336. Meet the Unicorn Founder Revolutionising Battery Tech w/ Sai Shivareddy | Nyobolt

0:00Sai Shivareddy:Hi, I'm Sai Shivareddy. I'm the co-founder and CEO of Niobolt. What is Niobolt? So Niobolt builds ultra-fast charging batteries with very high power density. So that means packing a lot of power in a very small space. So we power things like robots, anything that moves that needs a battery and a powertrain, and AI server racks of all the things that need a lot of power. So it's combining high power requirements with high uptime requirements. and high endurance requirements. And these are three unique features of our technology that doesn't exist, essentially allowing us to start something new.

0:40Amardeep Parmar:And you just had a big announcement as well.

0:42Sai Shivareddy:Can you tell us a bit about that? Right. So we just closed our CEC funding round where we raised$60 million at a billion dollar valuation. And it comes after six years of starting the business. So it's relatively long compared to the AI-native startups, but it's relatively short compared to the general startups. So it's a great milestone for the company and great milestone for the team.

1:03Amardeep Parmar:And I've seen that last couple of years, right?

1:04Sai Shivareddy:Demand has massively increased for what you're doing. Right. So when you start out, you never really know where the demand is going to come from. And this is one thing everybody, especially building hardware struggles with. You look at a problem and you try to solve a problem. But when you start with a discovery of a technology or a material where you can do some things, you never know when the real application that it creates will come. So we found this three years into starting the business, right? That's essentially after we've raised quite a lot of money because generally for startups, you either have a paying customer on day one or you have a technology that solves a problem uniquely and they would be customers down the road because you've solved the pain point for a lot of customers, potential customers.

2:03Sai Shivareddy:So people bet that this will work down the road. But some technologies, you never know when the real application will come. So there's an example of lasers being discovered in the 60s, but not until a few decades later, you had real applications for lasers, right? In many of the material space where new materials are discovered, you actually don't know where else they could be useful. And some of this is also true in life sciences, where you discover some active ingredients that could solve, essentially, it's a cure for one disease, but you don't know which other types of disease it could be a cure for until you figure it out.

2:40Sai Shivareddy:With AI, a lot of this is changing. It's being accelerated, but it hasn't made the hardware foundational technologies with new materials and things like that made it any easier yet, it will get there. But at the moment, it's at least a few years before you go from, here's a new discovery and let's sell a lot of products and make a lot of money. So it's very hard to know when exactly that will happen. For so many startup founders, their dream is to get to where you are now, to have that

3:16Amardeep Parmar:billion-dollar status. And you're saying that for the first three years, you hadn't really yet discovered how that company is going to work. So it must be like a huge, even the mental shift now, right? In the last few years and that journey you've been on, how has that changed? Because did you ever think one day you'd get to this kind of position?

3:32Sai Shivareddy:Well, you'd hope you'd always actually aim for this or not this, but you'd aim for getting to a place where the opportunity you set out with and the pain that you want to get rid of. So people in our world, for forever, like at least 200 years that we've known batteries, they've never really like charged any faster than like overnight. And I think for a big part of our lives, we've seen it go down from like 12 hours to eight hours, or like it's still overnight, or it might be like two hours to full charge. The last 10 years, things were improving and fast fast charge was under an hour. And even when we started about six years ago, fast charging was like, you can charge from 10 to 80 % in 30 minutes.

4:23Sai Shivareddy:So that's still half an hour, right? In the world of instant everything, charging was not. So when I started Nibold in 2019, it was actually at the back of over 15 years of research and experience in the industry in the supply chains and how things are made to really piece all those individual blocks that were required to fit that puzzle so yeah it it's even longer to get to that point it would certainly not be something that's even three years I would say for really getting all those insights from the lab stage to manufacturing stage and you can have a lot of a lot of things that never scale.

5:10Sai Shivareddy:So many materials companies or hardware companies just to like scale these new technologies to a level where it's viable, that itself is the challenge where if you do that, then there's a lot of potential because then it's at the right cost and for the right sector and people have a problem that's being solved and they'll come to you.

5:33Amardeep Parmar:I think sometimes people think of like the billion dollar valuation as the end point, right? But it's not you, right? No, it's not.

5:39Sai Shivareddy:It actually never is. I don't think I set out thinking this will be a building of another company or anything. It's just there's two things people will tell you, right? If you're taking external money, especially from investors, again, which type of investors, you would take VC, venture capital investor money, then they need big outcomes for that business model to work. And those outcomes are based on the size of the fund and how large it should be. So not every idea would be a venture funded idea. But if you are in that venture funded idea pathway, then the outcomes they're betting on are like essentially how big is the market going to be?

6:18Sai Shivareddy:Is the market going to go in that direction or not? Or does the founding team have enough capabilities to at least, you know, show people progress and more progress you make, the better its chances of success are. And that's it. like there's always a probability of a certain outcome. Now, how big is that outcome? It actually is dependent on how things turn out with the decisions you make as a team. So if you get luck, which is if you're trying hard enough, you get lucky, as they say, you know, you can ride some of the market conditions. And in our case, we had the electric electrification of transport as the first wave we were looking at when we started out.

7:05Sai Shivareddy:So we built an EV to show that an EV can be built an EV with three minute fast charge capability or four minutes to 80 % when we demonstrated it. But nobody really needs that in terms of now, now six minutes is fine to 10 minutes. So it's just like, how quick can you get there? And what's the willingness to pay? the market forces are quite different in terms of whether those are the right opportunities or not. So we had to pivot to other sectors and things of that to really find the right opportunities where you're uniquely capable of solving that nobody else can. So it's trying to find out what you can do as a team that uniquely solves a problem worldwide that nobody else can.

7:51Sai Shivareddy:And you give yourself at least a two-year lead. So the way you do that is you will not know until you actually talk to customers or put in customers. And there are three things that need to come together, right? Like you need to be an expert in what you're doing, the team around you, and then the market really times it. You don't have that choice. So you're always ready to serve the requirements. In our case, the robotic market started taking off. So in the last three years, all the robots that you're seeing now, you know, at home you have vacuum cleaners. That's happened during COVID because a lot of cleaners couldn't come to the house and, you know, people started buying robots, right?

8:34Sai Shivareddy:So in 2020, when we started, for example, we thought that could be a great market application. And we were led by one customer who was one of the market leaders in that space. In fact, 20 years ago, I worked on a project for Dyson looking into the future. So there are a lot of people who think about what the future needs to look like, and it's generally shaped by builders, right? People who actually think that, look, if the technology is moving at a certain rate, there will be a future where these problems can be solved uniquely through that technology. So 20 years ago, we saw this, where changes to materials, like there were new materials that were discovered, like carbon nanotubes, graphene, and what they allow to do is to make things more conductive.

9:22Sai Shivareddy:So you have lesser resistance for accepting a lot of power and that was what we thought would give us the answer but actually they were not that easy to scale up and we ran into a lot of challenges and spent a good part of a decade doing that. So I only got to this after a lot of failures. It was never straightforward from those days because people who discover things don't really know how to manufacture at scale. And people who do that generally don't have an idea for new things and they don't want to change anything because it has constraints around, you know, downtime and things like that. So you've got to really, like, knock many doors, literally, sometimes cold, sometimes.

10:05Sai Shivareddy:But learning is something that's common across all, right? Like, you want to create a future that makes life easy for people. as an engineer, you set out with a certain dream, right? Or a scientist, if you're looking at science for, it's a career choice because you like science, you know, then how can you use science to do good, right? And solve some problems. And it turns out that it's not that, it may not be the first time you try doing it will work or second time, but if you do it enough number of times, there will be a pattern that you may recognize over time. So that's how I got to this point.

10:48Amardeep Parmar:And looking forward, right? What's the vision with this, right? So you are where you are today, but there's so much more to come. What do you see like one day you've been able to achieve through Niobot?

10:57Sai Shivareddy:So if you look at the energy industry in general and the power industry, like how we have power delivered to every home is a hundred year old approach, right? So that's going to change fundamentally. And we've also seen that through transport, electrification, and battery-powered vehicles are now everywhere. So we are playing a big part in creating this future where power is available instantly on demand. and it allows us to do more with technology that we could not do before. And going into the next decade, you'd want your energy to be clean and you want it to be available with a level of security that it's always there and the prices are not fluctuating because somebody decides to start a war or stop a war or close a trade off.

11:51Sai Shivareddy:There's so many things that are affecting daily lives through change of energy And we're hoping with the rate of change of technology and part of what we bring here is the fast energy storage, instant energy that can enable new things. So we're starting with robotics. We're getting into the AI data center power infrastructure because there the GPU or the chips lead a lot more power than before. So the density there has gone up like 20 fold. And we were coming up with a technology that had like a hundred fold increase in density. So we're actually right up that street in terms of how you can pack a lot of power in a small space.

12:34Sai Shivareddy:So combining where things are going with AI infrastructure and with where power generation technologies are moving, they all need to be managed the right way and smooth from an energy storage system. And that's where we work.

12:51Amardeep Parmar:So before we start recording, you were saying how originally your parents wanted to be an engineer or a lawyer or something like that, right? And right now we've got watching 17-year-olds who are on work experience with us, right? When you were that age, did you ever dream of doing something like you're doing today? Tell us about that path to getting here.

13:09Sai Shivareddy:Yeah, so I grew up in a South Indian family and you had choice. You could be an engineer, you could be a doctor, right? That was choice you had. So I don't know how many of you've had that, but I grew up in India, so it was very different where choice was to not lawyer, maybe a third one here, or it could, you know, be something else. Or you could work in the city as a banker or consultant. I mean, I think that they were available for engineers as a career choice, like you get into banking or consulting and stuff. But today, it's so different, right? So I chose, actually, my choice was physics, not engineering.

13:49Sai Shivareddy:I mean, while you need science to be in engineering, it's not as deep. So I was going into the natural sciences as my first choice and then got a scholarship to Cambridge to a PhD in engineering here. So in a way, I was telling my dad, like, I said no the first time. But at a certain level, it doesn't matter what the degree you call because you end up looking at the applied science side of things. Because to solve problems, generally, it's an application of the science, right? So that's the engineering side of solving problems. And when you go to higher education or when you get into research, there's so many things converging that the boundaries of physical discipline, scientific disciplines, are very blurry.

14:38Sai Shivareddy:So it ends up, you know, you could be like a physicist, but like be in a chemistry department, or you could be a chemist in physics, or you could be in computer science doing like computational things. So they're very blurred these days. But generally, like if you're curious enough to learn, just acquire knowledge, right? That's most students are generally like trying to learn something new. And that never stops as you go through. And I think this is the thing that you learn over the years, which is the ability to keep learning and get better at learning and using technology now. Because with AI, it's just so much easier to learn.

15:16Sai Shivareddy:You've got the world's entire knowledge teaching you stuff to build stuff and learn. So I think the choices, if I were to make today, yeah, it wouldn't make any difference. But I don't think constraints are a bad thing, generally, because what happens after you learn something, you have a lot more choices afterwards. I mean, you were telling me that you read economics and then you started doing tech with other things. In that sense, it's more the process of learning and the curiosity that drives some accumulation of knowledge. whether it's to build a business or a product like you know those things can be figured out pretty easily once you've been through a journey that's driven by curiosity hello hello i hope you've enjoyed the show so far i'm amadi palma co-founder of bay hq and the host

16:10Amardeep Parmar:of this show for those of you who don't know bay hq is the community for high growth asian heritage founders and investors in the UK. Over 7 ,500 people have attended our events. 200 people have been for our impact programs. And obviously there's been over 250 episodes of this podcast. If you want to join us and take part in the programs and come to the events, go to bahiehq.com forward slash join. We also just released our first ever book called Startups for Outsiders, which you can get on Amazon now. And the link is in the bio. Hope to see you soon at our event. Hope you enjoy the rest of the episode.

16:50Amardeep Parmar:You were obviously in the tech space. When you founded this, it was COVID quite quickly afterwards, right? So you were more on that research space. And once you founded this, it was COVID and you couldn't really interact. And then now you have to learn a lot about the business space in the last few years. What was kind of the hardest transition from that, from going from more the research side to now running a business your size? Yeah, so with us, there was the story of founding a new material, the discovery of a new material.

17:17Sai Shivareddy:And then that material needs to be manufactured in a scale. So you can make like milligrams in a lab, but you cannot essentially make a couple tons without understanding how to control the processes required. So the first two or three years involved a lot of research in the scaling up part. but as somebody who is a scientist who is founding a business you know you've got to learn all the aspects of the business to run the business and now I do more selling and actually this is the most underrated skill that you can have right even as a scientist or whatever you are learning how to sell something is the most valuable skill you would learn yeah this nobody told me when I starting out but everything has to be sold whatever you you know whether it's a career or a job you're trying to land you know I think early days people don't tell you that or at least I don't know in the UK so much but in India it was like sales people are selling is not a good thing it's not seen as a good thing or it's just not a thing like you don't you don't think that there's a training that you can have to do a better job at even communicating what you do.

18:35Sai Shivareddy:So it might lead somewhere. Whereas in the US, it's very good. People just naturally are better at selling things. So I actually spent time in the Bay Area. Right after my PhD, I found my first company in San Francisco looking at, again, some IoT power sources, which at that time, about 14 years ago was new and it was just very different. The experience I had there played a big role in continuing this entrepreneurial journey.

19:05Amardeep Parmar:You said I think earlier, so you've got 120 employees now, right?

19:08Sai Shivareddy:Yeah.

19:09Amardeep Parmar:And obviously managing that kind of scale of number of people, you've got to pick the right people, right? So what are you looking for when you're hiring those people to make sure you have the right team to support you?

19:19Sai Shivareddy:Well, so there's a technical expertise that's pretty clear in terms of whether people have that or not, right? So if you're on that technical path, it's very clear, can that person do what is needed? There's also a level of extension of what the market needs. But this is following where the real pain points are that you can uniquely solve. And some capability you need to build ahead of time and some you don't. Until the customers say, look, this is what we want and you go in that direction. So for me, early days, it was helpful to learn from the sector that we were in, where people who were in the auto industry or, you know, in embedded electronics or software to control those things.

20:05Sai Shivareddy:You know, it was not needed on day one, but we had to, like, look at it holistically. We were a materials company on day one, not a systems or solutions company. And followed the market. So the team will look like what you're trying to actually sell. So in a way, if you're selling a material, your team would be like material scientists. Or you could be like even technicians. So if you stayed after high school, you know, we have a lot of technicians who work in the labs or in the production lines. So we manufacture our own materials that goes into our own battery cells. and then we design our own electronics, we design our own software.

20:51Sai Shivareddy:So it's quite a broad skill set and initially we hired for more experience because a lot of these projects take a long time to converge and you don't have a lot of room for getting it wrong. So we were quite a very experienced team at the beginning but again it depends on the sector like in software it's not necessarily the case or not as experienced as in hardware, perhaps. But the nature of business today and how AI is influencing daily work is changing dramatically. So I don't think that's true anymore in terms of how much experience you need to hire on the team on day one. But the rate of learning is also a big difference now compared to before you need to wait for an expert to come and say things and stuff.

21:42Sai Shivareddy:But now you have that expertise right in front of you. So the choices you make in terms of who you need on day one can be different. But one thing is common across it.

21:53Amardeep Parmar:You've got to work really hard. There's no other thing there because you've got to be constantly doing things that can work