This Week in Startups - How Founders Are Building the Next Great Startups | Paid.ai, iTruckr & Tenax AI | E2175

Episode Date: September 9, 2025

Today’s show:In this TWiST founder triple-shot, Alex digs into the real-world rollout of AI agents: Paid.ai’s Manny Medina explains agent economics and value-based pricing, iTruckr’s Camilo Ramirez shows agents booking loads and coordinating drivers, and Tenax’s Elise Myrans demos computer vision + drones that score a single home’s wildfire/flood risk for smarter underwriting—plus live office-hours on winning enterprise pilots without getting stuck in PoC purgatory.Timestamps:(00:00) Brainstorming hacks for sales cycles in regulated industries — castles, moats & alligators!(03:50) Meet Paid.ai: tracking costs & monetization for AI agents(04:35) Paid.ai’s Manny Medina on the “year of agents” & early enterprise traction(09:04) Netsuite - Download the ebook CFO’s Guide to AI and Machine Learning for free at https://www.netsuite.com/twist(11:06) The tough economics of AI agents vs SaaS — margins squeezed by tokens(18:20) How Paid.ai gets granular: tracking signals & agent activity with OpenTelemetry(21:20) Coda - Empower your startup with Coda’s Team plan for free—get 6 months at https://www.Coda.io/twist(29:16) Enter iTruckr: Camilo Ramirez brings AI dispatch to the freight industry(31:43) .TECH: Say it without saying it. Head to get.tech/twist or your favorite registrar to get a clean, sharp .tech domain today.(39:02) Scaling from small fleets to mid-sized trucking companies — lessons from AI Trucker(55:59) Tenax ai helps homeowners & insurers manage wildfire, flood & climate riskSubscribe 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:(09:04) Netsuite - Download the ebook CFO’s Guide to AI and Machine Learning for free at https://www.netsuite.com/twist(21:20) Coda - Empower your startup with Coda’s Team plan for free—get 6 months at https://www.Coda.io/twist(31:43) .TECH: Say it without saying it. Head to get.tech/twist or your favorite registrar to get a clean, sharp .tech domain today.Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck 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.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

So we need some vanguard here. We need some early adopters who want to get early access. So great. Let's get some of those going. And then the question I would put, this is something I'm loving, brainstorming around right now, are different ways to hack sales cycles and really regulated industries that are slow moving, right? So in that B2B space. So I love talking about this.

And I don't think you and I have talked about it. I would love to hear your thoughts on that. You know, there's a tough one. You know, whenever you go into education, let's say, or you go into housing, as you are, healthcare, these are some of the giant castles that are hard to scale. We've got moats around them, they got drawbridge, it's got alligators in there, got arrow slits. It's not fun. This weekend startups is brought to you by dot tech.

Say it without saying it. Head to get.com slash twist or your favorite registrar to get a clean, sharp dot tech domain today. Coda. Cota empowers your startup by bringing words, tables, and teams together. Strategize, plan, and track goals effectively with all your valuable data in one place. Go to coda.io slash twist to get started for free and get six free months of the team plan. And, NetSuite. The business landscape is very chaotic right now.

That's why you need NetSuite by Oracle. Download the CFO's guide to AI and machine learning for free at netsuite.com slash twist. Hey, everybody, welcome back to Twist. This is Alex. In today's episode, it's all about founders. We are talking to three different startups that are each taking a very interesting tack on the world. We're going to dig into what they're building, why, and how it's going to move the needle. First up, we're talking to paid AI, or just paid if you want.

They're a Twist 500 company working in the world of AI. agents, but unlike your Cierras or other companies that want to build an agent for you and deploy into your company, this is all about helping the companies doing the actual building. So what paid does is help companies track how much money their AI agents cost by checking their number of prompts and which models they're using to get a good idea of what they're spending, and then also helps them with AI agent billing. This is the kind of picks and shovel's work that often doesn't get quite as much press as the open AIs and anthropics of the world. But if we are going to bring AI agents into the enterprise into the world of small business, well, paid.

could have an absolutely huge business. Think of it a bit like, I don't know, Twilio, but for AI agents to make a very loose comparison. An absolute treat of a chat, you're going to love it. Then we're talking to the founders from I-Trucker. Now, the world of trucking, you may not know much about. You may not drive an 18-wheeler. If you do, shout out, but most people here, I don't think are doing that. So why do we care about trucking? Well, what I-trucker learned is that the world of truck dispatch freight management and all the relationships between individual truck drivers, truck owners, dispatchers, and loads, is kind of run by phones. It's not very efficient.

So what they've done is built an AI tool that helps all the communications be done simply, easily, and quickly from devices and services people already own and use. I love this company. I love seeing technology applied to kind of like flesh and blood industries. You're going to love it. Then to wrap up the day, 10x AI. Now, if you think about climate change from a risk perspective, what does that mean? Well, you might be worried about increased wildfire, risk, increased flooding risk, extreme weather

in general. And what 10x AI wants to do is help people both make their homes more resilient and also provide good information to insurance companies to make sure that they're doing intelligent underwriting. You don't want to underprice risk and then get your face ripped off. And also, if you own a house, well, you probably want to know what your risk is so you can go about mitigating it. 10XAI is super interesting.

It's a company that I'm paying a lot of attention to. I think you're going to dig it. So with all that said, let's dive in. And we're going to start with paid.AI. Let's go. AI agents. 2025 is supposed to be the year of agents, or at least the year that kicks off agents

as a common tool for companies to help automate their work. But while companies are working to integrate agents into their workflow to try and make more money themselves, what about the companies building AI agents? Are they making money? We know that major foundation model companies like OpenAI and Anthropic are seeing the revenue soar, but at the cost of huge burn, so the question really does matter.

One startup has its eyes fixed on the question of AI agent economics. That company, Paid AI, wants to better track AI agent costs and help with monetization so that the work of making autonomous AI tools can prove profitable for both the provider and the customer. To tell us more about paid and the state of the agentic economy, please welcome to the show. It's Mani Medina, co-founder and CEO of Outreach. Mani, hey, how you doing? I'm awesome. Good to see you. Thanks for having me.

You get 10 points for having your logo behind you in neon signage. That is fantastic. I have to ask, how long after the company was founded, did you guys get that made for your podcast studio? So the company was founded around January this year. We broke code in, you know, towards the end of January, February. And, you know, we've been rocking since. We have, you know, we started with pilot customers and that we now have close to 20 of them.

and we just landed our first enterprise customer last week, so we're super excited about that. And the neon sign was a detail that the team brought together. It turns out they're very easy to make. I didn't know how easy it were to make, but they're fantastic. Turns out there's actually just a bunch of services that'll make them for you.

But it does make you appear to be incredibly legit. I want to get into customer growth and the exact thing you're building in a second, but I want to just set some foundations here for folks. people have said, like I said in the intro, that it's the year of agents. What I'm curious from your end, Manny, is how many companies are really in the market today that are building AI agentic tools that they're taking to customers and therefore need what you guys have built?

But how many companies have reached that level of maturity, if that makes sense? So the agent market is incredibly early. And it's incredibly early in that anyone can build an agent, but very few can build an agent that is solving a problem for somebody that is willing to pay for it. That said, because agents are actually being sold, the majority of the agents that we're seeing are being sold into non-tech spaces, you're not going to hear about them. You're not, you're going to hear about them when, you know,

when your plumber tells you that it was the agent that they scheduled their appointment, and it was the agent that I told them that he needed a part. Or whenever your architect uses, you know, an agent to figure out the cost of the house you're about to build. Sure. or, you know, the mortgages are going to be performed completely by agents over the next, you know, in the next year or so. So it's a little bit like taking the red pill that once you take it, you can't unsee

what's happening out there. And we all here took the red pill and our agents in every single nook and crown of the economy. They're just getting started. Some of them are not yet quite monetizing. Some of them are just, you know, out there, you know, getting market share. But the great majority of them are fine-tuning the agents to work precisely well in the industry, which are deployed, which is incredibly exciting because it's opening an opportunity for people who are not traditionally in tech to be in tech and make money.

To use technology tools. Yeah, no, that makes good sense to me. Do you think we're going to see then agents make their way into technology companies more generally this year, next year, when does the other part of the economy come onto the agent side of things? I think that the, usually the way the economic cycles work with innovation is that, you know, software startups, by from other software startups, and you go up and down one-on-one and that's a majority of your market,

and you try to expand from there, and that's when you cross the chasm. I'm seeing it all the way around. I'm seeing, you know, real American, you know, real business companies that are already jumping directly into agents or bypassing the whole cloud thing and going directly into agentic purchases.

And companies that you will think have no business being an agent, such as freight forwarding or supply chain or fleet management or mortgages or insurances. They're all going directly to agencies. And there's two reasons why this is happening. One is because their workforce is aging out. And they found agents as a way to not have to go and retrain, new kids to become actuary who they may not want to be.

The other one is the fact that the comparison of an agent is not against other agents or human beings. It's against BPO's, which are human beings. But the, BPO's are business process, outsourcing jobs, people that will do the busy work for you offsees. 100%. Exactly. Exactly.

And an agent compared to a BPO is incredibly more efficient, more effective, and higher performing. So that's sort of like the table stakes right now of what's going on with agents. And that's a very rich market to go after. And we're going to see that for the next five years until we start seeing other effects of agents in the marketplace. Founders know you can't plan a future strategy for your business. without having the most up-to-date and accurate information possible. Listen, nobody's got a crystal ball,

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So agents are here today, often in places where you can't quite see them. You're optimistic about their ability to improve and expand their market share. So this is the year of agents, year one. I guess I should think of it. we're going to get to the end this year, but certainly we are accelerating towards an genetic future. Fair enough? 100%. You just planted your sparagos field, and they're all sprouting. So all you're going to see is sprouts. Next year is going to be a nice, bountiful harvest. Okay. Let's talk about where

paid fits into this, because everyone knows in a traditional SaaS context, software is very margin efficient. You can have gross margins in the 70s, 80s, some cases even low 90s. One reason why everyone loves it. AI, on the other hand, is often more expensive to run. And I presume that when you build an agent that has a foundation model from a third party inside the core of it, it's expensive to run as well. So can you just tell me what the economics look like for the average company selling agents for those products? How much do they cost to run? And if you can, before a paid game, and how are they tracking those costs? So the difference between a normal SaaS company, like a SaaS company of the, you know, 70 to 80% gross margins.

And an adjutant company is exactly what you talked about. Is it the cause of inference and the cost of tokens that are paying to the L, to the foundation model provider? And those go on top of your cloud cost. So now you have your 80% cost and you have the additional cost of, you know, pretty much the human replacement. So whereas a SaaS company will have, you know, 70 to 80% of gross margins, an agent company would have somewhere between 40 and 60% gross margins.

And that will significantly, and then that's problem number one or sort of situation number one, situation number two, and that is incredibly variable depending on the type of customer. So for instance, you can have a customer, if you're in customer service, you can have a customer that calls in and you quickly, you know, tell them the answer to what they're looking for and on they move. Or you can have a customer that calls in and they tell you the story of their life, they ask you a bunch of questions that are not relevant to what they're trying to get resolved. And then they ask you the question about they're trying to get resolved.

And you just got a free chat session with that person. And that costs you a ton of tokens. You're paying for all the tokens. You're paying for all the tokens. Exactly. So really, the more terse versus verbose your customers are, if they're chatting with your agenetic product, the more money you can make. So really, that does imply that you want to get to value very quickly in those interactions

to prevent excess token generation. 100%, but there's no way for you to predict it. The customer the service is out there and it's performing. I mean, the same thing is for agents that do document reviews. So there are some people who have short histories and some other have very long histories. And for the very long histories, that's just going to consume a lot of tokens. The same thing for people who are, you know, performing complicated tasks. The more agentic the behavior is, the more autonomous.

The more agency an agent has, the more likely it is to run off the right. rails and go to something that you are not expecting it to do. And it may be for good reasons, but you just don't know. And that's sort of the trade of that we're living in right now, which is a fascinating thing because you're giving them the ability to decide. And that's very exciting. It's very excited that they can decide, but you don't want them decide to spend your entire checking account on, you know, anthropic credits or whatever. 100%. Okay. Now, a question that I have is, do some agentic systems use multiple AI model providers? Because when I was thinking about the problem you guys are solved,

it seems like it would get even more complicated if I sometimes lean on GPT5, sometimes on GROC 4 and sometimes on, I don't know, Claudeaupe is 4.1. They do, but they don't do it for economic reasons. So if you think about every single model

from every single provider, they have different behaviors. They have different tendencies. They may answer the question completely differently, even if they're provided by the same vendor. So you don't know, because it's all a black box, you know, whether you can, you know,

hard replace, you know, son it with, you know, any of the versions of GPT. And whether that's going to work for you or, you know, Gemini, et cetera. So they, so there are definitely ways for you to arbitrage the token cost, but you have, but the tasks need to be relatively simple and relatively swapable. In which case, you may not even be solving the right problem because it will be an agent company out there that will take your problem, bundle it into a bigger basket of problems that are solving it and make you irrelevant.

So it's a very dynamic environment right now where there is no, free lunch for anybody, right? Like, if you're making a ton of money, you can rest assured that there's four YC startups that are going to come after you with a much better model that is going to solve a bigger problem you're solving in your roadkill. It's the old Bezos quote, your margin is my opportunity, right? Oh, 100%. A hundred percent.

At Amazon, you know, people used to live with like somewhere between, you know, six percent and 20 percent operating margins. And it was a good day when you hit 20 percent because people got a lot of books. But on the day that they bought a lot of electronics, you could be upside down. So you have to be really careful on how you operate. This is why, you know, most of the companies give you free coffee at Amazon. You got to put your 25 cents in the little jar before you put yourself a cup of coffee. I didn't know that, but that was my experience at the headquarters of State Farm once.

I got there after going to a lot of Silicon Valley offices. And I went to the little cafe. They're like, that's a dollar. I'm like, what? This outrageous. There you are where your Silicon Valley entitlement. We're helping for a free latte. And that's a use have to say.

It wasn't even a latte man. He was just a black coffee. But that's what you get for going to Southern Illinois. That's what you got. Okay. So clearly you don't want to undercharge for your agentic work because then you're upside down. That's terrible. So talk to me about how paid helps people actually sort out the discrete costs per.

I'm not sure the phrase here. Agentic interaction, agentic use case, where the rubber meets the road, if you will. Yeah. Yeah, so if you think about the dynamics of pricing, pricing has roughly three components. One is your cost. So you clearly want to be above that. The other one is what is the equivalent of the service that you're providing? How much would that cost?

And the iteration that we're living right now, that equivalent for the agentic cost is a human being. So you can easily compare, you know, what would a human do take to do the same work? And the third one, of course, is a competition. Like, if somebody is doing the same thing that you're doing and they have a different you have to be solely in the same ballpark of that. So what we help everyone see is the fact that, you know, A, we help you see your cost, but B, we help you understand what is that the agent is doing so that when you pitch it to your customer, the customer can figure out, out of all these activities the agent is performing,

which ones do they attach the most value to? And you can charge for those. And this is the change in mentality that we are embracing, we're actually asking our customers embrace is that you don't need a consistent price sheet for all your customers. What you do need is to make sure that your value aligns to the customer perceived value receive. Once those things match, that's where you should price. You shouldn't price in a way that is simple to you. You should price in a way that is consumable by your customer, in a way that your customer perceives, they're getting value. And that's what we offer. It's a flexible platform that understands what the agent is doing and allows you to

the value in a way that the customer wants the value to be captured. Okay, so that's two parts. Let's stick with the cost tracking. I was going through some of your developer docs, and you guys talked about signals as a concept of like breaking down work. I guess what I wanted to know is how granular can you get on tracking either an agent for a customer or an agent doing a task for a customer. Can you get down to the sense that it costs?

So what we do is just to get technical here for a minute. So we found out that the entirety of what you need to understand of what the agent is performing is in the runtime code of the agent. So once the agent executes this code, there is this egress that comes out of the code that is the runtime. And that could be captured by a technology that is open source called open telemetry. Open telemetry allows you to decorate the code and then see the entire egress of the execution. The eagris of the execution is like, imagine.

somebody's walking around right next to you, clocking every activity that you do and taking a note. Every time you drink coffee, I clock it. Every time you do a podcast, I clock it. You go take the kids, I clock it. And now you have a catalog of everything that you did today. And now you can choose what are you going to charge for and what are you going to show, right? And that's what other technology does. And once you do that, then you can go around and buy customer.

So if a customer bought your agent because it saves them time, if a customer bought your agent's because it shortened times to value to their, customer. You customer are your agent because it delivers higher MPS, you can charge for those things because you can see it. Okay, so you can get very, very granular and you can decide what to charge for. Are you pushing us towards a world in which each customer not only pays a different price for what they're getting in an agent context, but it could also vary based on the specific task that are putting to it in that moment? Is that responsive to the customer asks of the service? Absolutely. So let me tell you an actual exact example.

Okay. We're working with customer service agents for car dealers. And it turns out that this car dealer customer service agent is blowing up in the Middle East. And the work perform is the same. So they take an inbound lead. They convince it to come into the showroom. They get more information about the kind of car they want. And once it becomes a customer, they sort of try to get them in

for services and for up sales, right? So it turns out that the same customer, the same activity, sorry, not the same customer, the same activity the agent does, if that person, if that activity is performed in South Dubai, and you get a customer in into the Beamer dealership, the likelihood of they walking out with a car is in the 90-some percent. Why? Because they have a lot of money if they like the Beamer, they walk off with it. Versus North Dubai, where the likelihood of they walking out with a Beamer is a lot lower because

they tend to be a lot cheaper, a lot more price-conscious, and then go from dealer to to define the right price. So driving a lead into the store at the South Dubai dealer is worth significantly more to the dealer than it is driving a lead to the North Dubai car dealer. And how do you capture that value? Even though the work is the same, the value is significantly different.

And you want to capture that. Founders, you got a lot on your plate. You're running a company, and that means you have endless tasks to get done, and you're juggling a ton of priorities all while trying to hit. your KPIs. That's why I love CODA for keeping everything under control. It's the all-in-one platform that consolidates your documents, your spreadsheets, your apps, into a single, scalable

workspace with a beautiful, intuitive UI. Coda helps define planning sessions so you don't lose focus, and it creates flexible agendas so you can adapt to shifting priorities. It's going to help you set your OKRs, and you get access to hundreds of templates for tasks like setting priorities and mapping dependencies. We use Coda Every Day at Twist for important projects like the Twist 500 and Founder University. It's truly an all-in-one hub for startups. Head over to coda.io-slash-Twist right now, and you're going to get six months of the team plan for startups for free.

That's C-O-D-A.io-S-T-W-I-S-T to get six months of the team plan for free. Coda.com.com. slash twist. But if I'm the dealership, I want to pay as little for this as possible because I want to make the most money that I can. Am I going to be content with you coming to me and saying, all right, listen, Manny, if it's a South Dubai IP address, then we're going to charge you X dollars. And if it's a North Dubai address, we're going to charge you Z dollars. And I'm going to be like, wait a minute, it's the same work. Why do I have to pay more for it? Am I not just padding your margins? This feels like search pricing in the micro sense for each.

each customer interaction, which feels almost egregious to me in a way. Maybe I'm just being too cheap here, but many, I feel, are people complaining about that at all or are they fine with it? No, I think that it drives a conversation around value again. So if you're a dealer, let's take a step back. If you're a dealer, not an influencer, a podcast or host, like if you're an actual dealer, your job is to move cars off the lot. Yeah. Full stop, right? And you make money by moving certain cars of cars off the lot.

So whether the agent charges you more for, because you happen to be the South of I one versus the North of Y one, it may come into play in the conversation, but at the end of the day, if this agent moves cars of the lot, we're having a conversation and it's going to be a productive conversation. Okay, so I was really thinking too small things, because I was thinking about SaaS pricing, you know, recurring per seat, whatever. People moved into in the Twilio era, you know, pay for what you use. In this case, though, we're kind of moving to a new iteration, which is pay for demonstrated value, I suppose.

Exactly. Exactly. And just think about that. Like, if you are charging for the fact that you move the car of the lot and you are not charging for the 20 other conversations that didn't result in moving a car of the lot, there's a lot of economic unlock in that kind of pricing. I'm not suggesting that that's the way you go, but I am suggesting that that is well more aligned to both parties and how both parties can realize value than some kind of seed pricing in which, you know, you may have a person using

the tool that may or may not move cars of the lots. So you just said that when you manage a transaction when you pull off a transaction via an agent, it's a success, but you might not get paid if it doesn't lead to a sale. So are we going to see a world in which some agentic products only derive revenue when a customer completes a transaction on the other end and then otherwise it'll be provided for for free? Yeah. That's it that's entirely in the cards. Wow. That's super aligned. But also it sounds very complicated given you'd have to have so much information about you'd have to know that you're, you know, there's a split in Dubai. You've draw the line here and you'd have to probably defined in sort of some billing system. So has all of that technology been built that will need,

or are we still working on building the scaffolding up to provide the granular information you would need to be so detailed on your pricing? No, so that's what we do. That's exactly what we do. So we eliminate it. So we built and paid from the principles of what are the future interactions going to be like? And once you decide what the future interaction is going to be like, then you need that kind of flexibility. You need to be able to provide. You need to be able to provide, Like, again, I'm not saying anything new here. Like, you should be able to provide the value and deliver the value that your customer scares about and then charge for it.

But as it turns out, every customer is in a different, it's in a different path. It's in a different value perception curve. And they should be able to pay in the way they want. And like, what we have done in the last 20 years is convince the software vendors that because we're so powerful and so magical that we can charge this arbitrarily per seat thing because it's really hard for us to like otherwise scale the pricing. And I think that's a big bag of lies. I think that in the end of the world, software is very cheap to build

and you should be able to build exactly what your customers need. And like your inability to scale custom pricing doesn't seem like it's your customer's problem. That seems like a you problem. You should really fix it. Yeah. Okay. So in the future world then,

let's say that I'm selling an agentic product to a Dubai dealership. Do I have like a forward deployed engineer? that's helping them, you know, dig deep into their granular business to define the right pricing set up for them? Or is this something that's automated enough that a dealership could set up a relationship with an AI agent vendor without having to do a lot of custom coding work to make their iteration function? Because I feel like if it's the latter case, your business is going to be much bigger. If it's the former case, it's going to be slower growing. I think that a lot of these rules are going to be baked in. So like as one of the things,

that is beautiful about this agentic world, is that we're truly embracing services because we're replacing services. But as you embrace services and replace them, the kind of services you provide is higher level. You see what I mean? So instead of like doing forward deployed for, you know,

hooking up the agentic workflow that is going to do discriminatory pricing based on your location, I think you will do some other kind of services around, you know, you know where car dealers actually make money is on the trim, is on the services, it's on the absolute sell. So like the idea, then you're going to really have your juices flowing more into like, okay, so what kind of marketing program kind of run to get people back in here? You see what I mean?

Like, how can I elevate the trim? The moment you're falling in love with that red beamer, how can I sell you the one with a spoiler and the one with like, you know, more horsepower? So those are the kinds of things that you're thinking about that this kind of like, you know, pricing on locks. Well, I was really excited to talk to you because I feel like you were attacking a really interesting problem point in the AI economy today, figured out what it cost to run an agent and also how much to charge for it. I didn't realize, though, Manny, and this is so glad you came on, just how detailed where you're going to need to get and also how good that's going to be for the end customers. But what this does do is put a lot of pressure on the AI agent companies,

because if we're going to charge only for really defined value, they have to build high quality products that really get there. So I guess, I guess good luck everybody building because there's going to be no, you have to get signed up for a thousand seats to get the enterprise, you know, you know, SSO or whatever, you're going to have to really be good everywhere. 100%. 100%. But, like, isn't that the way he's supposed to work? Are you, like, I mean, I'm saying this is bad.

I'm saying it's exciting. So why will you go to a doctor that is okay versus the doctor who actually fixes your problem? The website is paid. com. Many, thank you so much for coming on. We really appreciate it. And when you hit 100 million ARR in like 40 months, just call me up and we'll talk again. I'll dial your write-up. Good to see you.

All right, Jason, speaking of founders, we have one literally waiting in the wings. I'm incredibly excited to bring Camillo Ramirez. He's the co-founder and CEO of I Trucker. Now, you know this company, Jason. It's based in Pittsburgh. It was in Launch Accelerator 34. And it's working on helping trucking companies do more using AI agents. And what's cool is, Camillo is not just another Stanford graduate out there trying to sling code to a market. No, he's actually driven trucks on a cross-country basis, both dry and, as he says, rifer, which means refrigerated. Camillo, welcome to the show.

Hey, nice to see you. I was absolutely in awe of your performance. You did a great job of presenting in the accelerator. And yeah, sometimes domain expertise is great. Sometimes domain expertise can ankle you, but sometimes it can give you an unfair advantage in the space. So what have you learned in that aspect? And maybe start with telling us what your insight was.

as an insider of what needed to be built here. That'd be a good place to start. Sure, yeah. Well, thank you guys for having me here. Appreciate it. Yeah, former truck driver a couple years ago where I understood the pain points of the driver when you're driving over 600 miles per day.

Then you're stuck with a flat tire at the midnight and no one is there to help you, right? So then we had the opportunity to own our fleet. We ended up with around like 15 trucks where we saw the problem from the other side. So at the time, we had, you know, 15 drivers calling us asking for a pickup number. Then we have 15 customers asking like, where's my load? You know, like, is you going to be on time?

And it's a 24-7 business. So we understood that in order to build something to improve this kind of like activities, coordination on a single basis, we needed to build something that is able to be part of the operations team. So basically that is able to talk to the drivers, to talk to the customers, to brokers, forward information. We have a ton of paperwork going around. So, you know, reading those documents

and forwarding the right information to the right party. So we learned that we needed to build this bottoms up in order to get to the trucking companies and put our service within their operations. You all know I'm obsessive about a good domain name, and I'm so proud of my exclusive collection of single word. Easy to spell.coms from begin.com, inside.com, Mahalo.com, a day.com. But the truth is, the supply is dwindling.

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It's time to move over to dot tech. So head over to get. Dot tech slash twist, GET. dot tech slash twist. So when this was done prior to your product, I trucker, which is IT, R-U-C-K-R, drop the E, for elite, you found there are dispatchers.

Dispatchers are cramageally humans. who have to get on the phone with all these parties and yell at the drivers and manage the people who are, you know, sending a load across the country and their chain smoke in Marlboro lights and some boiler rooms somewhere. And they're getting paid a large amount of money

to do this essentially air traffic control for trucks, yeah? Correct. Where do they get paid? Yep. So there are like two different ways on how that operates. So we have like some fleets. They are they are able to like bring those dispatchers like in-house team of people. So it's a little bit cheaper for them because you're hiring like a full-time employee.

But then there's a lot of trucking companies that use like dispatching services. So those fleets are able to, well, they're not able to, you know, bring a full-time employee. So they're paying like a portion of the revenue of the. Oh, that sounds expensive. Yeah, it's pretty much expensive. If you have like 10 trucks, you know, you're making 100K. So what was your solution then? You, I know you had an AI first solution to this.

So what did you build? And how has it worked? Yep. So we are deploying A. Workers, A fleet, within those operations. So basically we are automating the communication. So now a trucking company, instead of having like three dispatchers, to dispatcher a fleet of a fleet of 15.

20 trucks, they probably just going to need one because we help them with like booking loads, right? So now our agents are able to go to different load boards, find different option of loads, make the phone call, send email, book the load, then... And that's being done by an AI agent that's calling on the phone using voice or text voice, I guess, and you've built all these sophisticated AI agents. And they occur as a co-pilot where they're superfileged. or are they stable enough to deploy them and not have a human in the loop or a human checking them?

How does that work? Because we've heard a lot with this MIT study. Oh, my God, you know, AI doesn't work. Obviously, co-pilots work really well. Agents, people do have concerns. So, yeah, unpack that piece. Yep. So we right now have, well, they have a dashboard where they can see, like, the whole operation.

So they can see, like, how the AI is talking to the drivers through text messages. They can see, like, how the email. is replying on a lifetime, then they also have the option to, to like stop whatever the AI is doing or the AI suggests a few things. So let's say just to give you like a specific workflow. So they have a truck idling for six hours. So the AI notified the dispatcher or the fleet manager saying, hey, we have these drivers in this location. It's idling his truck for five hours. You want me to find a load. So they just approved the option. And then the AI go, find the load. book the load and notify the driver and notify the dispatcher saying like, hey, I found this

based on the metrics that we already have set up. Camilo, how do you get that information? Is it IoT that lets you know that this truck is idle for five hours? Because that's a very specific actionable data point, but you can't, you know, have a human looking at GPS data. So how do you get that nugget? Yeah. So in trucking, there's a system called ELD, which is an electronic logging device, where

Every single truck needs to put a hardware into their trucks to see where they add to, for this hour of service that the driver can drive. They can just drive 11 hours per day. So they have this GPS tracking kind of thing. So they have all these telematics, like, you know, field consumption and all that. So we are integrating those ELDs into our system. So we are able to see where the truck is, how fast they drive, if they have, you know, enough fuel to get to deliver location.

The truck drivers have no privacy. They can't stop and like have a couple of beers and drink or have a hamburger and take a nap and then go 75 miles an hour the next morning to make up for it. They're monitored like very granularly. Yeah. Yeah, exactly. So are they required to have cameras in the cabin too? Right. Yeah.

Some of them they put like cameras in front of the dashboard. Is that required now or is that like your trucking company decides? Is that like a federal mandate? No, no, no. That depends on the fleet and then depends on the insurance company. Some insurance are like, hey, you're going to record every single piece of the journey of the driver, but some of them they're just, you know, fleet. Which is why we now have this video tragically.

I don't know. You must have seen this of this. Did you see this last week, Alex? They have video of a lunatic truck driver who decides to make a U-turn on the freeway. And I think he had a double cab. I'm not sure if it was a double cab. Yep, it was the same way. It's so tragic.

He decides, oh, I missed my exit, so I'm going to use the U-turn, which is like the police U-turn. Yeah, in between the dual carriageway, the gravel bit in between, yeah. Yeah, and then he, because he decides to do this, a car can't stop and smashes into the side of him. And I think, tragically, two people were killed. I'm not going to play it because of that, but it's awful. It's awful.

And there's a video of his perspective on it, because you have. not only video of the driver, not only video of the road and everything and the review mirror, you have video of the driver and their reaction to it. Oh, yeah, yoy. Yeah, it was pretty tough.

What's your average trucker, how many trucks are the average customer review you guys have? What I learned prepping for our chat today is that trucking companies come in size from absolute pit squeaks to absolute behemoths. Yeah, so we started with smaller fleets, like one, three, four trucks operations. once we fully deployed the product,

we now are targeting like mid-sized fleets. So anywhere from like three trucks to 100 trucks. Those are the ones that are feeling the pain that they're having, you know, like four or five dispatchers, working 24-7, talking to drivers, talking to brokers. So those are the fleets that we're targeting right now. And we are focusing... How many of those companies are there in the U.S.?

I don't think a lot of folks that are listening to us right now have a good feel for how many mid-sized trucking companies there are out there. I presume it's a lot. Yeah. So let's say that in total we have over like two million fleets. That includes like box trucks and all kind of like flits. Then within the trucking, we have around like 800,000, right? And then within those hundred thousand, we have around around like 300,000 for midsize, like three to 100 trucks.

So there's like plenty of a room for us to play here. Awesome. Well, it's office hours. companies doing well. You got through the accelerator. You got customers. You're growing nicely. You're using AI to the fullest of its current abilities.

You're one of these companies that's like the tip of the spear in using this technology. But, you know, we're here. And there must be some things you're either struggling with or challenged with. Any questions for me that or anything you want to discuss? Well, now we are seeing a lot of opportunities. it is like an enterprises accounts, kind of like larger fleets, even like out of the country opportunities. Great.

So in order for us, you know, to stay focused on how we're growing because we're growing pretty fast, any tips on like how to handle both things, like, you know, like how we handle enterprises? Yeah. So the great thing about enterprise customers is that they will spend more money. and if they love your product or service, they're probably less price sensitive. The great thing about the small boutique, you know, smaller customers is they might be more scrappy and willing to try something, right?

Because they don't have the budgets. And, you know, that's why a lot of people will use startups as their first customers, because startups will actually use the product. Whereas if you go after the big enterprise clients, they take a long time to sell. they're going to need SOC 2, you know, so you're going to need to get in touch with Vanta, make sure your SOC2 is compliant and all that good stuff. And they just take forever, right? They might have a six-month sale cycle.

They may want you to build custom software, so they can be a bit of a headache. What's important is to study your customer-based. And if you're in a highly fragmented market, there can be many customers. What's a highly fragmented market startup that's done incredibly well? Spotify. They went after small merchants. There was Magento and other big products, you know, going after the large enterprises going after Target or, you know, I don't know, Walmart.

Maybe those companies are even too big. They build their own because it's so critical for the user experience. But they went after the long tail. HubSpot. They wanted, you know, small firms, Squarespace. There are big companies that use it. There are small companies that use it. So then you have to make a decision.

do you want to have a sales team? Do you want to deal with custom software? Do you want to deal with approval processes? And both can work. Obviously, there are Salesforce and other tools for large enterprises for sales and marketing functions, and then there's HubSpot. And this will inform a lot of product decisions

and a lot of go-to market decisions. Your go-to right now, I'm assuming, is founder-led sales. you email a small trucking company or they hear about it from another small trucking company, you get on the phone with them. And the person you're talking to owns the business, gives you their credit card, fills out a form, and you're done. Okay, so you get a nice quick hit.

But it might only be $1,000 or $3,000 a year. And you might start to say, you know what, I want the $10,000 a year customer. I want the $30,000 a year customer. So it really is going to determine. how you staff and fund your company. You may need more runway to go after that. So what does your gut tell you or what does your knowledge tell you about what type of market you're in? Are there a small number of large players and a long tail of small ones?

Are there plenty of both? So both business models will work? I don't know enough about trucking to know the answer to that. Yep. Yeah. That's pretty good advice. And right now we're seeing our product into this mid-size level, which is the sales cycle much faster because, like you said, the owner is involved. So it's really easy to show them the product.

Like, hey, here's the solution. They're scaling their operation. So it's really working right now. But then, you know, those enterprises comes and they're like, hey, I want to use your technology, not your product, but your technology to put into our current systems. So, but it's a different game, like you just said. So we will, you might need to price differently for them. And you then have one group that is easy, breezy. They'll just use your solution.

And like I said, the other group is, oh, my God, I need, you know, this custom thing. I need that custom thing. Can you get into our accounting system? And a way to do that is to say, yes, we can do it. It's going to require a $250,000 activation fee for us to build that. And we need you to pay up front. If you're willing to do that, we're happy to work on the project, and then you can hire two developers or a product manager and a developer, and you tell them, I will embed ourselves. You may have heard me talk in the accelerator or founder university.

Did you go to founding university too or just accelerator? No, just the accelerator. Great. And so I've told the story before about bear hugging a client, which is when you embed yourself at their company. So you could say to one of the big ones, I'll put a product manager in your company. your office for six months to sit with your team and to outline all these features. We just need 250K in advance. And that's for the first six months of this trial. And then afterwards, this is what the pricing would be. So you're kind of challenging them to not waste your time. The biggest problem

founders get into is that, oh my God, this is such an incredible lighthouse customer. And then some midperson there wants to get points. They drag you through different specs and dumps. documents and meetings, and then they try to sell it to their boss, and then that person decides they're going to leave the company. They get fired, and you lost your contact there. So you got to kind of let them have skin in the game. You got to say, listen, we're a small company. We're eight people. In order to do this, I need two more people. In order to do this, you know, I'm adding five new customers a month right now for the existing product. I just need you to, you know, make a commitment up front. And so how do you feel about a 250K pilot for six months?

And the person might say, I can't authorize that and say, oh, who in the organization can? Maybe we should have a meeting with them. And you just challenge them, you challenge them. And if they're not serious, you say, you know what, we're just resource constrained. We'd love to work with you. But we need to stay focused on this. Can we check in in six months? And boom.

Does that make sense? Yep, a lot of sense. Yeah. Thank you. So don't be scared of these customers. Look at how many employees they have in times that number by $200,000. So what's the biggest? the customers you've talked to who are the big fish, how many employees do they have? Do you even know?

Uh, where the thousand? Uh, where, yeah. So, a thousand times 200,000 is 200 million dollars. They're probably spending all in about 200 million dollars running that operation if they have a thousand employees. And if it's a public company, you can go find that out. But, you know, it's not that every employee is getting paid 200,000. It's that, you know, maybe on average, the employees cost 100,000 with their benefits, but they have. have to have office space. They have HR. They have turnover. They've got to recruit people. And you start just as a back of the envelope number for a mid-sized company, that. And then for a Google or for a Facebook, maybe it's 500,000 per employee. You can estimate what they spend. Alex, if you were to look

up how much money meta spends a quarter and how many employees they have ballpark and you were to divide those two numbers and he'll go do that in real time because he's awesome at these kind of things, you'll get a certain expense base per employee. It might be 500, 750K in total spend because they build signature office space. They have other kinds of infrastructure. They have consultants. Free food. Free food. All this stuff. You know what the free food bill is at those big companies? It's like 10, 20K per employee. Wow. The free food is so expensive that the IRS felt the need to investigate if they were end-running compensation by using their pre-tax dollars and giving an employee benefit, to which point the IRS said, hey, if you're going to spend $20,000 on perks for your

employees, we need you to pay tax on that because that would be the same as like paying for a corporate apartment, paying for a corporate car that's used personally. Like, they have to eat. That's on you to give that perk. And I don't know where that IRS investigations why. found up, but, you know, that's how crazy the spending they have per employee is. So I would- So far as we could tell Jason, you were very much close to debt on. 24, which is the latest full-year employee data, they don't drop it every quarter, about $550,000 in expenses per employee against revenue of $2.22 million per employee last year. And that's why Medda's a good business.

And that's why when they keep the team size the same and grow revenue 10 or 20% per year, the earnings increase, which is why people keep betting more and more money on the Mag 7. Listen, continue success. Camillo, hopefully we did a good job for you in the accelerator. Did my team work hard and support you? Absolutely. Yanker was great. We got a lot of connections, great connections, a lot of BCs, interest.

So it was really good, really good. What was the best part of the accelerator for you as a founder that you got the most value from? And then after that, what do you wish we would add to the program that would make it better for you as a founder? If anything, for a second to think about that, yeah. The best thing definitely is the pitch sessions, you know, like practicing this pitch, this two minutes pitch like every single week. So after that, like every time I have a meeting and I'm pitching and they're like, you're done. Like, well, you just covered everything because, you know, we cover the issue. what's the solution, his product, revenue, and that's it.

So that's definitely really, really... The pitching really helped you. Yeah. And Alex, well, we originally were at like five minutes of pitch, then went to three minutes, then we made it two minutes. There's a dozen companies. There's only 120 seconds, man. Yeah.

Well, here's the thing. You are making a trailer of your startup is what we tell the founders. Now, the trailer for Star Wars doesn't tell you, spoiler alert, that Darth Vader is Luke's father. It just tells you like, this is an. epic thing happening in space and there's lasers and there's ships and it's there's a wookie and you're like oh i want to know more about this movie that's what we try to accomplish which is oh wow this is a interesting founder or interesting founders and they found it's a really interesting market oh and

this is a really interesting solution oh and this is a really interesting tam oh and the competitive set is you know marge smoking those marlborough lights two packs a day you know yelling into a landline and who tells you to get the hell out of her office and throws the ashtray at you when it's filled with 20 cigarette butts if the boss comes in there and tries to give her a hard time. Too bad today is excessive smoking. If you're smoking too much, what's the side of you? I mean, I know these dispatchers.

These are crumudgeonly hardcore individuals. I love them. I knew them from the dispatch at Harbor Car Service in Bay Ridge, Brooklyn, where I grew up. because yeah there was like a large march there too who would yell and scream at people and get the hell over there pick up john the beards kids it's the middle one jason he's he's got to get to school he's late uh they give him a hard time okay what can we do better is there anything that you would have liked to add to it sometimes people ask for mentors i always felt the mentor thing was kind of garbage because they had these mid mentors but you tell me is there something that

we could have added to the program that would have helped you more i mean will yeah, the thing with mentors is that really depends, like, who's the one that is going to help us, you know? If it's going to be like a, you know, founder maybe, could be a good advice. But what else you can say? More money. It could be more money. Okay, sure. We'll double it.

Sure. Great. And more money to the program. Thanks, Alex. You just cost me more money. That would be a great opportunity to double the money. Yep. And, but now, for real, it's a really full program.

We really love the pitches, the introductions. I mean, we haven't seen programs like this one where you see every single week, five, six, seven different BCs and just not like associates, but also like, you know, the managing partner. And then he's the owner of the fund. So that adds a lot of value. To unpack that, Alex, you know, some firms do like this big demo day and they advise you, hey, don't do meetings with investors

before then. Just get your startup nice and tight. It took a different approach. I'm not saying the other approach doesn't work. It does to create like a bit of a marketplace at the end. What I said was let's pick our favorite investors who we have deep relationships with who give great advice and who are willing to give up an hour and a half of their time. And then we say to those ones we like best, here's the calendar. Pick a date you want to come. And then it becomes competitive. They're like, I want to get these companies in the first, second, third week because I want to pick them off before other people see them. And so then what happens is, you know, Camillo will get some great piece of advice, you know, three or four times where people are like, hey, this Tam is, you're charging too little for the value you're creating. And when a founder hears that, not from us, not from their customers, but from three or four VCs in three or four weeks.

and then they just try raising their prices and then they present, oh yeah, we have three pricing models. There's the introduction for, you know, one truck company or two, three and under companies, and we charge them, you know, 100 bucks a month. But then these ones, we charge $750 a month and $1,500 a month. And when we changed that pricing, we saw people, half our customers moved up. And when we deprecated the free product, we got rid of 20% of our annoying customers and the 80% said no problem. and they just, you know, agreed and checked a box to pay their higher rate. So we record every piece of feedback, Alex.

We normalize it and we say, okay, you keep getting this question about your pricing. Should we have a discussion about that? And do you want to read a module we've written on pricing? Or would you like to talk to an expert about pricing? And I find this model works better with great founders where we're not dictating to them how to run their company. They're just collecting lots of feedback. feedback, lots of feedback, and then they themselves normalize it and make their own decisions,

and we help them by normalizing it and taking out all that work. If you had to set up those seven meetings, each week for 12 weeks, it would be a full-time job to get half of that done with the associates at the firm. It's nothing wrong with associates. We have plenty of them, but, you know, like you said, we try to get more senior folks. The associates, though, I will say, can be sneaky influential in some firms where you have lazy VCs who are like, they just send all. be associates. I can't meet with all these companies. We do 100 meetings per week at our firm,

introductory meetings. I could never do more than 20 of those. You know, back in the day, I could do 100, but man, that becomes like hard. Your brain will melt. All right, listen, great job. Very excited for you. Thank you for letting us invest. And thanks for the kind where it's about the program. All right. Thank you guys. Appreciate it for the time. All right. Next up on the show, we have Elise Myrins. She is the CEO and co-founder of Tenax. It's Tenax AI. Jason, this is a company that wants to to get more information about potential risks, help homeowners harden their houses

to prevent wildfire damage, and also ensure that insurance companies can properly underwrite potential risk. It's an enormously important business because we've seen more natural disasters, higher repair costs. The entire U.S. insurance market seems to be a little bit upside down, so I'm very excited to hear more from her,

and here she is. Elise, how you doing? Hi, I'm great. Thank you. How are you? Nice to see you again. You were from the launch accelerator 35th class, if I'm remembering correctly. 34. 34.

Okay. So I'm not remembering correctly, but I was close. I was in the ballpark. And we had the chance to partner with you on your new company. Maybe you could tell us a little bit about what you're building and why it's important. Yeah, happy to. So 10xAI protects homes and their insurability from extreme weather. So I'm talking about things like flood, wild.

fire storms. And essentially what we have built is software that uses computer vision and AI to assess risk at the individual property level, so at a home level. And what that does is it gives insurers a granular view that helps them understand the true risk of that property, which enables them to underwrite and ensure that property more accurately. And what it also does is it enables the homeowner, so the people who live there, to understand their, exposure to risk and to take actions that could actually reduce that risk as well. So AI is the better way to do this? How is it currently done? And why is AI a better solution? And maybe you can show us because you had some really interesting demos and in your deck.

And I remember when you presented to Sequoia, I was there and they were fascinated by your approach. Yeah, absolutely. So to date, what has been done is insurers would normally make a regional sweeping decision based on regional models about the exposure of a property. So they might say this entire zip code or neighborhood is this general level of exposure. And then they use that to inform how exposed that home is to a particular peril, such as wildfire or flood or hail or winds. Now there's the introduction of some manual inspections where a person, a professional, would be booked and organize, and they would go to the property on behalf of the insurer, and they would do an

inspection that could take a couple hours, they got to write up a report, ingest all of their written and verbal notes to put together a report to explain that exposure, and then hand it over to the insurer who then has to adjust it into their underwriting process. What we do is about 80% more efficient than that process, because we have built, as I mentioned, AI and computer vision models that essentially enable images, which can be collected in up to 30 minutes max, on a mobile phone. So we can just take their cell phone, walk around the property with our app. Very, very simply, you need zero expertise whatsoever.

The average homeowner can do it. And we can upload those images and run it through our proprietary models to be able to diagnose the exposure of that property. The other thing we're doing that is quite unique is we are now starting to send drones to properties as well. And this is really important because in some cases, insurers would actually prefer that the homeowner not be the one collecting the data. It just offers another level of verifiability. Sure. Yeah. We've, as we've seen, homeowners can, you know, value their homes and maybe get into shenanigans on the margins. And, you know,

this is very interesting to me, this company specifically, Alex, because when we had the the tragedy in the Pacific Palisades. Yes. You know, I'm just playing a quick video here on YouTube without the sound. I'm assuming you two can see it, yeah? Yes. So this home was made to be fire resistant. It has a number of features.

And if I were to zoom in on this for a second, let me pause it there. Perfect. Now, when you look at this home, what you'll notice is it doesn't have overhangs of the roof. You'll also notice it's fire, retarded material everywhere. And around the home is a giant stone fence with landscaping with a lot of gravel and metal and not a bunch of trees around the home. You can build homes today that in a wildfire would be resistant to them. But this home, Elise, would have been bundled with all homes in Pacific Palisades. Correct?

Spot on. And that's because of the way that risk has been being calculated by insurers. As I said, in these sweeping regional models. And so what happens is even if your home was lower risk, so in that case, that home's insurance actually is probably higher because they're technically compensating or paying for their neighbors or regional risk, right? At least, if I understand, this is not because the insurance companies are lazy, but because there's actually a regulatory barrier they can't cross or couldn't cross until recently. Yeah, there's a couple crazy forces at work, which are kind of unexpected. And so one of them is actually in California until about a month ago. Insurers literally did not have regulatory-approved catastrophe models that they were allowed to use that were forward-looking that enabled them to calculate the exposure to true and up-to-date wildfire risk, which is bananas.

You would think that that would be very obvious, but it hasn't been the case. And so as a result, of course, they would be pulling out. They literally haven't been able to measure risk accurately. And so there are now three Catastrophe models that have just been approved in the last about four weeks, their risk and moody's among them. And what is really cool about these, if you are nerd like me and get into the weeds and looking at these models, is that they have placeholders within them where you can insert data about specific secondary very factors related to the home. So we're talking about characteristics like what material is the

fence made of? Is a combustible? And does it link up to a large patch of vegetation? Because you may think you have defensible space around your home, but say you have a wooden fence and it connects, you literally have a wick to a combustible source. Or what type of windows do you have? Are your vents covered with the right mesh? And what's really cool in what we factor in mathematically to our algorithm so we can actually tell a homeowner and tell an insure and tell a community how exposed they are is we have risk factors with each of those characteristics of a home. So if you have the right type of roof, you're reducing your risk by six times. If you have the right porch material, you could be reducing it by three times. If you have vents that are covered by the right size mesh,

so embers can't fly in, you could be reducing it by 1.5 times. And it goes on and on. And a lot of these things are not things that people think about every day. And so that's what we're able to to offer people really simply. This goes to the question that I really had for you, which is, who is the customer here? Because I can imagine the insurance company being the customer, or it might be the individual who wants to get a better rate, so they might pay for what you guys put on. So who do you sell to in the market? Yeah.

So insurance carriers are our ICP. So those insurers who have exposure to peril, like flood, wind, hail, storm, wildfire, which increasingly is kind of everywhere, as we all know, for anyone picks up the news. the homeowners themselves are the users. And so they would be prompted by their insurance provider, either if they are at a point where they're looking for a new coverage. So if an insurer is deciding how to price the risk and they need this kind of data so that a homeowner could actually get rewarded with discounts,

which is now there's new regulation that helps enforce that in California, for example. And then they would be able to access that software, basically, through their insurer. Yeah, this is, I am obsessed with this. And because we had an investment, it didn't work out in a company called Blockable. They were making prefab homes. Now you might think, oh, a prefab home, oh, that's just going to burn up. No, O'Contraire.

What they were doing was the gaps in these homes and the materials that you can build in a factory as opposed to on-site because cutting certain types of materials is, cutting certain types of materials is impossible in the field, Alex. And so Dwell did an interesting series on this. Especially in Australia, this is a big deal because of the wildfires in Australia are, I think they make some of the wildfires we have look like, you know, campfires, not to make light of anything here. But as you can see here, this is a firewist infrastructure.

This is a Dwell story, great magazine, Dwell.com. And you can see they're using steel for the roof, etc. but at least the gaps is a key because if there are tiny, even the tiniest of gaps, the air gets sucked in. You have all kinds of suction kind of situations that happen with heat that you've all experienced when you open an oven, et cetera. And what that does is suck embers into the home or it sucks embers into, you know, a pile of leaves in the gutter, all this kind of stuff contributes.

And they have been working on this, specifically to do fire-resistant timber. Here's an example of a timber that is fire resistance. And then other folks are making, what some people might consider ugly made out of iron, but you don't have to go that far. And then, as you see here, the distance of the trees to the home also critical.

So it is completely possible that if you clear the brush around your home, the chances of it burning down go way up. If you look at flood resistance home, that was another thing that happened in the wake of Katrina. and Breezy Point where I used to summer as a kid in Brooklyn and the Rockways, they started building homes that are four feet above the water, yes, at least, and have these really interesting panels on the side of them. My brother was a firefighter, my grandfather as well,

and what these panels do is when the water comes rushing in, you know, so you don't see under the house, but when the water comes rushing in, it just blows the panels out. The pressure from the water just blows them out. And then you just have, you know, whatever you have in your basement, It's like, you know, you keep surfboards there or whatever, things. You're not putting a full-on, you know, theater in your basement. These panels blow out allowing the water to flow through.

So aesthetically, it doesn't look like you're living on stilts, but essentially you are because the panels just are made to break away. So flooding is the other big high-order bit here, Elise, I guess. Yes, flooding is going to be second for us. And I think you're touching on something, Jason, that's really important. And we hear this so often when we talk to homeowners, who say, well, what can I really do? I live in an area that, you know, I'm told is prone to, in this case, wildfires.

The reality is there are so many things that people can do, but they don't know. And it's not only a roof, you know, and then people, you know, say it might be the roof. They're like, well, that's so expensive. Well, the reality is the numbers have been run. And we know, without a shot of a doubt, that at the very minimum, $1 invested in the right retrofits or controls on a property saves at least at a minimum six in, recovery cost, right? And then if you can do these types of retrofits and then get insurance as well, so you're insurable and you're not having to pay for, you know, an insurer of last resort that is

insanely expensive, well, then you're in a really good position. And so we're trying to give people advice on those things that they can do to help maintain their insurability. At least, I have a kind of annoying question here. But if we make it so that people who are very proactive about hardening their house from either fire or flooding or whatever, can be be insured on a one, a single house basis. And is that going to leave a lot of homeowners who may not be able to harden their homes out in the cold, essentially, because they'll become uninsurable because the risk pool will be narrowed from a neighborhood size to an individual home? What's the other side of the good news that we can have more information, I guess?

Yeah. Okay. So there's a few aspects of that. One is actually something that we are seeing as interest from communities themselves, like so from HOA's local and regional governments who actually want to take a community-wide approach to risk reduction. And so the idea here is that, you know, when you can harden multiple homes in a neighborhood, you can actually improve the survivability of the entire neighborhood. And we also see from a behavioral lens when one person in neighborhood starts to take action, it does spread. I was going to say like wildfire.

It's a wrong pun. But it does. There is a contagion, you know, in a certain aspect of. Exactly. These are terrible, terrible analogies. Terrible analogies. It spreads like a smile. I could have used.

That would have been even worse, Alex. But in some ways, those homes at least become a firewall. And there would be an argument in my mind, Alex, to even make the disparity between the safe homes and the unsafe ones even greater. To incentivize it because if, let's say we lived in a, you know, a thousand. in home planned community, that entire community could save the three communities next to it. When the embers start flying, they're just a natural blockage. And you might look at it in a community and, you know, the floral arrangements and the parks and everything and the structures that are not homes, you know, those are kind of a tragedy of the

commons. Like who's going to change those? But you could say, you know what? These trees are no one. know, there are some trees in California that are literally like, I mean, you could put doroflam logs around your house and it would be more fire resistant than some of these, like the, are they the palm fronds? What are the things that fall off of the palm trees, these giant things? I don't know what they're called.

Yeah. Palm, somethings. Anyway. And those light up like Tinder, Tinder, yeah. Oh, my God. And then they break off and they fly like a, like a, literally like a missile and land on somebody's roof. And then that person's got, you know, a shake roof. And, okay, game on now.

Yeah. So we're here for a little office hours. How's the company going? Is there anything we can help with? I love that question. Thank you. Yeah, things are going well. We're working with a handful of insurers that are helping feed into our product

development, which is very exciting. My question for, well, there's a couple things. One is actually an offer that I'm going to make, which is for any, insurers, brokers, and even homeowners who might be listening to this, who are really interested in figuring out how to protect their home and understand their risk. We're currently working with some partners in California. And essentially, if there are people who would like to get an early version, a test of their property, contact me at Elise at 10xAI.com. That's at TNAXAI.com. And it'd be happy to put you in the queue.

for some of that. Great. So we need some vanguard here. We need some early adopters who want to get early access. So great. Let's get some of those going. And then the question I would put, this is something I'm loving brainstorming around right now, are different ways to hack sales cycles and really regulated industries that are slow moving, right? So in that B2B space. So I love talking about this. And I love, I don't think you and I have talked about it. I would love to hear your thoughts on that. You know, there's a tough one. You know, whenever you go into education, let's say, or you go into housing, as you are, health care, these are some of the giant castles that are hard to scale.

We got moats around them, they got strawberries, got alligators in there, got arrow slits. It's not fun to scale those. One thing I've seen is companies like Brilliant.org, and Alex will pull it up. you know, they thought, hey, we can help educators, right? Teach kids math more efficiently, et cetera. But I think one of the lessons Sue learned over there very early was we can actually sell into the top parents and have those parents, you know, use these tools to make their kids superhuman to use a term, and another startup that we're investors in.

and then those people bring it to their schools or it becomes, you know, oh, the kids who are doing really good in the class are using brilliant.org and their STEM stuff. And then they say, hey, can we get this for our school? And so I wonder if you find high-end homeowners where you can consult with them or build some product or service that helps them navigate lowering their insurance. and also just lowering their risk and advising them. So if there was an audit of my home, and you told me for $500, $1,000, $2,000, $5,000,

you know, I have some expensive homes that cost a lot of money, and somebody said, hey, we can audit your home for $500 and give you recommendations right now of how to lower your insurance, or we can go call your insurance company, and tell them you've done these things, and whatever we lower your insurance by, we'll take half of the gain. You know, there could be something there.

Now, I don't know enough about the insurance business and lowering insurance based on these remediation, but that could create a way for you to integrate yourself into the industry, to just raise awareness. And I think I spoke to you a little bit about, you're so passionate and you're so great at communicating this, and you have that just natural and enthusiasm,

a YouTube channel just about this issue where you have homeowners, you have builders, you have the person who makes the roofs, you have the person who is a contractor who you met in Santa Rosa, you know, up by Napa where they've had some terrible fires and does this kind of retrofitting. And just short videos, even TikToks, hey, my name is Elise. I'm from 10XAI. We help fortify your home from floods and fire and lower your insurance. Today on the program, I'm going to show you this tip. or here's a tip for, you know, stopping wildfires and dealing with floods. Those kind of things could just make you, you know, the queen of this topic. And that would naturally start you off on second or third base with partners.

I know this because people, when I had this week in startups and I started my Angel Syndicate on Angelist and then moved it to the Syndicate.com, we're like, oh, yeah, I watched this weekend startups. I'd love to be part of your syndicate. or I saw a 10x AI. Are you going to syndicate that company? So we inserted ourselves into the discussion, and then we became the host of the discussion.

We became the place where the discussion about startups was happening. The discussion about angel investing was happening, which is why I wrote the book on Angel investing, literally called Angel, you know, now in 12 languages. And so I had that calling card that just made, you know, any meeting request happened very, quickly. And now with All In, it kind of moved over into pop culture. So when I go to another city now and I want to talk to people about bringing Founder University to their region or, you know, I want

to record an episode of This Week in Startups with a founder. We just had a founder on the pod from Nuro and he was referencing Alex and I's conversation from previous episodes about self-driving. And so that means their chance of coming on the pod goes up. The chance of me investing in the company goes up. You get the idea. All right. Everybody go to 10xAI.com. T-E-N-A-X-A-I, T-E-N-A-X-A-I dot com. And if you are a homeowner or in your insurance and you want to help a founder out

just with some conversations and maybe some tips and advice, Elise at 10X-A-I-com, E-L-Y-S-E-E-E- at. Great job. Thank you for letting us invest in your company. And we will see you all next time on this week in startups.