 A very warm welcome to all our viewers here today at the Capital Insider Series by Entrepreneur India. Today we are speaking on the rising role of data in venture fund investments. And we're very happy to be joined by Mr. Shailesh Ramakrishna from Rocket Ship VC, an early stage venture capital firm, while using data science to democratize venture capital and have more recently announced and it has that raised 100 million US dollar for its fund number round two. They're based in Los Altos, California and Rocket Ship had its first fund of 40 million dollars and this is the second fund that they have done and in that 40 million dollar first one. The firm had invested in 44 portfolio companies across CDACB rounds with 46% investments made outside the US. So thank you Shailesh very much for joining us here today as we talk about the kind of work that you'll be doing. I understand that there is some very interesting work that is happening at Rocket Ship VC where you're using data mining in order to sort of pinpoint to the companies and to the sectors which are tomorrow's most promising sectors and the future of, you know, sort of say tech in the coming times. So, you know, would love to hear from you of course you have got such a fantastic, you know, work model yourself I mean, look at him I mean he's an IT madras so back here from India when he did it and then of course he went on to do his masters and doctorate also in artificial intelligence. And then he's worked in various firms he's been an entrepreneur for a while before he sort of let go of his startup and has been working at Walmart labs and now of course he's the partner at Rocket Ship VC he is actually investing in other startups so thank you for joining us today. I would love to know about you know this wonderful model that you have at Rocket Ship VC which is really to sort of understand and use data in order to find out which could be the most promising startups and also understand that you actually pick up your startups more over Zoom meetings than you actually meet founders in person. So please tell us more about it. Absolutely. Thank you so much for having me this morning. And thank you for your kind words of introduction as well. So the reason we came up with this idea for Rocket Ship was a combination of two significant aspects. One is our own careers, my fellow partners Anand Venky and myself we are all data scientists. We've been practicing AI and machine learning for the last 20 years in our careers. We're also entrepreneurs as you mentioned we have either founded or build startups for most of our careers. We have a very strong interest in investing. My other two partners have been tremendously successful investors as well. So that aspect of our personality all combined was something we wanted to work on next. The next venture had to include a little bit of that machine learning and data science, a little bit of entrepreneurship and founders as well as investing. And the other aspect, which is also something you alluded to is we had in most of our careers as our founders had had the opportunity to raise financing from a wide variety of amazing investors. But a lot of that had to do with who we had met, who we had network with, who we had connections with, and we would go pitch them and hence those financing dons would happen. But we were always wondering how this model can be disrupted. And we felt that one of the great democratizers, one of the great levelers was the ability to find companies through data. So just those two themes coming together that led us to sort of creating what eventually became rocket ship. And of course, as with any interesting venture, this was not something we knew was going to work from the get go. And in some sense, we were just as much a startup at that time as any other startup, which is we asked ourselves, is this going to work? Are we going to be able to find a good company? Are we going to be able to connect with them without meeting them in person? Will we be able to convince both them and ourselves to write that check and make that investment? And much to our own pleasant surprise as well as the sort of the satisfaction of seeing something initially work, our algorithms worked amazingly well. And what we had going for us significantly was that entrepreneurship had become significantly global. It was no longer restricted to develop markets. It could be as easy for somebody in some small town in India to be building a world-class company as it could be for somebody here in San Francisco. So that enabled us to find some amazing companies all over the world. And we were after the races in becoming a global investor. And once you realize that entrepreneurship has gone global and that the old model of who you know and those networks are disrupted, the only way to reach out to this amazing, amazing number of startups is through data because there are thousands and thousands of these startups. And hence, data plays a significant role in our process. Sure. No, that's wonderful. And you know what is more important is that you just not looking in the Silicon Valley where you based yourselves, but you're really looking outside in developing and even less developed countries to find out startups. So just for the sake of our audience, if you can tell us what are the parameters on which you sort of mind these companies and you know what what areas do you look for in such companies when you are data mining and trying to figure out that these companies would work? It's a great question. And while I will tell you my answer to the best of my ability, you're also asking me for our secret sauce. So some of that a little bit held back. But I'm more than happy to share our experiences in this learning process. And it has been a learning process for us as well. So we started off by trying to see what information is available about startups these days. And once again, we were lucky in our timing because if you were asking this question maybe 20 years ago, there was not going to be much information available. Startups at that time were thought of as being stealthy and in the sense that they were quietly building this idea and we're going to launch it in some, you know, sort of big bang and then that's when you find out. Whereas in these last five to 10 years, startups being online has become tremendously important to them for their own execution, mainly because they have to reach out to their customers. And they also have to attract great talent. So if you start looking at it from that perspective, many, many startups are actively sort of have significant online presences, if you will. And given that aspect of a lot of them being online, they leave a lot of information behind, whether you think about it as just this sheer existence of the startup, where it's located, what business it's in, to things like social media, marketing, advertising, to team information in places like LinkedIn or GitHub, there's a lot of information about the startup itself. And then of course there's job boards where the startups are advertising for hiring for jobs, as well as doing, you know, media events and have publications in forums such as yours. So if you consider all of that data together, while it doesn't tell us whether a startup is going to become a very successful company or a unicorn. There is enough information where machine learning algorithm can glean the sort of the secret ingredients to when a startup is likely to be successful. And one other nugget I'll share with you is it's almost impractical to ask the question of a startup that is maybe one to two years old, are you going to become a billion dollar outcome. While some of the more prescient investors are able to make that judgment, a machine learning algorithm is not able to, for the simple reason, you're asking it to predict something that is in a five, seven, 10 years in the future from perhaps only one years worth of data. And so it's an impractical way of asking that question. So one of the innovations we did was to ask the right kinds of questions from the machine learning algorithm in order to figure out what kinds of startups are potentially likely to be successful. And I do also use the word algorithm, but it's actually not just one algorithm. As most people in machine learning will tell you we have several models running concurrently trying to assess different aspects of a startup. Having said all that, I will also answer your question directly as saying many of these algorithms are built by us, and hence we as humans provide the same sort of analysis that typical investor will do. So we look at what the company is doing, which business is it in, which country is it based, what is its market, who are the people, what are the teams involved, all of those things are also incorporated because we are the ones building these algorithms we think those factors are important. Surely. And understandably, Rocket ship we see is focusing on deep tech startups so you know what I mean and I've seen the portfolio and I see there's a lot of intake in the portfolio there is also a lot of emphasis you're putting on tech now understandably given the pandemic. So post the pandemic what what sectors are you sort of betting high on you know you think they were promising and therefore likely to go there. Sure. Just one clarification and I think you observed this correctly. We do invest in pretty much all applicable sectors in terms of startup investing, not just deep tech alone. It's just that our portfolio somewhat naturally represents areas of startups or sectors where there's more data. And then and fintech as you mentioned is one of those clear examples. There's usually a lot of data about fintechs available. Most fintechs are out in the market. There's a lot of marketing going on people talk about various fintech services. There's social media. There's a lot of rapid growth potential. So there's a lot of information available for fintech that naturally leads them to be better evaluated by our algorithms. Another similar example is also e-commerce. The e-commerce also lends itself more naturally to this approach. So if you look at the two most significant sectors in our portfolio it's e-commerce and fintech. But we also have a wide representation of startups all the way from things like food delivery to a hardware company that's producing a wireless chip. Now to answer your next question which is what are we so excited by in the coming future. One of the most interesting things for me personally is to watch our data show us these trends as they are about to happen or are happening. And so we have almost like a ringside view of what's about to happen and fintech plays a significant role in these trends. And India in particular also plays a significant role in these trends. India is I think rapidly growing up in terms of its maturity in terms of both as a market as well as the quality and level of services that are expected both by consumers but also interestingly by businesses. Businesses are no longer satisfied to be working on archaic software platforms. They are also looking for cutting edge solutions, things that work on tablets or phones and the whole consumer business interface is significantly being upgraded in India. In fintech in particular, one of the most important aspects of a growing economy is access to capital and hence we are seeing that aspect becoming a significant part. Access to capital in the consumer side looks like it's lending, lending from a wide variety of methodologies. Some as general purpose lending short term loans, long term loans, term loans, but also something more narrowly focused that is specific to a use case like loans for educational purposes, travel abroad to get a new degree or medical expenses or a short term, you know, sort of cash flow bridge until you get your next paycheck. So there are many ways in which this particular access to capital is transforming the sort of the uneven capital needs that people have in a fast growing economy. The same aspect is also happening on the business side. Business capital was typically underserved. It was a lot of, there was a lot more sort of, I would say, inefficiency in businesses getting access to capital and that is significantly changing. Of course, that also has come about because there's also better information available. Before part of the inefficiency was a lender like a bank would have to analyze a lot of information in order to understand the creditworthiness of a business. These days, a lot of that is computerized, you're able to look at the information that the business is able to provide and get a much better sense of their creditworthiness and hence access to capital is much more available. But even there we are seeing a significant innovation. We are seeing innovation where you're looking at specific aspects of a business. There's working capital loans. There's specific loans for backed by things like account receivable account payables, supply chain financings, transportation financing, things that are so much more specific, but are incredibly important in allowing a business to really scale up rapidly, given that India is growing significantly. So so FinTech is something we are very excited by lending and access to capital is the first layer we are seeing a lot of activity on for the next level down is banking itself is undergoing a rapid change as well. And this has been further accelerated by by the pandemic. If you cannot go to a bank branch if you cannot go to an ATM, how are we supposed to make these financial transactions happen. The answer is these these banks that are called neo banks or mobile only banks or mobile first banks. So it leads to a very different consumer interface, very different capabilities that you can incorporate into and provide the in the hands of consumers, and that is I think changing businesses, as well as consumers behavior significantly. The third and you know this is an area that is now seeing a second level of resurgence. There were many solutions for this initially but now there are even more fun, you know, sort of amazing solutions and India is I think in the forefront of this is payments payments across all the spectrum from small payments that you're using to, you know, something like ATM through to now UPI based payments through payments directly from your bank accounts to payments directly from off of your paycheck money transfers are much much more sort of easy and fast. So the whole payments infrastructure in India is being upgraded to a point where I would say in some instances it's actually much better than the developer. And this is a sort of a meta trend. If you work is that when infrastructure is lacking initially, it offers the country to leapfrog, not be tied up with old archaic systems but leapfrog to the next generation. And I think India is accomplishing that significantly. So I mean, can you give us some insights into the investments that you've made in India and Southeast Asia I understand you know there are, there are startups like Kata book and find where you put some significant amount of us and I mean later round capital. So what, what is it that you sort of what prompted you to them. And now what kind of returns in these startups are you beginning to growth you're beginning to see versus a similar startup and let's say in any other country in a developed market or Silicon Valley or maybe even Hong Kong or some other places. Absolutely. And as I said, I don't know if I mentioned this previously outside of the US India is the next largest country in which we have investments. And, and this is not because we are of Indian origin as you observe this is more because, as I said, India is is a very exciting capital destination at this point because amazing companies are being built amazing opportunities are available. And, and these opportunities are large, not just because of the, the, the, the sort of the lack of the infrastructure, but also because India represents a very, very large market. And so I think that's super exciting. In terms of examples are investments in India span B2C things like, you know, find, as you mentioned, to be to be companies like mogulix, we're an investor in mogulix, we're also investors and no broker in the B2C space but it's in the industry as well as it has a significant sort of software component of you will. We are also recently investors in Patabook, as you as you observe there that's a that's a, that's a, that startles the line between B2B and B2C and that it's for, you know, small Kirana stores but there are hundreds of thousands millions of them in India. And so that's been very exciting. We are also recent investors in Yulu. Yulu is the is the battery powered mobility service. And again, the metrics there were very interesting for us to see. And we have become strong believers in the fact that I think electric mobility is going to be the most cost effective and efficient way of transportation, especially in a congested travel congested country like India and the more recent investments that we have made have been companies that are getting significant COVID. Of course, there are companies in education as well as in in sort of skills management. So we have investments, most most recent investment is in a company called Upna. Upna has created a platform for sort of blue collar workers, but workers were who are a large enough number, but the hiring of them has never had a formal process. White collar workers perhaps have LinkedIn and the wide variety of job boards, you know, monster.com and so on. But for if you wanted to hire a local plumber or an electrician or a carpenter, there was never a process, there was never an easy way. And then, and I'm not talking about just, you know, for a home user one hiring a carpenter, there are, you know, there are building companies that need to hire a carpenter for a career and even that was hard to. And so this company has built an amazing platform that not only brings these people together, provides them a community, gives them a sense of identity in this new online world, and that's been amazing as well. So we are our investments span this gamut. We have investments like I said in education in in skill tree sharing in fintech, as well as in commerce. So most of the investments I also see are towards you know digital transformation of a sector, you know whether it is digitization of Kiranas or electric mobility which is of course going to change the, you know, your internal combustion engine of vehicles. So, I mean, given all this from an Indian perspective, what is the larger, you know, digital offshoot that you see coming to happen and do you feel that because of that and significant size that India has today to do that and I mean it's it's just started you know, there are millions of family businesses out here in India which would need digital transformations happening for them. So, where do you see India as an opportunity market. And I mean not just for your fun but at large in the coming years large mean maybe the next five years. You know, we are very excited for India. Like I said, while we are personally of Indian origin and we are always excited to be investing in India for from that perspective. What makes it even more exciting is that our algorithms and our data find amazing opportunities in India as well. And one way to sort of think about this is our algorithms are not just finding companies in isolation. What's actually happening in effect is a global competition where our algorithms are ranking companies all over the world in all of these ecosystems. I think that Indian companies are on rankings at such high numbers at high ranks that leads us to be drawn to making investments in there tells you the opportunity that is available in India surpasses any other opportunity elsewhere in the world. Right. And that's what's exciting about India as well. So, what's your question about how we see India in the next five years. I think the potential is enormous. And the digital transformation, I think has a ways to go. And I think the fundamental building blocks are being built across a wide number of sectors. This sort of started in the last five to 10 years, had a significant acceleration happen thanks to the geo rollout. I mean, adding a few hundred million mobile subscribers in a span of a few months rapidly change the ecosystem. But that transformation has been ongoing. And more and more of this this demand for this this ease of use removal of red tape making sure efficiencies are built in is permeating every sector. Recently, I think several investors have made a note of this but we saw this, you know, quite early on, even even sort of old state sectors like AgriTech were seeing a resurgence because, you know, farmers are always thought off as folks who are not that technologically savvy, but that has actually changed significantly. Most farmers want to know the exact moisture levels in their soil, how much fertilizer to add, because all of this makes a significant impact to them on their bottom line, whether they make a profit, or they take a loss depends on the biggest cost inputs which are water fertilizer, apart from seed stock. So what I'm seeing is, is every sector I don't I believe there is no sector that will be untouched through this transformation, and the core at the core of this transformation is ubiquitous connectivity ubiquitous computing, which is through the mobile phone but also beyond the mobile phone to other computing devices and ubiquitous financial transaction capabilities, which again, through UPI and a wide variety of other services, we are making available within the country. So these three aspects I think are at the core of this transformation, and we are seeing multiple versions of this happen. So if you think of commerce now commerce is already evolved to the next generation, where, you know, used to be in couple of days and then it became same day that you get deliveries in a few hours. Right. If you take a step back and think about what that entails, it entails an enormous sort of improvement in efficiency and infrastructure from how fast an order gets transmitted to how quickly a payment is collected to how quickly the product is delivered. All of those things start need to start working in sort of synergy for this transformation to happen. And once that starts happening in one sector, we see the trickle down happened very, very rapidly, because of one sector has proven how this can work, then all the other sectors start looking at it and saying why is this not happening for me. It was even a recent article about things like, well, you know, if you can deliver, you know, a thing that I ordered a toy that I ordered in few hours, that same thing can be used to deliver fresh food in two hours, right, a meal in two hours, and so on. So that just starts sort of enabling capabilities that change the common person's perception of what is an expected level of service. And I'm, again, very happy to say India is quite in the lead in some of these things. It is still a challenge here in the US to get those kinds of things to work here due to high cost due to infrastructure not being a little bit more legacy. And perhaps get things here in a few hours, but the costs are much, much higher than in India. So our expectations here are different. I think this is a clearest case of India being able to leapfrog, because the existing legacy did not exist for them to have to work on. Sure. Yeah, that's an interesting point. But coming back to your algorithm, you know, so I talked to a lot of VCs and I talked a lot of funds and you know one thing they always sort of hint upon is that how important is the founder to the whole sort of mission of building a startup where in you know his qualities and his, you know, his passion matters. So how do you how does it go to some measure that I mean, you know, how do you sort of deep dive into the founder's mind and figure out, you know, where is he going to or she's going to leave the startup to exactly. So, so, and the only reason I wanted to mention her was his is that this is the other aspect we are seeing our algorithms are seeing many companies founded by women as well in India and I'm very excited to see that happening within India. To further elaborate how this works. There is one level or one class of models within our algorithms that evaluate the quality of the team. But that by no means is the only way in which we we evaluate quality. And this is the reason why it's not just algorithmic algorithmic process identifies these companies. The role of human partners such as myself and my fellow partners is just as important in evaluating the company. And so the aspects that you are talking about the hunger in the founders eyes the way they approach the problems the way they break through barriers and challenges that are faced, they're facing those are things that we assess in multiple conversations with the company. So in one sense, we do a lot of the traditional VC work as well where we talked to the company multiple times we talked to multiple team members, we talked to potential customers. We do a whole lot more of the traditional VC work, but we also have a lot of confidence in the work we're doing is because the algorithms found the company in the first place. So we do that from a sense of there is a there is a core within this company that we are really evaluating. What what this does for us is to really understand both the fact that there is an engine inside the company at work, and that this team is capable of really revving that engine up to take this company to the next level. And oftentimes, and most investors will tell you this as well oftentimes not all the information is available, not all the questions are answered, not all the risks are addressed. And what you really have left with this, that conviction that this team will figure this out. And so that is something we also do. So, so to answer your question, perhaps much shorter than I should have elaborated is, this is not 100% algorithmic approach human is play an equal and important aspect so it's a hybrid approach, where the things that the algorithms are capable of assessing they do the things that are humans are better at assessing we do and combine hopefully the result is much better than either one of us. Sure. So we've got some questions coming so there is Eric on Facebook who's asked us that can you give us some insights on specs. How will it benefit the startup ecosystem. Spacks I guess are the flavor of the season, and I'm happy to answer my opinion about them. So, so this is always been a question with respect to startups is eventually when you need to go to the sort of the public level, how do you reach that process. And as startups grow and mature. Things get a whole lot more daunting as they get closer and closer to this milestone for, you know, multiple reasons. One of the biggest reasons is the is not just the increased level of scrutiny, but the increased level of processes and paperwork that is needed in order to go public. You need to do a lot of preparation you need to have a lot of systems built compliance mechanisms built, because those are required both by regulation and by scrutiny that will come from analysts and all the other folks who will first for the first time get to see your books. So, as, as time has gone on that challenge has gotten only significantly harder, especially due to the financial crisis here in the US, which cost further regulations, the Sabi Noxley regulations, as well as other myriad regulations, requiring the hoops that companies have to jump through becoming significant. The SPACs sort of sidestep a lot of that, but not for too long, because what it only does is it reduces the friction in getting to becoming public. But once you're public, all those regulations still land up on you so you may not have the time. You may not need to build them up in the first place but once you have gone public you are subject to the same regulations. So you have to do them anyway. In one sense I believe SPACs are, you know, not so much a long term solution as a short term convenience, if you will. And in the in the grand scheme of things, what you're really banking on is the SPAC creators choice in terms of which companies they merge with versus not, rather than any sort of systemic inefficiency that the SPACs remove. We've got another question from Panita who's saying that how has the early stage venture investing reshaped in the current times I mean this could be by of course fund size by expectation of the investor by. And I mean, you know, so just to sort of add to that question is that do you, does the fund foresee that you know, can be instead of giving a founder one round of fun give him two rounds of fun. So that you know he's more focused or she's more focused on the business itself rather than just thinking that you know okay now I need to go out and raise the next round. So, do you think that approach is now changing from a funds perspective. I think, I think something a little bit more significant is happening. I believe that the dynamic of investors being sort of these these people up on the mound offering largest or riches to supplicants who are startups is completely outdated that is no longer available to any more startups are able to build amazing companies with very little capital thanks to technology, and that has even the equation quite a bit. There are several companies for which investors have to compete with each other to be to have the privilege, if you will, of investing in these companies. I think the narrative has changed significantly. I think startups need to not just think about investors as sources of capital, but as partners who must and should help in making them successful. The majority of the owners is on the founders and the team of the startup, but everybody within the startups orbit needs to be aligned with supporting the startup, and that includes the investors and that goes beyond the money involved. And I think for those kinds of companies for those kinds of startups with those kinds of investors. I think financing is most likely not going to be that much of an issue because you have not just a small team you have a whole ecosystem supporting this company in its attempt to become successful. So, I think one of the final points before we need to close this is that you know you have 46 companies in your portfolio and they are spread across the world. So, do you in some way also promote inter learning amongst them, you know you sort of you obviously you seeing it from the nucleus point where in you know this startup can help the other startup or so on so do you sort of bring them closer together in order for them to grow and learn from each other. Absolutely we do. And this is one of the most interesting aspects of my job personally is having this kind of interaction with our startup founders. As you might imagine, we, you know, we spend a lot of time talking to them, learning about what they're experiencing and patterns very rapidly start to establish themselves and so more often than not we make significant interconnects between our founders. Not just from a, hey, you know, you guys are all part of our of the rocket ship portfolio so you should know each other, but tactical introduction saying, Hey, this person actually experienced this problem and had this solution. You might learn from this, or they are approaching this problem in their country through this way, you might want to look at that. So we have connected companies in Brazil to companies in India we have connected companies in India to companies in US. And those cross connections are happening. Because I think, and again, I, if I haven't said this, I should say it again and again, the quality of the founders is just amazing. These are amazing people who have taken the risk and have the vision to build an enormously successful and what they need is is sort of the right guidance at the right time to get tactically over some of these hurdles. But once you present the ingredients they're able to really blow through and and and build amazing companies. So, so we find that this ecosystem really helps them a lot. And we don't do this just within our own portfolio we also do this with every entrepreneur we meet, because every entrepreneur is going through a similar story to us ourselves. When we were entrepreneurs. So we are more than happy to share in our experience make these connections with very little if no expectation of any benefit to us personally other than to say, Hey, I've known what you've gone through as a founder myself. And so I'm more than happy to find a way to help you. Thank you very much, Shailesh for actually joining us today and talking to us about it of course our participants as the gradually they goes along, please keep your questions coming. I would request Shailesh you know as more questions add up on our Facebook live talk if you can sort of take some time to answer them and you know help the other founders and other startups who join us here today to be able to gain from your Thank you very much for joining us and we hope to meet you next time off the screen and in person, hopefully here in India as we continue to grow the startup ecosystem and you continue to invest in such startups. Thank you again. Thank you so much for giving me this opportunity. Thank you to your audience as well for taking the time to listen to what few words I had to say. And my parting thought to you is, you know, don't hesitate, go start a company. It doesn't matter what age you are what color of skin you are which country you are in. I think starting a company is one of the most transformative experiences that one can have in their life. And so I urge everybody to take that leap when they when they deem that time is right. Sure. Thank you once again Shailesh. Thank you. Bye. Bye.