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00:00:00 SUJEET JOHN: Welcome to this time Times Techies webinar. I am Sujeet John, and I will moderate this discussion that we are having in association MeitY, Nasscom Coe. Today we will discuss the value of open innovation and Co creation, especially in the context of developing AI solutions. By open innovation, we refer to the practice of actively seeking external input from startups, researchers, and other stakeholders to complement internal capabilities. This approach allows organizations to access new ideas, technologies, and resources that may not be available internally, enabling them to bring more impactful innovations to market faster. Co creation is about collaborating with startups to develop solutions, products, or services. Startups bring fresh ideas, agility and innovative approaches, while larger organizations provide scale, resources and market access. It's a great combination. And we have panelists today from companies that are all actively working with startups to Co create solutions. And our objective today will be to understand the value it has brought to them and how such relationships can help in developing AI solutions faster. And for this discussion, we have with us a very seasoned set of panelists, speakers, professionals we have with us Ramesh Kalanje. Ramesh is vice president and managing director of the India Center of Excellence for cybersecurity company Com Vault. Prior to this, he was VPN GM of Dean Software, a corporate travel management software platform company. And before that Analyt, he was with analytics and position support company Musigma, where he led top accounts growth. He was also at Cisco for three years and EMC for 15 years. Welcome Ramesh. We have Sivakumar Padmanabhan. Siva is the managing director and head of the India Global Innovation and Technology Center at AstraZeneca India. He's also responsible globally for all enterprise platforms and solutions provided by AstraZeneca IT to the business. Before joining AstraZeneca in 2014, Siva Leta Global in house Center for IT and digital at Flex. He was also with PwC in India and the US. Welcome Siva, we have Amitesh Sinha. Amitesh is vice president and head of corporate venture capital and Vedanta Spark initiatives of Vedanta Limited. His role involves driving value based venture investing and fostering a startup ecosystem. Previously recognized as one of India's top CFOs, Amitesh held leadership roles at LinkedIn, KPMG, GE and Green Light Planet. At his last organization, SEMA Funds, he managed over $200 million in assets. Welcome Amitesh. We have Sriram S Sriram is director and head of factory automation and industrial division at Mitsubishi Electric India. He has been with the Mitsubishi Electric since 2011 across multiple roles including strategic planning, sales and marketing. Prior to this, he was with Omron Automation for over five years and with Schneider Electric for eight years in sales and marketing roles. Welcome all.
And we have with us Sanjeev Malhotra. Sanjeev has been on this platform a couple of times before. Sanjeev is CEO of my team, Nasscom's Center of Excellence for IoT and AI. Sanjeev started his career in Intel in the San Francisco Bay Area. He led product development strategy and global operations at Intel and later Qualcomm and other companies. In his Nasscom role, he's building the innovation ecosystem with startups, corporates, government and academia, focusing on technologies like IoT, AI and robotics and its application in different industries including healthcare. Welcome, Sanjeev.
00:03:30 SUJEET JOHN: For viewing these concerning questions to the Facebook comment box, I will. If you have questions, I will put them to Sriram, Amitesh, Siva, Ramesh and Sanjeev. Sanjeev, let me start with you. I mean, the MeitY, Nasscom, Coe acts as a bridge between technology startups, established companies and government bodies with the idea of promoting collaboration in sectors such as AI, IoT, cybersecurity, and blockchain. So you are the forefront of fostering innovation in emerging technologies. You have worked in Silicon Valley where these ideas of open innovation and Co creation have been around, I guess for some time now. I mean, so tell us, give us an idea of what this means, open innovation, Co creation and how valuable that is.
00:04:11 SANJEEV MALHOTRA: Thank you Sujeet. So this concept of open innovation and Co creation this these these terms have existed for a while and but what's happened in last few years is actually bringing this into the mainstream. So there are a couple of things phenomenons that have happened. 1 is the change of pace of technology. You know what we call emerging technologies or frontier technologies. There are so many of them like, you know, when we started, they all start with the buzzword, then actually they come into the mainstream. So when we started the Centre, you know, the terms like IOT, AI, AR-VR, right? And, and all these terms were, were, were around, but there was a recognition from Government of India. This is going to play an important role in our industry and in our economies. And that's how we were constituted to to bring these encourage and enable more of these solutions, you know, in the country and also have them adopted by by the industry so that both the sides are benefited. So as I said, change your pace of technology. I mean, there's so many technologies which are changing at such a rapid pace. So that is one phenomenon. The second is technology is playing role in all the domains now like never before, you know, be be it in healthcare or be it in pharma and healthcare or be it in manufacturing or be it in logistics and supply chains and so on. So, so everywhere we see the impact of technology, which is unprecedented. And all the industries are as, as the saying goes, you know, that all the industries are trying to be tech industries now or tech companies to say. And, and given that, you know, there's another phenomena that is happening there. There's a rise of startup work. The Indian startup ecosystem has, has become pretty vibrant over the years. And we have seen, you know, I can tell you when I started the centre 8 years ago till now, the products we used to see were still coming up. They were trying to get to that level of, of the industrial scale. But now what we see is the maturity of Indian startup ecosystem, which has come to an international scale. So that's where the that necessitates, you know, or that brings sort of a good synergy for, for corporates to, to work with the startups for multiple reasons. And one of them could be, you know, to, to stay abreast with what's going on, you know, because startups are working on cutting edge technologies and ideas and applications. And at the same time, corporates would not make sense for them to work on everything themselves, right? You cannot, no matter how good or high, how, how big you are, you cannot cover possibly every technology. So this gives an opportunity for them to, you know, try things, experiment with things at a very low risk. You know, that's the beauty of the things. You can try so many things at a low risk and, and you know, you can dabble with things and you may get some disruptive idea also, if nothing, I mean it will be some of them will actually get adopted in your operations and R&D work. So, so I believe this is now some of the people we have here are The Pioneers in this, you know, who have actually led the way. And I'm glad that we have have them on the panel and, and, and I believe this is going to pick up as we go along. At the same time, you know, as I said, startup ecosystem is continuing to grow in India, thanks to the government policies and thanks to the industries who are beginning to support it both from the adoption as well as investment standard. So so.
00:07:50 SUJEET JOHN: That's large organizations don't have to do everything. And today Indian startups have become almost world class in many areas and it's possible for these companies to work with these startups to on various areas. So all the others, I mean all of you are from diverse areas from pharma to mining, electric software and all of that. Give us an idea, maybe see why you can start. What are the areas where you think we can, we can go to specifics later. But right now broad areas in your organization where you see the role of open innovation and Co creation.
00:08:27 SIVA KUMAR: Yeah, that's a great question. Thanks, Sujeet. So in pharma, you know it's evolving and things are changing at a pace that we've never seen in decades, right, Because of the some major trends like what we're talking about high level of personalization of therapies. So we're talking about things like cell and gene therapy, where in autologous cell therapy are actually using the cells from a human human being and then processing them and then putting them back into the same human being in a matter of days. So that is the level of personalization you're talking about, which we've never seen before. The second piece is the need for speed, right? Because of the fact that, you know, the the lives are at stake all over the world, right? And and innovative pharmaceutical companies need to bring treatments to market very fast. What used to take 8 to 10 years needs to take fewer and less and less time, right? So the needs for for speed, that is another very big theme that we see there. There could be a lot of innovation. Another theme is about early diagnostics, right? There's a lot of patients out there and, and we need to get to them earlier so that they can have a better outcome, right? It's always earlier, a better to catch and in fact prevention is even better, right. So we are also working in the industry on prevention awareness and so on. But beyond that, just the very early diagnostics and trying to reach as many patients as possible. So overall, I would put all of these under the larger umbrella of patients and to city, right. So we're thinking about the patient, we're thinking about everything around that patient, and there's a lot of room for innovation about their experience as they go through diagnostics, treatment, you know, post treatment and recuperation. So really focusing very intensely on the experience of the patient and how can innovation and technology make that easier, make that easier to predict and understand what they're going to try to go through in their minds and therefore have as pleasant an experience as as helpful an experience as possible through that journey. So that's the sort of the overarching theme, but these are some of the very important things. And the last one I'd mentioned is efficiency of usage of resources, capital, money, everything, because of the fact that we need to channel more and more into R&D in the innovative pharma, which is when we will be able to bring more new medicines to market. Which means that where we spend our manufacturing, supply chain, distribution, sales, commercial activities, we need to make that very efficient. We need to do it at high quality. But at the same time, we need to make it very efficient so that the capital allocation, the cash allocation can be channeled more towards really finding the next generation of medicines, helping more patients. So that I would say are the major teams in the pharma industry.
00:11:12 SUJEET JOHN: And you have you think there are opportunities to work with startups and have an open innovation ecosystem for in all of these areas?
00:11:20 SIVA KUMAR: Yeah, absolutely. I think it all, each of these is a fundamental shift. And therefore it needs a rethinking, right, which happens once in several decades on how these processes are run. You know, how the data is managed, how AI is used in a completely new way, right? Like rethinking every single thing you do in the context of AI, right, For example. This is all, you know opportunities for Co creation, open innovation. We cannot do it all as a company, right we because there is only limited number of people resources that are available, but then they have almost unlimited pool of capability that's out there in the ecosystem. And if we can find a good way to match that and tap into that, I think then we can totally accelerate, really accelerate all of these things. So definitely I think in all of these areas there is tremendous opportunities for Co creation and innovation.
00:12:13 SUJEET JOHN: OK, OK. Sriram in manufacturing tell us at Mitsubishi Electric, what are you into and how do you see collaborating with startups and all possible in this Sriram? You're muted.
00:12:34 Sriram S: OK. So thank you so much. You know, I mean, again, that was that's a very expected line question, you know, in, in this kind of engagement. So in, in, you know, Mitsubishi Electric, you know, we are almost like 100 year old company and we have been a very strong product oriented company for all these years. But you know, like Shiva said, the the automation space is also as rapidly changing as it has ever been before in the past. And for US, one of the biggest challenges that arises right now is, you know, in the areas of how to get the products in place quickly to the market. So one of the area that we very steeply focus upon right now is creating products where the go to market opportunity can be minimised, the opportunity can be increased in the time to go to market can be minimised as much as we can. We're also looking at, you know, areas like, you know, deploying applications to various industries while we offer automation solutions to the market. Each industry has got its own requirements. The nuances are very different, but the time to engineer and deploy them has to be that much faster to keep in pace with the kind of expectation that the industry goes through. So couple of areas on the on the business side that we work upon is on the development of product, on the R&D space and on the deployment of of those solutions to the industry in the space of manufacturing within the organization also.
00:13:58 SUJEET JOHN: You provide solutions to a wide range of manufacturing companies and all that is it.
00:14:03 SRIRAM S.: Yeah, that's right. That's right. So we cut across, we are, we offer solutions to the automotive industry, to the life science industry, food and beverage, so so many other industries as well. So on one side of, you know, on one side, adoption of AI and open innovation is basically centered around developing your own products and solutions. On the other side, we also find a very inherent need to you know, improve our own business processes. So we also find a very significant participation of open innovation into our own business process re engineering activities. And particularly, you know, when we talk about demand side management, you know, the supply chain was very disruptive for us during the COVID times and we had to find better ways of dealing with the situation. So we had really gone a little deeper to understand how we can make use of these available technologies on on open and you know, own open innovation along with Co creation to look at how we can deal with the demand side of it. We were also looking at how to improve our own production management capabilities to deal with the requirements of the market. And another important aspect that we are now deeply delving is into is the human resource management, particularly on the training and development areas of our people. So these are some of the areas that we feel that we can really work on on these basis.
00:15:18 SUJEET JOHN: We'll go deeper into AI later, but OK, Ramesh, same question.
00:15:27 RAMESH KALANJE: Yes, I did. So just to give a, a, a minute pitch on what Commonwealth does right. So we call ourselves as a cyber resilient company. So with the, with the advent of ransomware and cyber threats, there are a whole bunch of companies which are basically trying to defend the attacks and, and, you know, make sure that enterprises and, and any kind of customers are able to try and defend these attacks. But where we come into is making sure that the organizations are, are resilient. So when when we say resilient, when, when you have these cyber threats, it's not necessary that every cyber threat can be defended. So there is obviously there's going to be a whole bunch of cyber threats that is going to pass through the defenders and, and get you, you know, get you into a situation where your your data is not usable and your business is not going to be able to be, you know, effective and, and running right. So that's where we come in. We provide the ability to organizations and businesses to be resilient in, in a way that whenever an, whenever an attack or a threat actually happens, these organizations and companies can rely on on a particular data set that is clean and get it back into motion. And make sure that the the businesses and, and, and, and the organizations are alive and kicking so that you don't really have to give in to whether it's ransomware or other demands of the cyber threats. That's where common place, right? So based on, on this, there are two things Sujeet and you know that Sanjeev and and the team at Mighty Mass Com CEO have been very, very helpful and, and engaged with us. 1 is what I call as extreme experimentation, right? Extreme experimentation is, is is a great thing for enterprises, companies that are, you know, publicly traded, which are having certain things that there is in, in charter. So trying to do extreme experimentation is is a little bit of a tangential thing because you have a bunch of things that you need to work on to keep your shareholders happy. So there there's very clear cut charter on what you need to work. The second thing that this particular Co creation and open innovation actually helps us is total cost of failure, right. So the total cost of failure for us to go on on a charter with our organizations and, and trying to make sure that we incorporate the things that we want to try and look at different activities that might be very core to our product, tangential to our product. It might be useful for trying to get go to market on something and, and, and try and better do do our customer experience a lot better. So different categories, right. And and for us to try and put every dollar that we have in across all these categories becomes a little bit of an issue. So these Co creation and and open innovation aspects actually help us a lot in in in this particular piece. So going back to your question around the use cases for which we are using this open innovation Co creation, right? And one is of course, when when I talked about cyber resiliency, obviously data security, encryption optimization, anomaly detections, you know, and, and everything now has become very cloud oriented. So cloud security, cloud native security around how we are trying to do that. And, and, and a lot of this is, is, you know, a lot of these pieces, we do it ourselves, but there are going to be tangential pieces, some use cases that we might actually need some faster access, some resources which are very specific on, on that particular sector and, and has extreme good thought leadership. It really helps us try and get this. But Sujeet, going back to your point, I think we'll probably talk about a couple of examples that we can share.
00:19:38 SUJEET JOHN: Yeah, we'll do that later. Yeah, Amitesh tell us. I mean, you give us an idea what exactly your role is and also the larger group, is it primarily mining that you help or the other areas as well?
00:19:50 AMITESH SINHA: Sure. Thanks Sujeet. Thanks for having me. So Vedanta is a well known company. It's one of the largest conglomerate in India doing metal mining and biggest company natural resources. And what Vedanta Spark does is, and that is what I lead, is creating a collaboration, a partnership between the startups and the various business units at Vedanta of how we can. You know, Shiva mentioned about need for speed. It's kind of resonates with us that how we can expedite our innovation journey and who it could be better than startups because they're agile, they are Fastrack, they are very adaptable to the various situations. Because you know, when we are talking about metal mining, smelting, we are talking about some of the process which has been defined 50-60 years back and we're still following that with those kind of equipments and assets which we work with. So the idea was born when, you know, one of the start-ups specifically in the semiconductor industry with display glass business was acquired and then the chairman realized that we have just acquired one startup. Can we kind of create this like a regular initiative for Vedanta where we can work with several startups? And the idea was that we just do not work with startups, but the idea was to create a ecosystem of start-ups, an ecosystem of innovation. And this is where, you know, we were lucky to have partnered with meeting Ascom, Sanjeev and his team where they have enabled us to adopt various start-ups, look at various start-ups, look at their innovation centres and how they can help us in our operations. And with Anta being very diversified when it comes to, you know, the portfolio we have right from zinc, silver, aluminium, copper, oil and gas, steel, every process has its unique nature. And but we're lucky that we so far we have worked with 200 plus start-ups, 200 plus projects and it still continues. And our our chairman has set aggressive targets, which clearly resonates with how we want to, you know, drive this and make this integral part of it. He keeps saying that they should not be an outside project, but it should be the integral part of the business of how business thinks about innovation. You know, I'm going back to the need of need for speed. Every company has their own R&D and innovation centre, but something that really can expedite and has translated for us is working with start-ups because the way they think, the way they collaborate with our business units and team members has been exceptional. And that has enabled a lot. And not only that, since I also lead the corporate venture capital, we provide growth capital to the startups to see how they can grow in the ecosystem. And you know, after talking to various startup founders, we realized that we see money is out there, but somebody a company like us and we just like, you know, we have Mitsubishi, we have AstraZeneca combo companies like us. If we give purchase orders to these startups, sometimes this this value is much larger than the VC money because they're able to test their products, they're able to develop their products. So that way this, you know, the whole ecosystem which we are building is of course will help and create a win, win situation for startups and corporate. But to the industry at large, you know, we'll discuss some of the use cases in detail. But one use case where we are using one startup with an AIML algorithm to to enhance one of the smelters in zinc. And we got to know nothing has been done even close to what we are doing across the world. So which gives a lot of sense of pride and, and, and that we are fast tracking the innovation in the world that we are doing something which has never been done. The various areas, you know for plant large setups like us, the 2-3 key areas where we have to increase the volume, reduce cost and bring in the world class ESG. How do we do that? Number one, we reduce our unplanned shutdown, we reduce our planned shutdown because you know, every quarter, every year there's some planned shutdown. These are two very large focus area and of course there it buckets into various projects which we are doing and which we're thinking two more important aspects which we heavily focus is on the exploration and resource discovery. So we are using drones, we are using the advanced technology which has been used by NASA and ISRO in terms of satellite imagery and, and with drones, SAR and GPR radar radars for helping us to explore the metal faster, to do the mine planning in a much efficient way and worker safety and monitoring. That's also very important. We have partnered with startup coming out of IIT Madras, who are helping us detect unsafe incidents, which has made our workplace much safer. So you know, the combination of this and the ecosystem building which we are with partners like you know Nasscom and others, we we believe we are moving in the right direction and startups are the partners to help us. And we have just my last point, Sudeep, we have seen that we, you know, we have worked with large technology partners, but there also we have introduced the idea of bringing one or two startups even in the mix with the large technology partners and that's working very well for us. So everywhere we are seeing that agility which you know, can be brought to the system gives us quicker results.
00:25:47 SUJEET JOHN: Very interesting. We're working with more than 200 startups, you said. And yeah, across a variety of areas. Sanjeev, tell us. I mean, there you all heard. Of course, we'll ask us some specific examples from each of them. But before that, Sanjeev, give us an idea. I mean, we, of course, have a diverse set of companies here. But generally speaking, are you seeing interest among companies to come forward and work with startups? So is that a challenge?
00:26:15 SANJEEV MALHOTRA: Good point. I think, I think this when we started, obviously we had to go and kind of tell the idea of to everybody how to, I mean when we we have to kind of introduce this idea. But now everybody knows this, this is the, you know thing to do. It's just that everybody's trying to see how to how to manage this internally, how to manage it around their internal business groups, how to how to make it work internally. And I think from whatever we heard from people here and especially Amitesh, what he was talking about, they have introduced in so many business groups. So I think that concept is beginning to grow. There are more success stories that have come out of it. The value coming out of it is coming becoming very well known to everyone. And so that concept is picked up and so much so that we have even seen some of the smaller companies also working with us. We have a division for SMEs also, right, especially on the manufacturing side where the technology definitely needs to be updated and they need more hand holding than than some of the other companies and we see a trend even moving into that direction. So, so there are companies who are spread all over the continents working with us. Some of them who are not even present in India want to work with Indian companies because Indian digital has made a mark. I think I can say that without doubt, having worked on, you know, in, in the, in the technology hubs of the world, I can tell you these, these companies have made a mark. The Indian digital, some of the solutions that we produce out of here are world class and they also offer the same advantage, you know, I mean, which all start-ups offer of flexibility and, and, and, and adaptability to corporate needs and also the cost advantage. I would say. I mean, you may have a choice of doing that in Silicon Valley also. But the same advantage of being present in India for like, like, like GCCS, you, you get that with the Indian start-ups also. So while some challenges will remain, I'll not say that it is all a smooth run, but I think somebody driving it, the senior leadership, you know, people who are present here, if they they stand behind it, I think these things tend to pick up more. But I see that globally also picking up because visitors who come to us from the CCS across the world, right? I mean, we have, incidentally, I was just noticing we have European, Japanese, American and Indian company here today. And, and, and I can tell you that, you know, this is a phenomena which is we see interest from companies in all continents. So that's, that's the nature. And, and, and I'm happy it is picking up and happy that India is also stepping up, you know, on that the Indian startup ecosystem, this wouldn't have been possible if we didn't have something to offer here. And, and that offering is becoming bigger, wider, and for every use case, we have four or five companies who are there to, to offer solutions. So that's the choice people have. So it's not that they have to just go with one. I think that is there, you know, so I mean, I, I hear my job is very interesting. I hear use cases, you know, how to detect early cancer from people like as far as Anika, you know, and in the afternoon we talk about some operations in the mining, which Mammitesh will say, come and visit Rajasthan and see how mining is done and then talk about cloud optimization with Cornwall, right? I mean, so, so challenges are diverse and the there are solutions available for everything. And, and now even people come to me even beyond digital also, you know, I mean, just as a anecdotal thing, as a, as a little on the lighter tone, somebody called me, oh, I want to carry magnets in sub zero temperature. Tell me a solution for it. And I said, I'm hearing this for the first time. This is somebody calling me from Germany. I said, well, we deal with digital things mostly. But now that you're asking me, let me look around and believe it or not, we found somebody in Pune who actually it does that. So I am myself surprised about the country we live in that day. So much happening that we don't know. I mean that is to be discovered. I think the job of discovery and actually finding the things is, is a pretty big job. I mean we work with more than 30 people team day and night. And I feel we have not done the job 50% even. I mean we are just covered maybe sixty to six, around 60 to 65%. And there's more to be discovered and more to be done. There's so many things and biotechnology happening, right? So the list is pretty wise and it's increasing for us every, every, every quarter. You know, we increase the the type of solutions and the demands that we get and we're trying to cope up with that. So, so that's all I would say looking positive at this point.
00:30:58 SUJEET JOHN: Oh, so good to hear that Indian digital has made it's mark around the world and so many people coming forward. Wonderful. Sanjeev, there's I don't know how it started this time when you were speaking, there's some squeaky noise coming from your mic. I don't know whether what you can do to set it right, but I think kind of improved as you spoke, it became less irritating, but just see if there's something you can do about that. But I'll come closer to that.
00:31:23 SUJEET JOHN: Siva coming back to you tell, I mean some specific examples and Sanjeev was saying earlier AstraZeneca was one of the early ones to really start working with startups and the mighty Nasscom Coe on developing this ecosystem. Some specific examples where you startups, you work with startups, especially if you can find some AI AI examples.
00:31:45 SIVA KUMAR: Yes, yeah, there's, there's several. So in the in the earlier stage, we had a number of startups in the early diagnostics area, right, like early diagnostics of lung cancer, chronic kidney disease and, and, and various disease conditions like that where they were able to use imaging technology and the combination of that with AI, right? Like even simple X-rays and overlaying AI on top of that to distinguish, you know, the cancer occurrence from just general, you know, nodules that form in the lung. So that is one example which was very successful in that that was able to go to many countries. You know, after the based on the success in India scaling to many countries, we also had very similar ongoing collaboration on the diagnosis, treatment of, you know, lung diseases, especially like pulmonology. So they're basically you're, you're actually allowing patients to not only not only detect, but also manage it medication adherence and, and monitoring and keeping, you know, their health condition in, in check. So those are some of the specific earlier examples. Now we're seeing a number of examples in outside of the classic pharma value chain as well. Things like, for example, from a sustainability perspective and smart metering, right? How, how do we make sure that we are able to measure and manage our buildings across the world in terms of green, the green buildings, in terms of understanding enough microclimates inside a building and adjusting the heating and cooling in a way that we don't waste energy, right. So within a big building, for example, that could be, you know, zones which are too hot or too cold for people that are occupying. And if you can micro cluster it and, and regulate the temperature in this and at that level, then, you know, we have a lot of energy savings, which ultimately contributes to, you know, lower, you know, consumption of energy and, and in greening, right green buildings. So there's a number of areas like that. One of the examples we are, we are looking at is the safety side, right? Like when you look at the factories and you look at computer vision, because there are certain conditions in a, in a pharmaceutical factory that might be causing must, might be risky, which could cause accidents. And a lot of times, you know, as human beings, we cannot see everything, right? What are the conditions? There are a particular piece of equipment that's in the wrong place or is there a, is there a conveyor truck that is not moving correctly, right? It's moving wobbly or whatever. So those things you know, you, you tend to detect using computer vision, use AI to interpret, you know, the, the unsafe conditions within factories. So these are all areas where we are seeing the use of AI And there's a whole range of other examples. I think more and more we are looking at the, the highest value application of AI being in the drug discovery, right? And of course, we are working on some examples from India, but it's a global effort as well, right? Which is about how do I identify the candidate drugs much more easily. You might have thousands of possible molecules. How do I get it down to like 100 or less that I can actually do experiments on in a laboratory and be much more a chance of success, being much more if you find the right candidates. So that is one example. We are also looking at clinical trials. How do I speed up clinical trials using artificial intelligence? There you have adjudication of events that come up, right, adverse events and other events. And sometimes it takes a long time to investigate the events in the manual way that is done traditionally, right? Different people looking at it and scoring it and trying to understand if it's a really serious event or otherwise. And AI could really basically accelerate that, right? So you're therefore compressing the time of a clinical trial. AI could also help select better sites, better patients or or patients that are more suited. And so in that way you don't get medicines to market faster. So these are all areas of rich opportunity. Some of them they've already worked on, some of them we have, you know, very good interest in in working with, especially the Indian ecosystem that's rapidly maturing.
00:35:54 SUJEET JOHN: Do you find quality startups in in these areas and the ones that you worked with, you're very happy with them?
00:35:59 SIVA KUMAR: Yes, we have found very high quality startups and of course there's a process of working through it. It's not really made in that sense. But you know, I think maybe that your next question we'll address some of the challenges in that. But definitely the the raw quality is, is very good. The energy and the quality and the depth of thought in these startups is is really, really good.
00:36:21 SUJEET JOHN: OK. Sriram, same thing. I mean, especially if you can find and give some AI examples. And how was the quality of the startup? Sriram, you're muted.
00:36:34 SRIRAM S: So, you know, in Mitsubishi Electric we have, you know, what we call as the digital innovation centre. And, you know, we've been working through this digital innovation centre to identify various start-ups who can, who can work with us in the area of, you know, digital technology, then how to utilise this technology and then come out with a very strong solution to what the society might need out.
So, you know, over a period of time, you know, we've been really deeply, you know, and I'm very happy to listen to some of the so-called problems for which Amitesh and Shiva found solutions by themselves. But we have also been working on some of the solutions. Typically. You know, one of the examples that I probably would have would be of some interest to Amitesh as well is on, you know, getting the right combination of material properties to get the best metal out of it actually. So removing the impurities around the system so that you make a much more quality efficient product and not just bringing down the quality, but the amount of energy that is required to prepare or to make that particular product. So been working, we have been working with startups and here is where, you know, we've been very, you know, you know, happy to be working with MeitY and Nasscom. MeitY Nasscom particularly with Sanjeev and the other members who have been able to bring to the table lot of such startup companies who have been able to work with us and we've been able to work with them to define within solutions to some of these kinds of problems. Typically, you know, solutions centred around in a way we somehow to to answer your question, you know, we have been working on some of the solutions around preventive maintenance and maintenance for the industry. We try to work on energy management to bring down the cost of per unit of production. For example, this was one of the problem statements coming in from one of the, you know, automotive 2 Wheeler company where they wanted to see what is the kind of energy that is getting consumed for per vehicle and what is the best way to minimize and optimize those energy consumption so that the per unit cost of producing vehicle comes down. And that was a very typical area where you can, you know, you might start with the utility area of energy management, but then there are various process optimization also that can be done. So it's a combination of multiple areas of engagement which can eventually bring down the energy to consumer for a particular product to be produced. So, so there are these areas that we have been working on very deeply with some of these companies. We have also been working on, you know, on kind of a disrupting solutions to the market. For example, if you typically look at robotized solutions, Robo is something which people are looking at deeply. You know, AI with Robo is something which can work for a monotonous, repetitive work environment. But then for small and medium enterprises, investing into a robotic solution might not be as feasible as commercially viable for them. So we're also working on a model called Robo as a service where we are able to bring down the robo not as a CapEx, but an OpEx requirement. It helps them perform the necessary tasks, helps them improve their operational efficiencies and performances, but at the same time deliver the kind of output that they are looking for. We're also working on, you know, on startups where we are looking at fleet management services where, you know, we can identify, identify critical areas of operation maintenance, allow them to work on, you know, identifying, you know, preventive maintenance requirements, working on the assets before the assets gets damaged or failed. So we're working on creating a solution where there's a fleet of management services available and the users can take best use of it without directly investing into some of these activities. So again, we're working with start-ups around that. You know, sometimes it also becomes as an automation solution provider, these solutions becomes complex with the industry. Metal industry might need different solution. A life science industry might need a completely different solution. The product might look like automation, but the solution might be very different and complex in nature. And here is where we are also trying to see how well we can harmonize some of the solutions. The names might look very consistent. You know, for example, if I, if I, if I recall correctly, Shiva spoke about, you know, early diagnostics, you know, and Amit, they spoke about that preventive maintenance and maybe quality enhancement. So typically, you know, if we have to create a solution which can address each of these industries, that's the best thing to do so that the time to deploy is shorter and faster. But the complexities are so different. So we are working with startups where we acquire data. Data can be, you know, consistent for each of these industries. If you want to work on energy, energy datas are similar, you know, consistent for a life science industry or a, or a metal industry. But the, the, the challenge comes in how, how to use those datas and how quickly the datas can be, you know, assimilated and then worked upon so that we are able to create the right reporting solutions and reporting tools, which can be scalable, where the analytics can perform in this, you know, certain way so that the user can also use it. You know, you don't necessarily want a specialized engineer to come down and do the coding to, to, to make, to give shape to the data, to give interpretation to the data. So we are also working on some startups to develop no code solutions where, you know, you can just create a reporting structure where the analytics comes out and somebody can just drag and drop and, you know, visualize what they want to do that. So there are multiple areas. We've been also working with the Normatieness COM with almost about 3540 different potential solutions to the market across different industry segments. So yeah, this is a work in progress, but yeah, there has been some amazing experiences coming out of that.
00:42:17 SUJEET JOHN: Wonderful. So many areas. OK. A lot of opportunities there, Ramesh.
00:42:23 RAMESH KALANJE: Yeah, Sujeet, I think it's great to hear, especially coming from IT dominated cyber security world. Try to look at life sciences and manufacturing and you know, Amitesh talked about smelting, which I hadn't heard that word probably 30 years back, like when I when I was doing my engineering. So, you know, I, I think it's, it's, it's great because I, I see the opportunities where, you know, if it, it, whatever we are trying to do with the Co creation and innovation, open innovation, it's translating across industries, it's translating across, across what we can do as applications. But you know, just coming back to my industry, you know, by leveraging AI, cyber resiliency can actually become more proactive, efficient and effective. Yeah. And then says actually the ability to detect and and prevent and respond to threats by analyzing a lot of volumes of data. And I think Sriram also talked about data and, and how data analytics is actually coming into the picture across across the different industries that we are talking about. You know, basically there is, since there is large volume of data in real time identifying patterns and anomalies and automating it. It is, it's actually a lot of time consuming task, right. So this basically, you know, let's the security teams to kind of focus on decision making and, and threat hunting and, and try and strategize as to how are we going to try and defend or, or be proactive and trying to alert our, our customers. AI basically lets us handle the repetitive data heavy aspects of cyber cybersecurity, right? I mean, basically, you know, it is a complementary augmentative, you know, approach for human expertise and then basically tries and, and gives us an ability to adapt a, a very focus security posture against, you know, our, our landscape is ever evolving of cyber threats, right? So it's, you know, they don't have any regulations, they don't have any governments trying to monitor what they're doing and all of that. So they, they evolve like on a minute, minute to minute basis. So everything that you defended in the past hour may not be relevant to, for you to defend whatever you're doing for the next hour. So based on that, it, it really helps us to kind of have this Ave. Of innovation and Co creation because there are so many things that we might not really have understood and leveraged around you know whether it is data security, whether it's encryption technologies optimization, you know anomaly detection and and you know trying to understand all of these different use cases and and there are so many branches to try and use the segmentation and even with respect to our customer base as well right so there might be farmers like AstraZeneca using very hardcore you know specific test cases and and saved all the data and and coming up with a new vaccine, let's say and, you know the the bad actors might just put a a lock on on that data so that nobody can use it so for us to try and look at OK for that particular use case is there something that is being done along with working with life sciences organization and and trying to bring that approach with respect to whether it's animal detection and and things of that nature is really helpful Sujeeth and you.
00:46:15 SUJEET JOHN: Know find you find start-ups there in these kind of areas which could be we.
00:46:19 RAMESH KALANJE: We are you know, in fact Nasscom CoE is actually helping us find a few in in specific, specifically trying to understand securing use case specific scenarios, right. So and, and and they have kind of, you know, and the beauty of it is they're focused on one particular vertical. And since we cover the broad base of industries, it's useful for us to try and Co create approach. There are different stages. I mean there are different ways that we are exploring. I mean there are places where we are looking at acquisitions, there are places where we are looking at acqui hires. There are places where we are thinking of going join, go to market, right. So that's really, really helpful for us to look at it from a industry case perspective. But, you know, coming back to our own pieces, Sujeet, you know, one of the things and, and it's, it's a very, everybody thinks about all, all fancy things of AI, what you know, it can do and, and, and, you know, but, but what we have started seeing is it helps us to try and do the normal daily pieces. Like yesterday I was talking to somebody in, in the, in the aspect of AI invention and, and forward-looking and everybody and, and this person kind of brought it out really, really nicely. He's like, I don't want AI to kind of better enrich what I'm doing on art and, and other pieces. I want AI to take over my rudimentary tasks of getting, you know, washing my clothes, you know, try to take clean my dishes. I don't want to focus on this, I want to focus on art, on creation of life sciences and art and different aspects so that AI helps me on the rudimentary task, right. So one of the pieces that we are actually really working well is, is is with a startup. And this is, this particular startup is actually, it, it brings in a lot of valuable addition to our development tool set, right? So it, this product actually offers a bunch of features that would enhance our code reviews because we, that's a, that's a manual task, you have to kind of go ahead and look at all the different code. So this one is, is, is able to do that. It helps doing a lot of security scanning and, and, and all of that. So deploying this tool is actually going to save us about 30% of of our engineered folks time so that they can actually focus on the things that we are trying to solve for the test. OK. So this this is, this is a great use case. And as I said it's a the, the, the use cases around anomaly detection for industry based segmentation is going really well. We have we have finalized working with a few on on that venture as well.
00:49:20 SUJEET JOHN: OK, wonderful. Amitesh, tell us, I mean you said almost 200 startups, you work with one or two that have really impacted your operations globally?
00:49:31 AMITESH SINHA: Absolutely. One of them, one of them being into predictive maintenance. You know when we introduced that this start up into the our Vedanta ecosystem, everyone embraced it because you know, one of the challenges what we see in such a large group is the change management. But with this particular technology, people were very receptive and the technology worked very good. They were getting the results upfront. ROI was coming because if you have a single line manufacturing unit and if you're putting a predictive maintenance and if you're able to predict fault and take necessary action right on time, you are just not saving cost. You're actually increasing your production by reducing your unplanned downtime. That worked very well and that is something we have been scaling across with ANTA Group and I you know very recently we have placed large purchase orders and I have been told that once that gets deployed we would be Vedanta would be the most digitized metal mining company ever in the world with so many sensors looking after each and every equipments across business units.
00:50:45 SUJEET JOHN: Really. And this startup solution is the one that's going into all of these, is it? Yes.
00:50:49 AMITESH SINHA: And not only that Sujeet, what we are now envisaging with them because these sensors are doing acoustic vibration monitoring, temperature monitoring. Now the variation in all these parameters together with our certain variations in the raw material etcetera because the data being gathered is so humongous is so huge. Now this is something we have been Co developing with this startup is to see looking at that data and looking at other certain parameters whether it be current efficiency or certain changes and flux in the raw material and these sensing data are there. Can we come up with an operating leverage looking at the leading and lagging numbers and finding the right sweet spot where we can I have the maximum production load. So just imagine by just putting a predictive maintenance solution not only saved us hours, increase production, reduce cost, but now looking and working at with that data and with the startup, we are trying to build something which will be completely different from what we thought, you know, a predictive maintenance company can do. And it could become a product by itself which can be introduced at all the business units. This is something we are trying as a pilot in one of our steel plants. Once this gets successful, it's easily replicable in various business units, of course, with some tweaks. But you know, this is what we talk about creating the ecosystem Co creation. And the second one and the second one, Sujeet is it's a very simple technology and nobody thought that, you know, we could do this so quickly was permit to work basically digitizing our job cards. So in oil and gas industry it is very important and every industry percipit oil and gas is slightly special given it's complexity and and the safety measures. So we have completely digitized the whole permit to work in one of the small units and we were able to save more than 40,000 hours.
00:52:55 SUJEET JOHN: What is the permit to work?
00:52:56 AMITESH SINHA: Permit to work is basically you digitize your job cards. So if a technician has to do any maintenance activity, he or she would have to go through a paper trail. You know has to 1st initiate what needs to be done. A job order needs to be created and all that has to be done on paper. Then he or she has to do a lot of to and fro from the actual location of where the maintenance is required to the headquarter making sure that the paper trail sign off etcetera is done. Because first he will do a visit and assess what needs to be done. Go back to the headquarter, get an approval, the job card approval done, then go back again and do it. Now if with if it is digitized, it just one way he has to go get this done. And just on a digital trail he gets approval etcetera. And now with that digital trail, you're also trying to enhance your inventory because you have a complete digital trail of how much spares etcetera you're needing. So look when we come across solutions like this, you always we always keep thinking and together with start up of what extra can be done. So this is something which we have developed with you know the startup and the last one which we are trying to work as I mentioned about you know how we can explore faster and how we can do our underground mining faster. Because the economics for mining is very simple that you have to extract as soon as you can. The more you extract, the faster you extract, the more margins you get because your COP etcetera with certain fixed cost is limited. So the more you extract from Mother Nature a better enhance your profitability. Now how you do that is by using this SAR radar, our traditional system we were able to penetrate subsurface by up to say five to seven metres. But with this SAR drone technology, I can go up to 20 to 25 metres subsurface and assess the ore situation with image being created. And I can understand the continuity or discontinuity of the ore in the underground mining, which helps me reduce my drilling cost, which helps me extract the mineral faster, the metal faster, the ore faster. So these are the few things which we are being able to and all of the, you know, especially on this radar, this is in a POC stage. If you're able to do this, I've not heard anything being done of such thing in any underground mine, then we will evaluate of how what else application we can have. And our you know, there are several robots which are cleaning our acid tanks and several tanks which is out there. And you know which was done by manual labour, which was extensive, which was difficult, unsafe. Now it's fun done by robotics.
00:55:40 SUJEET JOHN: OK, OK, fascinating. Sanjeev, tell us. I mean, there seems to be lots of opportunities and startups often I would imagine they will struggle. OK, who should I contact? I have the solution. I could probably serve all of this. You said you might have tapped only about 60% of the startups that you could potentially. So what does a startup need to do to get to you and make themselves visible?
00:56:15 SANJEEV MALHOTRA: Part of the startup, what is the unique value they bring to the table? Our team tries to understand that first and the veracity of the claims also made by them, right? So that's the sort of a process.
00:56:25 SUJEET JOHN: How do you do they send an e-mail to you or what?
00:56:31 SANJEEV MALHOTRA: I mean, they can send an e-mail, they can talk to a person that we, our teams are spread in four different locations. We have centers in Bangalore, Gurgaon, Ahmedabad, Vizag. So, so they can connect any of the centers, call them up, send an e-mail, anything. It's a pretty straightforward thing.
00:56:51 SUJEET JOHN: Yeah, Sanjeev, you're not. Yeah, there's a problem with your mic. I don't know whether you can set it right without restarting, but I don't know whether we have OK let's.
00:57:10 SANJEEV MALHOTRA: Better I'll try to be short here. So so yeah I think it's a very easy process for them to to come in and be part of it and and and tell us some specific areas or use cases they are solving right. I think that is more important for us. So, and once we know the value adding, we can, we can connect them to the right, right industries. And and also, of course, there has to be need also of that kind. I mean, just some sometime, you know, we feel if we feel there can be a real value, we, we can, we can, we can pitch them to to the right, right industry. But you know sometime it is need based also we get a requirement from some side of the industry and then we can take them at that level. So, so both ways it goes so much demand generation and some of them we push from our side. So it goes both ways. But I think, yeah, everybody has to bring that unique value to the table.
00:58:10 SUJEET JOHN: You said you have some 1500 startups now in your portfolio. Is it?
00:58:13 SANJEEV MALHOTRA: That's right. We have 1500 startups and the number keeps increasing. Of course some of them drop out and then some of them get added up. But ballpark number is around that right plus minus hundred 200 here and there. But it we we and some of them actually have grown. They have become big companies that also.
00:58:31 SUJEET JOHN: Have to really.
00:58:32 SANJEEV MALHOTRA: Yeah, yeah. Then they don't need us also after a while, right? They, they and and and that's a good thing for us, right. I mean, it's all.
00:58:39 SUJEET JOHN: The things up to your mind, often any ones ones that have become very big.
00:58:46 SANJEEV MALHOTRA: No, I mean you will not see I mean it, it is not that you will see unicorns here, but but but but the companies like switch on, right. I mean they have now become 25 thirty, $50 million company, you know, and some of the cure dot AI that start when they were starting in 2016 working AstraZeneca. AstraZeneca has, they've taken them to different countries and they have, now they have their own connects and their own thing. I mean, obviously they, they, they are, they are, they're diversified. So, so, so things like there are, there are companies like that, you know, and AI now we are getting a lot of companies. So the growth path is there for startups and thanks to the people here, you know who are who are making this happen.
00:59:32 SUJEET JOHN: And you see acquisitions also happening and?
00:59:36 SANJEEV MALHOTRA: Yeah, yeah, yeah. Acquisitions also do happen. Investments happen. In fact, I get a lot of requests. In fact, they want to invest in a company while we are not working formally on that. I mean, but but lot of requests I get from across the world, they're looking to put, you know, looking at a company from 10 million to 50 million size and so on. So such requests have started coming and we're seeing how to handle such things. So we'll see acquisitions, investments of larger size. So I think it's important for company to reach that critical size of $10 million revenue. I think once they are there, I think then there is interest from a lot of companies around the world.
01:00:14 SUJEET JOHN: Okay, quick one. I mean, I know we are almost out of time, but quickly to Siva and so on. Since you've been there longer and started early and all that, the challenges that you face when dealing with start-ups or the challenges the start-ups face when they deal with you, what have you seen and to sustain these relationships over a long time, How difficult is that?
01:00:36 SIVA KUMAR: Yeah, that's a fantastic one. Just very briefly, right, I think the 4-5 challenges we have seen, I think the, the, the first one I would say is the business context and understanding of the business context in which the the technology of the start-ups innovation is going to be used. It's really important to understand that whole value chain and where are you playing that and how that's going to really benefit, you know, the, the stakeholders at the end of that value chain. So that we find sometimes it's challenging and that is our role right as companies, corporates to give them that context and to help them with that. But they, they, the start-ups have to attach importance to that, right? It's not just about a cool technology or algorithm, it's about how it's going to be used. So that's very important. And also the, the, the understanding of the speed, right? There's sometimes a lot of impatience to say, look, I have this great idea and it needs to be implemented in, in, in, in days and weeks. But it doesn't quite work that way in a corporate setting, right? You have to really, you know, sort of make sure that all of the, the entire thing is studied, the risks that are there, how it connects and how, how it, it'll actually, you know, sort of fit into the, into the value chain of the company. So the importance of having the patience and the wherewithal to work with the, the, the corporates to actually take the innovation to market is that I think another very important thing is the calibration of the speed. I would say regulatory requirements, paying attention to that, because the number of especially in the Pharmaceutical industry, a lot of us are ultimately, you know, regulated by folks like FDA or the European regulators. And it's, it's really important that when we introduce a device or a technology into a core process that needs to be validated. So the more the startups are thinking about that, the requirements for validation, building that in the more successful they will be. And finally, the fit with the architecture, right? The technology architecture, the company that that's already there and how this is going to fit with that. There are a lot of requirements that aren't security and and privacy and let's say the integration with the the remaining systems, the best practices in that API, use of APIs or micro services, all of these things that needs to be really sort of considered as well. So these are, I would say some of the things that we find ourselves investing time, you know, working through the startups to make sure that they can actually fit in, especially that technology enable startup side.
01:02:59 SUJEET JOHN: OK, great. One minute each to each of you, Amitesh, Ramesh, Sriram, can you your advice to startups, what should they do in order to get to you? In what shape should they be in what should they be? What kind of solution? Solutions of course, all of you mentioned, but as as an organization, what should they do to get to you? Cool.
01:03:20 RAMESH KALANJE: Yeah, go ahead. Go ahead, go ahead.
01:03:23 AMITESH SINHA: Sorry, so a quick one, Sujeet, I think one, one thing is working with corporates is not easy. You have to be come with a lot of patience, you know, because you're, you're changing a lot of things, bringing change management, you know, shaking up the status quo. So it's not easy. Your product, your solutions may be world class working at different levels, but you have to be very patient and try to see how you can actually get in the mix with the business if your solution gets mixed with the business KPIs and and what the business is looking at large as an outcome from a larger organization context. You know, working with start-ups for the corporates also becomes easier and for the start-ups also to see how I work with corporates, it becomes easier. And this is what we do, Sujeet, when we onboard start-ups, we make them few things very clear about, you know how things are going to be at Vedanta when you're working with Vedanta so that you don't expect much or expect more than you know what can be provided. Of course, we try to support them, but setting the expectations is very important. I think that is something where in startups trying to work with corporate should adopt.
01:04:37 SUJEET JOHN: Setting the expectations. Be patient.
01:04:40 RAMESH KALANJE: Yeah, Sujeet. So you know, the first thing that we always talk to the startups is trying to ensure they understand what is the problem that we are trying to solve, right and and make sure that there is a good amount of correlation around what they're trying to achieve and and also try and align that with the problem that we are trying to solve. There are instances where they are trying to solve at a very minute use case where that doesn't recommend, that doesn't have any relevance to what we do. And we are actually going and, and trying to mentor them and, and help them understand that this is not the right way to proceed and, and try and look at the larger picture. There is also a lot of startups that we have worked and, and quite a few actually been really responsive around what they're trying to solve for us from a use case perspective. And there have been changes based on external circumstances and environment and what we need and, and trying to be easier adaptive, right. And and that is something that we have started seeing a lot of start-ups that are coming now with working with us being enabled and being agile, being adaptable and trying to course correct as we ask for them to try and make sure that they they change a little course, tweak a few things and, and change all that. But the one thing that definitely, and I think Siva mentioned this in a different context, he's around IP, right? And that's something that Nasscom, the MeitY's Nasscom has actually been helping. But I think that definitely needs a lot of focus in India because IP he's there is a good amount of, you know, comment and, and regulatory authorities trying to make sure that IP is, is taken care of. But there's still a lot of, especially folks, you know, US based companies and, and worldwide companies, like all the people that we have in the, in the call actually have a lot of, you know, very uncomfortable feeling in trying to understand IP and working with the startups in India. Because that's, that's something that we need to try and push forward and, and make sure that, that, that ability of, of translating IP into being very prevalent and and very focused approach needs to come out pretty much in the open subject.
01:07:07 SUJEET JOHN: Yeah, focus on IP. Yeah, Sriram, quickly.
01:07:10 SRIRAM S: Yeah. I mean, I think for for Mitsubishi Electric, you know, we are on the solution side of the entire ecosystem and we offer solution to a very heterogeneous environment. And so from that standpoint we've been trying to address various, you know problems statements across different industries. So it's it's very easy to get connected to Mitsubishi Electric because, you know, we try to work on multiple areas of engagement. So any start-ups listening to this program, more than welcome to talk to them on various subjects because there are multiple diverse areas that we work on, particularly all those areas which can add value to the societal needs. You know, that's where we try to put ourselves into. Now, of course there will be challenges, you know, like you know, Amitesh mentioned challenge of working with the large corporate house. We have got our own inertia around which we work. Things probably don't move as fast as an agile startup company would probably want it to work about actually. But having said that, you know, there is always this fine balance between an opportunity to commercialize, an opportunity to experiment the. So when there is an opportunity to commercialize, there's always an an kind of a push that comes around with it and we can accelerate those things faster. And that's what has happened with us with the various startups that we have been working on. We have been working with various, many, many startups. But where the opportunity to commercialize has come up, things are moved much faster. And the opportunities where the experimentation is going on, it will still take some time because we need to find reasons for us to commercialize it in the future. So, so I think it's a good platform to be in and I would welcome any of the start-ups would like to probably work with us. And more importantly, you know, the other other aspect is we work on a very kind of a heterogeneous environment where data acquisition becomes an integral part of our entire activity. Now we are Mitsubishi Electric and likewise there will be, you know, peer group companies. You know, we're also in the space of automation. So any manufacturing environment is as complex as it can possibly be. You know, it doesn't come with one unified system. There will be Mitsubishi, there will be so many XYZ suppliers also. So the complexity of acquiring those data and then making meaningful sense out of it is where the challenge comes in. So all those startups who have ability to work on different platforms, different solutions and can complement with the kind of offering that we had today for the industry are more than welcome to work with us and we are looking forward to that.
01:09:37 SUJEET JOHN: So there's the message for startups. As Sanjeev early on said, we have a great startup ecosystem, very digitally advanced, recognized around the world. But sometimes as is concerned that not enough absorption of some of those technologies within the country. But now you see in this panel itself lots of big companies, especially the GCCS and all who are taking the lead in absorbing and willing to work and wanting to work with Indian startups. So huge opportunities there, diverse set of areas where you can startups can contribute to. But as Amitesh and all said, I mean, you have to be patient. There are challenges in being able to work, which is what Sanjeev and the mighty MeitY Nasscom CEO is trying to change. I mean, they are a body that can bring the two together. So if you want to be part of this ecosystem or to sell to Indian corporates to GCCS, register with Sanjeev's body. I think that's the one that can help you probably a little more easily to get to the right corporates and the GCC's that you could work with. Thank you all for, I mean Saturday morning, I know we can and all of you were willing to spend more than an hour with us. Thank you so much. Sanjeev Siva, Amitesh, Ramesh, Sriram, really nice having you on this platform. Hope to see you again. Thanks a lot. Thanks a lot.
01:11:06 RAMESH KALANJE: Thanks for having me, I appreciate.
01:11:11 SIVA KUMAR: Thank you very much.
