9 Mothers is building a 35-pound robot that shoots down fast-moving drones for the DOD — $1.6M already sold

Speaker 3: Can we get

Speaker 2: Tyler in here?

Speaker 1: Focus on counter drone protection. Yeah. Yeah. In between the next steps, let's slot in some Tyler for sure. Anyway, we have Russ Smith from Nine Mothers in the TBPN UltraDome in at YC Demo Day. How are doing, Russ? Hey.

Speaker 3: Good to see you. It's been a long time.

Speaker 1: Been way too long. Thank you so much for taking the time. I'm glad we can make this happen. For those who don't know you, introduce yourself. Give us a little bit of the the YC history, the entrepreneurial backstory, how long you've been an entrepreneur, and then take us through the current company.

Speaker 3: Yeah. I mean, I was an entrepreneur before I did YC. So like in in The UK. Yeah. But got into YC in the same batch as you. Yeah. That's how we met in summer twelve. Yeah. The batch that basically broke YC at the time and made them rechange it.

Speaker 1: 70 companies looks 30. Yeah. Yeah. You can can tell it.

Speaker 3: Yeah. It scaled and then they decided to change how it worked and it's the genesis of how they do groups now. Right? It was basically a free for all at the time where the loudest companies or the most like intense ones would get the most well, deliberately the most attention, but would would

Speaker 7: Yeah.

Speaker 2: It's sort of natural.

Speaker 1: Yeah.

Speaker 3: Yeah. Get the most love.

Speaker 1: Right? It's funny because it was the YC batch that broke YC. Everyone said, oh, YC's over. It's it's, you know, it's gotten too big. It's and then it was like Coinbase, Airbnb, or Coinbase, Instacart, Zapier, couple other companies that came became huge. Clever. Clever. Yeah.

Speaker 3: Benchling. Benchling. Benchling.

Speaker 1: There were a bunch of great companies.

Speaker 3: Bunch of decacorns and unicorns

Speaker 1: in that batch. Was good.

Speaker 3: So And soy one as well. Right? Yeah. Yeah. As in I remember going to your going to your Tenderloin office and carrying bags of your early product out in little bags.

Speaker 1: 1,500 a month for three people live in San Francisco.

Speaker 2: Oh, it's hard to remember. Remember that. It was guys a bargain. Didn't you move in there when you had like $818 or something?

Speaker 1: Yeah. I think we had like $20 left in the bank.

Speaker 2: And you're like, good. It's the last us like eighteen months.

Speaker 1: Yeah. Yeah. Yeah. We paid our rent a year in advance, owned our laptops. We just had to pay internet and food and that was it. It was pretty

Speaker 3: And then that's where Soylent came from. Right?

Speaker 1: Yeah. It's

Speaker 3: like Just eat that. It's cheaper.

Speaker 1: Anyway, we're not here to reminisce about the old times. Tell us about Nine Mothers.

Speaker 3: Yeah. So we make AI mission systems for the DOD, and our first product is Counter Drone. Okay. And we make a very small robot. So it's 35 pounds. We sell it for about a 150 k.

Speaker 7: Okay.

Speaker 3: And it's capable of defeating multiple fast moving drones day or night.

Speaker 1: Kinetically?

Speaker 3: Kinetically defeat. So yeah. It's basically a gun on a robot. Okay. And then we build all of the models for day, night, builds acoustic sensors, build models for that, and then basically capable of shooting down small fast targets.

Speaker 1: Interesting. Is it Can we pull up

Speaker 2: the video? Because I have no idea what this robot looks like.

Speaker 1: Yeah. Let's pull up the video. You know, put it

Speaker 3: with you. Narrate it. I have it.

Speaker 1: Oh, yeah. Yeah. We'll we'll we'll have the team pull up the video. I'm curious about the decision around acoustic models versus video models. There's so much energy around We do

Speaker 3: all of it.

Speaker 1: You do

Speaker 3: all And of so like the the key here is that no sensor is perfect. Right? Yeah. And so multiple sensors gives you more chance of Yeah. Finding something. And then for instance, acoustics is bad on some of the projects we're doing that are around turbines

Speaker 1: Yeah.

Speaker 3: Right? On Chinooks or other vehicles because it gets drowned out. But then radar is bad in some environments, and vision is bad in some. So the fusion, the ability to fuse all that together into coherent picture and also adapt to new sensors means that we can stop more things.

Speaker 1: Right? Yeah.

Speaker 3: And the key here is that this is kind of like the same problem that you saw in Iraq with or Afghanistan with IEDs. These are just now flying IEDs and all the demos you've seen, existingly, almost all of slow moving targets. So like sub 10 meter a second, sub 10 mile an hour, in some cases drones, people are struggling to shoot down. Mhmm. And that's just not reality. Right? As in we we've been shooting and demoing, as in we we shoot faster internally, but demoing 65 mile an hour small drones repeatedly. Like and that's way closer to reality, if that makes sense.

Speaker 1: Where does the name come from?

Speaker 3: Dude, it's it's North Norse mythology. Oh. So we're we're nerds and then our our product names are all around the same mythology. Okay. I like it. And so naming's hard but, yeah. That's that's where it came from. That's the story.

Speaker 1: That's good. What what does it actually shoot? Is it shooting like five five six like some commodity round?

Speaker 3: We can adapt to anything. As in we can do five five six. But the the thing that works the best is 12 gauge. And so we make our own we use a gun off the shelf at the moment. Mhmm. We're also developing our own belt fed shotgun system, like, as in the world's first belt fed. And that will be first firing in the next three weeks. Yeah. We also make ammo. Right?

Speaker 1: You make ammo?

Speaker 3: Yeah. That it's basically closer to match grade, which is like tighter tolerances Sure. And then slightly higher pressure. Oh. But owning everything, like the full stack, that means it means we have better results as a

Speaker 1: short version. So where races

Speaker 3: and blades for defense. Right?

Speaker 1: I mean I mean, you're you're obviously a very experienced founder. Where's the company right now? Do you already have facilities set up, a staff hired? Like, I imagine that you're pretty far along.

Speaker 3: For YC, we're a little later on.

Speaker 1: Yeah. So

Speaker 3: we are we've sold like $1,600,000 of stuff to the DOD as in direct sales of units, not not research and dev stuff Sure. Like actual sales. Delivered units to DOD, and then we're expecting to sell over a 100 units this year and a thousand next year. Have multiple believable parts to both. But, yeah. Aim is to do over a 100 mill of rev next year, and it's looking completely believable. Should hit 50 this year.

Speaker 2: There we go. Super impressive. Question for you. How let's say let's say there's a frontline Mhmm. And you set up a you know, I imagine, you know, let's say US Military sets up a bunch of these drones are flying over. How do you manage friend like It's a friendly fire. Like let's say a drone passes the line, there's actual troops back here and you wanna take out the drone but you're effectively shooting rounds into the air.

Speaker 3: Great question. And the the it's a complicated answer. And it depends on the mode the system's in. We can ignore stuff that's flying away from us and only prioritize stuff that's coming towards us. We can also take signals off networks they have if they know which drones are theirs. Really, the the common thing is that they don't actually have that kind of data. And so the operator can choose to not run it full automatic and then choose which targets. But mostly they will shoot them because of blue on blue risk. If it's not drones, they are physically flying in the same group.

Speaker 1: Mhmm.

Speaker 3: Right? It's that's the problem is is it a friendly drone that's misidentified you or not? If it's on a network and we know it's not, has it still misidentified you? That's where you get into the problem of this at this kind of range. Right?

Speaker 9: Mhmm.

Speaker 1: Well, congratulations on the progress. Exciting growth. Great to

Speaker 3: catch Congrats to you on the Come back on

Speaker 1: our show, and we'll talk more soon. Have a great one.

Speaker 6: Yeah. See you. Great to catch up.

Speaker 1: See you soon. Goodbye. Let me tell you about CrowdStrike. Your business is AI. Their business is securing it.