Interviewee
For today's agenda we have Anthony DiMare, Co-Founder and CEO of Bedrock, a company that develops autonomous underwater vehicles in order to explore, map, and classify the ocean floor in a much more efficient (also affordable) way than the traditional “big ship with a big sonar” method.
He considers himself a NYC-based product & sales-focused entrepreneur. Anthony loves challenging problems where new technology can be built to create dramatically different outcomes than humanity had seen before.
Transcript
Anthony DiMare: Excited to be here, pumped to talk about robots and sea floor data and whatever you want to!
So my name's Anthony DiMare, I am the CEO and co-founder of Bedrock. I have a super nonlinear journey. I started off as a Mechanical engineer. I worked in medical devices. Then in consumer electronics, I was the first engineer at two different startups before starting an additional company before this named Nautilus Labs, that company was a maritime software data optimization platform for commercial ships at sea. And the whole goal was to build a cloud platform to bring disparate data sets from commercial ships, market information, different things that were happening on land to try and help optimize what a ship should be doing on the ocean to ideally save on or reduce fuel emissions while increasing profits for different ship owners.
So I left that company in 2018 and got the opportunity to call up one of my old friends, Charles Chow. Who's now the CTO and co-founder of bedrock who had, you know, had 15 plus years of robotics experience. We got introduced.
We got introduced by an investor that said, “You know, you two are both ridiculously obsessed with the ocean in weird ways and you should just meet each other. And you know, Anthony, you're doing data stuff and he's doing autonomous robotics and has worked on submarines.” And so I called him up and, you know, said someone needs to solve this whole ocean exploration problem. Like we had a bunch of space companies at the time. This was like 2010 or 2018, early 2019.
And we looked at the unit economics of that and realized that there were some pretty great things. There's a lot of money to be made if you do it well. And a lot of technology would have to be built, but nothing that hadn't already been sort of figured out in other spaces. And we just needed to sort of put it together to make that possible for the ocean, and then worked our way back down to kind of what we have today, which is a, which is a data company.
Elisa Muñoz: Talking about Sea floor exploration, it's kind of like a new field because most of the people are focused on space. So how hard was it in order to build up another company related to this topic?
Anthony DiMare: It's hard, yeah. I mean, so building a company is hard. Building a hardware company is really hard. And then building a hardware company that also has to operate in the ocean is much harder. Because no one is actually there. There's no rocket companies and some people have done that. No one has built a pervasive ocean exploration ocean mapping system yet, even the government doesn't have something like this. So this is like complete white space. So we don't really know how hard it's going to really be.
Elisa Muñoz: But like at the beginning, I think people normally wouldn't consider putting money into this kind of project. How did you get investors at the beginning?
Anthony DiMare: So we raised about 8 million in our seed and we, we looked for people that were looking for contrarian bets, who I think were, you know, I don't actually think it's that crazy when you look at, you know, right now in today's world, people pay about $7 billion a year for surveys. That is the size of the rocket launch industry. Right? And we've invested billions and billions and billions of dollars into the rocket launch industry right now, maybe that industry is growing, but it's growing, you know, at X number, it's an x-ray right. Ocean is just like starting, right?
Like we are just beginning what I think many are looking at as a complete infrastructure revamp of everything we have on land. And a good portion of that now is including just supplemental infrastructure in the ocean. And the reason for that in general has mostly to do with we're running out of land, around our metropolitan areas. And most of our metropolitan areas are close to the ocean where we have lots of land or lots of space. And so what we're seeing is actually this sort of new nascent shift, where even if we don't ever change the way people buy or consume seafloor data, like we're in a very new nascent space.
At the time I don't think the picture was actually that different. It was just, you know, it was Charlie and I, we had built this big system in a spreadsheet and we had said, “You know, look, look at this. This is what we think needs to happen. And here's how we're going to start. And here's the kind of systems that we need to figure out. We need to solve the acquisition problem. Someone's got to build a better way to move sonars around the ocean period”.
Elisa Muñoz: It's super new. It's refreshing. But, how are you dropping the prices down? Because I imagine that this whole process, since it's really long, you said like six to twelve months, depending on the client, like how, how expensive it is?
“Just pull up any Wall Street Journal, any New York Times, any Economist and open to any page. You'll find some problem that probably is worth, you know, a ton of money to solve. We need more people trying to solve those problems. We're in like a golden age of anything that has an intersection or a vertical component, a vertically integrated component around hardware, autonomy and software data”.
Anthony DiMare: Yeah. I'm going to go from like the, I'll sort of explain the process now and we'll start there. And then I'll, I'll sort of explain how we work and you'll sort of start to probably understand. So the cost benefits and acceleration of timelines, all this stuff, right? So right now you've got this terrible permitting process that you gotta go through. It's about six months and then you gotta put out an RFP. So, so you gotta go to all the surveyors out there and say, listen, we're going to do a survey. Here's the area. Here's the specs that we want.
Here are the deliverables. And then everyone creates a month. They basically have two months to create a proposal. They do the proposal, the company picks a survey company. Then they get to move the ship from the, you know, you get a contract, you've got to move the ship from wherever the hell it is in the world. Sometimes it takes a month or two to get the ship, you know, maybe it's in Brazil and they're like, cool. We want to serve in the United States. And they're like, all right, well, it's going to take a month for the ship to get there. So yeah, we'll do it, we'll start the survey in a month. So the ship sort of takes its time, goes up sales up to the new offshore wind area and the United States, South Dakota, New Mexico, whatever it is, right. They get to the site.
Then they have to do all kinds of HSC checks. They have to get all the crew on board. So there's like anywhere between 40 to 60 people on board, each of these ships at any given point in time needed to both operate the ship, operate all the sensors, make sure everything's being collected correctly, do the processing overnight check and make sure they're not running into any Marine mammals. So whales, dolphins, sea turtles, anything like that.
There's really strict regulations, at least in U S waters around protecting the creatures, right? And the areas where we're building all of this new infrastructure is in these Marine protected animal areas. Those are very important to be able to basically make sure you're not doing damage to those animals. And so you have to keep watch and it takes you, you know, then you have bad weather days. So, you know, God forbid, you've got a storm that comes through all of a sudden, like, you can imagine, you know, this is your ship. And imagine that your cameras are the sonars on the bottom. Like when the ship is doing this, like you're not collecting goods.
It's just bad. It's just bad data. Right. So you can't use it. So you just have to sit there and wait. So sometimes you'll just sit there and wait for a couple days a week. And generally you assume about 30% ish of bad weather days. So 30% of the time, you're just like sitting out there. It costs about 200 K a day to run one of these ships. So you do the math and then, and, and that's now you've just collected the data. Now you have to clean it, process it with a geo geophysicist, have to look at it all, interpret it, put all these different data sets that you collected together.
Then it has to go to an environmental review company that has to go to an archeological review company. And it has to go to the government for a stamp of approval. And then finally it gets to, to the client, who's an engineer who can say, okay, I'm going to put, I think I can put an offshore wind turbine right here. And then they got to do that every single year. And so it's about a 12 month process to go from. I want data to, I have data. And so that's how it works today.
Bedrock, we don't have to go through the printing process because of the sonars that we have on our particular AVS. So that already just gets rid of that whole upfront sort of issue in general, we're much more environmentally friendly. We don't hurt Marine mammals. It's all electric. It's a totally different sort of operational profile. The vehicles themselves are about, you know, they're seven feet long. They weigh a little over a hundred pounds. They break up into two, you can fly them anywhere in the world, overnight air like that. There's no waiting time. We can use traditional shipping methods to get all of our survey equipment anywhere you'd like. So just already upfront, you've just saved. You know, that's like eight, that's like six months just, you know, gone.
Elisa Muñoz: You mentioned challenges, right? What do you think is the biggest technical challenge you have solved since you started Bedrock?
Anthony DiMare: Ooh, I wouldn't say that I've solved. I would say that the team has solved.. And I would say like the way, the reason I'm having a hard time answering is that we started with, we started the company, assuming that we would be able to have like a good chunk of the vehicle, be commercial off the shelf. And we would have to do a couple of things that were core technology developments that would be needed, but we can operate with a bunch of different systems. And it turns out like, as we started to integrate those systems, as we started to test those systems, like, we literally just kept pulling a commercial off the shelf system off and it would have to go figure out how to go build it ourselves. So I'm like a battery, for example, like we bought one and it didn't work the way we wanted it to. And so we had to build our own.
The propulsion system started with something off the shelf that didn't work. And so like, it just literally didn't work. And so we were like, good, try to buy another one or we could just build our own. So we ended up building our own, which is why you see, you know, an exfil configuration with two thrusters. Like that's all now customized. Right. And that's got its own sort of power management system and control system all on all itself. And then you look at the antenna and we tried to buy an antenna that doesn't have all the different radio frequencies. We want the way we want them. And, you know, we couldn't tune them in. So we ended up having to like, oh shit, okay. Like, I guess we gotta build our own.
Being able to then incorporate all of those new technologies together in one integrated system, while also having it be something that can be flown everywhere, easily serviceable, since we own an operator on fleet, we actually are the con, we are the customer of our own robotics, like our own robotics development. We are the users of our own robot. We are not, we don't sell our robot. You don't, you know, no one else can buy it. So it's in our best interest to make it as easy to operate as humanly possible. But that's a whole nother layer of difficulty of, you know, sometimes you would say a design is easiest this way.
And so you layer in all of that. And I don't know which one is hardest. I don't know which of those is hardest. And then that's not even talking about the technical cloud problem where.
Elisa Muñoz: Last but not least, do you have any advice for future entrepreneurs or people in the industry, for the future engineers who are listening to this podcast?
Anthony DiMare: Yeah, I do, work on hard real problems. Like we have really, we have way too many hard, challenging, absolutely must solve problems that have far too few people working on them. And, I even mean this is like a rallying cry around, like, we need the smartest people. We need anyone that has any like deep passion or interest in anything that has to do with like solving, you know, whether it be a sustainability solutions, whether it be rearchitecting old systems, whether it be, you know, I mean, you could look across the board, just pull up any wall street journal, any New York times, any economist and open to any page.
And you'll find some problem that probably is worth, you know, a ton of money to solve. We need more people trying to solve those problems. And, and so I think it's, I think we're in like a golden age of anything that has an intersection or a vertical component, a vertically integrated component around hardware, autonomy, software data, right. Like there's a lot of really interesting stuff there. So just start working or learning about those spaces. And I think, you know, you'll find really interesting things and maybe not the most popular thing at first, like everyone, you know, no one understood why, you know, the ocean.
Elisa Muñoz: Amazing. Thank you so much Anthony. This was amazing. Thank you so much for taking the time to be in the Podcast, it was a pleasure!
Anthony DiMare: Thank you, Elisa so much. This was fun. Hope you have an awesome day.
