Sequoia Leads $75M Series B Into Nominal | Alfred Lin Joins Board

Cameron McCord, CEO & Founder of Nominal, discuss their recent $75 million Series B round led by Sequoia, bringing their total funding to over $100 million. With this funding, #1 on the Midas list investor, Alfred Lin of Sequoia is joining their board. Alongside Stephen Slattery, Growth & Product at Nominal, they delve into Nominal’s rapid 10-day funding process, driven by thorough due diligence and their impressive customer testimonials. We go deeper into their innovative core products, Core and Connect, for hardware testing, software management, and their impressive traction in aerospace, defense, energy, and maritime industries. Closing large early customers like Shield AI, Antares, and Vatn. Cameron and Steven, share insights into their backgrounds, including experiences in the US Navy, Anduril, SpaceX, and other prestigious institutions, and how these experiences led them to create Nominal. Learn how Nominal accelerates testing processes, the company’s growth strategies, and the unique challenges and advancements in the hardware sector. Plus, Cameron’s fascinating background as a submarine officer. Molly on X: https://x.com/MollySOSheaCameron on X: https://x.com/cameronlmccord Brought to you by: Brex—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, and travel. As a Sourcery listener, you can unlock up to $500 toward Brex travel or $300 in cash back, plus exclusive perks to help you move even faster: https://brex.com/sourcery Kalshi—The largest prediction market and the only legal platform in the US where people can trade directly on the outcomes of future events: https://kalshi.com/sourcery Fourthwall—The #1 way to sell merch online — Fourthwall is the easiest way to launch a fully branded merch store—used by big brands like MKBHD, Acquired, & even the Smithsonian. 100+ products. No upfront cost. Visit Fourthwall to start today: https://fourthwall.com/Earn Sourcery Content Rewards: https://whop.com/sourcery/?a=sourcery Follow Sourcery for the latest updates! https://www.sourcery.vc/ TIMESTAMPS: 00:00 - $75M Series B Led by Sequoia 03:12- The Journey to Nominal: Backgrounds and Convictions 06:01 - Market Opportunities & Challenges in Aerospace and Defense 08:58 - Continuous Hardware Testing: The Future of Development 11:48 - Nominal's Unified Operating Platform: Features and Benefits 15:03 - The Role of Connect in Hardware Testing 17:55 - Trends and Predictions in the Defense Sector 20:48 - Navigating the Supply Chain and Testing Landscape 23:48 - The Importance of Collaboration with Primes 26:49 - Delta Qualification: Accelerating Hardware Development 34:06 - Nominal's Products: Core and Connect 44:27 - Scaling Success with Nominal 48:21 - Performance Management in Complex Industries 52:10 - Case Studies: Aerospace, Nuclear, and Maritime 01:00:24 - Efficiency Gains & Cost Savings for Customers 01:03:20 - Navigating Innovation in a Rapidly Changing Landscape 01:06:49 - Go-to-Market Strategies for Diverse Customers 01:09:10 - Building a Talented Team for Growth 01:14:57 - Lessons from Fundraising and Future Outlook#podcast #investing #technology #venturecapital #entrepreneur #startup #siliconvalley

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Molly O'Shea?

  Well, we're here to congratulate you on a massive round that you just closed, a $75 million Series B. This brings your total funding to just over $100 million. Who led this round and what was the process like?

• 0:12Speaker 01

  Thank you. We're super excited to be here and share this news with the world. The round, Series B, led by Sequoia, specifically Alfred Lin is a partner there who will be joining Nominal's board. We're super excited about that. And the round is also co-led by Lightspeed Venture Partners. And so Guru Chahal and Connor Love from the Lightspeed team. You know, Androl had all the resources in the world, really, really, really smart people, but still was sort of limited by the ability for that software to perform. Because you either had Scenario A, where you would use really old outdated software to do modern test engineering, and it's really bad, and it doesn't work, and most of those technologies were built in a pre-cloud era. Or you have modern technologies that were generally built in a software-only world,

• 0:56Speaker 01

  with like no consideration for hardware limitations or constraints. Really, like my time at Androl, I kind of left there shocked that a product like Nominal didn't exist on the market.

• 1:05Molly O'Shea?

  Cameron and Stephen, welcome to Sorcery.

• 1:09Speaker 01

  It's awesome to be here, Molly. Thank you for having us. Thank you, Molly.

• 1:12Molly O'Shea?

  Thank you for the hat. I love merch, and this is pretty nice. Look at this nominal hat. Not bad. Well, we're here to congratulate you on a massive round that you just closed, a $75 million Series B. This brings your total funding to just over $100 million. Who led this round and what was the process like?

• 1:33Speaker 01

  Yeah, thank you. We're super excited to be here and share this news with the world. The round, Series B, led by Sequoia, specifically Alfred Lin is a partner there who will be joining Nominal's board. We're super excited about that. And the round is also co-led by Lightspeed Venture Partners. And so Guru Chahal and Connor Love from the Lightspeed team.

• 1:59Molly O'Shea?

  That's great. Was it a long process? How did you guys meet?

• 2:03Speaker 01

  Yeah, we uh, it was a very short process, which is great. Uh, it honestly, from, from starting the, uh, yeah, from starting sort of formal, you know, pitches and conversations to signing a term, she was about 10 days.

• 2:21Molly O'Shea?

  What?

• 2:21Speaker 01

  Yeah, which was, which is awesome. Um, and it was not a lackadaisical 10 days. It was very intense 10 days. Um, I think this Sequoia team in particular did an insane amount of diligence in that time period, which got us excited, like when investors really digging in. Um, and sort of seeing the world the same way you do as you're going through that, that process. Uh, it was amazing. I, it's been a very, uh, exciting, you know, period for, for me. I, on the personal front, got married.

• 2:55Molly O'Shea?

  Congrats.

• 2:56Speaker 01

  Thank you. Uh, went on a honeymoon, did actually get to like celebrate, uh, and, and check out for a little bit, uh, as much as one can when running a then series A company. Um, but basically as soon as I got back from that, had sort of let, you know, investors know that we were having a lot of traction in the business and, and we're going to be doing another financing. And so, um, as soon as, as soon as I got back, full focus and attention on, on the financing and, and yeah, it went, it went, um, fast. It was very much oversubscribed and, and a really good outcome that we're excited about, so.

• 3:27Molly O'Shea?

  It's fantastic. I think I heard Pat Grady speak at the upfront summit and mentioned that they do so much preliminary research that once they get to the deal, it's like, you, you really impress the founder with how much research you come to the table with.

• 3:43Speaker 01

  Yeah, we, uh, in our case, like they, I think this Sequoia team spoke to, I think a hundred percent, I think they spoke to every customer of ours.

• 3:51Molly O'Shea?

  Wow.

• 3:52Speaker 01

  Which was amazing. Um, and just watching them go through and like build their kind of conviction and, and come to their own kind of, you know, conclusions was, was really impressive. You know, part of the conversations were during the, during that process was they're actually kept kind of telling us like, oh, you guys actually might be underselling some of the TAM here, um, as they were like having more of these conversations. And like, when you hear investors like, you know, doing that, it gets you really, uh, really excited. And, um, yeah, the Sequoia growth team is no, you know, no joke. I, uh,

• 4:26Speaker 01

  That's sort of like final. We had a couple, two different partner meetings, one with like a smaller group with the growth team and then one with the whole, you know, the whole partnership. And they, you know, they had, they had receipts. They had done a lot of work and were able to really impress us with what they had sort of learned from, from a lot of these conversations. So it was awesome.

• 4:44Molly O'Shea?

  How did Lightspeed manage to co-lead with them?

• 4:48Speaker 01

  No, it was awesome. As is always, or as is so often the way in venture, you know, we, we were lucky to have a pretty fast Series A process as well. That was led by General Catalyst, Paul Kwan. That was, you know, about a year and a half ago now. And two of the people we were having conversations with early then were, were, you know, Sequoia had chatted with Alfred and then with the Lightspeed team. And so it often happens, then they're the first people to, to really move fast and get a lot of conviction. So that was how that, that happened. We love the Lightspeed team, particularly Guru there. I'm always partial to folks that

• 5:30Speaker 01

  have an operating background. And so Guru has, you know, led, founded two different companies, one in the hardware space, one in the software space. So he just gets what we're doing really, really well. And then, you know, Connor Love is awesome and is like, just a growing name, I think in the DOD venture world particularly. And we've had Connor, like over to nominal to speak at our all hands to like contextualize like the moment we're in with defense tech and what's going on right now. So Connor's awesome. And the combo that they, they bring as a pair, it was too good, too good to not have. So, yeah.

• 6:08Molly O'Shea?

  Super cool. Well, Cameron and Stephen, you both have pretty big names in the hard tech community. Cameron, you specifically, you worked at Anduril, you were in the US Navy, which we'll get to later, and Applied Intuition, Saildrone, and Lux Capital and various other government agencies. So how, what brought you to this problem and how did you gain conviction?

• 6:33Speaker 01

  Yeah, really? Well, thank you, Molly, for us. It's very kind. But, no, I mean, nominal for, for me is really a like, a

• 6:42Speaker 01

  A converging of like a lot of like seeing this problem from a ton of different angles. And what really made it come to life, it was the time that I did at, at Anduril.

• 6:53Speaker 01

  You know, I guess going back like started off my career as a submarine officer. So spent eight years on a submarine, which I know you want to, you want to talk about, we'll talk about that. It could be the whole podcast, but it won't be, don't worry. Uh, started off as a submarine officer. So just basically, you know, eight years of operating with the best technology that the US Navy and the Department of Defense has to offer, um, straight out of, you know, 1980. And so just like a lot of empathy, frankly, for what the warfighter, uh, you know, goes through when they're trying to do their job. I left that world. I was very fortunate. I had met, um, some of that early, you know, the Anduril team. I had met, you know, Trey and, and Brian Schimpf, um, through some mutual connections.

• 7:36Speaker 01

  And so ended up at Anduril relatively early on and was really fortunate to end up on this. The Anduril like counter UAS team, which is a team that will, uh, I'm sure will like go down in, in history as like a ragtag group of, of folks. But, um, you know, Gokul, who's now functionally like the, one of the senior vice presidents of Anduril and sort of leads essentially all engineering, you know, was an engineering lead there. Um, a lot of people know Scott Sanders, who now works at Forterra. Scott was, was, um, leading a lot of the growth efforts, um, worked with like a lot of those, those folks in the early days. And what I ended up spending a lot of time doing, in addition to sort of product efforts on this autonomous, you know, tower,

• 8:19Speaker 01

  anti-drone system was actually thinking through and architecting a lot of the software stack that was going to power the ability to test really rapidly, test iteratively, look at data after test events as, as quickly as possible. And, you know, Anduril had all the resources in the world, really, really, really smart people. But still was sort of, you know, like limited by the ability for, for that software, um, to perform. Because you either had scenario A, where you would use really old, uh, outdated software. Things like win plot, people know, but a lot of MATLAB is used, Python analysis, Python scripts, some of the national instruments, you know, tools, things like that to do modern test engineering.

• 9:03Speaker 01

  And it's really bad and it, it doesn't work. And most of those technologies were built in a pre-cloud era. Or you have modern technologies that were generally built in a software-only world with like no consideration for hardware limitations or constraints. And so you might have new technologies like people use Tableau, right? Or like Looker or Grafana or Datadog or other things like that that aren't built for hardware engineering. Like you certainly wouldn't wake up and be like, oh, those are like the technologies I would want to use if I were testing a like, you know, kinetic kill drone system that's like gonna get like computer vision lock and be deployed in Syria where it's like 120 degrees and like there's batteries that need to be right. Like you wouldn't, you wouldn't think of those.

• 9:47Speaker 01

  And so really like my time at Androl, I kind of left there shocked that a product like nominal didn't exist on the market. And then the journey, you know, you mentioned places like Lux or Applied Intuition, like really it was, okay, how can I actually go out and really educate myself on the market opportunity here? Some thesis that there's a product that needs to be built here, but like was there a real business to be built? And so a lot of the, the time spent after that was watching at Applied Intuition, like amazing, in that this case, modeling and simulation software be built and be sold at scale. And in the case of Lux, you know, an opportunity to basically speak to like hundreds of hard

• 10:31Speaker 01

  tech companies and ask them a series of questions around like what software they were using for this, this problem and really build conviction like there's a massive market opportunity here.

• 10:39Molly O'Shea?

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• 11:43Molly O'Shea?

  And Stephen, you're one of the earliest employees. So what got you hooked into it?

• 11:48Speaker 02

  Yeah, when I was getting ready to leave Anduril, really the two main things for me. One was a very small, extremely high caliber team. And I had a pretty high bar coming from Anduril and then before that SpaceX. And meeting the initial folks at nominal, it was it was evident from those conversations that this team was above and beyond even those groups I had worked with at Anduril and at SpaceX. So that was extremely exciting. Checked that box immediately. And obviously I knew Cameron as well from our Anduril days. And then I was looking for a product that I just really believed in and really could passionately develop and sell and be a part of that process.

• 12:28Speaker 02

  And I wasn't actually at the time, very picky about hardware versus software or whether it was SaaS or something else. But got the product pitch, saw the demo and immediately tied it full circle back to my sort of career path, which was starting at more of a prime Sierra space, a small group within that organization, having to build a lot of this software tooling myself and doing it also in air gapped environments for secure testing. And really there was just no buy option. I had to go and build it with some teammates over multiple years. Going to SpaceX, they've invested millions in their tool chain, everything from ERP

• 13:11Speaker 02

  to fleet management to data analysis, obviously. And so experiencing kind of, you know, I saw the light of what it was, what a hardware development program could look like and how fast it could move with that really first class tooling. And then went to Anduril and kind of went back, you know, very early into the dark ages there where, as Cameron described, There were a lot of good tools being built internally and particularly on the engineering development side, there were good tools being built. But my organization at Anduril, the technical operations group responsible for the global forward deployed operations of all these robotic systems, we really struggled to leverage those internal tools. And really for two reasons.

• 13:54Speaker 02

  The first was a lot of them were not designed to go deploy behind these security boundaries, out to customer locations, down range, behind air gaps. And even if we could get the tool there, then my team had to go and train on it. And these were tools built by engineers to do really tactical important things. And so we had a lot of inefficiencies trying to get folks who were on the front lines, often quite literally, being able to analyze data from these systems. And then concurrently, we're going through LRIP, scaling manufacturing for different products, and those same tools are starting to break. And so seeing nominal's product, I was sold pretty much immediately and came aboard.

• 14:32Molly O'Shea?

  Amazing. Well, it sounds super comprehensive and also in an incredibly untapped market. I'm curious, you mentioned a little bit earlier, but your investors had a hard time finding what the TAM was. Maybe you have the same problem, but exactly how big is the market for this in aerospace and defense and other industries?

• 14:54Speaker 01

  Yeah, it's, we joke internally a little bit that like the TAM is like infinite TAM. Because I really think it is massive. And so the challenge becomes like, how do you focus? And how do you, you know, sort of step by step, build the product suite that's going to unlock that TAM? So we've been very focused, yeah, initially on, you know, we're a dual-use business. So we have aerospace and defense commercial customers, more broader industrial commercial customers. We work with energy companies, transportation, you know, advanced mobility, even just more traditional manufacturing. And then we also obviously serve the Department of Defense directly.

• 15:34Speaker 01

  So we've started there, but I think as you look out at, you know, a lot of the fun conversations we were having with investors during this round, and a thesis we really believe in is like, Our vision is continuous hardware tests. Like, that's what we talk about internally. That's the language we use. And it is really that, like, the world is moving from this, like, type-one hardware development, where you will work really hard, you'll iterate on a prototype or a design of something, a widget, a machine, and then you will sort of set that design, you'll lock it, and you will print, manufacture 10, 100, 1,000, a million of those. Sometimes you won't even do it. You'll just outsource it to someone else to do it.

• 16:17Speaker 01

  And the world is very much like Stephen mentioned SpaceX, but even now Anduril and other places have sort of Tesla flipped that paradigm where the power in hardware development just comes from like how tightly you can iterate between those two things. And so, that's what to us continuous hardware test is. How do you allow the people that are doing this to link those two? And it's really linking testing, R and D, development, and experimentation to deployed operations of hardware. And so, when you think about, a lot of the customers we work with in the early use cases are in testing. You know, it's R and D, it's like early, and it's a fun place to start because there's like a high-risk appetite. People need to build new products. There's always a budget for it. There's always like a way to get started.

• 16:59Speaker 01

  But really, like, the pull that's been exciting for us is customers that think the same way we do, that say, actually, the software suite that I, and the tools I use to do developmental tests is exactly the same stuff I want to have when my system's deployed and it's in sustainment, and I want to like monitor a fleet of those assets. Or, we joke also internally, we have a phrase, we say like, you know, every asset, every drone, every plane, every, you know, ground vehicle, every UUV is a test asset. Fundamentally, it's generating, you know, telemetry, sensor data logs, just like you would a hardware in a loop, you know, test stand, or a test cell, or a wind tunnel. And so, our whole vision is like that the software stack should, should spread between testing and operations completely.

• 17:42Molly O'Shea?

  There's certainly a ton of market shifts and trends that are helping companies like yours and others in the industry. Things like reshoring manufacturing, reindustrialization, a trillion-dollar defense budget, hardware, hardware, hardware, humanoid robotics, drones, all of these things. What are you bullish on?

• 18:06Speaker 01

  Yeah, no, I can start there and then you should jump into Stephen. I think in like, you know, macro trends that get us really excited, I think the test world, the test community, if you will, testers, it's like, we love testers, like, those are our people. Their job is getting like harder and harder and harder. So that's just like a trend that we see. Just like, so, you know, these systems are more and more software-defined. They're just generating more data than they ever have. And that's not, it's not happening overnight, but it's been a steady rise over the last, you know, decade of just like software-defined hardware. So there's more data that's being generated. And then I think, talk about the DOD context, you know, the DOD is like shifting the way

• 18:50Speaker 01

  that it's thinking about a lot of these larger programs, trying to get away from 10, 12, 20-year program development life cycles. Like, let's build the next exquisite, you know, bomber, exquisite plane, or submarine, right? Those things are massive capital investments, they take a ton of time, and we're trying to much more get to, you know, distributed systems, smaller, autonomous, attributable, like all these words that you hear. But what that fundamentally means from a development perspective is, hey, we want to, things that used to take a decade, we want to do in 24 months. But we still want to do the same amount of testing. Oh, and by the way, there's more data. And so that community in general has felt like, I think, a crunch, and a crunch where we feel like software is a really big lever.

• 19:33Speaker 01

  And so we're trying to really just like help, help out there. So, you know, we work with a lot of organizations within the DOD, Air Force Test Center, is like the organization at Edwards Air Force Base that is basically in charge of and has a mandate to test and validate, you know, all Air Force, you know, weapon systems and new, you know, new planes, et cetera. And in groups like the Test Resource Management Center, TRMC, like, that's an organization we were really excited to work with. They have a mandate at the OSD level just to look at all test resourcing for the US. Physical infrastructure, but also software. And so I think like, that's something that we are bullish on is that

• 20:15Speaker 01

  test is like having a moment, like it's having a renaissance, if you will. And we want to be, God, it's such a test is having a renaissance. But that's what we believe. So I think we're very bullish on that. I think another thing that we talk a lot about and a point that I try to make is like, this is not, this is a coordinated, like reindustrialization is like, it takes so many different players. And I think what we think about is like, I think a lot in bottleneck theory. But basically, just if we solve, you know, like we meet amazing founders building like rare earth, you know, magnets and rare earth, like, you know, supply chain, production manufacturing, you know, additive,

• 20:59Speaker 01

  all of these things, like, those are real problems that we need to reshore in the US and sort of just modernize the industrial base. But we believe like that that is happening and people are solving a bunch of those problems across this like this chain. But again, what that's going to do is just like, put more focus on the ability to test and validate these systems. And so we were playing in that space and excited to, but I mean, you should, you can talk about maybe some of the like technology trends that you've seen, you know, in this world, I think you'd be, yeah.

• 21:34Speaker 02

  Yeah, I was gonna add just to the onshoring piece. I mean, doing that as an integrator, the large part of the problem is obviously just solving the supply chain and finding an alternate vendor, whether they're stateside or in an allied country or otherwise. But once you find that vendor, the next thing that happens is testing. If I'm, you know, previously was buying my brushless motor from China and now I'm going to buy it from a US vendor or a Czech vendor, whoever it might be. That is a test campaign that needs to go and maybe it's relatively short. Maybe it's longer for a larger system, but I need to go and validate that, that the performance is the same, understand how to validate every new unit that arrives. And that is happening across, you think of the bill of materials for an aircraft or

• 22:17Speaker 02

  a UUV, that is just an immense amount of qualification work that needs to happen and that that needs to keep happening in perpetuity. And so we're seeing this at some of our customers and then as Cameron mentioned, all of these new suppliers that are cropping up in the US and elsewhere, they are also potential nominal customers as they need to do their own validation as the supplier. So really, I mean, on both sides of this, it's just, there's an immense amount of opportunity.

• 22:44Molly O'Shea?

  To flip it, what do you bearish on?

• 22:49Speaker 01

  I mean, I can, um, I have a, I can do what I'm bearish on also, and then I have one that's like maybe a contrary intake, which I always just, I think it's like an approach. But so what am I bearish on? Um, yeah, I mean, I think I'm excited at like a trillion dollar, I think, sort of defense budget. You know, I think it's probably a positive thing for nominal, but I think my sense is this, the current administration now is like, is not in the business of, as much as we talk about, uh, cutting budget and cutting programs and, you know, Doge or whatever, um, those have been small cuts to nature, um, their efficiency gains. The new administration, I don't think is in the business of cutting big programs.

• 23:30Speaker 01

  Uh, and so unless you cut really big programs, like I don't think there's gonna, like there, there, there are efforts that are being like really well funded right now. Golden Dome is one missile defense agency, like that, that's exciting. And I think that a lot of companies realize that, see that, um, there's a lot of money and effort, obviously going to southern border, like efforts like that, that the administrations, I think, kind of made clear. But I think like, when I look at the sort of overall budgetary picture, like there's just not, there's not enough of these big program cuts, I think, for, um, all of the amazing new companies building out there to like really get the big program of record wins that they want over the next five years. So, so not everyone, you know, is going to, on the nominal lens, like I flip and say,

• 24:13Speaker 01

  like, um, I think it, the administration is definitely looking for efficiency gains in existing programs and we think a big part of the efficiency gain is, is helping people, you know, test.

• 24:24Speaker 01

  A contrarian take that I will make in this ecosystem broadly is like, you know, there's a lot of anti, anti-prime rhetoric that people like to talk about. And I think like we take a pretty vocal, like, you know, different approach, just like the primes play a like really key role in national defense. They have resources, they have capabilities, they can do things frankly that, you know, essentially no other startup can do. And so we need to treat them accordingly in that way. And so like we nominal, like we love the partnerships we have there. And we take a very like, I think as an American, like I want

• 25:07Speaker 01

  to take a very optimistic approach to like what modernizing those companies can do because they really are national assets. It's just, you know, the incentive structure is warped a little bit, but like, we need those companies to succeed and do well. So. What do you, what do you bearish on?

• 25:25Speaker 02

  I think you nailed it. I mean, the, maybe, maybe this is partially bearish, partially contrarian, but there's an immense amount of hype and focus around vertical integration. I think a lot of companies moving through that process are realizing that there's a huge amount of power in outsourcing to suppliers and you don't need to reinvent the wheel everywhere. And our lens into that often is the software side, right? You can buy, there's, there is an offering off the shelf nominal to go and address your, your software and telemetry management needs. But it's true on the hardware side as well. And I think, you know, maybe it's the, this like misconstruing of companies like Anduril and SpaceX that have espoused this idea of vertical integration, but they have massive

• 26:09Speaker 02

  supply chains, right? SpaceX is always going to look and see first if they can go and buy something before they go and build it themselves. And flipping that around can get you into a really dangerous place. And so I think things are trending, you know, generally in a natural direction, but as the supplier base for all these different hard tech industries grow, I'm excited to see the buy decisions being made in a lot of places and helping to support those companies as well. So.

• 26:39Molly O'Shea?

  To go further into where nominal software fits in, could you just explain out the end to end hardware development process?

• 26:48Speaker 02

  So, starting on the hardware development process side, generally, our customers are going to fall into one of two buckets. And sometimes, if they have multiple products, they're in both. So, on the one hand, you have the zero-to-one development program, and you're starting from pure simulation data to prototyping to initial qualification testing. Qualification testing can take months, often takes years. It's a very arduous process. And then into production testing, which is kind of, you know, things are rolling off the line, and we're just making sure that everything works. And our software product overall is focused on this entire spectrum of test cases. All right, so we have customers that use nominal only for simulation data,

• 27:31Speaker 02

  and customers using it all the way on production manufacturing lines and out to their fleet. And all of this data is relevant to pull into a single consolidated database, be able to manage it, present it back to engineers, to technicians, to VPs in an easily consumable way. And then the second piece is, in the hardware development process, right, you need to scale one to N. And that means bringing up a production line. But to Cameron's point about everything is a test asset, you also need to be aggregating all of the data from your fleet back into the same telemetry management and analysis tooling that you're using for development to be able to close that loop.

• 28:09Speaker 02

  And so, the platform that we're building, both from a deployability standpoint, a usability, and a feature standpoint, is trying to work across this spectrum and unify that tool chain. I think, in general, we've seen a lot of really exciting success, both with small startups as they're moving through that maturation process, as well as coming into an existing, pretty mature program, and really transforming the way that they think about tests and the way that they do engineering.

• 28:34Molly O'Shea?

  Where do current tools and workflows fall short in this?

• 28:40Speaker 02

  I mentioned, yeah, one earlier is it's not an intractable problem to build a tool chain for a single product for internal development only. All right, you can cobble together MATLAB and Jupyter Notebook and Grafana and two or three other things and kind of get by. The places where that is going to fall down is as you scale production and move into customer operations, that tool chain is not going to work either at that scale or with that new user base. All right, your users are no longer the experienced disciplined engineers that actually built the platform. They are field technicians, flight test engineers, customer operators, technical operations engineers like at Anduril.

• 29:22Speaker 02

  And so your bar for usability moves very, very quickly. And then the second piece is as companies are bringing in their second, third and fourth product, they might have built a tool chain that worked very well for product one, but almost always what we're seeing is that it's typically over tailored to that system in terms of the data types it supports, the analysis workflows, how commoditized it is. And then they go and, you know, decide, hey, we need five more widgets in our product line. And that tool chain cannot just be extended into those. And you start doing a new zero to one process for building entirely new tool chain. Or you're looking at hiring five to 10 really experienced software engineers across

• 30:07Speaker 02

  a pretty wide range of skill sets to be able to build a platform like what nominal has. And so those are generally the points where we're coming into customers from a sales motion standpoint as well. And they're seeing this kind of coming down the tracks for them. And we're just kind of presenting this very easy end to end solution that we can drop in and really get running on very often day one, within hours of starting with a new partner, we're delivering value.

• 30:33Speaker 01

  Steven, can you talk about Delta Qual?

• 30:37Speaker 02

  Yeah.

• 30:38Speaker 01

  I just, Steven. Whoa, what is that? No, no, just it's, Steven was sort of articulating it, but like, it's a thing he, you know, like, people have a thing that they just say internally a lot. Steven says Delta Qual a lot right now, and it's catching on. Okay. But yeah, it's a, it's a, it's a good articulation of like, what, what makes nominal powerful, I think.

• 30:54Speaker 02

  Yeah, and this was something that originally experienced at SpaceX. I was working on the Crew Dragon program. I was working in the test automation group specifically, who were sort of productionizing all of these processes for building Crew Dragon. And we talk a lot about mission criticality at nominal. I don't know if there's a more critical mission than the first flight of a human-rated spacecraft with people aboard. And so my role there was looking at these different test assets and processes and ensuring that, A, we were meeting these third-party requirements levied upon us by NASA or by the FAA, or if it was an Air Force account, by the Air Force, but also meeting our own internal bar and determining what that was. And the Delta Qual process is, let's say I have my, my asset out in the field and I

• 31:38Speaker 02

  determine I want to make a change to it, a design change, or change the supplier for a part, or make a firmware change. If I've already qualified that system, I don't need to go back and do my multi-month qualification test campaign all over again. I don't need to do all the vibration testing, thermal testing, performance, lifecycle, vendor qual. What I do need to do is demonstrate that that one small change that I made is not going to invalidate all the previous work that I did. And where you get this acceleration, if you're a SpaceX or an Anduril, is how fast can I identify an improvement I want to make and then convince my customers that that is a safe improvement and that I can deploy that into the field, whether it's new software or a new part.

• 32:20Speaker 02

  And so a lot of the testing activity at SpaceX kind of falls into this general bucket of Delta qualification and how quickly you can provision that test, collect the data, analyze it, build that body of evidence to go present back to your customers, your regulators. That is what it means to do continuous tests and continuous validation and to do iterative development in an agile way in a hardware product. And SpaceX is very, very good at that, and we're helping a lot of other companies become very good at it as well.

• 32:49Molly O'Shea?

  Delta call.

• 32:50Speaker 01

  Delta call, yeah. It's a big, I mean, I think like, I think it's a thing we see, um, you know, Stephen was sort of talking about it in the commercial context, but um, it's, this is a, I think, a huge area for the DoD broadly as well. And what happens often is, I mean, these programs are massive, really big budgets, very, you know, very, very costly from just the, you know, budget perspective, but also the human beings that go into these, you know, these programs. And so being able to help, you know, in the DoD setup, like it has services, right? And so it's like, there's intentional ways of, you know, the Navy version of the F-35 versus the, you know, Air Force version, right? Um, what we see is like, there's a lot of retests

• 33:32Speaker 01

  that happens, um, that probably doesn't need to happen, right? And so this concept of Delta call, like, our vision would be to be able to provide the tools to determine exactly what does not need to be retested. You know, if I'm doing the, the variance between the Navy and the Marine Corps for the F-35, for example, like, um, very small, um, some significant differences, obviously, in what the operating picture and like what the vehicle's supposed to do, but a big swath of that, um, is the same. And you shouldn't need to like re, you know, retest a lot of that, but often that's what, that's what's happening.

• 34:06Molly O'Shea?

  So to get deeper into the products, can we start off with the unified operating platform?

• 34:11Speaker 01

  Yeah, absolutely. We have two products that we'll talk about today. Uh, and then there are some more in the works, but, um, the two products that are out kind of on the market now, nominal core, that's what we started with. Um, I'll talk a little bit about like what, how that, you know, got, got off the ground. Um, and then we're really excited. We released, um, just honestly, a month or two ago, uh, nominal connect, which is our second product, which has been really exciting. Um, and we can dig into that a little bit. But like, I think it's a good, just telling the story of like where we got started, like, we got started specifically building a product that would, like this testing and validating hardware is massive process, very, very complex. We wanted to do a single thing really, really

• 34:54Speaker 01

  well. And so that was this like, you know, data review process. So if you're engineering, you're building hardware, like everyone knows that what that term means. It gives you like an emotional connotation of just like, oh God, I have to do data review. Um, but making it just really easy for engineers, like after a test has happened, to collaboratively interrogate their data, have it organized, make sense of it. Do both like ad hoc exploration, so like find data, query channels, just like have a really interactive picture of their data and then also start to build out sort of validation logic and rules that can automate that process because it's highly manually intensive.

• 35:34Speaker 01

  Like a thing we hear a lot is you have really expensive engineers, very smart engineers, that with the way the software is sort of the status quo, they're spending a lot of time doing like very manual processes of their data, things that can be done by software, can be done by automation, but it requires a really powerful interface for those humans to be able to sort of like enrich that data and make sure that it makes sense. So we started with data review and the product has obviously grown, this is, you know, that was three years ago now, has grown extensively since then into this like beautiful product at its nominal core. Steve, I'll kick it to you to give the sort of core overview and then talk about Connect.

• 36:19Speaker 02

  Yeah, it's, like you said, really a unified platform and the way that I generally break it up when talking about it is these three main workflows, the first being data management, second is data analysis, right, more of a manual process, and then the third is the automated validation. You kind of want that second piece to flow into the third over time where as you're learning more about your system and doing that analysis in nominal, in nominal core, that you're starting to move those learnings into the rule set to automatically evaluate it. The data management side, though, is very, very important and it's something that ironically is, you know, we want it to be invisible to the average user. We don't want a nominal user to be thinking about what is the particular file I need

• 37:04Speaker 02

  to look at today, where is it in my file system, what's the right version of the tool to go and analyze that? And so when you look at the makeup of our engineering team, about half of the headcount is backend software engineers. And just brilliant people from Palantir, from financial industry, from Big Data, folks that are used to these really heterogeneous, complex data problems. And so when we say data management, it's sort of two pieces. One is, how do we go and be able to upload or ingest all of the relevant data into our platform? Whether that's sensor data or video data, high rate, low rate, regardless of the source, be able to pull that in and do that very, very quickly. And we're very opinionated about meeting our customers where we are.

• 37:48Speaker 02

  And so rather than just kind of throwing them some documentation and saying, we do have a really good documentation, it's beautiful. But rather than just throwing them some documentation and saying, figure it out, we're actually going and building what we call these first-class integrations with these data types. And this is one of the benefits of being focused on hardware testing is that that's not a super-long list. We can go and build out all of the necessary file upload routines, streaming data connections that we see across these industries, so that we can get running, like I said before, you know, within hours on day one of starting an account. And then the second big piece is presenting that data back to the user and doing it performantly. The performantly piece is very hard. Hundreds, thousands of nominal engineering hours into ensuring our backend,

• 38:32Speaker 02

  storage and compute systems are highly optimized, highly scalable. But then, as a user looking into that data, it should be presented to me in a way that is representative of what was happening in the field. Right? And so we think about runs being these test events. And so a lot of nominal customers, that just enters their vernacular where they're talking about nominal runs and they're referencing tests that are happening on the production floor or flight tests or customer operations. So the run is kind of the real thing that happened, bound in time. And then the asset, like Cameron mentioned, the asset is the actual physical device producing the data. That could be an entire aircraft, or you can make it as granular as a single motor or a single circuit board on your system.

• 39:13Speaker 02

  And so that data model maps very well to the way that your average engineers are going to think about their systems and what they're trying to evaluate. The data analysis piece, briefly, it's really just merging these Grafana and MATLAB-esque workflows together, where Grafana is a very good tool for extremely agnostic cloud data and really just looking at time series data. And so at a company like Anduril, very early on, they might implement Grafana for fleet monitoring, right? And then you have MATLAB at the other end of the spectrum, which is very, very engineering focused, very hardware focused, that has all these toolboxes for different specialized analyses, but is locally deployed, right? I'm running it on my personal laptop. And if I want to share the results

• 39:56Speaker 02

  with somebody, I can't send them a link. I need to take a screenshot of the plot or send them 4,000 lines of MATLAB code to run. So we're lifting both of those workflows into core, into the analysis platform, so that people can do this collaborative, really deep data analysis, all in one place, right next to where their data is stored. And then the last piece, like Karen mentioned, is the automated verification. And so whether that's validating that a particular component performed well on the production line, or running just a continuous evaluation of data coming off of a fleet of assets, you can create those rules in nominal, using what you learned in the analysis platform, and deploy it everywhere. And so that's the unification piece there, whether it's production, or

• 40:37Speaker 02

  simulation, or customer operations, consolidating that single source of truth for what right looks like in your data.

• 40:45Molly O'Shea?

  What about Connect?

• 40:47Speaker 02

  Connect is extremely exciting and close to my heart, because my work at SpaceX and my work at Sierra Space before that was very, very close to the hardware, right at the edge, as people would say. And the things that make Connect really special, the first is, this is a desktop-native application. Web frameworks are wonderful, Core is a fantastic, performant, scalable product. But when you are out in a propulsion test facility, and you need to be able to abort a test within five milliseconds if something is going awry, and you need to go into a safe condition, a web framework is generally not the architecture that you want for that, right? Traditionally, you're looking at something entirely custom.

• 41:30Speaker 02

  Or you're calling in a third-party provider to implement a PLC-based architecture. So there's this huge market for deploying an application at the edge. And Connect has been just a fantastic rollout over the last three months and a fantastic time to value. And really, what it is under the hood, right, you have this very, very performant data backplane for pulling in data. But this can look a little bit different than Cores lends into data, right? Connect, you're thinking more about PLC pub subnetworks, extremely high rate, you know, potentially frequencies up into the megahertz. So pulling that data in, organizing it, again, presenting it back to the user, and doing that in a

• 42:14Speaker 02

  commoditized way. So we're building out all of these different drivers for different hardware systems, whether it's national instruments, or, you know, more hobby systems like LabJacks, for example, or PLC protocols to be able to plug in quickly. And then on top of that, we have this great sort of widget-based architecture for running these tests. Widget-based architecture.

• 42:35Molly O'Shea?

  Wow.

• 42:36Speaker 02

  And that's everything from, I need to run a checklist, to, I just need to look at some data on a plot, to, I want to actually upload data to Core, to the mothership, as we would say.

• 42:46Molly O'Shea?

  The mothership.

• 42:47Speaker 02

  And so between this driver layer that's connecting into the hardware, and then all of these very easy-to-use GUI widgets, we can walk into a production line or into a test facility, and our Connect team, our instrumentation engineers, can get to value in less than a day, right? They're kind of looking at this smorgasbord here of different things to pull in from our Connect framework, implementing it, and then giving it to the customer, such that they can, if they want to, continue supporting it themselves. We're not giving them this black box of like spaghetti LabVIEW code, which is the case for a lot of these solutions. We're giving them something that's more modern, more transparent, and so that, you know, they can help extend and build it if they wish as well.

• 43:29Speaker 01

  I'll like, I'm just super excited about Connect. So I'll hit on a couple of things too, which is um, so Connect's being like, you know, kind of run and managed by Jack Palmer, who we hired uh, almost a year ago now. Um, but Jack, most people know Jack as the former founder and CEO of Plotly. So one of the largest open source visualization libraries and kind of companies, extremely successful, is used by many, many customers in our industry. But Jack built that business, ran it for a decade, got back to his roots and was sort of, you know, building uh, software in the hardware world for a little bit. And we kind of came across paths and decided to join, to join forces. We hired Jack.

• 44:14Speaker 01

  Um, and as Steven said, like, we, we broke ground on, kind of got around the table as a, you know, executive team and sort of, Jack had this really strong thesis that this product needed to exist. We'd heard a lot of pull from customers um, and slapped the table in, in December. And, you know, in January, it was uh, you know, MVP'd and was already like selling on contracts, right? And so like that, that was really exciting for us. Um, it's now, you know, doing really well and we're, we're sort of doubling down on um, on that team. We're here, yeah, we nominal just raised a series B, but I always talk to Jack, like, we kind of made a seed bet for Connect and like, now I want to preempt the A. It's like, Jack, go like, go really, go really um, scale this because it's, it's working really well. We often get asked,

• 45:00Speaker 01

  you know, a question investors would ask or sometimes people would just ask in general, they're like, you know, you've got this infinite TAM, but like, how generalizable can you make a product like nominal to serve all these use cases? Like, how could it be useful for someone that's doing flight testing? And also someone that's just doing manufacturing and then someone that has building a nuclear reactor, like a few, you know, fusion. Um, all of those are nominal, examples of nominal customers. Connect is kind of like our demonstrative answer to that, which is by actually building an application framework. Like, we have very sophisticated, very technical users that um, are proficient in Python and can build a lot of this like last mile. Work themselves. And so I think it's been like super powerful to see our users,

• 45:44Speaker 01

  in addition to sort of our instrumentation team, start to build up these applications in in our framework and just do that last mile to get Connect valuable for them, but then also to get data to the mothership, as we, as we kind of said. And then the third, the third thing is Connect is exciting because it's also kind of like a direct replacement for existing spend categories. So with my, my business hat on, National Instruments, LabVIEW, Siemens, massive software, industrial software conglomerates that have had, you know, billion dollar businesses here for, for decades. Generally, there's like a very low NPS for those products. Like, people don't like them.

• 46:30Speaker 01

  They're not very good. And, you know, Core is this like vision. It's sort of this light like on the hill, like, you know, shining light on the hill. That's like, here's a better way of doing organizational test data management and hardware management for your organization. And Connect is sort of this like extremely practical, like you are already using a similar tool like this right now. Nominal is cheaper, better, faster. Like, you already have the line item approved in your budget. Like, you should just swap out. And so it's really, it's helped us really go fast from a business perspective there, too. And I think, you know, Stephen made a point earlier about the sort of supply chain broadly. It's been really cool to work with customers that have, one of the first questions or second questions

• 47:15Speaker 01

  they often ask us when they're using Connect is, you know, oh, my God, like, I have a supplier who I work with across the country, and they're maybe a 200 person company, and we rely on them. They make a widget or a component or a servo or a pump. And like, I need to interact with that data. Can you extend a nominal license to them? And so we've, we've done that model where we've sort of given nominal Connect to those companies, companies that would have probably, like, we just naturally would not have probably come across unless we were, you know, actively trying to, to seek those companies. So there's this huge, like, industrial, I'd say, almost middle market that I think Connect is helping us sort of break into in a, in a really exciting way. So.

• 48:00Speaker 01

  Needless to say, we're bullish on it.

• 48:03Molly O'Shea?

  But actually talking about spending smarter and moving faster. Sorcery is sponsored by Brex and they're all about performance. So in this next question, I want to ask about performance. So you're entering a legacy industry, one that's super complex. Each scenario, each case that you're working on is unique. How do you guys manage performance for your customers?

• 48:28Speaker 01

  Yeah, basically.

• 48:29Speaker 02

  Yeah, I think I'll hit it from a couple of different angles. The first is, and maybe pushing back a little bit on the uniqueness. One of the things that's made nominal possible now, or say, three years ago, is that there is this crunch happening across all of these disparate industries in terms of the data types that they are using. Where 20 years ago, if we were going in and trying to integrate nominal, either connect or core at N different companies, we'd be looking at N different potential data integrations because everything was so bespoke. But as everybody's migrating to more common data models and you have also this diaspora of SpaceX and Anduril engineers going out into the world and bringing these best practices

• 49:11Speaker 02

  to industries like nuclear, like maritime. We can go and plug into these, you know, previously fairly unique workflows in an equitable amount of time. And then everything downstream from that also looks quite similar. The data management problems are the same. The analysis problems are largely the same across industries. And, you know, we need to be a little bit focused. And if you read some of our previous media, we've been very focused on flight tests, for example, and recently posted about test facilities as well. And so we are kind of marching through and thinking about, you know, for the analysis workflows for visualization, let's make sure we really nail these one at a time as we move through the different industries. But from a performance standpoint, you know,

• 49:55Speaker 02

  the additional thing I'll add is there's a lot of really fantastic open source or even licensed tooling that's available for us to leverage. Right? And so, again, 10 years ago, if we were building this platform, everything would be from scratch. Right? There just was not. The level of performance in the openly available systems to go and integrate. But we can do our own sort of buy versus bill decision as we're looking in and saying, hey, we need to, you know, set up this particular functionality in our cloud stack or in Connect. Is there something out there that we can pull in and leverage and build upon ourselves? And so we're doing that and making sure that we're using these industry well-known, best-in-class tools to pull in.

• 50:36Speaker 02

  But then simultaneously, we're building an immense amount of custom code and, you know, just the nominal proprietary magic sauce. And a lot of that has to do with horizontal and vertical scalability. And if we bring in a system that works very well in isolation, we might need to do additional engineering work to ensure that we can scale it to meet either surge demand from one customer or the introduction of, you know, 10 times or 100 times more nominal customers over time. But then also just continuously testing our own stack, right? We don't want to wait for a customer to push an immense volume of data to us to discover that our ingestion or compute is insufficient.

• 51:16Speaker 02

  And so we're getting ahead of that ideally months in advance and doing synthetic testing of our stack, pushing representative data loads through it and just exercising it both discreetly as well as continuously as we're making code changes. So that we are not keeping up with our customers, but we are well ahead of where they are in their data scales. And generally, I think, you know, we've been very successful.

• 51:37Molly O'Shea?

  You're not secretly building nuclear reactors in the back just to test it?

• 51:42Speaker 02

  No comment.

• 51:42Molly O'Shea?

  No comment.

• 51:43Speaker 02

  Yeah, we do have a really wonderful hardware lab. We posted, I think, about it at some point, but we've bought all of this great data acquisition hardware, these different sensors. And so we have our own, we call Hiddle, hardware in the loop lab, where we are continuously streaming data into our platform from systems that are representative of what our customers are doing, which A is great for testing, but B is really valuable for our own engineers to kind of get hands on with a lot of this hardware.

• 52:09Molly O'Shea?

  So I do want to go into some case studies because I think this will be so fun actually applying it to some of your customers. Maybe if we could lay out three different kinds of industries and how nominal is being applied to those specific problems or solutions.

• 52:23Speaker 01

  Yeah, awesome. We, um, there's three, there's three great ones we can, we can talk about and have some public case studies on too, but we can dig even deeper here. I think one is, um, you know, aerospace, traditional, we talk a lot about flight testing, but, um, we, a customer we love and have worked with for a while now, Shield AI. Um, so we can dig in there. I think another one Stephen kind of referenced and you talk about, we're not building a nuclear reactor, but we're trying to help people. Um, and so a company we work with is Antares, um, which we love. And then a third one, um, we talked about kind of the multi-domain aspect, but, um, but Vatten Systems, um, builds, builds submarines, uh, small, uh, UUVs, near and dear to me, obviously. That was just a personal one that I love. But, um, no, I'll, I'll start by talking about, um,

• 53:07Speaker 01

  Shield for a bit and then Stephen, you can cover and we'll kind of go through. But, uh, yeah, this was, Shield was really exciting. It's been, um, it's been over a year now for the partnership. We came across at a really exciting time where they had actually just brought in a new, I think, then, you know, sort of VP of Hardware Engineering, but this gentleman by the name of Armor Harris, very well known, I think, in the SpaceX kind of community, but he's coming over from SpaceX. Um, I think he's now the Senior Vice President of Aircraft. So like all of the aircraft sort of development for, for Shield. But he came over, I think he had experienced like the vertical integration benefits that, that, you know, SpaceX had, had, um, had invested in. And so we hit him at a moment where he was coming in and, um, I think rethinking and thinking about

• 53:49Speaker 01

  how Shield was going to sort of move into this next moment for the VBAT, which is their vertical takeoff and landing, you know, drone, really awesome product. And I think Shield had sort of won some big and exciting contracts for themselves. And so they're thinking about, you know, how are we going to go through all of the testing, kind of Stephen's like Delta Quo, like how are you going to go through that, um, exercise as you produce new variations, new variants of, of this VBAT drone and trying to do as fast as possible. Um, it's been, it's been really exciting. You know, they nominal is sort of, I think, be Kind of the de facto piece of software for experimental flight tests, developmental flight tests, how they're going about iterating on the Vbat. And it's been really exciting to go from a mode where, I think, just given the sort of some of the software tools that were available to them,

• 54:34Speaker 01

  they were using a lot of Python scripts and MATLAB, and then sort of bridging into this world where you have nominal, where everything's really collaborative. And you can just get kind of cross-functional engineers that mechanisms or avionics or GNC or flight software, or even more just like mechanical engineers, access to flight data. That was just very arduous for them to kind of get access to before. And what that does from an organizational perspective is like, it just allows you to test faster. And so with them, it's been cool to work through. And this is very much, it's less the customer, it's like an actual kind of partnership. And they've been really awesome in pulling our product development forward.

• 55:18Speaker 01

  But the outcome we're able to deliver, like why I think they're, you know, been excited about nominal, is testing like more tests a day. And when you think about that from a six, nine, 12-month program development lifecycle, that's when you can take a step back and be like, what if, you know, using nominal and investing in nominal as an organization, instead of taking nine months to get through the development and validation, it was eight months or it was seven months. Like, what does that do to your top line and bottom line as a business like Shield? That's been really, yeah, that's been a really exciting one that we, yeah, we love the Shield team. It's been great. So you want to talk about, yeah, Antares and Man?

• 56:00Speaker 02

  Yeah. Antares was an early partner of nominal, one of our earliest customers. And I think, you know, they, as we do, saw the light very quickly that this was a tool that they wanted to put in place early. Right? And, and you know, we'll often hear folks arguing for, oh, well, you know, we'll wait a year, we'll wait six months. Rarely the right decisions. You want to get these platforms in place as soon as possible. And Antares, you know, took that bet and we rolled out the platform and have been kind of growing with them, which is very exciting. We had a fully functional and working product when we started with them, but as they're scaling their production of modular reactors, nuclear modular reactors, and we're scaling our product and introducing Connect, they've been this fantastic partner

• 56:45Speaker 02

  and really just a thought partner for building out features, getting feedback. And I think, you know, one of the major pieces is just the usability. And one of the hard things when you're hiring very quickly as a small company is as new folks are coming onboard, you need to onboard them to all of your systems. And for most engineers, right, those are analysis tools, data management tools. And one of the big values that we provide to all of our customers, but it's most apparent, I think, at these earlier stages is they're trying to get people in and being able to do analysis and deliver value as disciplined engineers as quickly as possible. And if you're spending two weeks learning about the tool chain and learning about where to find the right data, that is a ton of

• 57:28Speaker 02

  lost time when you're a 10-person or 20-person team. And so as we've seen their group growing, bringing folks into the platform and seeing our focus on usability really just kind of coming to fruition or manifesting here as they log in, they start doing work, maybe they have a, you know, a question or two and, and they're just going, right? There's no like onerous training thing that we have to go through as they bring in new folks. So it's been cool to kind of scale alongside of them. And like I said, they've just been really, really great partners. And then on the maritime side with Vatten, similar, you know, smaller firm scaling up. One of the things that was really interesting there

• 58:10Speaker 02

  was again, the speed that we were delivering value and doing that, you know, roughly six months after Antares, right? Antares was maybe a year ago and Vatten started eight months ago or so. And being able to integrate their data quickly, get those pipelines up in a matter of a few days, and they lifted and shifted their analysis workflows into our platform very, very fast and just kind of did this cut over. And it was a moment for me looking at this and realizing like, this is going to scale and we are breaking free of this world of A multi-week or multi-month implementation challenge that you see in a lot of other really heavyweight platforms. The other piece that was interesting with with Fattin, well, A, their product is awesome.

• 58:52Speaker 02

  And I got to go out to their facility and meet the team and go out on the boat, which was very cool. But what we're seeing, you know, maritime, nuclear, aerospace, is that we're not getting bombarded with a million different maritime-specific feature requests. Right? We're seeing a lot of commonality across these industries. Folks want the same answers. They want to have the same processes. And so in a very good way, right? They are using the product that we have built for everyone. And, you know, they'll, for example, Fattin came in and said, hey, we need to have bathymetric maps. When we're looking at our data, looking at the location of our assets, it doesn't, it's not very helpful to look at a satellite map of the ocean. We want to actually see the bathimetry and what are the, you know, contours of the earth underneath the water.

• 59:37Speaker 02

  And so that, you know, we went and built and rolled out and it's benefited our other maritime customers as well. So there's these little unique things that we need to do. But in general, the universality of the telemetry management analysis world has just been very exciting for us to to build upon and, yeah.

• 59:55Molly O'Shea?

  How much time and cost do you think you save your customers?

• 59:58Speaker 01

  Yeah, it's a good, it's a good question. We, you know, as the company's gotten more mature over the last three years, like I kind of think about, I'm saying like, there's like three value, you know, conversations that we get to have. One is often the easiest, which is, you know, a quote I'll often hear is like, oh yeah, we hired a really good software engineer to build, you know, our internal version of nominal. And then like, whoa, I didn't realize like two years passed and there's now like 15 people on that team. And so we hear that time and time again as companies, you know, scale. And it just like, there's a lot of overhead that goes into maintaining a productionized quality version of of something like nominal.

• 1:00:41Speaker 01

  I say like nominal because they won't, won't be as good. But, uh, but it's costly nonetheless. And so I think like, we can often have a conversation there, which is just like, how valuable is it for you to not have to? Staff up to four, five, six people.

• 1:00:54Molly O'Shea?

  It's like minimum a million in overhead.

• 1:00:56Speaker 01

  Yeah, exactly. Fully burdened, you know, engineering employee like, and so that is the value conversation we have for sure. I think like the next layer up is probably that sort of like incremental time savings. And so if you're, you can take a flight testing customer and you can say like, in a given day, you can test six times. When prior you were testing three times, like three times a day and often it's like these, this is a human. Sometimes it's literally like a bus full of humans that are bussing like three hours away to a test site or a test range. You know, performing test operations, like think about the salaries and all the ops overhead for like those humans.

• 1:01:35Speaker 01

  And when you like, the moment when they come back and realize like, oh, that one test like didn't actually get the data we needed to, or like those types of occurrences. So there's like all of that just efficiency spend of, we were living for folks often, you know, hearing things like, things that used to take 24 hours, taking like under 10 minutes. Right? And so like, when you stack up those processes in an individual engineering layer, like it used to take me 24 hours to just get, to look at this piece of data and now it's 10 minutes. And then I'll go back to like, the stuff that's exciting for me is then when you actually get to go to like a executive or a vice president and be like,

• 1:02:11Speaker 01

  what if you had confidence that you maybe could like beat your competition? Because you're moving faster on the like month time horizon. Or you could increase even incrementally by a small number of percentage points. The probability that your system is going to work when it needs to on a tight timeline. Those are, those are, I think, value discussions that are measured in the like percent of contract. And so if we go to a program and they say, hey, we just want a 10 or a 50 or a $300 million program. And nominal is able to sort of make the case that if you invest alongside us as a partner, you're, you're like, you're having like a very exciting, it's a value, value conversation at that point, so.

• 1:02:57Molly O'Shea?

  So you guys are creating immense efficiencies for your customers.

• 1:03:01Speaker 01

  Yeah.

• 1:03:02Molly O'Shea?

  We're in a rapidly changing AI world and environment. And alongside that, you're growing a company. So how do you manage innovation internally with these huge macro factors?

• 1:03:14Speaker 01

  Yeah, I mean, I'll give a, I'll kick it to you, Stephen, for some of the specifics, but like, I'll give, um, I think a general, like, philosophy that that we have at nominal for is like always thinking short, mid and long term. And a lot of companies say that, but like we, one of our core company values, um, is cultivate advantage. We talk about it all the time. And so I think we, you know, know in a nominal is, is, this isn't a quick adventure for anyone. Like we want to, we're building a generational company in this space and it takes time. And so I think we think and invest in long-termism whenever we have the opportunity to. So I think what that means is like, we look at this space of software for hardware broadly.

• 1:03:56Speaker 01

  I think it is one where, you know, AI has not yet taken a foot. And I honestly think it's going to be a little bit of time before it really does. There's a lot of, on the government side specifically, I think there's been a lot of like false goods that have been sold, predictive maintenance, prognostic, you know, type things that, um, when you actually get down to it, like the data, the telemetry and the sensor data and the logs, like it's so unstructured and so messy and so disorganized. That it's not really possible to actually, you know, do proper, you know, machine learning or just train inference in general on, on that data. So we see nominal as actually a necessary like stepping stone, um, there.

• 1:04:39Speaker 01

  Uh, and so I think like, you know, that's, that's a big area. But I do, I do get excited as I look at more, um, like agentic workflows. I think that's an area where, um, the workflow of like what an analyst or a test engineer goes through. I mean, Stephen has gone through this like thousands of times in his career, like looking at test data and going through that process. Like, I think there's a lot of power you actually can prompt humans with to help make their life easier. Once you sort of build this like, this space of like what it, what it's like to go through that, that workflow as a test engineer. So, um, I did say we're, we're far from being, um, anti-AI and we're actually, I think we're working on some exciting stuff there, but, um,

• 1:05:22Speaker 01

  we think that it's definitely a crawl, walk, run kind of process. You want to add anything?

• 1:05:27Speaker 02

  Yeah, I think you nailed it. The introduction of AI into a lot of these robotic systems is itself a market for us to be able to go and validate what a lot of people see as black boxes. And if you were to go on top of that and say, the nominal validation software is also leveraging AI to go and evaluate the AI-enabled robotic systems, you start to probably raise some eyebrows here. Like, at some point, you need the human

• 1:05:49Speaker 01

  It's become self-aware.

• 1:05:50Speaker 02

  The human tranche has to be doing the due diligence.

• 1:05:53Molly O'Shea?

  Testing itself.

• 1:05:54Speaker 01

  Yeah.

• 1:05:54Speaker 02

  Yeah. But there's good opportunities for us to bring that into our own platform, things like natural language queries, things like anomaly identification. And the latter, you know, to me, is more like the, it's like the Clippy paperclip in Microsoft Word, right? It's not doing it for you necessarily in the analysis workflow, but it's saying, hey, something looks odd here. You should go check it out. Here's why I think it looks odd. And then there's still a human in the loop to do that actual due diligence.

• 1:06:20Molly O'Shea?

  I'm curious, because you have such a wide set of customers, what exactly is your go-to-market strategy across them? And are you, you're dual-use, or?

• 1:06:29Speaker 01

  Yeah, yeah, we're definitely, we're definitely dual-use. Yeah, it's, on that point, in the dual-use nature, like, I think, we've been really excited, like, this, the exact same product serves commercial and federal customers. So there's like zero differentiation with either Core or Connect there. It's been a big, like, North Star of like, how do you not drive yourself crazy from a resourcing perspective? So like, the same product works there. The go-to-markets are totally different, obviously. And we, I think, have been fortunate to invest in just like a killer federal BD team, folks that are very experienced, like that scenario that I'm super passionate about and have a good, good depth of experience. And then on the commercial side, yeah, I think just getting folks that span the, you

• 1:07:14Speaker 01

  know, span the gamut of like, very technical sales. And so we have folks that have sold, you know, databasing technologies and like, they, they love the technical sell. And honestly, a lot of it, we see as like, be worried about the challenger sell. Like, a lot of it is sort of, hey, why, like, hey, you know, company that's doing this, like, why can't, why can't you do this better? Why can't you do this faster? But done, not in an antagonistic way, but done in a collaborative way. Like, there is a better way. Like, let's show you and let's work together to like, to get there. That opens a lot of the doors. And it's totally different, again, if you're serving a legacy prime, where, you know, it's, it's, how can you?

• 1:07:56Speaker 01

  Navigate 15 phone calls before you like get to a decision maker that has like some, you know, some input or some, you know, some authority. So you, you had anything in that? I think it's great. Yeah, I think like, um, it's, it's hard. Like we're setting up multiple go to markets uh, and kind of routines at once. But, um, you know, I think there's,

• 1:08:21Speaker 01

  there's nothing, uh, it's very simple. It, it all kind of boils down to, I think, like, pincer movement. That sounds very aggressive, but, um, I think it's just like building the, the technical alignment and base case with end users, uh, is like a thing you always have to do. And then, um, being able to have this sort of like executive level alignment over what would values actually being delivered, you know, if something like nominal is adopted, that is true across all of the instances. So, yeah.

• 1:08:49Molly O'Shea?

  I'd love to go deeper into the nominal team.

• 1:08:53Speaker 01

  Yeah.

• 1:08:53Molly O'Shea?

  You guys have attracted tremendous talent from really big names. So how many employees do you have?

• 1:09:00Speaker 01

  Yeah.

• 1:09:00Molly O'Shea?

  And where are they coming from?

• 1:09:02Speaker 01

  Yeah, right now we're, uh, we're about 60, a little over 60, growing pretty rapidly. Um, we are hiring. Check out, um, there's jobs on the website and they'll probably be posted in this thread as well.

• 1:09:13Molly O'Shea?

  What kind of jobs?

• 1:09:14Speaker 01

  Uh, we're hiring for, uh, pretty much, pretty much everything.

• 1:09:17Molly O'Shea?

  Everything, hiring for everything.

• 1:09:18Speaker 01

  Hiring for everything. A, a role that is like very, uh, we love and we cannot get enough of is mission operations. And so that's a, uh, for us, that means it's kind of like one third account manager for our, you know, for our, our customers, one third like product management. Um, and I think one third, like technical sales. Um, and so it's very exciting. We get, we have folks who came from robotics backgrounds, folks who did flight testing, you know, folks who were systems engineers at NASA and also just like love engaging and talking with customers and.

• 1:09:52Speaker 01

  On the pitch, I can say like, in a single day, you might be able to work with a company like Shield AI and Antares and Vatten, which is pretty sweet. You could be out on a boat, like cruising around with UUVs and looking at a new generation small, you know, small modular reactor and watching autonomous, you know, Vbat fly around. It's like, it's a pretty sick job. So we're hiring, we'll probably grow to, I'd say probably over 100 this year, this calendar year, to just meet, you know, meet customer demand. And yeah, I think like the secret, the secret sauce or a lot of what we think about is so much of nominal or really world-class software engineers from diverse backgrounds. And then there's this perfect ratio of the like Steven

• 1:10:37Speaker 01

  archetype, to someone who spent a lot of time operating hardware. Because the beauty comes, and we talked about, we have this little like hardware lab, like the beauty comes when you can expose these amazing software engineers to the like, the brutal world of where software meets hardware. And just people who've done it, who've been at, you know, disconnected environments, at test ranges all over the world. And so that's been like a big part of the nominal culture is like getting all those folks under, under, under one roof. But yeah, it's, team is a big, a big thing. And I think it's, it's definitely one of the things like I personally am most, most proud of it, of what we've assembled at nominal. And it's just, it's just getting started, so.

• 1:11:20Molly O'Shea?

  What about the existing team? Any shout outs?

• 1:11:22Speaker 01

  Oof, I feel like I've given, you know, Steven a shout outs, but yeah, Steven, you want to give some?

• 1:11:30Speaker 02

  I think, you know, I reflect back on some of the initial folks that I met who are all still at nominal and, you know, in very senior positions now, leading the team, these really fantastic engineers from Palantir, Helen, Mark, Ross, Andrew, just this great initial cohort of absolute hitters. When you talk about talent, I mean, there's like the real recognizes real moment when people come in and they, they meet these folks and.

• 1:11:58Speaker 02

  Them having spent between five years and a decade dealing with really complex data problems has just been absolutely immensely valuable for us. And then we're supplementing those backgrounds with folks from a dozen other different industries, two dozen different companies, and you get this really great mishmash of different lenses into these problems. And so I think about our folks from Applied Intuition, Nick and Drake, coming from the autonomy side, from a very customer-focused lens, excellent engineers. Michael from Relativity Space, standing up his own data architectures there. So it continues to floor me that every

• 1:12:40Speaker 02

  new person we bring in is just up-leveling us in a new way, bringing new talents, and it's just an incredibly smart and a team that just works together very well. It's very, it's very easy to interact between sales and product and design and C-suite. There's a lot of transparency across the org. I think people even see that in the interview process when they come in. So.

• 1:13:03Speaker 01

  I'll give a couple, I'll give a couple more, because I'll have even chats. I'll give a shout out to Joe, Joe Holiday, who's our Head of Mission. So he leads the Mission Operations Team. Joe's phenomenal. Shout out, Joe. Shout out, Joe. Yeah, Joe, you know, was a Palantir for a little over seven years and sort of led a lot of the commercial pilot efforts there. And so if there's like a place, there's a dojo that you would have wanted to train in, in terms of like big, high-stakes, complex deployments of software, Joe has done that at scale. And so is able to, it's just a symphony watching him like work with our customers and get them value

• 1:13:42Speaker 01

  nominal like rapidly. And then Jen, shout out Jen. We have a very, often sometimes when I contextualize the federal side of the business and like the federal footprint, people are like, wait, where's the other 10 people? Just given the results, I think we've been able to deliver with a very, very small team. Jen is like almost a one-woman show there. And she's been amazing in, in leading a lot of the DOD efforts. So no, we, we have an amazing, amazing team and we're looking to really double down as we grow.

• 1:14:18Molly O'Shea?

  Love the shout outs. Very necessary.

• 1:14:20Speaker 01

  If you, I could just shout out to the whole company, it'd be, but um, we'd be like, what?

• 1:14:25Molly O'Shea?

  Well, we'll keep it. We'll keep it at that.

• 1:14:28Speaker 01

  We'll keep it brief.

• 1:14:29Molly O'Shea?

  But all of these team members have helped you build an incredible product, scale, and then also raise over a hundred million dollars in total from some of the biggest names in Silicon Valley.

• 1:14:42Speaker 01

  Yeah.

• 1:14:42Molly O'Shea?

  Sequoia, Lightspeed, General Catalyst, Founders Fund, the list goes on. What have you learned from your fundraises to date? And how do you think about milestones going forward?

• 1:14:55Speaker 01

  Yeah, I think, um, no, it's a really good, uh, it's a really good question. Obviously, this, we, we started at the beginning, like this fundraiser happened quickly, you know, 10 days kind of from start to finish. I think one thing that, like a new learning, um, going through that process was we, we have a pretty killer, uh, you know, team and we, we were putting together these like very comprehensive response memos. You get a lot of RFIs, you get a lot of like questions, you can tell when an investor is like really serious and digging in. And we almost, it almost became like a game. Um, we're very serious about it, but like we would put together 10 page responses overnight. Just.

• 1:15:36Molly O'Shea?

  That's amazing.

• 1:15:37Speaker 01

  Yeah. And it's like, it should, I mean, I think it should, I think if you're an investor, and I've been an investor on the luck side, like it shows that that person's serious. And I think being able to have this like trove of information that you can sort of expose to people, I think was, was one. We were, you know, you have to be always careful, like customers, our customers are busy. Um, and so you want to like protect, ruthlessly protect their time. But I think the willingness we showed also to get our customers on the phone, like I would always just be like, you should just talk to one of our customers. Like it will make sense to you. Um, if you do that, I think that, um, willingness, sometimes when people are going through this process, like they're kind of like, don't want people to talk to their customers. I'm sure I'd be like scratching your head and being like, I wonder why.

• 1:16:19Speaker 01

  We were just like, please let me get you on the phone with our customers because it will all make sense after that. Um, I think is a big one. And then, um, yeah, maybe we're just more general. The thoughts here is, uh, you.

• 1:16:33Speaker 01

  You want to give, they want to give investors data points that they can make sense of. Like, they're going to be investing, you know, this is Sequoia led this round. It's the growth team. They're investing in growth, right? And so you need to give them some data points and they will infer, is the slope here? Is the slope here? And so just making sure that you're having those conversations before it comes prime time for a financing, so that they know like, oh, wow, this team says they're going to do something and they will, I love the base episodes, I'm going to make a reference to violently execute. I think that was it. Yeah. Can this team violently execute? And just like go do the things they're going to say they could do. So, yeah, I think those would be the three, the three takeaways.

• 1:17:16Molly O'Shea?

  Violent execution.

• 1:17:17Speaker 01

  Violent execution.

• 1:17:18Molly O'Shea?

  Setting the gold standard.

• 1:17:19Speaker 01

  Yeah, I love it.

• 1:17:21Molly O'Shea?

  That's great. So just a couple of questions left. First, I want to know, where do you see nominal in the next five years? What's your future outlook?

• 1:17:31Speaker 01

  Yeah. I mean, right, right now, I think with this, this new, you know, pot of capital, we're focused on, you know, a handful of things immediately. I think kind of four of those to talk through, but one of those is like really expanding more and more into these larger enterprises. And to do that at scale requires a large team. It requires a lot of focus. And so we have a lot of really good traction with some more of these legacy prime providers, and we're going to move really fast to scale there. I love this headline, you know, and I worked at Applied Intuition. They had this incredible slogan that I think it was just, you know, 18 of the top 20 automotive

• 1:18:13Speaker 01

  OEMs in their case, you know, trusted Applied Intuition, used Applied Intuition, like crazy stat, they literally had 18 in the top 20. And so I want, like, where we want for nominal is like, I want that to be the case in certainly the big five, you know, primes, but the same 18 in the top 20, I want 20 in the top 20, but you get the point. To be loving nominal and to be using it and to be sort of ubiquitous with what it is to, to test in a modern manner and field hardware in a modern manner. So expanding to the enterprise, a thing that we're really excited about is, we talk a lot about, you know, the US lens here, but this is a global opportunity massively. We have international customers today.

• 1:18:53Speaker 01

  Like, we have successfully sort of done that motion, and so we're excited to double down and expand internationally. That looks like nominal offices overseas and just saying yes to more and more customers, which is really exciting. A big thing, we talked about core and connect, but to win really big here, nominal is a multi-product, multi-product business and multi-product strategy. We're keeping tight on a couple of those. But you'll be hearing more, you know, more about them as the year unfolds. But delivering five, six, seven, eight products that all work together in this sort of hardware testing and operations domain,

• 1:19:35Speaker 01

  I think has been really exciting. And then I, you know, I give a shout out to Jen on our team, the one woman DOD show. Like, we're going to be expanding and doubling down on the federal side. Like, we've been really lean there, and frankly, the ROI has been really, really high, but we're bullish on a lot of those trends. And so we're going to be staffing up, opening a formal DC office later this year and really just building out, you know, that team. That is certainly what we're thinking about in the next, you know, 12, 15, 18 months. And then I think where, yeah, where nominal goes on a five, you know, the five-year time horizon, I think is just becoming a, I always say, like, the North Star for us is when

• 1:20:20Speaker 01

  a hardware engineer, generally speaking, someone says, like, what is it that you do? Like, what is your job? Their friend might visit them and be like, what do you do all day? They would open up nominal. And that's like the thing, that's the vessel that they would use to explain, like, oh, this is like what it is to be a hardware engineer. Like, I have to fuse all of these data sources from my machine. I have to, you know, visualize them and like... Tons of it's automated, but there's some things I still am an expert in, so I need to like, double check or explore this data. And then I like build these, these rules and validation logic that governs this, my hardware system when I deploy it like that's, that's the North Star for us. Um, and so we will just be building towards that vision.

• 1:21:02Molly O'Shea?

  Well, to close out, one final question, I want to bring you back to your roots. And this, you both can answer this, but this is a, this is a very hard question. All right, I'm setting the stage.

• 1:21:14Speaker 01

  Okay.

• 1:21:14Molly O'Shea?

  You're in the Mediterranean, there's a severe storm. You're trapped on a very large yacht, okay? Maybe the rogue wave comes by, what do you do? Do you take a helicopter or do you take a submarine?

• 1:21:30Speaker 01

  When you said the Mediterranean piece, I now I have this like, is it Wolf of Wall Street? Is that the, when the, I'm thinking of like Wolf of Wall Street. I feel like you like, um, would I take a helicopter or a submarine? I've been, I'd say I've been on a submarine a lot. So my inclination would be to take a helicopter, but you said it's stormy. And so submarine fun fact included, uh, when you're on a submarine, very deep underwater, you generally have no idea that it is stormy. Uh, and so it's very calm with the exception, this is a double fun fact.

• 1:22:13Speaker 01

  Um, because I've done this and submarine people have as well, but, uh, if you are in a submarine underneath like a hurricane, uh, you can actually feel the swells down to like hundreds of feet deep.

• 1:22:26Molly O'Shea?

  Have you experienced that?

• 1:22:27Speaker 01

  Yeah, yeah. Normally when there's like a hurricane, I was stationed in Norfolk, so I was on the East Coast, like hurricanes come and they like sound the alarm bell and like the safest place for a submarine to be is not in the pier, it's out in the ocean. Um, and so you like scramble and get ready and you go out and you go deep. Um, but just showing how powerful hurricanes are, like you can, you're still jostling around at like 500, 500 feet underneath, whatever. So, um, it's pretty wild, but.

• 1:22:50Molly O'Shea?

  That's crazy.

• 1:22:51Speaker 01

  That's a long-winded answer, but, um, I think I would, I think I would take a submarine. But I want to hear what Stephen has to say about this.

• 1:22:56Speaker 02

  I think I'm switching my answer because originally I was team submarine, but I'm considering that first I have to get onto this rescue vessel and the odds, I've never been described as sure-footed, like the odds that I will make it. Onto the surface of the submarine and not just like slip off and disappear into the deep.

• 1:23:13Speaker 01

  That was Steven.

• 1:23:14Speaker 02

  Yeah, yeah, I'll be gone like I'll be gone in an instant. And so I'm going to take the easier, you know, hop into the basket of the helicopter.

• 1:23:23Speaker 01

  Yep.

• 1:23:23Speaker 02

  And then I'll probably go down 30 minutes later in a blaze of glory.

• 1:23:27Speaker 01

  It's very morbid answers we have to.

• 1:23:29Molly O'Shea?

  I would hope not.

• 1:23:30Speaker 01

  Yeah.

• 1:23:30Molly O'Shea?

  Cause you're getting rescued.

• 1:23:32Speaker 01

  Yeah.

• 1:23:32Molly O'Shea?

  Wait, okay, so going back to your job as a submarine officer, could you just explain that a little bit further?

• 1:23:37Speaker 01

  Sure.

• 1:23:38Molly O'Shea?

  We skipped a lot of details there.

• 1:23:39Speaker 01

  Yeah, we skipped a lot of details. Um, yeah, I first part of my career as a submarine officer. So what does that mean? Um, was there really did two major jobs and, and almost all submarine officers start as an engineering officer. So the, the day to day is operating the nuclear reactor, provides propulsion for, for the submarine. Um, when I say operating as an officer, you're not actually touching the things as much as you are, um, comprehensively sort of managing the state of the reactor plant and giving orders and receiving information. So telling, um, others how to, how to, to operate. Um, that's what I did, uh, in the sort of engineering side for, for a while.

• 1:24:22Speaker 01

  And then the other job I had is I was our kind of assistant weapons officer. So after you've done the engineering for a bit, you go forward is what it's called, but it's literally like forward half of the submarine, the back half's engineering, the forward half is operations and weapons and tactics. Uh, and then I was a weapons officer, so, um, torpedoes, mines, uh, tomahawk missiles, et cetera. But just having visibility over all of that, if we needed to use them, thankfully we, my submarine did not, um, did not ever use them. But that's a lot of the job. Um, submarines do a lot of what's called ISR, intelligence, surveillance, reconnaissance.

• 1:25:01Speaker 01

  So the mission set is mostly being places where others don't know you're there because you're very quiet and very sneaky and collecting useful pieces of information that others don't think that you're collecting. Um, that the, in this case, the, the US can use to, to get an advantage.

• 1:25:20Molly O'Shea?

  So many questions. How long have you been under the water for?

• 1:25:23Speaker 01

  Hmm. I always, I say this and then people are like, what? Um, I've been underwater 484 days, not consecutively, which most people, see, you were, you did it too.

• 1:25:32Molly O'Shea?

  Um, it's still impressive.

• 1:25:33Speaker 01

  No, no, it is. Um, yeah, thank goodness. Not, not consecutive. That's my total like underway time. Um, but longest consecutively was 84 days, uh, which is still a long time.

• 1:25:43Molly O'Shea?

  Very long.

• 1:25:44Speaker 01

  Yeah. And most people don't really realize like you, you generally don't communicate when you're, um, under. So, uh, you know, you learn things like if you don't get an internet sync with Spotify after 30 days, it just, all of the songs that you thought you downloaded are not actually downloaded. They go away. Like you learn these little, little tips and tricks that, um, so it, it becomes very sad after a while when you have no internet connectivity and no, you know, comms with the outside world, but.

• 1:26:14Molly O'Shea?

  Gotta bring a cassette tape.

• 1:26:15Speaker 01

  Yeah. Gotta go.

• 1:26:17Molly O'Shea?

  Did you see any monsters? Did you see any large squids?

• 1:26:21Speaker 01

  Uh, I did not see any large squids, but you actually do hear a lot of things. So you hear whales, um, you hear dolphins, you hear shrimp, like you, submarines, all, it's all sonar based. And so you do hear a lot of sea creatures. Um, and normally it's like fun because you're like, oh, it's like, it's a whale or it's whatever, but it can get, they're very loud. And you're, you might be trying to listen to like another submarine or a ship or something that you need to, and you're kind of like. UFOs. Yeah. Um, you like Pacific Rim, I'm thinking of Pacific Rim. Um, and, uh, you may be trying to listen to stuff that's like productive and then you're like, these animals are like so loud. Um, because you can't hear what you mean to. Yeah. Yeah, exactly. Yeah.

• 1:27:04Molly O'Shea?

  Okay. Well, I've, I've taken up a lot of your time and I very much appreciate it. Congratulations on your 75 million dollar series B. Massive. And thank you so much.

• 1:27:16Speaker 01

  Thank you, Molly. It was awesome to be here. We loved it. Thanks, Molly. This is great.

• 1:27:20Molly O'Shea?

  You're welcome.

• 1:27:20Speaker 01

  Thank you.

• 1:27:21Molly O'Shea?

  Hey, it's Molly. If you enjoy our interviews, check out our newsletter sorcery.vc, where we deliver a once a week top deals and tech headlines email and also go deeper on our podcast interviews. Subscribe to sorcery today and don't forget to subscribe to the podcast on YouTube, Spotify, Apple, or wherever you listen. Link in description to sign up.