Debjit Mukerji, Partner at NGP Capital, explains why deep tech’s defining moment has finally arrived. Drawing on a thesis-driven approach, he shares how he evaluates companies at the intersection where “atoms meet bits”, backing founders building in the physical world. Debjit breaks down the convergence of three powerful forces—labor shortages, generative AI’s expansion into industrial use cases, and faster hardware development cycles—that are unlocking a new era of opportunity for physical technology companies.
Debjit Mukerji, Partner at NGP Capital, explains why deep tech’s defining moment has finally arrived. Drawing on a thesis-driven approach, he shares how he evaluates companies at the intersection where “atoms meet bits”, backing founders building in the physical world. Debjit breaks down the convergence of three powerful forces—labor shortages, generative AI’s expansion into industrial use cases, and faster hardware development cycles—that are unlocking a new era of opportunity for physical technology companies.
In this episode, you'll learn:
[05:28] Why venture capital?
[07:40] Inside NGP Capital’s deep tech focus
[11:05] Why now is the moment for deep tech
[17:02] What Debjit looks for in founders
[19:17] The Tractian story: founder intensity
[31:39] Key deep tech trends: Robotics & AI
[35:43] What makes a great deep tech pitch
The nonprofit organization Debjit is passionate about: MedShare
About Debjit Mukerji
Debjit Mukerji is a Partner at NGP Capital, where he focuses on Deep Tech investments across robotics, AI, and industrial systems.
With over two decades in venture capital, Debjit brings a strong technical foundation, holding a PhD in mechanical engineering from Stanford University. His career has spanned roles across multiple leading firms and industrial technology platforms, where he has consistently focused on translating breakthrough research into real-world impact.
He is particularly passionate about backing founders building at the intersection of software and the physical world—where innovation is hardest, but most enduring.
About NGP Capital
NGP Capital is a global venture capital firm dedicated to investing in Deep Tech companies. With a focus on “digital-physical convergence,” the firm backs startups that apply AI, software, and hardware to transform physical industries.
NGP Capital invests primarily at the Series A and B stages, with a global footprint spanning North America, Europe, and beyond. The firm partners closely with founders building in sectors such as robotics, industrial software, space technology, and connected systems, supporting companies that aim to redefine how the physical world operates.
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"With one of the founders, he was the quiet one. We really wanted to understand were they willing to take this company all the way or not? How big was the vision for the company? And he was relatively quiet. We're trying to figure out how much fire he had, and I asked him, "If you were to get an offer from, say, an incumbent to buy this company for $300 million. Would you do it?" And you should have seen the reaction. He got so angry. He actually got literally very mad at me and was about to maybe physically assault me because I had offended him so badly and he said, "No way! We actually wanna buy them." - Debjit Mukerji
[00:00:48] Gopi Rangan: You are listening to The Sure Shot Entrepreneur - a podcast for founders with ambitious ideas. Venture capital investors and other early believers tell you relatable, insightful, and authentic stories to help you realize your vision.
[00:01:09] Welcome to The Sure Shot Entrepreneur. My guest today is Debjit Mukerji. Debjit is a partner at NGP Capital. He focuses on Deep Tech investments.
[00:01:20] We're gonna talk to him about trends in Deep Tech, the kind of companies he invests in, why does he get excited about certain types of founders? And we're gonna talk to him about his journey as well in venture capital. And we're gonna learn more about NGP Capital.
[00:01:35] Debjit, welcome to The Sure Shot Entrepreneur.
[00:01:37] Debjit Mukerji: Thank you so much for having me, Gopi. It's a great pleasure to be here and I'm excited to have the conversation with you.
[00:01:43] Gopi Rangan: I'm looking forward to this conversation as well, but let's start with you. You grew up in California, you went to Stanford, and you stayed in Silicon Valley. You stayed in the tech side of the world for a bit, and then you've built a venture capital career. I'm curious to understand your background and how all of this evolved.
[00:02:02] Debjit Mukerji: Yeah. I appreciate the opportunity to talk about it. My approach into venture has been maybe slightly different than a lot of people, at least earlier on in my venture career. Today in venture, we see many different walks of life represented, but my path into venture is non-finance oriented. So as way of brief background, I grew up in Davis, California in an academic family. My dad was a biochemistry professor. I grew up with a longstanding interest in science and technology and math. That was always my forte. And early on I felt like I wanted to go as deep as I possibly could to study those disciplines and ultimately to be an academic.
[00:02:45] So I studied mechanical engineering and I was always interested in physics in general. And I pursued the branch of mechanical engineering that was really focused on understanding the physical world. And that is things like fluid mechanics, aerodynamics, heat transfer, thermodynamics, combustion, really the understanding of the natural world, but how they intersect with products that we engineer.
[00:03:09] So that was something I was very interested in, and I pursued it through Stanford, did a PhD there, so I kind of went all the way. At some point, there was a departure in my thinking around being an academic. I think I had my feel of going very, very deep into a specific problem. I started to have this desire to learn more about different disciplines and branch out, and ultimately my path into VC was paved by actually a professor on my reading committee at Stanford.
[00:03:39] He had just started a company doing microscale heat transfer, I was writing my PhD thesis. He said, "Do you want to come consult for me and help set up the foundational IP for this company?" And I said, "Absolutely!" And it turned out I was working then part-time for a venture capital firm. I had no idea what venture capital was.
[00:03:59] And I started to get intrigued by what VC really meant, and for me it was really this translation of research ideas and deep innovation, fundamental innovation into commercial products impact for people in their daily lives. So that was the beginning of the journey.
[00:04:16] Gopi Rangan: I grew up in an academic household as well, so I relate to the desire to do deep research and get nerdy and involved in various topics. I also thought that I could be a professor one day and I kind of stopped that, uh, path and moved into research. Actually, I would say I did more real research, applied research in the real world than I would've done if I had continued pursuing the path. But I have a tough question for you to start with. You went to Berkeley and you went to Stanford?
[00:04:46] Debjit Mukerji: Yes.
[00:04:47] Gopi Rangan: Where is your loyalty between the two schools?
[00:04:50] Debjit Mukerji: Well, I think you have to go with your undergrad if it's a tiebreaker. I love both schools.
[00:04:55] I think they're two of the best institutions in the world. And you know, one's public, one's private. I love them both dearly. I think the loyalty has to go to the undergrad.
[00:05:05] Gopi Rangan: Ouch. You spent more years at Stanford?
[00:05:08] Debjit Mukerji: I did. I did. Like I said, I, I love them both and Stanford's just down the street from me and obviously it's a fantastic place for ideas. And Stanford is, in my experience, a lot more commercially oriented, so a lot of great ideas get commercialized quickly at Stanford, which which is fantastic.
[00:05:27] Gopi Rangan: Yeah, that is fantastic.
[00:05:28] Indeed. One of my first investments was university research that spun out and became really successful. You started your career in Deep Tech research, and then you moved into venture capital. Now you were at Row Ventures, you were at the Cleantech Group. You were at Dripper Nexus and Siemens, and you later at Next 47, and now at NGP Capital. Clearly you love venture capital. Why?
[00:05:55] Debjit Mukerji: That's a great question. I really do love it and I have to say that for me it goes back to the foundational element of my personality and the things that drove me in the first place, which is really a love of learning. I think venture is a great privilege in the sense that we get to learn from the best innovators in the world in all of these respective fields.
[00:06:16] For me, I'm actually very lucky that Deep Tech is starting to be almost mainstream, and we're getting so much interest around deeper tech. That wasn't so much the case when I started my career, but I love products and ideas that have a physical angle to them, things that you can touch and feel. It's kind of why I became a mechanical engineer in the first place, and I'm finding in VC, there are so many great ideas around robotics, industrial automation. You know, we're seeing autonomous vehicles. We have incredible space technology that's evolved. All of this is within the purview of physical tech. So there's a learning opportunity every single day in VC and we get to meet the most amazing people on a day-to-day basis, when I meet with founders, there's an energy that I get that I can't really replicate, and I can't really think of another job that would really afford that. So I feel very privileged to be in VC, and it's been 21 years for me now, and I've really loved every phase of my career in VC.
[00:07:19] Gopi Rangan: We get to work with some really ambitious people and some of the projects they work on when they become successful transform we live and do business. It's truly fascinating and it's, a privilege and an honor to have the opportunity to work with such founders.
[00:07:33] Debjit Mukerji: Indeed.
[00:07:33] Gopi Rangan: You focus on a Deep Tech, and I'm curious to ask you more questions about Deep Tech, but let's talk about NGP first and we'll come to Deep Tech.
[00:07:40] What is NGP Capital? What kind of sectors do you focus on? What stage do you invest in?
[00:07:45] Debjit Mukerji: Yeah, so NGP capital has been around for as long as I've been in venture exactly 21 years now. We celebrated our 20th anniversary last year. It is a global venture platform that has had multiple funds. We are currently investing our fifth fund.
[00:08:02] Fund five is a $400 million fund, and I think it's very important to state this. It is dedicated to Deep Tech. We came up with the idea, this was really the partnership that I joined, so it was before I had joined the firm, but they had come up with this idea of digital, physical convergence. This is effectively the place where atoms meet bits to signify that this fund would be entirely focused on physical industries.
[00:08:30] And the opportunity for software to transform the physical world; AI and software to transform the physical world and also hardware, beautifully engineered hardware to play an important role in that transformation. What that means from a practical standpoint is that we invest in robotics, AI-backed connected sensors and systems, industrial software, space technology, data center technology, cybersecurity. All of these are within the purview of what we do.
[00:09:01] And in terms of stage, we typically like to invest at the series A and B stage. We like to really roll up our sleeves and work closely with founders, and we're certainly not driven by volume. We're driven by exceptional ideas and truly disruptive technology, and I can talk maybe a little bit later about our unique approach. But what really pushed me towards NGPI joined two years ago was this dedicated focus on Deep Tech and convergence. It was a perfect fit for me. And I also liked the global nature of it. I'm based here in Palo Alto. We have a team based in Germany and a team in Finland.
[00:09:41] We cover the globe. We've invested in Israel and China in our past. We've invested in India and South America. So there's no region that's really off the map for us. We're simply looking for the best companies in the world and the categories that we care about.
[00:09:55] Gopi Rangan: You're a truly global firm. You focus on all geographies.
[00:09:58] What stage is the sweet spot for you, and how many investments do you roughly do in a year?
[00:10:04] Debjit Mukerji: So the best stage for us, where we feel greatest comfort is series A and B. So it's relatively early stage. Sometimes we will do late stage seed rounds and sometimes we will do what I would call early series C rounds.
[00:10:18] And of course we will support our portfolio companies as they progress. Usually the check size that we like to deploy is about $15 million. And like I said, we like to lead and be active on boards.
[00:10:29] Gopi Rangan: Deep Tech is hard. That's kind of the popular notion. It's capital intensive. It takes time. And the risk involved in technology breakthroughs is... there's a lot more ambiguity than market risk or business model risk or product risk, or even team risk.
[00:10:46] But Deep Tech is essential. The Deep Tech kind of goes in favor, out of favor a few seasons. I get the feeling that now is a really important time for Deep Tech. I can see that your whole firm focuses on Deep Tech. Can you talk about some of the important trends and why Deep Tech is important today?
[00:11:05] Debjit Mukerji: Sure. So I think Deep Tech does have fundamental lasting, durable value. If you look at global GDP, ranging from 30 to 50% of global GDP is driven by physical industries. Having a physical presence from a product or a solution is very sticky and so there are natural advantages to it.
[00:11:27] It does have the reputation of being difficult and we've seen various evolutions of Deep Tech over the years. I think right now we are seeing an incredible interest in Deep Tech for three reasons. The first is that if I think about what customers are saying, and I've been following industrial customers for a long time, call it 15, 20 years, there's a change in their voice. Deep Tech is not just about technology being ready, it's also about the market being ready. And what we're hearing from the voices in our customer networks is that things like chat, GPT, that moment, actually we, we don't think about it often, but that actually had a ripple effect in industrial segments.
[00:12:12] Humanoid robotics is another thing that has captured the imagination. The reason these trends are so profound, these are moments in time where there's a great technology idea is because we're facing a backdrop of true scarcity and need. The scarcity really is in the form of labor. Labor shortage is a real thing. There's a lot of market research out there, about 500,000 US factory jobs being unfilled today, growing to probably 2 million in the next four to five years. We've gone out and asked customers on the factory floors in supply chain and logistics, in process industries: is this true or not? And it's been categorical and universal "yes, it's a problem." There are not enough workers. We have training issues. Churn is an all time high. We have generational turnover. Resuring is a real trend. Manufacturing resilience, and in part related to military independence and the upsurge in defense, these are all driving factors. So the first thing that I would say is there is this market need and customer attention that I have not really seen before.
[00:13:23] So there's a moment now in Deep Tech on the market side. I alluded earlier to the technology factors. I think that if you look at the new technology that has come up, that's things like generative AI, new form factors within robotics. So moving from very brittle application specific form factors to much more generalized form factors. Today, having multimodal data is no problem at all. A model can break down multimodal data, which was not really possible before. If you think about industrial segments, they're all about silos. Very, very specific data, but locked up in specific domains or locked up in silos. Those barriers are now beginning to break.
[00:14:05] So I think it's a combination of technology trends that started earlier and we saw a lot of those trends being discussed in the context of industrial IOT. Things like pervasive connectivity, lower cost of compute, faster sensing, and better sensing, better data health.
[00:14:23] I mean, all those things are happening, but then we also have brand new models coming out. AI is now at a different level. We kind of went from machine learning to deep learning to now generative models and robotics is also hitting now a point I think that people didn't expect before. I think there's a certainly now a number of companies that have made automation much more mainstream, and now we're getting into more generalized, very, very intelligent, very flexible automation modalities that are now opening the aperture wide.
[00:14:56] Gopi, there is one other factor that I would point to, and that is that generative AI is also changing the landscape in terms of software. We're of course seeing that as a repercussion in the markets today. You can look at the rise of a company like Anthropic in some ways displacing potentially many, many vertical software applications and commoditizing a lot of basic software skills. I think there's a resurgent interest in Deep Tech and physical tech because to some extent those categories still require real world deployments. They need to be installed by customers. There's the physical presence. And it's very hard to unstick those or disrupt those. So I think this may be resilience against the software disruption that we're seeing. This is another factor.
[00:15:46] Gopi Rangan: So you're saying now is the time for Deep Tech.
[00:15:50] After years of research in the labs and in universities and other places, now physical AI and all the advancements that have happened is moving into the real world. And that evolution is your main area of focus when you look at investments.
[00:16:06] Debjit Mukerji: I think the moment for Deep Tech has arrived. I would add that there's one other thing that is a part of my thesis, which is that Deep Tech often invokes the idea of hardware. And you know, this is kind of the convergence of Deep Tech and physical tech. While hardware is now easier to design than ever before, and some of it is with the advent of these generative tools, it used to be very difficult, for example, to tape out a chip, all the things that you needed to do, you needed to design, then you needed to test and simulate and error correct and manufacture, and then deploy. All of these things now are being made much easier with software.
[00:16:47] So even the hardware design and engineering and manufacturing cycles have shortened with the advances we're seeing in software. So there's been a real acceleration in even creating and deploying new hardware paradigms.
[00:17:02] Gopi Rangan: Let's take some examples of portfolio companies. Maybe start with one. What happens in that first meeting when you talk to a Deep Tech founder? What questions do you ask them and what do you wanna know?
[00:17:13] Debjit Mukerji: So typically what I start with, and I think the interesting thing about VC is that we all kind of need a superpower and we all play a little bit of a role by maybe building on our strengths. So being a PhD in engineering and being a former aerospace engineer, one of the things that I like to do is to go deep on product.
[00:17:32] And one of the first things I ask is just tell me what was the hardest part of your product to build. What was the thing that really took the longest time to crack? What was the thing that really frustrated you? I'm looking for two things.
[00:17:45] A, because the frustration, tends to be a very natural, emotional human feeling, I can tell when the experience is authentic. A founder is maybe venting their frustrations or excited to tell me about the hardest thing that they had to overcome.
[00:18:00] It is usually not the thing that you would expect. It could be something very plain and straightforward, meaning it may not be the crux of their intellectual property, but it may be a more mundane characteristic of the product that was just very difficult to execute. Maybe it was for people reasons. Maybe it was because they needed access to some resource that was hard to get. But really what I'm looking for is an authentic answer. I look for the emotion in the voice. I'm also looking for evidence that the founder has a lot of resilience and was able to overcome a challenge, get over it, and then probably learn from it.
[00:18:36] And the third thing I'm looking for is if this founder and if it's a thoughtful founder, had a difficult time solving this problem, it's also probably going to be hard for somebody else. So I'm looking for those moats that really differentiate the product and create replication difficulty for others.
[00:18:55] Gopi Rangan: So you're a product guy. That's what you look at first. I like the way you framed the question, what was hard to build? What was the biggest challenge, and how did you overcome it? It gets straight to the heart of how they think as technology experts. Can you give an example of a company that you've invested in?
[00:19:11] Like how did the company appear to you when you first met them, when you invested, and how has the journey evolved?
[00:19:17] Debjit Mukerji: Yeah, I'd love to. I'd love to talk about one that's near and dear to my heart, which is Tractian. It's a company based in Atlanta, Georgia, and it's a global company now. They have basically built a combination of hardware and software solutions to manage industrial operations and maintenance, specifically being experts in machine intelligence.
[00:19:40] So they have a network of sensors that provide condition-based monitoring and predictive maintenance, offer all sorts of insights to maintenance, reliability, and operations teams. They also have designed workflow software that enables execution of the insights that they generate. It's one of the fastest growing companies I've ever been a part of in industrial categories.
[00:20:01] They have a real hardware product, so it is not a trivial exercise to build these, get them shipped, get them installed, have them working to customer satisfaction, generate data. But at the end of the day, it's really an AI company. The sensors are beautifully designed, beautifully engineered, and they always took the highest level of care to build the best hardware in the world. But at the end of the day, those sensors are a way to get data into their system. So they're collecting from over a hundred thousand sensors now deployed. They're collecting a giant amount of information and processing all of that, combining it with other machine data sets, like work procedures and OEM catalogs and data sets. They also even have a physical testing lab where they're creating data. So the data is the moat. It's truly a physical AI company.
[00:20:56] My history with Tractian goes back to 2021 when I first met the founders. They were actually raising a seed round, so this was a very early company. I met two of the three founders at the time. They were in their mid twenties, very young, but they had an intensity about them that was hard to deny. It was a category that I had looked at before. I had already decided this was a very difficult category because I had talked to probably 10 companies in the space. They were all kind of going about it the wrong way, in my view, and I thought in some ways that way was the only way to tackle the market. So I didn't think there was another way in.
[00:21:37] These guys, the first time I met them, they almost had the antidote to the poison that I just talked about. They had a kind of an answer to everything on my anti list that I had created. But it was very early. I just didn't think they would be able to hit. The targets that they had set for themselves in the next nine to ten months.
[00:21:57] So I told them "it's a little early, but please come back to us at the end of the year." I think we created a good enough connection because I asked a lot about product in tech and I'm not sure anyone had asked them those questions before, that they wanted to come back to us for the series A, so they came back nine months later, they said, "Hey, we didn't just meet our targets. We exceeded them." And that got me immediately excited. And then we went deep and we ended up leading the series A. The things that really stood out to me, I think in those first few interactions were an incredible intensity. I think that's hard to quantify. It's just something you feel an incredible sense of drive. There was a sense of almost a revolutionary spirit. You could tell that they wanted to redefine the whole category of asset maintenance and machine monitoring. It was just something that they were compelled to do. And there was a learning and a curiosity. This is something that I look for in founders all the time. There's a learning desire and a curiosity, which I had not seen in others.
[00:23:08] And I'll give you an example of what I mean, Gopi. So in that series A diligence there was a whole section of the product, specifically metrics around the product and usage that they hadn't really looked into. So I told them, "Hey, I'd love for you to actually decode all of this. Please go into your data archive and give me all this data." Now, to many founders, that can sound like a lot of homework. It can sound a burdensome. To these guys. It was a challenge. It was something they were excited about doing. They were excited about doing diligence to uncover something that they knew was going to be important for them. So that was an amazing thing to see.
[00:23:46] Another example is with one of the founders, he was the quiet one. You know, we really wanted to understand were they willing to take this company all the way or not? How big was the vision for the company? And he was relatively quiet. We're trying to figure out how much fire he had. And I asked him, "if you were to get an offer from, say, an incumbent to buy this company for $300 million, would you do it? Would you sell Tractian for that amount?" And you should have seen the reaction. He got so angry. He got, actually got literally very mad at me. And was about to maybe physically assault me, uh, because I had offended him so badly and he said, "No way, we actually wanna buy them." That was the reaction that I wanted to see. It was this idea that there was nothing that was going to stop them and they wouldn't be satisfied until they went all the way.
[00:24:38] So those were a couple of examples, but there are many more interesting anecdotes from the long journey I've had with them.
[00:24:46] Gopi Rangan: What an amazing story. I noticed a few unusual things here. First, the company's based in Atlanta, not in Silicon Valley. So you truly are global and you're investing in places where most other investors don't focus on.
[00:25:00] The second is I see that Igor actually dropped out of college. He went to college at University of Sao Paulo, and he also spent time at UC, Berkeley. He didn't have a master's degree. He didn't spend years doing research on Deep Tech and those kind of things. He's actually a self-taught engineer and he built his own thing.
[00:25:19] In fact, he didn't even have a job, like a full-time job post undergraduate. This is his first job. Yes. And this is not a common trait I see in the world of Deep Tech. Is this common for you where you take unusual things and, uh, you actually look for the core substance of what is getting built and who the founders are, and you don't really look for pedigree and other typical signals?
[00:25:42] Debjit Mukerji: Yeah, I do. I think it's fairly common. I mean, in some ways it's not something that I necessarily look for actively. But I will say that his background is not uncommon, and at the end of the day, I think his background led directly to the kind of person that he is. He's a very unique founder. He marches to his own beat and all of his experiences led him down this exact path.
[00:26:05] And we see that in other founders too. So I would say that it's not that I don't look for pedigree or that I'm looking for a very maybe atypical profile, a priori, but at the end of the day, he exhibited the characteristics and not just at low volume, but in high definition, he exhibited the characteristics that I always look for in founders.
[00:26:29] And what we find is that that kind of a background maybe lends itself to those characteristic outcomes.
[00:26:35] Gopi Rangan: So let's take this example, Tractian or other startups that you've invested in. How does it work with NGP? There are many partners who needs to agree for the firm to say yes. Let's go through the investment.
[00:26:47] Does the founder need to spend time with all the partners, some of the partners? How long does it take from the first meeting to get to the investment decision?
[00:26:56] Debjit Mukerji: I'd say we are a very close partnership, so there's a lot of trust in the partnership, and usually there's a sponsoring partner who drives the process.
[00:27:05] That was the case with, for example, the three investments that I've made: GrayMatter Robotics, Skylo and Tractian. I've always kind of led those investments, but gotten the team involved fairly early. So typically what will happen is that we will go through the motions. We'll do a first meeting and a second meeting. I'm based in Palo Alto. The founders will probably meet the Palo Alto team first. So in the first week usually there will be a broader meeting with maybe one of my other partners and maybe other members of the investment team. We can go fast. I think we have to go fast in this current market to get access to the very best companies, and usually that means the two to three week cycle. And we are a global team, so we know it's not possible to meet in person. But we will have one kind of full partnership management presentation before the investment decision in which the founders will meet with the full team. And then the decision is made within the partnership but we like to think of ourselves as taking input from every member of the team. Everybody's opinion is valued. Oftentimes, contrarian and opinions are good. They lead to better outcomes. And so we have a process where the partners vote, but everybody also has an opportunity to weighin formally. That's actually an important part of learning for especially the junior team, is being able to chime in and knowing that they have a bit of a voice in deciding where we invest.
[00:28:38] Gopi Rangan: What if one person on the team really doesn't like the deal? They get really nervous.
[00:28:44] Debjit Mukerji: Usually what happens is we take that under advisement. I think it's a case by case basis, and it hasn't happened while I'm here. But usually if the other partners feel that the opportunity is worth pursuing, then that will carry the day.
[00:29:01] So we don't have, I would say, a firm veto from anybody, but it's taken under advisement. And typically what we like to do is obviously take the feedback seriously and translate it into a practical ask. So maybe it's a concern about the team or maybe it's a concern about the go-to-market approach, whatever it may be, we try to turn that into a strong recommendation for the founders and potentially at least surface it.
[00:29:28] And so it's known ahead of time that that was a concern. What I don't want to do is turn it into a requirement or any kind of formal term as part of our investment. I think that leads to bad outcomes, but we take everybody's opinion seriously.
[00:29:43] Gopi Rangan: So you've been at NGP for two years and you've invested in three companies so far. Typically a partner champions a deal and gets it to the finish line.
[00:29:53] How much time does it take to go from beginning to end?
[00:29:56] Debjit Mukerji: It usually takes, I would say, two to four weeks. Where we really need to hustle, we can. Where we have preexisting knowledge and maybe a predefined thesis then it goes faster. Where we have to spend more time unpacking maybe complexities of the business or even getting to know the space than it can take a little bit longer.
[00:30:18] But usually two to two and a half weeks is about as fast as we can go. I should mention that I personally am very much a proponent and try to follow a thesis driven approach to investing, which means not just investing opportunistically by meeting a company and liking it out of the blue, but rather having a prepared mind.
[00:30:39] And that means doing thematic work before meeting with founders. Sometimes that means that you may not have thoroughly explored the exact space that that founder is pursuing, but you've maybe explored adjacencies or areas close. To that category where you have a semi prepared idea before going in, and I think I really followed the scientific approach, the scientific method when it comes to thesis driven investing, which is meet with some companies, get smart, talk to customers, have a starting thesis. The thesis could be wrong, but you go with it, then you collect additional data and you refine the thesis.
[00:31:19] Gopi Rangan: I see that you have a very methodical way of approaching this in the ambiguous world of early stage investing,
[00:31:27] Debjit Mukerji: I make it sound a lot more systematic than it actually is, Gopi
[00:31:32] Gopi Rangan: Deep Tech has many themes inside. In your thesis, what are some specific trends you are excited about?
[00:31:39] Debjit Mukerji: I think one of the trends that excites me the most is what I'm seeing in robotics. I've invested in robotics now for many years, having invested in companies like Locus and Gecko and Skydio. Early in my career investing in Avo, which was the sensor company. Now investing in GrayMatter Robotics.
[00:31:58] So robotics is a category that I feel strongly about because it marries fantastic software with great hardware. The best results are those where you have some tight vertical integration and you own the whole stack. One of the things we're seeing is a progression in robotics from more application specific rigid brittle systems to now as the AI is getting better and better, and we have multimodal models available, much more flexible form factors. That is really the holy grail in robotics if you think about it. If you really want a need to replace a human. The greatest capability of humans is the versatility that they have. They can be easily moved from one task to another.
[00:32:42] We're getting to a point now where robots are becoming more and more flexible. I think GrayMatter is a great example of that. It's the surface finishing robotic solution that is initially targeted sanding, but they can also do things like grinding and polishing and buffing, and now getting into coating and blasting.
[00:33:02] So it's a much more generalized robotic solution than I think would've been possible even 10 years ago. We obviously hear a lot about humanoids. I think humanoids right now are obviously very sexy. It captures the public imagination. There are a lot of reasons why humanoids might be compelling. The most compelling reason for them is that they slot into existing infrastructure where humans are already working and ideally they can replicate many human tasks. But I think we have a long way to go to make them performant in most applications. So I see humanoids more as a long-term kind of end game for a lot of similarities that I see between self-driving and humanoids.
[00:33:46] And you could point to self-driving as ultimately now you know, we're seeing the culmination of a decade's worth of incredible investment, incredible technology development, and you see Waymo now obviously deploying commercially and there are a few other great players in that category. I think with Humanoids it may take a similar amount of time, but in general, the flexibility that we're seeing with robotics to be able to slot into more and more applications flexibly is one that excites me a lot.
[00:34:15] One of the key technology bases for that is, as I mentioned earlier, the multimodal models that we're seeing. I do think, Gopi, that training will be one of the hardest challenges there. It's very, very difficult to get physical data to train these models. You can do it with humans basically performing the task and kind of imitation learning. You can do it through simulations. And of course there's the hard way of doing it, which is sheer operational data and field experience. But it is very difficult to coordinate all those different modes, create a comprehensive, I'd say model training strategy and build the model or models that deliver the kind of performance that's expected. One thing I've learned in a long history in working in industrial categories is that customers have very high expectations. Nobody has time to babysit a robot. Nobody has, I'd say, intrinsic interest in technology for technology's sake. They want results. They need ROI, and I'm very much biased towards solutions that can deliver ROI.
[00:35:21] Gopi Rangan: Until recently, some of these topics were science fiction and now they're turning into reality like we live in a very, very interesting time indeed. It's hard enough to build a startup. What's your advice to founders in Deep Tech? What can they do to make that first, second meeting with you effective? And what can they do to make their journey much more successful?
[00:35:43] Debjit Mukerji: It's a great question. I'll start the answer with what to me makes for a great pitch; a really compelling story and pitch.
[00:35:51] I'm very interested when a founder can come in and convince me that now is the perfect time to capitalize on a giant market opportunity that they are addressing, that everything is lining up. There's a combination of both of macro trends. I talked about customer adoption readiness and other macro forces, secular trends that are creating tailwinds, but also there the convergence of that with the technology trajectory and technology trends that make new solutions possible. If they can convince me it's the perfect time, big market opportunity, tailwinds and technology readiness. That's number one.
[00:36:32] The second piece, you've defined the opportunity, then you basically say, "we are the team to back." There is no other team in the world as superbly qualified as us to address this incredible, unique opportunity. The most compelling founders can almost make the convincing argument that everything they've done in their life has prepared them for this moment. And the best pitches I've heard really articulate that well. It's like everything coming together, we're the right people at the right time. We're the ones to back. And of course as part of this, I would look into the tech and there has to be a technology approach and a customer understanding, both that suggests to me that this is the right solution at this time. But if they can convince me of that, then they've already come, I'd say 70 or 80%.
[00:37:21] Gopi Rangan: We're coming towards the end of our conversation, and I wanna ask you about your community involvement. Is that a nonprofit organization you are passionate about which one?
[00:37:30] Debjit Mukerji: Yes. There are a few that I feel strongly about.
[00:37:34] The one that I wanted to highlight that I feel quite passionate about is an organization called MedShare. MedShare is a medical nonprofit. It has a large Bay Area presence. So what they do is they collect medical supplies and equipment that are thrown away. In the US, regulations for use of medical supplies are incredibly stringent. The amount of waste in that industry is really hard to fathom, and what they do is take perfectly packaged sterile, still not expired, medical supplies equipment, and they take those. And they reuse them. These are things like bandages, gauze, tape, walkers, crutches, things that we often take for granted.
[00:38:16] They deliver these to every corner of the United States to needy people who can't necessarily afford it, or they send them to about 120 countries around the world where the need is very high. This could be war torn countries. They could be places where abject poverty is prevalent. I love the idea. I think they don't just accept supplies, but they also accept cash donations. They accept volunteer work because there's actually a lot of sorting and loading and packaging that they have to do. I'm proud to say that I have done all three. I actually learned about MedShare through a work excursion where we had a volunteer day. I spent a full day at the facility, met the team members and staff.
[00:38:59] Incredibly impressive. I love the mission, and so subsequently I've donated items that we had had in our family that were unused, and I've also contributed in a monetary fashion. So this is one I feel strongly about.
[00:39:12] Gopi Rangan: Debjit, thank you very much for spending time with me today. It's fascinating to hear all these interesting trends in Deep Tech that are going to shape our future very quickly within the next few years and decades.
[00:39:23] I'm so excited to see that you are at the forefront supporting founders in their journey from the early days onward. Thank you for sharing real-life experiences based on what you do with your founders. I look forward to sharing your nuggets of wisdom with the world.
[00:39:38] Debjit Mukerji: I appreciate it so much, Gopi. Thank you for having me on. It's been a great pleasure.
[00:39:44] Gopi Rangan: Thank you for listening to The Sure Shot Entrepreneur. I hope you enjoyed listening to real-life stories about early believers supporting ambitious entrepreneurs. Please subscribe to the podcast and post a review. Your comments will help other entrepreneurs find this podcast. I look forward to catching you at the next episode.