This Week in Startups - It’s a boat, it’s a plane, it’s REGENT’s Seafarer | E2205

Episode Date: November 8, 2025

Register for Founder University Japan’s Kickoff: https://luma.com/cm0x90mkToday’s show:*The key to avoiding long airport delays? Low-altitude sea planes! Why didn’t you think of that?We’ve got an awesome line-up of TWiST 500 founders giving us an inside glimpse inside their startups on this Friday special edition.FIRST: Billy Thalheimer of REGENT introduces us to their aircraft/boat hybrid The Seaglider, and walk us through how it all works, AND why they’re operating in BOTH the commercial and defense sectors from their Rhode Island HQ.THEN, we’ve got Convexia co-founder Ayaan Parekh showcasing how they’re using a collective of specialist AI agents to exploit other pharma labs’ leftovers and turn them into new drugs and treatments for rare diseases.FINALLY, Hunter Leath of Archil joins the show to tell us why efficient utilization of cloud data remains a surprisingly complex, and unsolved problem. His solution? Caching-as-a-Service! Find out how it all works, and why pre-caching is SO difficult to do, in this TWiST exclusive chat.Timestamps:(03:01) Billy Thalheimer of REGENT introduces us to the Seaglider(05:06) Inside the EV aircraft/boat hybrid’s three modes of operation(08:22) How REGENT uses low altitude flight to avoid airport-related hassles(9:42) Sentry - New users get 3 months free of the Business plan (covers 150k errors). Go to ⁠http://sentry.io/twist⁠ and use code TWIST(13:57) The converging tech that makes Seaglider possible(18:20) How REGENT is operating in BOTH the commercial and defense sectors(19:39) LinkedIn Ads - Start converting your B2B audience into high quality leads today. Launch your first campaign and get $250 FREE when you spend at least $250. Go to ⁠http://linkedin.com/thisweekinstartups⁠ to claim your credit.(25:05) Why Rhode Island?!(29:23) Pipedrive - Bring your entire sales process into one elegant space. Get started with a 30 day free trial at ⁠https://pipedrive.com/twist⁠(31:04) Convexia co-founder Ayan Parekh joins Alex to discuss “the world’s first AI-maximalist pharmaceutical company”(33:02) Using AI agents to revisit leftover bio IP and unused data(33:22) Why so many drugs fail to reach market(35:46) Applying different agents to different kinds of tasks(44:26) The unique opportunities posed by rare diseases(46:58) On the road toward vertical integration(50:48) Hunter Leath of Archil tells us why utilizing cloud data effectively remains a complex, unsolved problem(51:56) What is “Caching as a Service”?(55:53) Why pre-caching is NOT obvious and “tremendously difficult to do”(57:00) Why the major cloud players didn’t built this themselves(01:00:37) Deliberately keeping the focus narrow… for now…Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:Sentry - New users get 3 months free of the Business plan (covers 150k errors). Go to http://sentry.io/twist and use code TWISTLinkedIn Ads - Start converting your B2B audience into high quality leads today. Launch your first campaign and get $250 FREE when you spend at least $250. Go to http://linkedin.com/thisweekinstartups to claim your credit.Pipedrive - Bring your entire sales process into one elegant space. Get started with a 30 day free trial at https://pipedrive.com/twistCheck out Jason’s suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.com

So how do you manage to have a thing that flies and doesn't use airports? It feels like you've hacked the system. We are creating a fundamentally new vehicle. It goes fast. It flies low. It's sort of operating in this different way. Sea gliders are sort of hybrids of boats and planes, sort of use the best of both worlds. We'll go from Providence here to New York.

That's about 180 miles. We can do that on battery technology. So you're going to board right next to the city center. We don't need to travel to an airport. It's floating at the dock like a boat. then we're going to hydrofoil through the harbor or through the bay. We're going up to about 50 miles an hour on those hydrofoils to maneuver through the crowded waterways. We take off from those foils, so it's float, foil, fly.

This is exactly what I was hoping to get because I do go to New York and currently takes three to half, four hours on Amtrak when the trains are on time, which just seems archaic in the extreme and unimproved since like 1860. Technical hard part of what we're doing and why we can only do this now with electric propulsion and digital flight control systems. Where are we? In terms of progress. This week in startups is brought to you by PipeDrive.

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And Century. Your team should be focused on shipping features, not chasing down bugs. New users get three months free of the business plan, which covers 150,000 errors. Go to century.io slash twist and use the code twist. Welcome to This Weekend Startups. This is Alex. It is Friday, November 7th, 2025, and we have three awesome interviews for you. That means three Twist 500 startups, three founders, and three chances to learn from some of the best out there today.

First up on the show, Regent. It's a Rhode Island-based electric boat, hydrofoil, airplane startup that could shake up both how people commute today and also play in the rising startup defense market. I love this company. Then Convexia, a self-titled AI Maximilus Pharma company. It wants to mine IP and bring drugs to market that may be overlooked with a commercialization twist. in the near term that I absolutely love. It's brilliant. Then to close off, Arkill, they're building a tool that helps developers interact with cloud data as if it was local, something that matters quite a lot in the AI era because companies really want to bring their

own proprietary data to bear, but may not have it on site. I learned a lot. I hope you do two. Three interviews. Let's start with Regent now. Here in the U.S., trains are a joke, ferries are under capacity, and our airports are creaking because there's too many people that want to get around. Essentially, we have cars or very little else. But there is a company called Regent that wants to make electric sea gliders that are going to take us around the coastal regions quickly and safely. I'm excited about this because I want to use it. So please join me and welcoming to the show. It's Regents Billy Tallheimer. Billy. Alex, good to be here. I'm so happy that you're here because I never get to make Nish, Rhode Island jokes in the pre-show. So thank you for

showing up. But first, let's talk about the technology here. This is not a seaplane. This is not and a hydrofoil, you guys are Regent are building something that is kind of in between them using wing and ground effect. So for the folks out there are not in aerospace, what the hell is that? And why do you like it? Yeah, well, definitely next time we're going to have to do the show in person. We'll just walk right down the road and shoot in person. We'll do it from a sea glider. Sold. Regent builds sea gliders, as you mentioned. Sea gliders are sort of hybrids of boats and planes, sort of use the best of both worlds. As you mentioned, the technical part is we are a hydrofoiling wing and ground craft. There's a lot there. What does that mean? We are wave

tolerant and super efficient. So sea gliders use hydrofoils to rise up out of the water, giving us very high wave tolerance, therefore high utilization. You can rely on sea gliders. They operate in all weather conditions, up to five foot waves, which is basically a hurricane. And then when we do fly, we fly on this cushion of air over the surface of the water called the ground effect. sort of think about it as compressed air under the wing between the wing and the water. Same thing that you see birds flying on when they're flying low over the surface of the water. It makes it very aerodynamically efficient for us to fly. And that allows us to get very long range on battery technology, 180 miles on our battery electric version.

So overall, there are a lot there. We float, foil, and fly. We operate in all three modes. Okay. So I presume that I start floating at rest. and then I'm foiling at middle speeds, perhaps, and then I'm flying a couple of feet, I think, off the ground, or off the sea, I suppose, at peak speed.

That's exactly right. We'll go from Providence here to New York. That's about 180 miles. We can do that on battery technology. So you're going to board right next to the city center. We don't need to travel to an airport. It's floating at the dock like a boat. Then we're going to hydrofoil through the harbor or through the bay.

We're going up to about 50 miles an hour on those hydrofoils. We're using technology from America's Cup and SailGP, you know, these advanced racing yachting worlds to maneuver through the crowded waterways. We take off from those foils, so it's float, foil, fly. Take off in the air, we actually retract the foils. So it's like take off gear instead of landing gear and then we fly on that cushion of air. We'll be about 30 feet over the surface of the water. That's not very high at all. That seems actually quite pleasant. Yeah, it's pleasant. It's high enough that the waves aren't a huge issue. So again, we want to be able to to take off and operate in, you know, a wide range of weather conditions, low enough where we still

get that compressed air effect so we get the long range. We'll fly 30 feet over the water, zip on down to New York. We'll be there in about an hour and the ticket price is less than $100. So we're talking about like high speed rail and every coastline on the planet. That's why I started out with public transit because it turns out that building high speed rail in the U.S. is impossible because we have a multi-stakeholder form of governance and landownership. and that's tricky. But this is exactly what I was hoping to get because I do go to New York

and currently takes three to half, four hours on Amtrak when the trains are on time, which just seems archaic in the extreme and unimproved since like 1860. So I'm stoked that this is coming. Where are we in terms of progress? Because I went through your guys' company timeline, you know, opened your DC office in 24.

You kind of picked, you broke ground on your manufacturing facility here in Rhode Island in January of this year. and you started sea trials in March for Viceroy, your first sea glider. That's a little bit smaller than your later one. But I'm kind of curious how far this is from commercial application because that's what I'm clearly waiting for. We are moving really fast. So as you mentioned, that Viceroy Sea Glider prototype is in the water right now

undergoing sea trials. We started that in March. Viceroy is our first product. So that carries 12 passengers or 3,500 pounds of paper. payload on our cargo and logistics missions. Viceroy prototype is in the water right now. You know, the hard part of building this machine that floats, foils, and flies is that we're simultaneously building the fastest hydrofoiling boat on the planet.

And then we're also building the slowest flying machine on the planet at the same time. That's why this has never been done before is because those two speed regimes have not been able to overlap. So we're bringing up the hydrofoil speed, bringing down the flight speed, and we're able to overlap them for the first time with our electric propulsion digital flight control technologies. We'll get to the EV side of this in a second, but the speed of the air component to this brings a question up because it feels like you're cheating in the best possible sense because going to the airport sucks, going to security sucks, waiting at the gate sucks, being crammed into a southwest, you know, Boeing 737 sucks. The whole thing's miserable. So how do you manage to have a thing that flies and doesn't use airports? It feels like you've hacked the system.

So is the low speed a component of that? It's actually the low altitude on that front. So the low speed allows us to use the foils. There's sort of a top speed of the foils, waters 800 times more dense than air, right? So you only go so fast through that. And then there's a low speed of landing, which is you need enough air going over the wings to generate lift. So that's why you see we have that distributed propulsion system, a lot of different propellers. Yeah.

Mining the wing. We're sort of blowing air over the wing, tricking it into generating high, lift, at low speeds. And in so doing, we can slow down that takeoff speed and for the first time overlap it with the hydrofoil speed. So that's sort of the technical hard part of what we're doing and why we can only do this now with electric propulsion and digital flight control systems. How do you have so many propellers, right, pushing so much air to create enough lift to make this happen? but not end up with a lot more forward speed. We can size the system with these electric motors, which give us compared to sort of conventional jet engines

or internal combustion engines, we can really size how much power we put anywhere, how much thrust we're putting places. So we can really dial that in to sort of be the perfect amount and also make it an efficient system for our long range operations. So that's sort of the big unlock, right? We can do these unique configurations, and we can distribute propulsion wherever we want it,

and we can dial it in with electric motors and batteries. I've been working with and investing in founders for so long. I've got supernatural startup powers. For example, I know your team is spending too much time on debugging. Your engineers are chasing down bugs at 1 a.m., 8 a.m., and every time in between, instead of building amazing new features or pushing fresh code. Just admit it, you'll feel better.

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being a loyal twist listener. That covers 150,000 errors. Just go to century.io and use the code twist. That's s-en-tr-y-d-R-Y. And make sure you use that code twist so they know we sent you. To me, this is competitive with trains, for sure. It's competitive with all sorts of other kind of ground transportation. And it's better than flights for a lot of things. I will never have to fly to Newark again. For example, I'll just take a boat. Yeah, take the boat. Exactly. It's a sea glider. It's a boat. of a boat, kind of a plane. I'm going to have to figure out how to talk about it. Well, it goes back to your previous point of, you know, what allows us to fly without

using the airport, because we stay in that ground effect, because we're within a wingspan of the water, actually about half a wingspan at that 30 feet, we are regulated under the Coast Guard as a vessel. There is a special rule in U.S. law that is also mirrored in international law and regulation that this kind of vehicle, and a sea glider is a wing in ground craft, is a vessel under maritime jurisdiction, and that makes sense because we stay over the waterway. We do not rise up to airport altitudes or going to airspace. In fact, we're flying, you know, below the height of a sailboat mast and well below the height of a cruise ship. So we're in the maritime domain. And that's why this is regulated as a boat. We call it a boat. We have a lot of boat builders on

the team. Here in Rhode Island, there's a lot of boats, so you'll have to deal with traffic. You're also talking about a deal. You guys did a joint venture with the UAE to, quote, bring manufacturing and aftermarket services for Viceroy and similar to the UAE. Lots of boats there. So how do you handle regular maritime traffic when you're going a multiple of the speed of any ship that might be in and around the Viceroy's area? You mentioned the boat builders in Rhode Island here, and that's actually one of the reasons why we're here is sort of, you know, a non-characteristic startup market that's actually

perfect for us because we can leverage this incredible local talent that we have here and building composite racing boats. It's like the center of the sailing racing worlds. But in terms of traffic avoidance and maneuvering, that's where float foil fly comes in. Because a conventional seaplane, you think about it just goes from float to fly. So you need to clear these long takeoff routes.

You need to get to very high takeoff speeds to get on the wing. In our case, we don't need to do that. We can separate our high speed takeoff and landing operations from our docking operations. And so we can be hydrofoiling. You can get at 50 miles an hour. That's like highway speeds. We can actually, it's almost like a high speed taxi. We can go very far from the dock.

We can go through rivers or bays or harbors on the foil where we're as maneuverable as any other boat. And then we can take off once we hit the open water. So here it would be like we get south of Newport and we take off south of the bridge. Got it. So essentially because you'll be being a boat around other boats, there's not much of an issue. And then when you get out where there aren't boats, then you can just fly. Exactly. Exactly.

That's lovely. It makes sense. What changed in technology terms to allow this to be possible now? Because when you explain to me, the combination of float foil fly seems quite obvious. Like, oh, God, of course, why not? So was it the composites that have changed? Was it battery technology? Was it just people finally getting around the idea that we will have electric planes? Like, what changed? Yeah, there's really three big things. The first is, you know, hydrofoil technology being used in the Americas Cup for the past, say, decade or so, but really seeing a lot of maturation in that technology and the modeling of it, the hydrodynamic modeling of it. It's sort of like how we saw a trickling down, or there's always been a trickling down

of the most advanced automotive technology from the racing world and F1 into sort of commercial automotive. All of this incredible racing technology in America's Cup world did not have an outlet until now. It's like we can use that hydrofoiling technology. And I think you probably seen, the listeners have seen around a lot more applications of hydrofoils. There's hydrofoil boats and hydrofoil surfboards and all these things. There's the famous Mark Zuckerberg with sunscreen in his face doing the, yeah. He was doing that for us, really, to try to, you know, advance the state of awareness of hydrofoils.

That's why he's an early investor in the company, I think. Great partnership. Really great partnership there. So, you know, hydrofoil. So we're capturing that hydrofoil wave. Next is electric propulsion, that doing something. like blowing the wing like that to enable takeoff from a hydrofoil at a relatively low flight speed. I mean, 50 miles an hour is very low speed to take off a plane.

And so that is enabled with electric propulsion and not only unlocks that takeoff and landing operation also brings down that cost incredibly. If I told you you could get from home here in Rhode Island to New York in an hour, but it was going to cost you the same as a flight ticket, it may not be that interesting. But if I could say it's going to cost you less than your train ticket, you know, maybe less than the tolls you're paying on the road anyways, and it's faster, and it's greener, and it's more comfortable. All of a sudden, you're way more interested. So we bring down that maintenance costs by switching to an all-electric system. You should just match whatever I pay for

M-Track, which is several, I think several hundred dollars to get from Providence to New York City, for example. I mean, if you guys are cheaper and faster, I mean, it's game over. It's absolutely game over. And so the last piece now, because the control of that, float, foil, and fly, all different modes, all different controls. So the last part of this is the flight control system. So we now have flight computers and softwares. We have this incredible, you know, half of our engineering team of software engineers. So we have this incredible control system to keep it safe in all modes to the point where you don't actually fly it when it's a plane. We have this autonomous control system that governs it and make sure you're safe in your flight envelope and controls that height above the

water. So the only thing you do as the captain is boat controls, left and right, fast and slow, and it just locks you in on that 30 foot plane. So now we can train mariners. So it's kind of like super crews for like cars in that it does the, for cars, it's distance to person in front of you, tracking things and stuff. But you're just really doing left and right. So in this case, you're doing kind of the same idea. You're doing boat controls for a play. Well, that solves your pilot problem right there. Because if you can have mariners, and there's a lot of people out there who know how to do boats. So what do you think that's going to do? So what do you think that's going to to take in terms of time and money to get like, I don't know, let's say a tugboat captain,

geared up and ready to rock a regent. Yeah, we're working on the training course right now. We actually have some great partners on that. We expected to be about a four to six week course to go from, say, your trained commercial captain into a sea glider because the operations are very similar. And it's really just familiarity with, you know, the speeds and some of the systems. But, you know, I'm a pilot. My co-founder is a pilot. A lot of our teams are pilots coming from the aviation world. So much of your pilot training is how to take off and land and how to recover from an unusual attitude and all these failure mitigations and a sea glider, you don't even have

control of that. You're driving a boat and if something goes wrong, you land. Press the land button. I Google that what we're talking, the minimum takeoff speed for a Cessna 1 and 2, what I have most of my flight experience in is about 50 knots. So, you know, that's a number that comes up quite a lot in this conversation. You guys have talked about having, it was $7 billion in order. I think at the end of like 23, and I think it was $9 billion in backlog by the end of 24.

That's great, Billy. But why not not sell it and make your own coastal airline that just consumes tons of business and becomes enormous? Like, why sell it? Why not just run it? There's really three reasons. The first is brand recognition. And, you know, we are creating a fundamentally new vehicle. It goes fast, it flies low, it's sort of operating in this different way.

You know, I do expect a lot of people to just think this is an incredible experience. The ride's going to be smooth. You know, if you're afraid of heights, this is a great thing for you. But it's net new. And I think there will be a lot more brand recognition by taking the service with trusted airliner, trusted ferry company where you're already operating versus, you know, jumping on this net new region system. It also allows us sort of to use a very simple. business model in selling to defense, which is actually I would say one of the fastest growing parts

of our business and not operating in defense as commercial. So, you know, that's one. Two is from economic perspective, we can sell the sea gliders, get them off our balance sheet and onto our customer's balance sheet as owners. And then Regent participates in the aftermarket maintenance. And then number three, if you look at value accretion across, say, airlines today. Versus Boeing. Exactly. If you look at Boeing and Airbus and all of the tier. one's suppliers, the engine companies, avionics companies, significantly more market cap and value there than there is in all of the world's airlines. So that took us down this road. What is the United

Airlines price sales ratio? Airlines tough. And airlines are a tough business. We're going to help, though. You know, there's much better margins in operating sea glider lines to those entrepreneurs out there that are interested. Founders, listen, if you've got a B2B company and you're marketing your product or service to other businesses, you need to use LinkedIn. ads. Otherwise, you're wasting your time and you're wasting your money. LinkedIn isn't some random social network where everyone's using a fake name and posting nonsense. It's a network for professionals. LinkedIn knows who the big players are and who the key decision makers are in your vertical. Based on the data they're already collecting. Everyone's on LinkedIn. Me, you, everyone. The

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LinkedIn.com slash this week in startups. Maybe the better question than Billy is, do you think there's going to be eventually companies that specialize in using Regent Kraft to run what we might call regional C routes? Because United guy, shout out United, they've flown me so many miles. But I'm not quite sure I need to have United run my Providence to New York City, you know, Regent Craft Line. I mean, we are already seeing it. We're seeing, so, you know, in that order book, which is now over 10 billion, including firm orders. You know, we're one of the few companies in the space where we're taking substantial non-refundable deposits, millions of dollars worth of these non-refundable deposits that Regent is using to subsidize the build of these vehicles and actually non-dilutive capital for us, which is. fantastic. What's the list price for Viceroy when it comes off the manufacturing line?

So we haven't been public with the list price. We have an awesome sales team that's going out there, but I will say it's sort of between, you know, a Cessna caravan and a twin otter. You know, we're sort of in the middle of the size class. Our payload at 12 passengers and 3,500 pounds is right in between. And so your upfront cost for the vehicle for the sea glider is right in line with those competitors, and then the operating cost is half of those competitors. So huge, huge value in that operating cost. But yeah, so we're seeing entrepreneurs put together now sea glider lines, and some of our orders are from net new operators that are saying we are forming to operate sea gliders. So we have the airlines, we have the ferry companies. We have

energy companies and oil and gas companies. We have hotels. No more helicopters out to oil rigs. It's a big market. That's a huge market. Exactly. And then, And then one of the biggest ones is actually defense now, too, that's buying these. You know, we're with the Marine Corps. We've been working with them for three years. We have $15 million worth of contracts with them to do this experimentation. And so the great thing is, you know, I think it's hard to be a dual-use company. But what we have here is an asset that actually works for both of these customers in very similar ways.

Briefly, what is the defense application for the Vicer? Because I can absolutely see it as a way to, like, maybe move people between Navy, ships, but I don't see as many obvious applications for it as I do with, say, unmanned aerial drones. So just fill that in for me. We really started with the Marine Corps on the mission of high-speed logistics and contested logistics, which is moving around island chains. We're sort of in the secular shift from desert operations, you know, Afghanistan and Iraq sort of conflicts to now distributed maritime operations, South China Sea, right? Exactly. Big island chains, long distance. We need more boats. We need faster boats. We need faster boats.

The boats we have today are slow. They're easy to hit with missiles and things. And the aircraft we have today, drones included, are still fairly expensive. And if you need the range to go between islands, you're building even more expensive systems, and you still need land basing. So what we have is really in between. We're like a boat. We can operate from the water. We can sit out there indefinitely.

But we have the speed of a plane. And so that's a huge, huge gap. that we're filling right now for Indo-Pacific operations. So we're doing contested logistics, which is moving people and supplies around island chains. There are drones out there right now, lots of drones, which is definitely a focus of DOD, but you can win a battle with the drones. You cannot take and hold land and win a war with drones. You need people to do that at the end of the day.

So you still have to move people. When you're putting people into a fight to do that, you have to be able to take them home safely. And so Medivac is also one of our fastest growing applications for this vehicle of actually being able to go out, land on the water, rescue people, and bring them home. So to be clear, you're going to be able to serve airlines, net new carriers, various military applications. And also, I presume it's going to be some rich people who just buy these for themselves. Big market. Big market. Which brings me to my last question for you, Billy, which is just you're doing it in Rhode Island.

And like, look, Rhode Island's a tiny state. no one knows who we are outside of like the Northeast. But I find it really exciting that not just regent are here. I mean, we're talking about Vatin Systems before the call, and you mentioned Havoc and Anderil has the prisons here. What's the Rhode Island pitch? Like what types of companies and startups should be thinking about putting down some boots here? Rhode Island is sort of in the midst of this maritime defense renaissance,

which is very well aligned with, you know, national priorities and that whole defense scheme I laid out of, you know, national defense for the next decade plus is going to be water-based. And so you have a lot of sort of overlapping things in Rhode Island that make it compelling. Obviously, it's the ocean state. You have an air against a bay. It's an incredible testing facility. There's a great military presence here, Naval Service Warfare Center and the war college are here. So you get, you know, the top brass, the generals, the admirals, the decision makers coming into Rhode Island. And, You can call them up and say, hey, we're a half hour away.

Come check it out because everything in Rhode Island's a half hour away. So you can just come on over and check it out. So it's been great for engagement at the highest levels of defense leadership. One of our senators, Senator Reid, is one of the ranking members on both Senate appropriations and Senate Armed Services. So he's an incredible support to companies in the state. And being in a small state in Rhode Island, it's like he comes in visits, you know, quarterly, personally.

You get so much more hands-on, like compared to like California, for example. I mean, I've run into, like, the mayor of Providence was just like eating in my local diner, and I was like, this does not happen in San Francisco where I used to live. You know, like you're not as abstracted from government. It's right there. Exactly. And then I'd say the last thing is we're in what's called Kwanzit business park here. So like General Dynamics builds their nuclear subs here.

And there's just this huge growth going on because of the compelling financing that the state offers. and we're just building factories left and right. Like, Kwancett is the factory factory right now. Is Governor McKee sufficiently engaged? For sure. I mean, I was with him last week. Super engaged in this, growing this out. The state is investing real capital into growing the manufacturing base here,

all focused around maritime and defense. But for example, we are building our 255,000 square foot manufacturing facility that we were able to build, I mean, this is a $50 million project. We were able to build this as a series A, startup that had raised a total of 60 million to date. I know. Crazy leaning in from the state. It's really incredible.

So that facility will open in the spring. We'll start cranking out sea gliders for both those commercial and defense customers. We'll deliver our first sea gliders in 27. But it's not just us. You know, Anderals building their facility across the street. Yeah. All these other companies coming in. Saab is bringing their undersea warfare center.

There's a good, you know, presence from Raytheon and RtX. It is a very cool state to be in right now. I mean, Narragansan Bay is essentially one large subpin. Like, let's be honest. Like, it's just, it's great. It's awesome. I love to be enthusiastic about a company and my adopted home state. So, Billy, thank you so much.

I will come down at some point and say hi and just see what y'all are building. But 2027, last thing, early seven, later 27, when did these first touch customer hands? I would say second half of 27 is where we're focused right now. First half is going to be a lot of sea trials. So they'll be out on Narragansett Bay. They'll be working. They'll be in the hands of the Marine Corps, certainly, you know, working on those missions as well. Second half is those 27 deliveries.

Can I come on a sea trial? You got to come out. Yeah. Come on over. Just walk. Just walk here. I think I will get in my EV and drive down. But I would love to see this before it's fully baked and such because I'm a huge dwee for both

airplanes and boats and getting places faster than Amtrak. So a pleasure. Billy, it's regentcraft.com, and any job you're looking to fill, you want to shout out while we have you. We actually have a ton on Regentcraft.com slash careers. We're growing right now. We're looking for technical support on building the prototype. We're going to start to build our manufacturing team very soon as that building's soon to be open. So definitely go to that website there and check out careers.

And we have a bunch of cool videos too. Billy, you're the best. Thank you, man. We'll talk to you in late 26, early 27. Hopefully before them. We'll get you on to see Goddard before them. You can be a brilliant founder with a great product and you can have an amazing team. But it means nothing if your sales process is disorganized and if customers are slipping through the cracks. Trust me. If your pipelines is a mess, you're going to spend way more time getting organized than talking to customers and closing deals.

If this sounds like you, write down this name, Pipe Drive. They're the number one CRM for small to midsize businesses like me. I use Pipe Drive and have for almost a decade. It brings your entire sales process into one simple, elegant, and central space. That's why the sales team here at this week in startups uses it day in and day out. You just drag deals along your pipeline and you're good to go. Plus, they've got some amazing new AI integrations, generate sales reports with advanced metrics and personalized suggestions based on where your company is struggling and automate your sales

conversations with AI generated prompts. And when you use my link, you're going to get a 30-day free trial. No credit card, no payment needed. Go to PipeDrive.com slash twist to get started. If you listen to the show on a regular basis, you know we talk about AI probably too much. The one thing we talk about in the realm of AI is agents, little things that can go out there and do stuff for you.

This usually comes up in a context of SaaS or enterprise software or something incredibly boring, like expense reports or, I don't know, refactoring your spreadsheets. But there's a startup out there who wants to use AI agents to find old unused bio-IP, test drugs out, and maybe bring them to market. It's a really interesting idea. I love the company. And I wanted to learn more about both how it works and how fast it's going to change our world. So please join me and welcoming to the show. It's Ayan Parikh from Condexia. Hey, how you doing? Hey, doing good. Thank you so much for having me, Alex. Looking forward to chatting with you.

My pleasure. I just love to talk about AI in a context that isn't like trading or something involving enterprise SaaS. It's such a nice page. So Convexia, as far as I understand it, essentially wants to use a series of AI agents to find unused IP or just leftover ideas, vet those ideas, run business queries about how popular or commercially viable those drugs could be, and then help bring them to market. Is that fair? Yeah, pretty much. So we're looking at all types of drugs. They could be really early stage drugs that are just sitting in labs. They could be shelved assets that are, you know, sitting in the shelves of these small, mid or big pharma companies. Or they could just be things that have been overlooked. We evaluate the science,

the clinical viability and the commercial viability to score which ones have the highest chance of succeeding and which ones can save the most number of lives. And why are those the most two important metrics? I can think like speed to market or number of people you could impact maybe on a non-life-saving basis that would also be good vectors to judge against. Yeah. So I mean, when you consider like what will bring a drug to market and what will make it succeed, there's generally, or the way that we think of it is like what will cause a drug to fail,

essentially. And the three reasons drugs will not come to marketer because either it's not safe and effective in human bodies, either there's too high of a clinical risk, meaning like there's some manufacturing problem or just running a clinical trial is really, really hard. Or it could be that there's no commercial viability that there will be, that there's already something out there that's way better or the market size just isn't there. Or perhaps that like an insurance company will never cover because the standard of care is already so good. So those are the three key reasons why drugs will fail. And those are the, that's why we look at those and consider why they'll either or not succeed in the market.

Okay, no, that helps a lot because I was really curious about, like, to me, there's a lot of ways you can approach this, but you have to narrow it down. Right. The thing that I was really kind of hung up on prepping for our job today was just how much leftover IP or ideas on the shelf or, I don't know, preclical trials out there, like how much stuff is there for you to go out and look at and run through the agentic stock that you're building? An incredible amount.

So just to put some statistics out there. out of all the drugs that enter into phase one, only about 5 to 10% ever even make it to market. And the percent of drugs that even make it to phase one is a really, really small proportion as well. So the point being that there's a whole bunch of preclinical drugs that are never making it to clinical trials, and that even when they are entering clinical trials, many of them are shelved for reasons beyond just the molecule not being good. For example, the clinical trial might not have been run the right way, or a company might just have a change in strategic incentives or in strategic alignment. And now they just have this really cool drug that's just sitting on their shelves.

So there's many, many examples I can list off as to when potentially life-saving drug was just sitting pre-clinically in a lab for really, really long, or from where it's just sitting on a shelf even after entry clinical trials. There's a lot of examples like that. And I think as, you know, AI drug discovery continues to increase, the number of drugs being produced will simply continue to increase. Creating novel drug molecules will almost to some degree become commodified. But what will become really critical then is actually trying to evaluate which one of these will actually be successful. Out of all these drugs we're making, which ones of them will actually be successful in clinical trials.

And I think that's kind of where the future of the space is going to. The future of pharma is an MNA. I can talk a bit more about why that is, but the larger point here being that we want to be on that forefront. Okay, so down the road, you know, five, ten years from now, we're going to have A.M. models of sufficient quality to kind of come up with their own ideas, and then from there we can vet them and then eventually get them to market if they work. Today, though, A.M. models, maybe not quite there yet, but there's tons of stuff out there that you can't go out and mine. Okay, that makes sense to be glad that I understand that. The question is, how do you get access to the information?

because I presume that if I was Merck or some other large pharma company, if I shelve something, the public may not know about it. So how do you get the ability to have access to the information you need to do the work to vet as these drugs as possible candidates for convection? So I think the last mile of this is always somewhat relationship-based. Like in order to actually strike that deal to some degree, you need to know the right people. However, in order to like even start those conversations without already being in that circle, there's still a lot of predictive that you can do to understand what is shelved and what was being pursued at some point. For example, you can mine company reports.

You can mine how much a company is manufacturing certain molecules. You can mine patents. There's a lot of information that you can look at to predict what is being pursued and what is not being pursued. And we've built our models to be able to do that and predict which drugs are up for market or are up to be sold or outlicensed, which ones are just sitting there and which ones are actually being pursued right now. And this is the first layer of your agentic stack, as I call it, which is your sourcing agent, the thing that goes out there and pokes around and finds stuff and brings it back to

the company. Is that part of the company's technology in production today, is that going out there doing this or is that something that you're working on building so far? We've done this. So we're not only using this in-house internally, but we've also sold this technology out to some customers as well. As we kind of talked about, it's not only does it mind both structured and unstructured data, but it's also kind of hypothesis generating and thesis-aware, which is how we compare to a lot of these other, you know, typical competitive intelligence tools. That's really the alpha that we generate compared to those. Essentially, you better understand not only biology, but also the pharma industry.

And so with that information, you can just make much better guesses. Exactly. Then comes the next thing, according to your rundown, which is the scientific agent. And this uses a number of, as far as you can tell, just like AI bio models. I'm not as familiar with how fast those are advancing. Can you give me just, I don't know, a state of the industry, if you will, for that part of AI? I guess the gold standard for a lot of these in silico tools has for the past years been physics-based models. And that's been pretty true for a lot of, I mean, the entire world of computational biology and computational chemistry.

But now we're kind of seeing a bigger and bigger push towards ML-based models. Like just in the, today, some cool models were released. Yesterday or a couple of days ago, Boltzgen was released from MIT. So a lot of really, really cutting edge tools are being released in this ML space. And I think, like, when we look at the next five, 10, 15, 20 years, I think these ML models will become increasingly better and become the goal standard, whereas right now and in the past, it's been more so the physics-based models. So I think, like, in different worlds, there'll be different, I mean, in different kind of sectors

of the science side of things, change will be seen differently. Like right now, if you look at, like, binding, the ML-based models are actually pretty good, but if you look at like toxicity, there's not a lot of good ML-based models or even models at all. So I think like there's a lot of room for growth in this space, but we are getting there. So physics-based models for the work that we're describing to my non-biologist brain seem like the way to go. Why are ML-based models in your view going to supplant and surpass them? Well, I mean, I think the pace of ML innovation is faster than anything we've ever seen before. Yep.

So like they're growing faster than ever before. And like even physics-based models, they have a lot of limitations right now as well. A lot of physics-based models can actually predict everything that an ML-based model can even touch on. So I think the capability as far as compute goes, as far as speed goes, as far as raw capability goes, will soon be, I mean, the physics-based model will be far exceeded by the ML-based tools. That makes a lot of sense to me. Now, the next thing is your commercial agent. That one makes great sense to me.

Then we get to the clinical agent side of things. This is when I get even more excited because you're talking about using digital twin simulations. And I think digital twins is a brilliant approach from, I mean, a lot of places, everything from, you know, factory design on down. But in practice, how good is digital twin simulation for individual drugs? Because to me, they could be a cool technology and maybe a tough use case. So I'm curious how well they wed, if you go. Running digital twins is a very, very difficult problem. And I think, like, we're still exploring what that looks like to its fullest capability.

I think, like, kind of where we're starting is by not trying to boil the ocean and, like, you know, try to create these digital twin simulums. but more so starting with like, okay, how can you understand the manufacturing? How can you understand the patient stratification? How can you understand even the trial design? These are all small components of clinical trials that might lead to a clinical trial failing, but aren't like the whole, you know, digital twin in itself. So I think like the way that you eventually build to like being able to run a digital twin is by starting off with smaller components.

And that's what we're focusing a lot of our time on right now. So if we go from sourcing through science, through commerce through the clinical agent, and we get all the way to a phase one trial. And you said earlier that, what, 5% of drugs make it through phase one more or less and get out on the other side? No, so 5% make it to market. So 5% of make it through phase 1, 2 and 3. When you guys have this full pipeline in place,

how much better do you think you'll be able to do on that 5% from start of phase 1 through production? I think significantly better. We've been doing a lot of internal back testing and we're going to be publishing some really cool results. We're actually publishing a paper pretty soon. That'll like talk about. about specifically some of these benchmarks.

So I think that's coming up pretty soon. And we'll be excited to kind of publish what those exact results look like soon. But I mean, based on what we've been seeing, there's a lot of promising results that we've been seeing by just doing simple back testing of our agents. Are we talking about like 2% better from 5% to 7%?

Which would be 40% quite a lot. Or are we talking like 5% to 25%? Like a 5x? Yeah, something like the latter. It'll be significantly better. And that's just because not only are we now able to predict like just commercial success. Like that wasn't too difficult before.

But like also being able to look at like the actual science of this, being able to understand like out of all the history of clinical trials, how much better is it to, you know, use this contract research organization or this manufacturing organization. Like these are all very, very small details that we can actually fully understand and understand like how that affects the probability of success of a certain drug. And I think that's where we get really excited because of how granular we can get with some of these details.

Well, I mean, that explains why you've decided as a company to sell bits of your technology to other people and you're seeing uptake from it. What does your customer base look like today? Are you selling to like the pharma companies that I can name or are you selling your technology more right now to companies that are more in the startup realm? It's not big pharma. Most of our customers are small to mid-cap pharma companies and then quite a few like investment firms as well. So things like biotech VCs, hedge funds. We're starting to work with some investment banking like bioterrorism. tech IV firms as well. So that's what the primary customer base looks like right now.

Is the future of Kandexia building technology that you sell to other companies that then use it to bring more drugs to market? Or are you eventually going to have the full stack put in place and you're going to run the process yourself? Because I can actually see a great argument for either direction for the company. I think the goal is to be like as the tagline says, an AI maximalist pharma company. That's kind of the long term goal. The way that we think to our company is that in order to actually bring the drug to market, you need a lot of information. you need a lot of experience and you need the right team. And the way that we eventually get to that long-term goal is by first working hand-by-hand

with our current set of customers and partners to understand how they do it. And then we would leverage those insights to eventually run this process for ourselves. So the long-term goal is to be fully vertically integrated and to be a pharma company. How far away is that? Is that five years, 10 years, one year? I just don't have a good guess. Yeah. So when you look at a lot of the other companies that have done something similar, for them,

like, Shrodinger is a good example. recursion is a good example. These are all companies that it took them like anywhere from like nine to maybe 12 years. I think our pace can be much, much faster. We're already helping a lot of companies make decisions about drugs to in license. So I think like, I mean, we're keeping our eyes out. If we spot something that really piques our interest and that makes sense for our portfolio, like there's no reason why we can't pursue it if we have the confidence that our models are actually that good and that it's worked in the past. So I think it could be as near as like, You know, a year from now, it could take a couple of years as well.

It's pretty cool how quickly we can move in the space. And given the right circumstances, we can actually move on some of these drugs pretty quickly as well. Is your ability to move quickly predicated on simply the advancements in ML we were talking about earlier? Or is there something else going on at the regulatory level that's providing the tailwind just to your pace? I think it's a bit of both. I think like we certainly understand that like these models will continue to get better and we want to be on that forefront. I think Sam Olman talks about this. Like as the model gets better, our company will also get better.

so we're not really competing against models, but like it's very synergetic. Yeah, sure. Yeah, I think like there's also some interesting regulatory tailwinds, specifically with rare diseases that we're very, pretty excited by. Like, we can get into specifics of them, but like CNPVs and PRVs. These are all like vouchers that can essentially make it very lucrative or very like monetarily exciting to pursue a rare disease drug if you actually achieve some of these vouchers. I think this is like a really, really compelling space that, I mean, that's why we've been

looking a lot into rare disease. is severely underserved market. And our model, like, we're a really, really small lean team. So whereas, like, a Pfizer, they're looking for a $10 billion outcome. We can actually, like, under a billion dollar outcome is incredible for our company, which is typically what the ultra rare or rare disease space might look like. Now, what is a good example of a rare or an ultra rare disease that people listening might be familiar with?

So I feel like we should ground that in something that can do an example. What's defined as an ultra rare is under 200,000 people get affected by it each year. So, I mean, there's a lot of examples. KSax is an ultra- Rare, and there are also some more commonly rare ones as well. But anything that kind of falls under that perspective is what would be defined as a rare disease. 200,000 per year per around the world, not just here in the U.S. In the U.S. Oh, okay.

So 200,000 in the U.S. per year. That doesn't seem that ultra-rare to me. That seems like my hometown times four. So that's what rare disease is. Ultra-Roid would be under 50,000. Still, that's my hometown. I grew up in 10,000 of 50,000 people. that's a non-instant. I thought it was like, fine. I had this entirely wrong. Okay, but essentially,

because Convexia is so lean and because you don't run wetlands, you have lower operating costs, etc., you can afford to go after these drugs that don't match the cost structure of one of the pharma companies that we can make. Exactly. How many of these rare diseases are there out there that people need help with? Like, is it, I don't know, a couple thousand? I mean, how long will it take to chew through them? An incredible amount. So I guess for some person, perspective, out of all the rares and ultra rares that are known right now, only 5% of cures. So 95% in the market is still up for grabs. So there's an incredible, like, thousands upon thousands of ultra rare diseases that are like,

that are, that there's no solution for right now. And we've been spending a lot of time thinking about like, not only like developing new cures, but also just repurposing existing drug composition. We've been working with a select number of, um, select number of partners to understand, like, can we build out repurposing models using some version of our agents to help them find how some approved drug can be repurposed for an existing or like for some rare, ultra-rare disease? So a bit like how GLP1s are great for reducing your appetite, for example. They're also great for diabetes, I think, and they're also good at like addiction control.

They need to do a lot of stuff. So single compounds can have multivariate impacts. And so you want to see if existing compounds can help these supermarkets, you know, Where how do you, how do you do that? What's the, what does the AI model or agent do to try to form fit existing compounds into known but unrelated problems? There's a couple of ways. I think the kind of the standard way of doing it right now is just using like a graph neural

network. I guess this is the standard way is in terms of like how we would develop it or how we have developed it. I'm essentially trying to understand like what mechanisms is a certain drug hitting. And can those mechanisms like whether it's through off target impacts or on target impacts, can any of those be reapplied to fix diseases or to fix some of these ultra rare diseases? So just like cross-applying like, oh, this drug hits this mechanism, can that be used to help solve this drug? And then there's a lot of other steps that kind of go into it. You have to

look at the pharmacokinetic properties. You have to look at like the dose ability, the toxicity at certain different levels. So there's a lot of kind of sequential steps that go into it. But at a high level, it's like it's a version of like making this puzzle based on all these different pieces of information that you have available to you. Okay, but if we have improving models, if we have agents that can do more and more, we're able to collect the data and do a lot of work outside of the lab to see what might be functional and we can go after lower commercially viable drugs. It sounds like if convection ends up winning, we could tackle quite a lot of these rare

and ultra-ware diseases in the next five to ten years, which would revolutionize quality of life for millions of people here in the U.S. Agreed. I think that's the goal. I think there's a couple of other people. players working in this space as well. But I think like, I think like the general vision of being able to find and bring drugs to market faster and use, find existing drugs and seeing is there a way to, they can repurpose these for existing companies or sorry for existing rare diseases.

I think it's a really, really exciting space. And I think given, as you said, that the models are getting so much better so quickly, I think there's certainly a path to seeing a lot of value come out of this space in the coming five, 10 years. One question that I have, though, is just about capital because right now if you look at where venture dollars are flowing, I don't think it's biotech's best year ever. And so I'm kind of curious, are you guys classified as a biotech company that uses AI or as an AI company? Woo, easy fundraising that's working in bio. A mix of both, I think. Like, I think for our seed round, we just closed up our seed round.

Hey, congrats. We, thank you. So that was, I guess, more so the latter, like an AI company that's being used for bio. I think, like, as we transition over towards becoming a pharma company and actually, like, having an asset pipeline, I think we'll transition more towards like the kind of the bio side of things, the biose side of the spectrum. But I think right now it's more so, it's more so oriented as like being an AI company that is being applied for the bio slash pharma space. I love this. You're giving the actual hope for the future that when I get old and need help,

there'll be much better things there. So thank you for that. Two things before I let you go. One, what is the place people can find the company online? And also, in case you want to shout it out, is there a job you're looking to hire for and having a hard time finding the right candidate? they might be listening to the show today. Of course. Yeah, convection. com. Bio is our website.

So we have a lot of information about the company there. And of course, all the socials are linked as well. We're looking to work with AIML people. I mean, as is everyone, that are very interested.

Good luck. That are interested in the bio and health space. So if you're interested in working in that space, but we'd love to chat. We love making great conversations. And if you're interested in hiring or interested in getting hired even better. All right.

Well, thank you so much, my man. And when you have your next milestone, whatever that is, come back and tell me about it because I have an eye on you guys. I think you're obviously big. Thank you so much, Alex. I really appreciate it. I freaking love data companies. I love companies that store it.

I loved box. I loved Dropbox. I've known Databricks for so long. I think I actually grew up with that company. But that does not mean that we have solved a problem with information in the cloud and using it. And that brings me to the startup we're talking to today. They are cart R-Kill, A-R-C-H-I-L, and they have a very interesting, may I say, innovative way

to ensure that you can access your cloud data very quickly as if it was local. How does that work? How is it going to make money? Let's find out. Please welcome to the show. It's Hunter Leith from R-Kill. Hunter, hey, how you doing? Great.

Thanks for having me, Alex. Dude, my absolute pleasure. So let's start with, did I get that right? At a very, very high level, Ar-Kill wants to make it possible for me to interact with my cloud data, say, on Amazon, AWS. as if it was local to me, therefore it's faster to access and just easier to work with. Fair? That's right.

Traditionally, you would spin up like a server in a place like Amazon or Google. And then you would have to transfer that cloud storage to your server in order to be able to do anything with it, which is slow and expensive. And so we've cut out that step completely and just made cloud storage appear local. So for folks out there who are not deep into the storage weeds, instead of having to drive to a place and put something in my car, drive my car home, and then walk back and forth to my car, it's essentially already in my living room, and you guys make that possible via some tech that we'll get to in a second.

But fair? That's exactly right. Now we can go kind of one level deeper. You've created a caching system, and this is where I begin to have questions, because I get caching, for sure, and I get the idea of having a cached copy of something that you can access more quickly,

but where does the cache live? And you still need to get all the original data from, for example, S3. That's right. So we, in the general sense, like to put everything in the same. We offer like a SaaS kind of model where you sign up with us. You get access to our mega shared cash and we only bill you for the amount of data that you're actually using. So you don't have to worry about any infrastructure to take advantage of the performance benefits and the cost savings. How does the caching element of this work? Because that seems to be kind of the magical thing you guys are bringing to existing S3 customers, for example, to make their data more accessible. maybe give me the idiot version and then the actual version in sequence. We effectively, if you think about S3 or cloud storage in general as this low-cost, slow storage, there is also high-cost, high-performance storage you can buy, which are traditionally like the SSDs that you might have in your laptop.

We run a fleet of servers with those drives attached to them so that we can serve the data that's in the cache really, really fast. and then we have a bunch of magic on the back end to effectively predict what kinds of data you're going to need so that you're never waiting for us to go to the cloud to download that data for you. How effective is that intelligent pre-cashing? Because my concern would be if I'm paying for this as an active gigabyte per month and we'll get to price in a minute, I would not like you to pre-cash more stuff than I need and therefore possibly incur either a higher bill on my side or unnecessary costs on your side. Yeah, I think that's right.

And so what we aim to do is effectively make our service as simple as possible for anyone to use. This strategy is used by every company out there, Databricks, Snowflake, Netflix. Everyone is effectively trying to cache data out of places like S3 to make it more accessible. And so we want to make that available to people. But then there is this next level of configuration around what if you know what you want. What if you don't want us to pre-cash? What if you're cost-sensitive that we can expose as knobs to our customers who care about that level of detail so that they get exactly the experience they want?

So essentially, I might be able to tell Arkhill in the future that, hey, you know, don't pre-cash too much. Let me just kind of walk around and tell you what I need. And then you guys talk a lot about data being available effectively instantaneously. I presume that's after you've taken stuff out of S3 and then put it into the Alex Incorporated cash. It is, yes. Okay.

But there's a different model of accessing the data in our system than before, whereas if you were using, say, a 10 terabyte folder that was in S3 before, generally you would have to download this entire 10 terabyte file in order to use any of it, which backed everything up in your system. Okay. And what we've done is we make it possible for your applications to go ahead and use the data, even if it's not in the cache, and they will wait as they request individual pieces so they can get started earlier, even though we might be backfilling it asynchronously.

I don't need to wait for 100% of a folder to make it over into the Arkell cache. You guys will intelligently help me know what has been cached, and then I can interact with that part of the dataset or part of the files in question. Okay, that makes good sense to me. Silly question, but as someone who hasn't really written code since high school, How hard was that to do? Oh, it's incredibly difficult. Because you're making it sound pretty easy.

I have a question after this that I'm getting to, but I'm just curious. It's really interesting. So I built this company after spending eight years at Amazon, working on a service called the Elastic File System, which does something similar in shape, which is offer this high-performance storage in a fully elastic, expandable way. And it's really interesting if you look at the cloud companies and they're offering. because Amazon is the only company that has actually built a product in this space because it is so tremendously difficult to do. So it's easy to explain. Everyone understands caches, but it's

extremely hard on the back end. That kind of answers my next question, which is why hasn't someone built this before? Because going and looking at your kind of marketing speak, you know, 90% lower cost than using EBS and 30x lower latencies than using S3 directly. It sounds almost like a magic potion for the problems of moving data around online and interacting with it at the corporate level. Like, it seems like magic. That's good. That's exactly how we want you to feel. Well, everything feels like magic to me because I mostly bang rocks together and rub sticks together.

Why were you able to do this when Amazon and Google Cloud and Azure haven't been able to? Is it partially because you're no longer inside the beast, as it were? And so because you're outside, you don't have to follow, I don't know, normal Amazon development patterns? or what was the unlock that made you, Hunter, and our field able to do something that, you know, $10 trillion worth of market cap cannot? Well, I think if you look at the clouds as a market offering, you can effectively draw a through line from how people used compute and storage

in the 1970s to actually the products that they offer in the cloud today. It's like servers, multi-tenancy, hard disks, object storage, done. And I think what the unlock was for our product is really understanding that the cloud has actually changed the way that we can offer these primitives to customers. And so it's very non-obvious that this product is like, A, worthwhile to build and B is possible to build. But you guys talk about how, you know, everyone has to kind of collage together a similar cashing system if they want to have a similar thing today. So it seems like the need for this is pretty obvious. And I'm curious if you guys have managed to convey what you're building to the market effectively. Like, are people reacting strongly to what Art Kill has cooked up?

Oh, yes. I think what is I feel very lucky to be a part of is there is tremendous demand for what we're building. And we get to collaborate with some of the largest companies on Earth, as well as some of the most innovative startups, maybe working in AI, that need this kind of technology and need it yesterday. So I think so. Obviously, we can always improve. And because we're such a technical product, simplifying and making it easier for people to understand

is this really important part of how we think about marketing. I did complain a little bit internally. I'm like, why do I always fall in love with companies that are very complicated that I have to explain to an audience? It's just like, why can't you guys just do SaaS for bunnies? You know, that would be so much easier. A question about where you guys actually store the cached data on the SSDs or whatever, is that also a bit of cloud technology that you're

renting from one of the major cloud companies? That's right. Yes. So we actually rent servers from the cloud that have these SSDs attached to them. We then pool all of that storage together and then we rent that storage space out to our customers at a smaller granularity. But even being on top of the clouds, we're able to effectively turn a profit on a service like this. We'll get to that, but I was curious if Amazon hates you because I feel like you've kind of

showed up to their party and been like, these people can't dance. Let me show you how. But it sounds like because you're helping, in many cases, I presume, Amazon customers better access their store data on AWS. And you're also a customer of AWS. You're probably like their favorite person because you're doing the hard technical work for them and they get to have two customers instead zero. I think that's exactly right. People will frequently ask me about what it is like competing with Amazon, and I have to kind of tell them that we're not, we're not in competition with Amazon. Amazon is in this great position where they win no matter what happens because they own the underlying infrastructure. And so if we're able to unlock AWS for more enterprises that couldn't

otherwise use it, or if we're able to bring these startups that are doing the new things in AI to Amazon's infrastructure, that's a net win for them. Do you guys plan to have a similar setup with Google Cloud, Azure, OCI, and, you know, et cetera, et cetera, et cetera. There's a lot of cloud providers now that are doing quite well. It's not 10 years ago when AWS was kind of the only game in town. So one, do you guys support other calls today or two? Is that something that's coming in next year?

Yeah. And this was one of the shocking things that I found out after leaving AWS was that there were other clouds that other people used. but we are today in Google Cloud as well. We intend to be in all of the major hyperscalers as we're just following customer demand, as well as the GPU clouds that are actually becoming popular now. So your core waves, et cetera, et cetera, et cetera.

That's right. That's interesting, though, because when I think about caching lots of information, I can see how a company that wanted to use its information for, let's say, RAG in an AI context, would want to have access to that data, but how does it interact with a neocloud directly? They seem like related, but different conversations to me.

I presume I'm missing something. No, I think you're right. And so we actually, like, we segment the market a little bit internally, which is that there's all of these existing players, like maybe geospatial companies that are doing data analysis on imaging and bioinformatics and things like that, where they have applications that are in the cloud but maybe need better performance

or are just otherwise underserved by the storage offerings that exist today. And then there's all of this new stuff that's happening with AI that we're excited to be a part of. And that spans everything from pre-training where people need to adjust a tremendous amount of data

into the GPUs very quickly, of which there are only a few storage solutions that can support this at very high cost. And even all the way down into the kind of agent space that people are talking about today where you need these agents to be able to crawl something like a file system in order to find out what data is available and use it effectively. Hence rag. Okay, so it sounds like for training

use cases, you want to be able to move a lot of data into a neocloud for training. So you'd want to have it cached for quick transfer, fair enough. And if you're doing anything in the agentic realm, you want to have access to specific information, lower quantities, but very quickly. And that's where you guys fit in as well. Oh, interesting. So you're kind of like you help facilitate both inference and training for AI. Ah. Well, that's a huge market. I like to tell people that our goal over like the next three years is to become the universal access layer for data, which is that our product, because we offer this kind of rare combination of performance benefits and cost benefits, should be the easiest way for anyone building any kind of cloud application to actually interface

with their data, no matter where it lives. So how long until I don't need to go to Amazon to start my storage journey and then layer R-kil on top? How long until you use white label S3 for me entirely? And I come to you guys and I'm just like, I don't really need to care about the cloud. I just want to have my data pre-cached and available around the world. I absolutely think that we will get there in time. But today for us, it's a matter of focus.

And we are so focused on building this high-performance layer on top of things. that that's probably where we'll be in the short and medium term. That helps me with some timelines. Now, on the customer side, you know, I can absolutely see why companies that are deep into the AI weeds would like to use this. But I'm curious what other company sizes, industries, sectors, whatever the right question is, are taking up our kill for their own uses. Because storage is so broad, we see our customer use cases also be incredibly broad.

We see tremendous pull from enterprises that are trying to see. spin-up research environments for their ML and AI engineers who need to collaborate and share data very quickly and effectively. We see, like I mentioned earlier, kind of geospatial and bioinformatics companies, which traditionally don't have applications that connect to cloud storage natively. It needs some way to bridge that gap, which we make possible for them. And let's pause you there because this is actually, I think, is pretty important. You guys use something called POSIX, POSI-X, to ensure a

consistency and also to make it possible to treat storage serve via Arkhill essentially as if it was local. So apps don't need to be cloud-nated to access it. They can treat it like it's on machine, which probably makes it more flexible. That's right. It unlocks an entire segment of applications, which is to say that traditionally S3 has this API that applications need to be written against in order to take advantage of. And while a lot of applications over the past 10, 15 years have changed to actually use S3 as their backend. Most applications don't. If you think about databases or like FFMPEG

kind of the video transcoding stuff, all of these things are things that you could imagine running on your laptop against files and folders that you could see in Finder. And so we take that cloud storage and turn it into this POSIX, is the right word, compatible format that can run with any application

that works on a machine today. It's freaking awesome. What stops Amazon from just buying you now? Because I feel like you're going to become bigger and bigger and more expensive, but I can't see any major cloud not wanting to have this offering as part of their quiver, if you will. I agree. And if that becomes relevant for us, it will certainly be interesting.

But I think we're in a really good spot to execute on this quickly. And because of kind of the incentive structure that the clouds have around the products, that they're selling today, I think it's unlikely that in the short term, anyone builds this themselves. So that's a very interesting statement. Unpack that for me. What are the incentives that are pushing back against them building this? You can be rude.

You don't work there anymore. I have tremendous respect for my people who are working at AWS and Oracle and all of these places. Here's the boilerplate kids in case the startup fails. Andy, take me back. But because these clouds in the storage realm today generally sell object storage, S3, which is something that is built per byte used, it is very low margin for the cloud. And then in addition to that product, all of the hyperscalers also sell effectively a hard

disk kind of product where when you launch a server, you tell the cloud how much storage space you need on that server, and they provision something that looks like a hard disk. And you pay, in this instance, for the amount of space that you asked for, not the amount of space you've used. This is one of the core things you guys put out as a developer sticking point, as something you're trying to solve by making it essentially elastic. That's exactly right. And so if all of these clouds are making billions of dollars on effectively the unused space that's on those disks, it's very unlikely that they would want to spend a tremendous amount of R&D to get rid of that extremely high margin income stream. That makes a lot of sense,

especially right now when technology companies are at once their most profitable and their part. because they can't afford anything. Let's talk about costs. So for folks out there who have not looked up the S3 price list recently, if you're curious, for S3 Express 1 zone, it's about 11 cents per gigabyte. You guys are currently charging about 26 per quote active gigabyte per month. It does seem like you're not charging that much because if you have to pay for S3 yourself to a degree or compute, there's only so much margin there, Hunter.

So tell me about the economics of this and how it works. I think that's right. And this is another reason why a lot of companies are not super interested in building storage solutions is because it's not your high margin SaaS play where costs and revenue are completely unrelated kind of a thing. We are selling, much like the AI companies, effectively something that has costs of goods sold, that we have to deliver actual margin on top of. COGS plus margins how it goes. That's right.

But when we talk to engineers who are at these enterprises that are interested in using our products, they are very indexed on wanting to use cloud storage like S3 because, for one of many reasons, it's very low cost. And so they want in the default case to only pay the cost that they would have for storing that data in S3. if nothing else is happening on the system, and that would make it a good design. So when we think about charging, our pricing is directly tied to what our customers are doing. If they're actively using that data and we're caching it and we're facilitating access for them,

we're charging them for it. If they stop using their data, it's no longer in our cache, we charge them nothing and the data is just on S3 for them to use as if they only used S3 in the beginning. So there is enough margin there for you, and it's positive for customers because they're just not paying for unused capacity, unlike the current object-oriented storage system set up by the major clouds. So you're more developer-friendly and you're speedier. That's right. Pretty good combination of things. It does seem, though, that companies over time will sometimes try to take a bit of margin back, a bit of a little customer surplus.

How are you guys going to avoid becoming this sort of company that puts ads in consumers, video subscriptions, a la Amazon? It's funny. It's kind of hard to put ads on someone's file system, though we have, you know, thought about what that might look like. Don't do that. Please God. I think that for us, the story is the same as it is for something like any AWS or Google Cloud or things like that, which is that storage is a place where we start. And then we want to provide services on top of that that might be more valuable to our customers. So rather than offsetting these prices with things like ads, we would rather offer things like compute on top of the storage that provide a better experience because it's tightly integrated with what we do to generate additional revenue.

So if cloud computing and storage is abstracted compute for companies, it sounds like what you want to build is like a synthetic layer on top of that that takes kind of the raw grunt of data centers that other companies have built and makes them. much more modern, if that makes sense, and offer them to people in a manner that's much easier and better to consume and interact with. I think that's right, which is that over time, the way that we see people interact with systems continues to become higher and higher level, which is like maybe 15 years ago, developers really wanted to use S3 directly, use disks directly, put all these blocks

together themselves. But, you know, now people expect higher level. primitives. They want to just use Vercel and send us some JavaScript and have that work. And so I think that you'll see the same arc on this back-end data-intensive work, like even Databricks, where people just want to ship a problem to us and have us solve it for them in whatever way makes the most sense. Well, being pretty darn asset light, because you're not making your own data centers. You're not buying land. You're not trying to get power generation sorted out. You kind of get to lean on what has been built and take it a step

further. I really like that. Last question for me is you guys raised some capital. I think it was in June or July of this year. I think Felices led that. Who was your lead investor? So Stasia at Felisa. I love Stasia. She's fantastic. One of the smartest VCs that I've ever met, actually. She was at Red Point before, right? That's correct. So how much capital do you guys need, though, to take us as far as you want you in the next couple of years? I ask because I've talked to a lot of companies that are raising amounts of money that don't seem to track with their needs. And so I'm just kind of curious, like, what will it take in dollar terms to get you to the next, I don't know, three or four years? I think it's hard to say. And I think, like, there is obviously a spectrum of companies that

you see today from all the way on the left, like light capital requirements, your traditional SaaS, where there's not really any costs outside of R&D, to all the way on the right where you're building a foundational model and you need to, you know, go buy a billion dollars of NVIDIA chips. We're neither of those things. We're somewhere in the middle, which is because we're offering storage as a service and storage is something that both the capacity and the performance and the safety actually scale with the number of servers you have, we have a fixed cost to actually appear in any region, which is why we're only in a couple regions in AWS and GCP.

I see. You have to, okay, right, you have to provision or kind of take on to yourself a certain amount of, let's call it flash storage or whatever. And so if you replicate that in every single AWS instance, that's very expensive. Or region, I mean, sorry. Yes. And so we do have capital requirements. They are low compared to, obviously, model training or data centers or energy.

Yeah. But we hope to raise more capital over time to be in more places and then fund more R&D into the higher level services that we chatted about. I'm even more excited about the company now. Where can people find you on the internet? and what is a role you are hiring for? You would like to shout out to the audience in case there's the right person listening.

So you can find us at arkill.com, A-R-C-H-I-L dot com. If you've heard this and decide you already need the product, we also have disk.new, which you can go to and just immediately get logged in and set up with something that gives you high-performance storage.

We're also on Twitter and LinkedIn, of course. As far as open roles go, everything for us is engineering, as may or may not be a surprise to you. I'm blown away by that revelation. No marketing people. You're not hiring on the GTM side yet? Not yet.

I think that if you look at companies like modal, for example, which are this kind of high performance compute platform, one of the things that they did well early on is just focus exclusively on engineering. And if you get the best engineers, you can grow the product and then fill GTM in later. And I hope we take the same playbook. I think that's the right way to go in your case, because you have to sell to developers who are famously relaxed,

casual and not picky whatsoever. That's right. Hunter, an absolute pleasure. Thank you for teaching me so much. Good luck. And I love to have you back in six or nine months. Thanks so much, Alex.