Harvard to XYZ. And it had concepts like adaptive learning and other things that are being talked to constructivism and other things that are being talked about now. In fact, we were ahead of our times. And we could not do a sale of even $100. It was we never went to the market. We did not launch our product. We did not take customer feedback. We had no understanding of the market. We were great entrepreneurs, great tech entrepreneurs, which were very passionate about building this product. So we build a great product as most tech entrepreneurs do. And this is the advice that I give as part of angel investing. I made at least 200 startups in a year. And this is the advice that I do that you need to go to the market as fast as possible. You need to interact with customers. You need to understand your market. So we did nothing of that. So for two years, we after two years, we figured out that actually our customer was not the child for which we are building the product who we thought would learn mental math. But it was these large companies which control 99% of the market through their franchisees. And if we could not build a product which was for them, this market was not available. So it was too late by that time that we realized that the customer was not what we thought. And we never tested the hypothesis about who the customer is, what the customer wants, and what is the problem that we are solving. So basically, you know, this classical question, can this product be built? Yes, we build a great product. Should this product have been built the way it was built? No, we should have, if we would have gone to the market in three months, we would have realized all this. And it would have changed the whole outcome of what it happened. So during the same time, 10 marks was had been formed, which was in the similar domain of math learning. And because they had gone to the market early, and they had some traction, it was acquired by Amazon. So we had a good market that we could see, we had a great product. But we had absolutely no idea of the market and we basically failed. I think there are very important learnings from this. And this is why 90% of the startup failed. And the figure of 90% is as you know, Tathagat was mentioning, this is about startups which have been funded. So total startups which actually, you know, start work 99% fail, out of the funded startups, 90% fail. And most startups fail not because they cannot build a great product. Any product that you can think of today, any technology can be built. Anything, you know, weirdest thought that you would have can be built. What is important is we have wasted our resources in trying to build the wrong product. And we were not able to acquire the customers. So as Steve Black, who is the founder of the lean startup movement said that startups don't fail because they lack a product, they fail because they lack customers and a profitable business model. So these were important learnings when we closed our product. So the last learning is that 70 to 80% of the startups start from doing something else and then they pivot to doing something else. So we have to have a mechanism where we can take the feedback from the actual customer, understand who the customer is, find out what the customer wants, build that, and then basically or pivot, and then we would be successful. So these were the learnings from my, from my first startup venture. Besides that I have done, you know, I have other businesses which I have built from scratch, but those are normal businesses. We are into telecom. We have about 1000 engineers working for various telecom companies as a service as engineering services company, but those are standard products, standard businesses. So with this, you know, today, when we do a new startup, and that's what I'm going to talk about, we employ agile lean startup design thinking from day one, to not just build software, but to build products to build the, the organization, the whole culture is now based on this. And that is why we are seeing early success. And this I think is applicable, as I said, to companies large and small of in actually in any domain, not just tech domain. So I'll just talk about briefly about the, the new startup that we have, it may be slightly technical, but bear with me for three minutes. So we are in the domain of Vertigo Designation Balance Disorders. It affects, so Vertigo is the sensation of spinning. Incidentally, many of you are maybe, you know, software people and the computer vision syndrome also may lead to Vertigo and Diziness. So this affects 5% of the population, which means 60 million people in India. And there are not even 20 centers in India, which can diagnose and treat this, it is being treated symptomatically, but there is no, there are only about to, you know, less than 20 centers in India, even in the whole of Asia, Africa, there are very few centers, which actually diagnose and treat this, this, which is a huge problem. So we have developed the technologies for diagnosing these sensation of spinning, Diziness, instability. We have applied for four patents. And these equipment are very different from what you see as normal diagnostic equipment. They are basically, so the balance system is one of the most complex systems in the body. It consists of the inner ear, we do not, you know, most of you, because your engineers would understand this. So the inner ear acts like an accelerometer, a gyroscope, it has a gravity sensor, it has a linear acceleration sensor. So it's all physics. And it is very difficult for doctors to understand this. And so only in the last 10 years, you know, some developments have happened in US and Europe where these technologies have been identified, which can basically diagnose various diseases of this balance system. So we have developed these, we have applied for patents. These are four of these that you see. I'll just give you, so this is, this equipment is called a video on stagnography. This has high speed infrared cameras, which track the eye movement to tell you which part of the brain has a problem. So it's a very sophisticated equipment that we have, sorry. So I don't know whether you can see it, but the, you know, as that object moves, the eyes move here, I think the quality is not good. And then you are tracing the eye on the graph and various parameters like slow phase velocity, slope of the curve and other things will give you if there is a problem in the brain. You know, in some countries, so Europe and US, there are companies which are manufacturing this kind of equipment. We have not reversed engineered them. We have made them from scratch. So that's why they are patentable. And they are much more simpler than what has been done outside India. So, you know, just to give you a perspective on this. Now, when we were building these, you know, the basic assumption, the basic premise was that, you know, these equipment are available from outside India, but they are very expensive. So the problem by India does not have these centers is that these equipment are expensive. And so if we could build them in a, in a, in a way that they are cheaper, we would basically be having a great market, you know, share. So this is another kind of eye movement that is taking place. And you see a different kind of a curve. And, you know, so, like, this is the difference between the normal eye movement and abnormal eye movement is called latency. And that can tell you if there is a problem in the cerebral hemisphere. So these reports are also very different from what you see in a normal medical report. So this was, we have built an EMR system for vortico-designation balance disorders. So this was just a brief on, you know, what we are doing today. So my next, you know, 10, 20 minutes, I will break it down into three parts. The first part is about, you know, innovation. So when we do innovation, we try to think of complex solutions. Our philosophy has been always that, you know, simple solutions are actually the best solution. And the greatest things in life are actually, you know, invented by experts, not by experts, but by, you know, entrepreneurs like us, who were stupid enough to ask, you know, why it can't be made simple. So I'll just give you an example of that. So one of the diseases that people with vertigo may have, some of them would be that they do not see a vertical line as vertical. So if they are asked to hang a painting, they'll hang it slightly tilted. You know, they would see objects, normal objects like this. And there's a test called subjective visual vertical. This test has been there for 40 years. It's called a bucket test where what they do is they will have a bucket and they'll have a line here at the end of the bucket. And they will put that bucket in your face and ask you to rotate it till you see that line as vertical. So the difference between the actual vertical and when you rotate it is basically the deviation. If the deviation is large, that means you have that problem. So, you know, then somebody came up with this and said that, okay, why can't we have a plumb so that you don't need to, you know, when you rotate, you know, what is the value of the difference. Then Germans came up with a, you know, rotating system where all this could be rotated with computer and you could basically, so this was about $30,000 that they were selling about 20 years back where you could rotate this. So you are getting the point of the line, correct? It's so, so basically what we had to do was to rotate the line so that you could, the patient could try to make it vertical and the difference between the actual vertical was to be calculated. Then somebody in Italy came up with this, what it was to have a disk which had this line and then you put it in the face and then there was a rotating thing. So the patient was asked to rotate it and this is, so this came down to about $10,000 and then the Americans came up with a new concept which was that, you know, they had a laser projector which would project this light, okay, and they gave a PSP kind of a thing and you could rotate the laser light to, you know, make it vertical. So you have got the various, you know, things that people have been doing and when, you know, so I am not from this field and I had no baggage and I had no understanding of why. So, you know, when I was coming back from a flight in US and I was just dosing off and one of the things that I want to comment on what was discussed in the morning about brainstorming. So there is a lot of neuroscience research which now says, and I think it is applicable to all our companies, that you cannot have people sitting in a room and deliberating to get a great idea. There was a research done on 125 CEOs, CTOs actually by, I think it is Harvard and they said that they asked the CTOs what are the top three ideas that came to you in last one year and then they asked those CTOs where did you get those ideas from, was it in a meeting and out of those, you know, basically 125 into three ideas, 375, about 350 came when they were either sleeping or dosing off or getting up or in a flight or, you know, taking the dog for a walk or in, you know, basically in the toilet. So this whole concept about brainstorming is flawed because brainstorming and there is neuroscience research which says that when you actually sit down to solve a problem, the solution will never come. So anyway, and I can send you this research which is there. So anyway, so I was just dosing off on a long flight, it was a 14 hour flight and suddenly it struck to me that this problem has a very simple solution and that Eureka movement came and what it is, is it's a PPT slide which has a black line and every one degree basically you can rotate it, correct? So you give a clicker to the patient, you have a PPT slide with a black background and it does exactly what all those equipment were doing. This is now in textbook. We have sold these PPTs to doctors, correct? So and there is no difference between what the data of, so we have data of about 1500 patients on this with other equipment and this is as good there are no moving parts, it is simple, there is nothing wrong in this and for whatever reason for 30 years nobody has thought about it, correct? So we need to build simple solutions, simple. So it's not that we are building all simple, so you saw the other thing which is very high end but you do not need to create complicated product, you need to think fresh. I think you are getting the point of you know how simple it can be. So this was you know, so as you know my point is as one explores a new domain basically one has no baggage, no preconceived notions, no fixed ideas and then you know you can think much better. So this is now in textbook. This is world class, there is nothing wrong with this versus the others that has been done. I like this quote that innovation is seeing what everybody has seen and thinking what nobody has thought, so basically this. So this was just an input on simple thinking whenever we do and lean startup, agile everything should be about you know thinking simple solutions and not complex solutions. Okay so the second part of my discussion is on lean startup. So we have talked everybody has talked about it since morning. I just want to highlight you know one point that the focus has to be on customer which is the same as in design thinking. The goal of the startup is to find out the right thing to build and in our my first startup as I said we built we did not build the right product. Things that customer wants and pays will pay for. I think this was in one of the sessions one of the speakers said this what the customer wants and will pay for. So in a startup who the customer is and what the customer finds value in is not known and that is why it is a startup that is why we are basically trying to find out what the customer wants what is the customer behavior. So when we started so this is a good quote by Steve Blank who is the founder in a way of the lean startup movement. It is no business plan survives the first contact with customers. So we build these great products we build four of those products which I showed and our thesis was simple we are building it we are selling it at a cheaper price than what is available so you know we should be able to get great orders. And as it always happens we realize that that was not true. What was important is that we started so this was the name of this is the name of the company we started selling the equipment in a very crude stage. People told us that if you sell because we were competing against Europeans and US companies their product were great they looked great they felt great and the doctors had a lot of faith in anything which is white skin. So they had those great products and when we started marketing them people told us do not market till you have a great product but we started we went because of the learnings we went with crap products very quickly into the market and what we realized was not that doctors did not want to buy it because they were not good they gave us a very different feedback. This is a science which is developed in the last 10 years it is not taught in MS or MD. The doctors do not understand the interpretation of these results so they said you give it give us free we will not be able to do anything with it because we do not know how to interpret the results of these tests. So the problem statement was not cheap equipment the problem statement was there were no doctors to use these equipment. Once we realized it you know we and we realize it very early we basically change our whole strategy. So you know what is important is sell the problem you solve not the product so do not try to push product as tech entrepreneurs tech startups we tried we are very passionate about our product as I was with my first startup we tried to push that product without understanding what the market wanted. So once we realized that the problem was of availability of doctors we totally changed our whole thesis our hypothesis and we started then saying that if the problem is of doctors not being available let us try to solve that problem. So we are what we are doing now is to put the equipment in clinics across India all the data comes on the cloud we have a panel of ENT neurology and psychiatry because it's a multi-disciplining review all the reports and send back the diagnosis. So now when we set up clinics across India we have one in Cyprus also from where the data comes here and we send back the diagnosis and treatment we do not we have solved the problem of doctors being available there. So we now have a panel of trained doctors in Jaipur from where we are operating and we do not require super specialized doctors to basically do this. So there are doctors who are ENT doctors and neurologists who can who do not have this expertise but who can then treat patients based on the diagnosis and treatment that we are giving. So because we could go very early in the market and learn this we are not done too much investment we change the whole protocol so now our equipment all sits on the cloud the whole software and we build the whole company that way. So our pivot was basically we changed from this to advanced vertigo and balance clinic and so this journey from being an equipment manufacturer to being you know so we are now we are the world's first chain of super specialty vertigo disease and balance disorder clinics across the world. There is no other setup in the world which has even took you know two centers we already have 14 centers Gangaram hospital has our whole clinic in Delhi and we are you know basically planning to have one 25 centers across India to treat a million patients by 2018 next year. So you know basically rapidly going to the market rapidly iterating is something that we need to do once we do it the success improves and you know to define pivot basically again from Steve Lang these are business model changes without crisis. So in the earlier one you know by the time we realized we had run out of money we had run the team was disintegrating because for two years you know we whatever passionately we had built finally there was no market for it here this time in three months we basically changed to so there was no crisis it was a learning and we changed so this is I think important. The third part of my presentation is on that as tech entrepreneurs we think too much of the product product is important but not you know let's say 20% important what is important is the business model so here again equipment we could build but we had to change the whole business model so business model is important and what is important is business model innovation. So this is something which is you know which people do not very you know basically focus on that innovation is required not in technology but in business model innovation and just to give you an example this debate so I had I was competing against companies which are so these companies the multinational there are three of them there are two european and one american company combined they do not sell even 10 equipment in a year so there was no market there there was no market today we are building a market of 125 clinics so I was pitted against them and they have they are all 500 million dollar companies they have a great network across the world they have a great research and they have the money power so if I say I will be 10% better than them that is being foolish because I will never have the resources to be that correct so you are competing or pitting yourself against a competition by saying I can be 10% better 20% better that will not happen but it is very easy to be 10x better so basically 10x better is changing the rules of the game so we from being a equipment manufacturer are now a chain of clinics which is basically we have changed the rules of the game and there is no competition across the world we will set up 125 clinics with no competition and in a way if you see we have sold in a year 125 if you want to think of it that way that 125 equipment of ours will be in 125 clinics so we have changed the rules of the game so it is always better easier to be 10x better it is very difficult to be 10% better I think if we think innovatively in for business model not just technology we can change the rules of the game and then there is no competition and that is what you know we want to tell all our start-ups that we mentor that if you are changing the rules of the game then life is much easier if you are trying to compete then it is very difficult so I you know we could have chosen to be three things we could have chosen to be equipment manufacturers which we start started from we could have said we will build a large vertigo center where people will come from all across India or we could set up a chain of super specific clinics which was scalable and because technology was ripe to be able to do that we chose the third one and there are no other models across the world for doing that just to you know correlate this with lean startup agile and with design thinking I think some of these quotes are important one is think big so you know we are thinking as we will treat a million patients by 2021 five million by in the next 10 years and we have acted small you know starting from a PPT product and things like that correct so it's you built on that and you quickly go to the market it iterate and then you know improve your product we failed fast in the sense that we realize that we could not market the machine and the machines and and you know rapidly if you can learn so some of the things that we do we have very short fee so in medical diagnostic people say that you know you have to have a stable product you have to have a product so functionally our products are equivalent to the best in the world but on in terms of software we do a release every seven days which is unthinkable in the medical world we do a hardware release which means a new version of the hardware every two months because we are using 3d printing for prototyping so we are constantly changing our designs and we are constantly you know releasing them so we were told that doctors and clinics are accustomed to stable systems if you do this basically they'll think there is something wrong with it but we realize that doctors are very happy for the first time they can participate they can give feedback because all these G's and Siemens were not taking any feedback from normal doctors they would have their own set of doctors but here they felt empowered they felt they could contribute and they have been very happy with our whole journey one of the other things that you're doing is you know we are keeping the team small only differentiated IP or differential IP is being created in the company everything else so we are using virtual reality for rehabilitation of these patients we are one of the only three centers in the world who is developing this that virtual reality platform is basically it's all our design but is being outsourced we have an app and I'll come to that that outsourced we have a communication platform for these 125 clinics again open source so we are trying to build only three things one is a platform which integrates all our equipment and our data data analytics and some core equipment technologies which we are doing in house the other thing that I want to say is as an MVP we should be very clear that we do minimum features we should be audacious enough we should have the strength to basically go ahead and deploy the product rather than say I'll do a very intense feature so you know the the person is happiest when there is minimal features and this is a this is available on the web lot of people use it basically if you have a remote 99 percent the usage is of these these five buttons and that is what we need to build initially correct anything on top of this is actually crap so when we launched our app for our own patients you know we it has just one feature it shows some videos of the exercises that they have to do there is a long list of products that we will have features that will have over a period of time so there was a you know debate and people said that if we do not have at least three four features features you know patients may not understand may not take it well but we have realized that just one feature you have nothing there is no UI you have to just click it and you will see the videos of what the patient has to do it has been a great success because it is there is no UI nothing it is a very simple thing that we have developed it solves a major problem so the problem that we are solving was that in vestibulary habitation of these kind of patients you give exercises in week one exercise week two exercises will be different week three will be different how does the doctor communicate what he has to do in week three so we said whatever you put in your prescription on the platform on the platform that we have will automatically show in the third week it will be a different set of exercises based on what you have shown it's a simple feature which actually solves a problem and so doctors instead of saying and the patient said of saying that why is there is nothing else why should we download it they're very happy with that so we need to think start thinking on simple things on implementing them I would suggest all of you to Google this so Astro Teller is the head of Google X and he has given this great tech talk on celebrating failure in our company you know copying from them if somebody or the team decides that this feature will not work or this product will not work we actually celebrate because they actually decide not to put for the resources in this otherwise what happens is there is always the tendency to keep asking for resources to keep running that project even though you know it will not work so copying from them we have basically implemented that we have two kinds of so when we are putting the clinic we are putting the clinic in a hospital or in a clinic and we have the patient so we have two customers we have the doctor and we have the patient it's a b2b2c model when we have the doctor and the customer there are two personas that we are talking about and our team from day one has been told always when they are testing the product before they built anything they need to test on these two personas so it is in our culture to basically look at every feature from these two personas and we do it day in and day out and we you know we are not afraid to basically release products which will which will help you know benefit these personas as I said the app so you know design thinking the main thing is you build the right personas and run all your features all your products on them all your services on them and that feedback is very important so the last thing is a last one minute and we realize that once we have let's say we do a million patients in 2021 we would be doing on a peak day about five to seven thousand patients and for those reports to be analyzed by the doctors the panel of ENT neurology and psychiatry will be a huge task because how do you get so many number so we have solved the problem of not wanting to have experts across India but still we require experts in Jaipur which is easier to do now because we are scaling up but then it will be a problem at that time and so we are using machine learning and algorithm based diagnosis and treatment and so if you see here this is the clinical impression which the doctor team gave and this is what the computer analysis is what we write this is an internal this thing so at about we are at about 80 percent accuracy with very limited data in about a year's time we will read 99 percent accuracy so you know we have thought of what will be a bottleneck one year from now and basically started developing that so that one year from now we are not you know stuck in this this is called left vestibular peri... vestibular peri... left peripheral so the computer is giving the same I'll also show you where it is not giving the same so that you know here it is saying there can be two diseases while there is actually as per the doctor there is only one so there are there are you know it's a learning thing it's not perfected and it will take time just to finish you know these are the technologies we think will disrupt the future big data machine learning synthetic biology internet of things 3d printing virtual reality you know just as a as a corollary or you know to sum it up we are using all of this in our in our thought up so thank you I think we have time ten minutes yeah yeah yeah so at this point this is an internal document we are not we this is basically to help us learn machine learning to help us develop algorithms where we can reach to 99 percent accuracy so this is today not being used for treatment at some point when and this is a gray area so in us there is a problem in India there is no regulation which says it cannot be used but there is no regulation which says it can be used so in us there are issues with FDA and so we we basically are not using it as a tool but we are developing it that it can at any point of time if it is perfectly fine can be used what we plan to do is that in a year's time when it comes to 99% accuracy we would have this so there will be a confidence level which says I have diagnosed this with 100% confidence level and they'll be 95 and then so we if or when we start using this basically we would have an oversight panel which will basically say that if the diagnosis is less than 95% then you need to give your interpretation and that will go correct so in large majority of cases we will still not need it but this is we go as we play so it is like Uber you know so Uber was illegal in 99% of the countries of the world the concept of Uber was illegal in 99% and they knew this and they still start went ahead we are not going ahead we this is a back end but I'm just giving an example and today in 90% of the countries of the world it has become legal because it is it solves such a big problem that you know and you know I was trying to fight it out in Delhi and all that but finally they realize that the customer is very benefiting hugely the customer at the tip you know I've been in five minutes or two minutes can get a cab which was never possible so once the the efficacy is known and there will be enough clinical trials clinical data so nothing that we have done is which is not in the scientific domain so whatever protocols we are following are what would be followed in let's say Harvard Medical School Vertigo Center so so we are not doing any alternate therapy we are not doing any but there now with big data that is give you know with our own data the big data is giving us new perspective into how to solve the problem which we will first publish they will go to the to the scientific community and then we will basically implement other questions we have time so in a way we are so it's in in so it's not related to this but I will just give you an answer which is which is slightly unconventional so we are talking to government of Rastan so I am forgetting the name of the company it was net star I think so in 2003 to 2006 this company built they invested about about two billion dollars to build intelligent express highways in Europe which had all the traffic and you know speeding and this and that all the signals and it was in thirteen countries I don't know about 1700 kilometers at the cost of two billion dollars this was built this was acquired by Nokia in 2008 for about four billion dollars in 2013 ways came up which was acquired by Google in in one billion dollars which basically is Google Maps that you see which tells you where the traffic jam is correct so they are taking our data to do that why can't our government plug in to Google Maps to basically direct all the traffic lights and this and that correct this is something which can be done easily but if if Ola and Uber can basically tap into those APIs why can't we do it so you can divert traffic you can do so the government app and this app should basically integrate and have a seamless flow of things the policeman should know when traffic is happening there are ways of today doing it in a very low cost mechanism not to build those kind of hardware but to do so the driverless car is another example so that they were trying to build actually lanes which will be able to you know channelize the cars and there would have to be specific lanes which were driverless cars could move and then they realize that that was too expensive a proposition to build software once which can be automated and then you have any car which is so today Tesla and e-class Merck and all have this feature that they can actually if regulation allows be driverless correct so we have to think and build system which utilize this new technology rather than basically trying to say that we will put all hardware to solve problems hardware will not solve problems we have to think this is so you know politics is out of this discussion politics is something that we cannot discuss and we can't blame our politicians you know how us politicians are any other questions that you have we have I think two minutes more so so so we have built the system such that it is scalable it takes me two hours to set up a clinic everything is plug-and-play and the data starts coming here so that that local doctor does not need to be trained and then here we are building the AI machine learning to scale it up so we are doing all components to make it scalable it is just a matter of you know now basically deploying it in various places there is no technological or any other logistic barrier that is so that is how we build a system start a clinic yeah so a clinic requires an investment of eight lakhs the payback period is less than two years yeah so that's what I said we learned certain things the first thing was build a crap MVP go to the market fast when you go to the market you have to have your antennas open to learn what they are saying rather than have your own hypothesis and trying to say I will ask this question to get the answer that I want correct so we asked a different question we told them so we did not ask them any questions so market surveys don't work we actually gave them the product they said yeah this is a good product it's very cheap they did not say it's a good product they said it's very cheap but what do I do with it I do not know how to interpret it so that so the input was so that input came very fast and then you have to think scalable you have to build the vision has to be large and then do small pieces so we slice the problem we we have you know we slice the problem build small components and integrate them so so all these learnings came from the first thing yes so we have we are C certified we have ISO 385 which is for the medical diagnostic equipment we have so the in the team in the equity team is our doctors who are the best in this field they are internationally known we have got the right teams I think that is also important that you have to have the right team to do it correct so we have the so one of the doctors that we have on the equity team has written eight books on vertigo business and valence disorder I think the highest number of books that any doctor across the world has written in this he is also part of the international various committees on equilibrium at three and vertigo and business so once you have the right team you have the credibility and then you have all the certifications done so that is what you are considered yeah so we are now building a marketing team we have 14 clinics of all this has come out come about without a marketing team it has come about because of word of mouth and now we are putting in place a marketing team to do the marketing so we went very early we talked because we wanted not to have a marketing team because we wanted to go and interact with all stakeholders doctors patients everything to get the feedback on what is happening and now we are so that's why the scaling up you will see it took us eight months to reach to 14 and next one year will reach to 125 so this is now where so the marketing team is now already in place from this month this month means February and we will start basically exponentially expanding so I did not tell you a secret and this is that my wife is a vertigo business and balance disorder expert and he is one of the doctors and the other doctor is Dr. Anibar Mishwas who is an international authority on that and basically these are the two people who are also in the equity team so in a way so basically you know I wanted to be a doctor and became an engineer so I married a doctor and this is in a way you know engineering at the service of medicine or you could say I serving my wife yeah so so once we scale up we will have these 125 clinics which are ENT clinics correct and there are so let's say your vocal cords are a problem so the tamangeshkar voice goes bad you have nodules on your vocal cord then there are machines so there are only two centers in India they those machines cost of 1 crore each correct we think the technology has changed platforms have changed where it can be built much in a much better mechanism just to give an example that has a storage which cost about 40 lakhs now I would I cannot imagine why you know you don't use a Google to basically upload or cloud to store correct why would you have a feature like that today so these are all legacy machines and so once we once we have these 125 clinics there will be a lot of services which these ENT doctors or neurologists will require and we can build these technologies and then there will be no cost of differential cost of marketing if I build a new technology for a new service on day two it can be installed in 125 and you know move ahead so but if standalone I want to start selling that then it's a huge issue I think we are we have run out of time any questions last question no thank you thanks a lot