The Exchanges

Q And what is your criteria of evaluating companies when you meet, let's say, AI specialists, uh, NLP experts who are building solutions?

A Sure. I think our criteria is no different than, uh, let's say we, if we were not an AI fund for most part. So we, we still look at, you know, what's the market size, what's the problem you are solving, how good the team is, et cetera. Um, uh, so in that way, our criteria is very similar, but we do look at additional criteria. And that is, uh, what is AI adding to the whole problem solution statement that you are trying to address? And how deeply does it address it? Uh, you know, and, um, um, um, if I take out AI, what will the impact on that? Right? Etc. So that AI impact and value creation aspect is something that we look at additionally apart from the normal things that you would look as a venture capital.

AI assessment note: “what is AI adding to the whole problem solution statement that you are trying to address”

Q And what are the markets that didn't work out for you?

A I think, uh, uh, I, I don't know. I think there is no such market which has not worked out for us. Uh, yet. I think it's too early to say that because some of these companies may take six to eight years to, um, uh, I don't know whether markets fail or sometimes a solution in the market fails, right? So some companies will fail in our portfolio. There's no doubt about that. And, uh, a bit too early to sort of, I think we're just three years into the fund. Some of our investments are like six months old. So I think, uh, I would prefer to answer that question maybe after five years where we have enough runway or for that, Teams to have been able to go through that journey and then reflect back of what worked or what didn't work.

AI assessment note: “there is no such market which has not worked out for us. Uh, yet.”

Q And your approach, is it bottoms up or top down where you develop thesis on certain sectors and then you go out looking for entrepreneurs?

A Yeah. I think, uh, primarily it has been in the initial part of the fund. It has been, uh, we had a top thesis, like let's look for AI and, uh, then we developed a bit more. What does it mean for us, right? What does AI mean? What does, uh, business leveraging AI mean? So we did that sort of work, but we did not Do and say that we are going to look for AI in this sector, that sector, this sector, right? That part we didn't do. That part we grew bottom up. Uh, so we met entrepreneurs because we also wanted to see what's happening on the ground. And, uh, then slowly over a period of time. So for example, healthcare does form a very large part of our portfolio, but it is not a top down design. It just happens that the problem statements that the health entrepreneurs were solving sounded exciting and therefore health became a large part of the portfolio. So after that top work of the overall thesis, I think it has been primarily bottom up so far.

AI assessment note: “after that top work of the overall thesis, I think it has been primarily bottom up”

Q And coming to a more personal side of yours, what's your daily routine like?

A Oh, all right. So, yeah, uh, actually, uh, I'm a little bit of a routine person, so that, that is a fair question to ask. Uh, typically get up in the morning, five AM, six AM, depending upon how it goes. I'm an early sleeper, so I'm, I'm in the bed by nine 30 or so, but I get up early. Uh, typically like to do a little bit of yoga in the morning and meditation. That has been super helpful for me. Last few months I started doing yoga. Um, very good, uh, I think for the mind and body. Finding it very, would love to say that everybody should do yoga in some way. And typically in the office by nine plus minus, uh, then the day takes over in some sense, a bunch of meetings, things to do, uh, like to get home by six PM if possible, chill out a bit. And then typically there are some calls and emails to follow up. So it becomes a busy day and then just hit the bed. So nothing unusual.

AI assessment note: “typically get up in the morning, five AM, six AM... in the bed by nine 30”

Q And when you focused, you know, that, uh, I'm going to start an AI fund, you must have gone through a huge learning curve, reading books, meeting people. Uh, can you, can you take us through some of, you know, for the listeners who are interested, some of the books which you believe, which held you at that point in time?

A I have not read a single book on AI. So sorry, don't have a recommendation. So my way of learning is slightly different. I wish I could read books, but I'm not good at reading books. So the way, one is I've built quite a bit of technology, so understanding technology somewhat comes a bit naturally to me. Reading web articles, yes, and that there has been a whole bunch of them which I read. Talking to entrepreneurs has really helped me, actually. So when an entrepreneur is pitching, I think in the background itself, my mind is working in terms of how I would build that product, or what are the different things, and that gets me to engage with the entrepreneur at a different level on the technology side, which helps me clarify my own doubts, and that builds a curve which actually becomes a good loop. So if, if I'm meeting 10 entrepreneurs in a week, each one of them has incremented my knowledge By a delta and over a period of time it has built, right? So my method of learning has been more of that rather than reading books.

AI assessment note: “I have not read a single book on AI. So sorry, don't have”

Q And what's the reason why these two companies accelerated? Extremely fast. Was it the market factors, more market adoption for the solution?

A Sure. I think it's a variety of things, right? Sometimes it's about timing, sometimes about teams, sometimes about, you know, getting the right product market fit, et cetera. So I think in Locus's case, um, and, uh, Locus, and I would also say that these two companies are probably the oldest companies in the portfolio as well. So sometimes it just takes time as well, right? So it'll be, uh, not fair to say that the other companies are not going to get there or whatever. It could be just a question of time. But for these two companies, I think couple of factors came together. One is for Locust, for example, they were primarily in the domestic market, um, couple of years back, and then they started flowing into international market, uh, which, uh, which was a very strong uptake there. And, uh, uh, full, full points to the entrepreneur, Nishith, He has built a very, very strong team. I think that is super critical. Entrepreneurs who are able to build the next level of team, which is strong enough, or very strong, are able to handle the challenges of scale much better than others. I would say the same factor has gone for Siktipl as well. Uh, they, they, they primarily were working on technology. Then they realized that there's a bigger opportunity in having their own pathology labs, which goes in the name of humane health now. And they built a team for it and they did it within six…

AI assessment note: “One is for Locust, for example, they were primarily in the domestic market”

Q And because these solutions are, uh, I would say, you know, sometimes before the market need is there. How do you go on convincing the next stage investors, series A, series B investors, so this startup really can make it big?

A Yeah, I think some of our companies have gone to raise more money after our investment. Frankly, we did not have to go and convince, right? I mean, if, so thesis is that if you are doing AI in a meaningful way, and you are near about product market fit, right, then you will be much better than the competition around you. And if you are able to demonstrate that, I think the, it is, it becomes evident, um, to the investors downstream. So, so far we did not have to do very aggressive, uh, positioning over companies. I think by just natural traction and built up that they have had, it has been okay for the investors to build confidence in them.

AI assessment note: “Frankly, we did not have to go and convince, right?”

Q And how has your experience been of fundraising for your fund? How, what are the challenges faced by doing it?

A I think I can, I can say two things, right? It has been the, probably the most challenging thing I have done in my career so far. I mean, building Slingbox was easier than fundraising for five inches. Um, and, um, and in some way it has also changed me as a person in an irreversible fashion, right? You go through, uh, some ups and downs. So it took us two and a half years. It was, it was, uh, it was quite difficult. Um, we did not have an anchor investor, so we had to convince a lot of people. I met a mess. Must have met around thousand people, I think, and, um, to, to, to, you know, knock on the doors, make a pitch, and it lasted over two and a half years, and then we were able to raise, but it was super difficult, yeah.

AI assessment note: “we did not have an anchor investor, so we had to convince a lot of people.”

Q And you have been, you know, an entrepreneur, you know, building R and D for companies have started next venture and PI venture. What have been your key learnings, you know, which you share with entrepreneurs? Let's say there's three key learnings while building.

A Yeah, sure. I think we're still learning, um, I guess, but few things that do stand out, um, in, in building these companies is, uh, number one, um, don't do it because others are doing it. Uh, you should do a startup or a venture when you feel so strongly about it that you can't sleep properly. Um, and, uh, to devise a test, I have a hundred day test for it. So if you have an idea that I want to do this, right, as a startup, sit on it for a hundred days. Let it sort of simmer in your head. And if you feel so passionately about it, even after a hundred days, there is something in it, then go and follow it. So, uh, I think the first thing is, it has to come from the heart. It has to come from an insight. It has to come from A much deeper, um, uh, um, belief than just because somebody is doing an entrepreneurship, a startup, I should do it, or somebody is doing a fund, I should do. Pi Ventures is also a startup, by the way, right? So, although it's a fund, but then the journey of Pi Ventures is also like a startup.

AI assessment note: “number one, um, don't do it because others are doing it.”

Q And throughout your career, what habits would you attribute to your success?

A I think I'm still a work in progress, uh, in the, uh, venture space. I think a few things that, uh, sort of always have helped me is, um, um, I tend to believe I work hard in everything that I do. So, uh, that comes with discipline as well. So that part has always been there. And, um, um, uh, the other part where I've done, um, um, I, I would, uh, uh, Say that hopefully I can do even better, but building good teams, I think that has really helped me because, you know, it has really helped me to work with people whom I can learn from, etc. So that has kept my learning curve going, and the learning itself, right? So you, you do new things, you learn from them, and then you sort of become a better version of yourself every single day. So, uh, maybe those things helped.

AI assessment note: “I tend to believe I work hard in everything that I do.”

Q And how have you helped them beyond Capital?

A Yeah. I think this is a question best answered by the founders we have supported. Um, and that's the question we were coming back to last time, right? That, you know, how can we help? So I think, uh, it has been different for different companies. In some companies we have not helped much because they did not need any help. Uh, in some companies, uh, uh, you know, the, the, the way I think our philosophy of work is emerging is Um, in early stage companies, typically, they are lacking on something. Um, and something comes naturally to them. Just because of our filtering criteria, uh, tech is something which comes naturally to all of our companies. Because that is a very strong evaluation criteria for us, right? And tech is something which we are strong at as well. But I think on that aspect, the help is very minimal. Uh, typically we end up helping companies on the strategy side. I think when you are building the company in early stages, it's like a problem solving and nobody knows the solutions. Not that we have the answers, but can we be alongside the founder and debate on what to solve and how to solve together? I think that continues to be the bulk of our board discussions, if you will. Building teams could be another one. Connecting them for market expansion could be another one. Fundraising help. Of course, we do that. So, but it has been very different for different compan…

AI assessment note: “typically we end up helping companies on the strategy side”

Q 10. These companies have all been from the domain of AI, solving different problems, transportation, healthcare. What is the problem which you feel that is still not solved in AI and you're not got a company for it?

A Yeah. So, um, I think, um, So, um, it's a little bit of a tough question, but let me try and articulate in a way. So, I think we're very excited about the companies we have back. There are, in AI, we divide our companies into two buckets. What we call as AI first companies and AI second companies. AI second companies are companies which have a solution without AI, and with AI, it gets many, many fold better. But AI first companies are companies which cannot, which are problems, which Companies that are solving problems which cannot be solved without AI. I think that field is very exciting. So our latest investment, for example, VISA, where it's a mental health chatbot, but there's an AI psychologist sitting in the back, right? I mean, it's a very sophisticated AI engine, and to be able to chat with it and it able to see what issues you are facing and suggest something to you is a non-trivial technology to build. Right? And this cannot be done with AI. So those are the problem statements which really encourage us, like breast cancer, like, uh, which Niramai is doing using AI, or Sig Tupul, we're doing pathology with AI, etc. Front desk, uh, which is doing front desk management for you completely without any intervention per se, right? So these are very exciting problems where AI is, without AI, that problem cannot be solved. I think taking that deeper, further, Uh, there are sev…

AI assessment note: “one of the primary use case there is just conversations”