Tag: machine learning

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Rob Carpenter is the CEO and Founder of Valyant AI, the first Artificially Intelligent “Digital Employee” to work directly alongside employees in customer facing roles. Valyant’s AI “Holly” works in fast food restaurants to greet customers at the drive-thru post, answer questions and take food orders. The revolutionary nature of this technology is that it pulls AI from being a hidden back-office tool, to something that feels like a real staff member, which humanizes a brands personality and brings the AI
experience front and center to a physical location.

We discuss the power of their technology, the ethics of AI and the effect on jobs, plus how to empower people with technology and in the startup ecosystem.  Another great chat that is a must-listen for founders everywhere.

Check out Valyant AI here: https://valyant.ai/

Connect with Rob on LinkedIn here: https://www.linkedin.com/in/rob-carpenter/ 

Thanks for a great chat, Rob!

Transcript powered by Happy Scribe

Hey there. Welcome to the DiscoPosse Podcast, and this is one of those fun ones because you actually get to hear the really fun technical snafu that happens right in the middle. But it doesn’t cut into the conversation, which is one you’re going to enjoy from Rob Carpenter. He’s the founder and CEO of Valyant AI, which is something that’s really, really cool because he talks about the idea of AI as a digital employee. This is especially being used in the area of conversational AI in fast food ordering.

So really, really cool. In fact, I bet you’ve already used one and you don’t even know it. And speaking of conversation, you want to have a great conversation. Let’s talk about data protection. I know it seems an exciting some days, but you know why it’s unexciting because you need to make sure that you’ve got Veeam to protect your assets. And that means everything from your On-premises world to your Cloud to your digitally native experiences that you’re running in Microsoft Teams, Office 365 and there’s many more neat things that are coming, so hang on tight.

You’ll see lots of good stuff. But let’s save the conversation because no one wants to have that Monday morning conversation. What app to the app? It went away this weekend and we can’t get it back. That won’t be a problem if you use Veeam, so go to vee.am/DiscoPosse. They are the leader in data protection and real true anywhere, always on availability for your application. So get it done. Go to vee.am/DiscoPosse. See what it’s all about. Speaking of protection, remember that as you’re moving around and you’re on the road, or even if you’re just trying to protect your identity and protect your data in transit, the best thing you do is use a VPN.

I know I use one, especially for not just day to day stuff, but being able to make sure I can do testing against my services from different parts of the world to see what the behavior is and what latency is. So whether you’re an application tester or whether you just want to make sure that you keep your identity safe, you can use ExpressVPN. I’m a fan of the team and love the product. So the easy way to do this, go to tryexpressvpn.com/DiscoPosse.

I make it really super easy by just naming it after me, but go check it out. And one of the places you should make sure you do it. Don’t go to coffee shops, get your own coffee, go to diabolicalcoffee.com and while you’re doing that, strap in. This is Rob Carpenter, the founder and CEO of Valyant.AI, and this is an absolute must listen. He’s a fantastic human. We talk about EO, we talk about Valyant, and we talk about a lot of things. Enjoy.

Perfect. My name is Rob Carpenter, the founder and CEO of Valyant AI. And you are listening to the DiscoPosse podcast.

Alright, I feel like I should have, for this one, I should have your platform introduce us, Rob. Because first of all, I’ve listened to a lot of content, so I am excited by what we’re about to discuss. This is something that’s near and dear to a space of study that I’ve been in and looking more around the business side of it and the idea of conversational AI, I’ve been lucky enough to have a lot of great folks on the show who are in the space and it’s just so exciting.

It brings interesting emotions when we talk about the advantages and what the potential displacements are. So there’s a lot of really good stuff that I’m going to love hearing from you, in your real first world and first person view of it. So before we get going, Rob, if you want to give yourself an intro for people that are new to you.

Yeah, thank you. I appreciate it. So just new to me. I’m originally from Alaska, so I grew up right on the Bering Sea at the top of the Aleutian chain. Probably one of the more random background you’ll hear out of somebody.

That’s a first. That’s a first. Definitely a win.

And we literally have like grizzly bears roaming around in our backyard and we could go out and fish from the bank and catch 20, 30, 40 pound king salmon. So this is a very interesting life, but very early on, I really had a big interest towards entrepreneurship and starting businesses. I just kind of looked at the people that are living the life that I want to live, other than astronauts, what do they do? And almost every one of them were entrepreneurs, people who had built and founded companies.

So I read Rich Dad, Poor Dad and started to kind of get an idea of how a different part of society work that I didn’t fully understand and ended up getting an undergrad degree in entrepreneurship. Ended up in 2010 out in Denver, Colorado, got an MBA with a specialization in enterprise technology management, founded a mobile application development company, did my first M&A transaction ever. Acquiring a company in India took a year and we literally run into problems because we are using the wrong type of ink on our paperwork.

So there’s a tremendous opportunity, grew that company to seven figures in revenue. But like anybody listening to this podcast, I mean, service based businesses are just really hard. You are constantly out hunting and killing, and you’re only as good as your current project portfolio that you have. And it was exhausting. And so when I ultimately came up with the idea for Valyant AI, I was just really excited to transition into a product based business. And so I’ve been running this company now for five years is making that transition.

Wow. And this is a great place to start, Rob, because by the time you can say what you’re doing. You have to have been doing it for a while when you’re in the product world, especially one that’s in the area of AI, and you’ve chosen your specific, targeted customer niche, which is the right thing to do, because too many people, you can get big eyes at the buffet, as they say. It’s very easy to think of too many use cases. But five years in now, when was kind of the first time you felt like you could really go to the world and say, we’re here?

Like this is something that takes a while to develop to even get to that MVP kind of customer ready environment, right?

I mean, you talk to anybody that’s in the conversational AI space, and there’s a little bit of puffy in your chest for a few minutes. Then there’s a little bit of actual bonding, and within 20 minutes, you’re in a therapy session. It’s amazing how quickly you end up in that space. It’s hard. And I think we’ve been at it, like I said, for five years, we’ve seen a lot of companies come and go. We’ve had our own serious kind of soul searching. Do we need to look after another industry?

And I think conversational AI and maybe to some degree, AI in general is just so hard because you can do proof of concepts or really simple demo fairly quickly. I mean, literally, in a weekend, you could put a demo together. But then when you actually try to bring a product to market, it is just crushingly and painfully hard to get to a true, fully functional, especially for what we’re trying to do. We’re trying to emulate an employee. I mean, it’s hard enough to get Google Home to understand my wife when she asks for a music request.

Let alone something that as capable as a human. When did I think we were going to be there? I mean, at any point you ask me, I’m like we’re three months away. We are so close. Just another three months and then another three months and then another three months and a painful statement that has always stuck out in my mind. It was either the CTO or the CEO of SoundHound said, it takes three years to realize you’re ten years away.

And so I desperately hope we’re not ten years away now we are in market. We have a product. We are automating orders today, but like anybody in the AI space, we do have human in the loop backup support. And so the question really is, how fast can we reduce the reliance on those humans in the loop and get to a point where it’s just pure AI without any outside support?

This is the real interesting thing. And when we talk about what it is that you’re doing, it’s an experience that will be viscerally understood by people because they’re going to know what it’s like being on the other side of that little box. So Rob if you want. Let’s give a bit of a walk through of what Valyant is doing and where your first customer use cases are.

Yeah. So when we initially came up with the idea for what became Valyant and kind of early on, knew we wanted to pick one industry. I mean, it’s good conventional wisdom. Pick up each head, own it, and then strike out into other industries from a place of strength. And so I sat down. I kind of came up with my own rubric of ten to 15 categories and then identified roughly 20 different industries. We were at that time a future solution in search of a problem. So it’s like, where could this technology be applied?

And so we ultimately settled on the restaurant industry. Now there are some cons to the restaurant industry that people are familiar with in terms of low margin, a lot of price pressure, things like that with things like point of sale systems, there’s a lot of pressure and commoditization. So there are some challenges to the restaurant industry. But relative to some other big market verticals, like take retail. For example, the nice thing about restaurants is you tend to have a more limited domain set, especially as you look at quick serve restaurants or fast food.

You might have 75 to 150 different menu items, a couple of permutations on there, and then maybe a few hundred other key terms, catchup, fork napkin, things like that. But if it’s a very limited domain set. And although I don’t always agree with everything, Kai-Fu Lee says, if you read this book, AI Superpowers. He talks a lot about the importance of kind of a vertical integration approach, at least in these early stages of AI. And I do fully agree with that. And so we decided that restaurant was really where we’re going to make our mark.

And so we’ve pretty much been super focused on it in five years. And we’ve turned a lot of companies way and a lot of other verticals. And we’ve just tried to stay hyper, hyper focused on this one key space. And then for us, specifically, what we look at, where we see the most demand from the market is around drive-thru automation. So there was interest prior to COVID, but over the year and a half of the kind of first round of COVID drive through became one of the most important areas inside of the entire US restaurant industry.

And you’re talking to $865,000,000,000 per year market. A lot of the quick of restaurants we talked to, they were up 30% year over year. So you look at how painful it’s been for sit down, you know, high-end, fast casual. Those restaurants all suffered under COVID, fast food boom. I mean, they did huge business, and 90% to 95% of that business was done through drive through. So it was just serendipitous place for us to be having three years of kind of wind in our back at the point that all this came about.

And I was on a call this morning with the restaurant operator, and they’re already seeing another big surge in terms of demand for drive through as we go into kind of the Delta variant of COVID. So we hyper focus on that one specific use case. We manufacture our own hardware. We stick it inside the restaurant. It hooks into the technology that the employees use for their headsets to talk to the customers in the drive through. We currently process everything in the cloud. The goal would be in a year to move towards edge computing so we can do everything on site, even when the Internet goes down.

And then we have our own proprietary speech to text engine, NLP engine. And then what I refer to as the natural language generator or just kind of more vaguely, just the logic engine. It’s kind of a common sense brains of the system. So we’ve developed all those systems in-house to specifically address this one use case.

There’s so much good stuff I could do an hour on each subset it to you. So first of all, just the fact that we refer to QSR. I love this quick serve restaurants because fast food is like a pejorative at this point because you just think of just negative connotation of food. But as an industry like you said, the address of a market is fantastically huge, especially now that people are moving to this idea. They want to get out of their house, but they don’t want to be sitting in a restaurant in a risk situation.

So it’s kind of a really good mix. But quick serve restaurants like you said, they they’ve got a specific target, and it’s a very repeatable thing. And the first thing that I think of and I know people are listening and thinking, isn’t this going to get rid of somebody wearing that headset? And that’s why I want you to allay those fears, because I know a lot of my own reasoning that I do not believe that. But first hand, you’re in this, that’s got to be, I’ll say, a common if not a top objection when you talk about the value of what you can do with Valyant.

You know, and for whatever it’s worth Interestingly, when we talk to end customers, employees, the brands, some of them bring it up. They’re generally not worried about it. It tends to be all of the media interviews, and it’s about 100% that it comes up. So I’m glad we’re addressing it right out of the gate, because it is a very important topic for us to touch base on. So specifically, what we’re talking about right now is labor repurposing. So the person that’s in that order taker position. And this was something that I learned along the way, 90% of all QSR restaurants across the country that order taker is also doing sometimes three or four additional jobs to order taking.

So it’s not a dedicated position. So really, what we’re doing is we are automating a task, and that task may take that order taker 50% of their time, but they still have to process payment. They still need to fill up soft drinks. They still need to clean up after spills. They’re being pulled in multiple different directions simultaneously. We talked to one at a top seven QSR brand and their order taker on averages, doing five jobs. And so the critical thing for them is like we just need to automate this task because that person’s life is really hard.

Turnover is really high, and there are only certain subsets of their employees that they can even put into that position. So it’s a really critical challenge for them to figure out how to backstop all those employees and just make their lives better. That, I think is a kind of microeconomic view of the situation. If you also step back and look macroeconomically at the service and specifically restaurant industry, there’s 1.4 million unfilled positions in the United States today. So even if we were taking a whole position, which were not just task automation, there’s still not even the people to do those jobs.

I mean, you go anywhere and you’re going to see help on these times on pretty much every single business. Look at the airline industry, especially as our economy that starts to recover over the summer. It was a nightmare. I mean, look at Spirit Airlines, right? I mean, those guys practically went bankrupt because they had to cancel, like, three weeks worth of flights because they just literally didn’t have people to work. Alaska Airlines, they’re near and dear to my heart, they were forcing executives in Seattle to go out and do baggage handling work on the Tarmac executive.

You’re talking of VPs of marketing or chief operating officers hauling luggage because the labor shortage was so acute for them. So we’re really helping these restaurants because they cannot find the labor and on average, within the industry turnovers 150% to 300% per year. So you have a really hard time finding somebody. When you can find someone, you’re refilling that position one to three times per year. And if they do stick, that person’s being asked to handle five different jobs simultaneously. And that is a perfect application of AI or, more generally, probiotics.

When you don’t have enough people to go around, the job is monotonous. It’s dangerous. It’s boring. Automate it. Let humans focus on the things they’re better at than doing something that is just a repetitive task over and over and over again. How’s that?

That’s perfect. Number one, you’ve affirmed my belief in that we are not removing roles were, in fact, elevating people into more opportune roles. And I love that such perfect examples. And thank you for bringing numbers to it as well. We can see the impact there. It’s frightening, right? People think of this idea that we’re like, of course, last night, as we’re recording this, the news hit that we’re creating the Tesla Bots. And so immediately there’s this, somehow that Elon is looking to get rid of the citizens of Earth and replace them all with robots.

And it’s, like you said, it’s such a media frenzy reaction, just because it’s something to talk about that they know can trigger someone to listen. And I guess when you’re in that business, that is your that’s your business is getting people to listen, getting people to read. And these kind of tropes are so easy to latch onto. But like you said, when it comes down to it, the people who you’re talking to that are going to use these systems in their own environment that they’re working in, they’re like, thank you, Rob. Bring it on.

Yeah. And I think, too. I mean, we got to get a little more nuanced with things as well, because the innovation has always been part of human society. It’s woven into the fabric of the American psyche. What we need to be concerned about, which is why I think this question is important, and we should talk about it is the pace of innovation. If we look and we step back and we say 100 years ago, turn to the last century, something like 95% percent of the entire US Labor Force was involved in the agrarian industry.

And I don’t know about you, but I really love going into my office and sitting at my quiet desk with a warm cup of coffee or playing Ping pong with my team or grabbing a beer for a happy hour versus being out and working with livestock or out picking vegetables. Not that there’s anything wrong with those types of jobs, and that’s obviously critical to our survival as a species. But if you look at where we are today, it’s something like 1.3 or 1.4% of the entire US Labor Force is still involved in the agrarian industry.

So we have more food than we’ve ever produced in the history of human civilization. And we went from 95% of people involved in that to one and a half percent. That is innovation. Innovation is not bad. That has made a lot of people’s lives a lot better. I think, where we have to get concerned. And I think this was maybe a bigger fear five years ago. But it’s just the pace of innovation too quick, because there’s a natural attrition of jobs every year and the creation of new jobs, like, 20 years ago, who would have thought social media manager would be such a critical position and how it is. So like that’s innovation.

If the pace of innovation is too fast, that’s when it creates problems, because then you’re losing too much of the workforce before you can replace it with new jobs. And I think that big fear does come down to some element of conversational. Ai, automating, service based work and white collar jobs. And then I think the other big part of it was everything going on with self driving cars, for example, like truck driving. That’s the number one profession in 26 States in the United States. So if all that gets automated and then all customer service work gets automated, that’s a big problem.

But going back to the Tesla Bot and what we’ve seen over the last five years in these kind of AI updates of where self driving, we’re still not even at level four. So things that we thought would be easy. Elon Musk was promising we would have it in 2017, still aren’t even really ready in much of a real way for a beta consumption. And so I think that’s maybe alleviated some of those concerns. Are these things coming? Yeah, absolutely. Will there be self driving cars in the decade? We thought it out.

But by stretching out the timeline for innovation, I’m actually significantly less concerned now because, yes, jobs will be destroyed. But the new jobs are going to be created while we wait for things like self driving car to hit level five and actually be able to work in a place like Alaska where there’s snow everywhere and there’s nothing really tangible for the cameras and the light are to really play off of. So we’ll get there. It’s going to stretch out a lot more than we thought it would five years ago.

And that’s going to give us plenty of time, I think, to replace those jobs with new jobs.

And in a way, you bring an interesting point, I think, isn’t the fact that we talk about the potential innovation. It becomes an antibody to the removal of value of the current human counterparts that are doing the stuff, the fact that we have these discussions and we talk about the potential to reach the specific areas that we’re aiming for, that we’re not there yet. It gives the industry and humans a chance to kind of go, if this is coming, we better start to innovate processes and companies.

And the way that we work like, I’ve never known anybody that automated themselves out of a job. They’ve automated themselves into a better opportunity almost every time. There are, very certainly, some specific roles that, like mechanical robotic process automation. That type of stuff did replace some things. But again, if we looked at the numbers, it’s such a small portion of the global industry and the ones that it is. In fact, it was literally killing people to do this work.

Right.

This is stuff that shouldn’t have been done by humans. We just had no choice because we weren’t born with the machines. So that’s an interesting thing.

I think the perfect case study for this is right at 100 years old. And that was Henry Ford and the Model T. And he was one of the very first kind of industrialists to bring in this idea of automation and mass manufacturing. And when you have one manufacturing line and you start to automate 20% or 30% of that mass manufacturing line. People get scared. And he had employees. He had family members. He had people from the community that were literally picketing outside of his factories because automation was destroying jobs.

This is 100 years old. And what happened is that by automating things, he was able to bring down the price of the Model T so that more people could afford it. So then what happened? More people bought it. So he opened a second line and a third and a fourth and a fifth and a sixth. And before you know it, you’re employing exponentially more people than you ever employed before. And you’re doing it because you’re becoming more efficient with your use of capital. And that’s exactly what’s going to happen here.

But that doesn’t mean there’s still not concerned in the short term, just like there was 100 years ago when people were picketing out in front of this manufacturing facilities.

The other thing as well is the acceptance of the new innovation becomes a baseline pretty easily the point leading up to it seems like a forever moment. Like my example, actually, I used this in a presentation recently at work, and I said, like, you know, Elon went to first principles when it came to space travel. And we said, like this, everybody told him it couldn’t be done. It’d be silly to do it, just even in that specific one area. He then said, I’m going to land the rocket, not just going to send it up.

I’m going to land it on a launch pad. And they said, this is crazy. It can’t be done. And then one step further, he does it repeatedly. And now Jeff Bezos goes to the edge of space, and he lands the Blue Origin rocket nose up. And not a single person said anything about it, right?

They were just like, yeah, that can be done now.

Yeah. Like, it was like, if it hadn’t landed that way, people have been like, whatever dude. They would have been angry at him. And so it allowed us to move the conversation to something new, which was okay now that we can do this repeatedly, what can we do with this availability of technology? And now this is. And there’s an interesting thing as well. People said, well, we’re lining in the pockets of Elon as an example. And look, I’m not going to go. I don’t want to have a discussion of the weight of the billionaire or whatever the challenge there.

The result of the work that they’ve done has resulted in the US government saving a $150,000,000,000 in spending while still sending objects to the ISS now. So then it has had a significant benefit to the entire, every citizen of the United States has benefited as a result of that. So it’s definitely there.

And this is going to be a whole new world for innovation, right? I don’t really even think it’s a question of if anymore, within a few years, the SpaceX, Heavy Falcon Rockets, they’re going to be landing people on the moon. They’re going to be landing people on Mars. And by doing that, you’re going to need habitation, you’re going to need food, you’re going to need water, you’re going to need rocket propellant, and SpaceX will do some portion of those. And the companies that come behind them will do some portion of those.

But they’re not going to do all of them. They probably won’t do more than a few fractions of single digits of everything that has to be done. And so it literally opens up entire new worlds from an innovation standpoint, from a work standpoint, from an economic opportunity standpoint. And so, hey, are they automating parts of a rocket manufacturing process that used to be manual? Yeah. Is that reducing a few jobs that used to be there? Yeah, for sure. But they are now producing dozens and eventually hundreds more Rockets that could have ever been done before.

And through that process, opening up a whole new world of economic activity. Absolutely. That goes back to that kind of more macro economic view that economies are dynamic. You were meant to automate stuff. That’s been part of civilization since we invented the wheel that allowed us to do things faster and more efficiently, and that will continue to be part of our future.

So looking at, I apologize, my video is suddenly decided. Speaking of the amazing thing of technology, and yet somehow a simple laptop can’t keep up with humans and what.

I’ve been there. I get it.

What I love about what you and the team are doing, Rob is again, very quickly jumping to the human value and impact that you can have with what you can do. So conversational AI has had its really, really interesting adoption in a lot of different areas, and some people didn’t even realize like it starts mostly in text. But the voice conversational AI, where have you seen the challenges and the real wins in bringing this product to market?

Yeah, I think the core of the challenges I’ve kind of learned the space over the last almost half decade now is sort of the daisy chain effect. Conversational AI has multiple critical path things that all have to happen in a row. And if any one single element in that process has degradation, then everything after it is degraded. So let’s say just using kind of easy numbers here, you have five critical processes within a conversational AI system. If every one of those systems is just degraded by 5%, take speech to text.

If you have a speech to text engine that was 95% accurate, you were talking about a world class product at that point, but you still have 5% degradation from a 100. If you have four things after that for a total of five and each one is accurate, you’re still talking about an end result that’s wrong 25% of the time. So you have to have every single one of these elements operating at 98, 99. 99 and a half percent accurate so that you can achieve something like 90% total success of orders, in our case, over the course of the entire interaction.

And so that’s the extremely hard problem. None of it can be just good or good enough. Literally, every one of your core elements basically has to be world class or close to world class to get to a point where you are automating the vast majority of the orders that flow through a system. So I think in a nutshell, is the hardest part of building a conversational AI platform.

Yeah. And this is the challenge. Like you said, the demos are easy to spin up when it goes well, it’s easy to get to a very simple MVP, but I’ll go back if anybody’s watch Silicon Valley sort of a famous thing, and it comes up with this visual. We can take pictures of food, and I can show you what the food is. And he takes a picture of the hotdog, and it says ‘hotdog’, and they’re like, yeah, we did it. And then the next one is not hotdog.

So if it works, it works well. But then very quickly the edge cases become core use cases, especially in conversation, because it’s such a nuanced thing to do with.

Yeah, the entire product is edge cases. There really is no happy path in these types of environments where we’ve seen the most customer facing conversational AI adoption is when it’s really like limited term or just one meaning you ask Alexa a question and it answers and you’re done. And for those guys, they’re effective on kind of world classes. They can do one round of context follow up. Our average interaction with the customer has a minimum of ten, and we can have some that are 20 or 30 in terms of asking, answer, asking and carrying on a more true type of conversation of what you would expect from an employee.

And so you have to carry the context through from all of that. You have to carry the nuance through from every one of those. Every single time you request a new response from the customer, you are opening yourself up to an edge case because they might say something like “nah”. You and I, we understand “nah”, that means no. But let’s say simultaneously the customer said that kind of quiet or their car radio is on or like we had last week, there was a leaf blower in the background.

And suddenly when speech to text treads to transcribe ‘nah’ that comes back as ‘yeah’. So you have in one moment completely inverted what the customer said and you might be 15 turns into a conversation. And the AI is an 100% accurate. You missed one small word. And now suddenly you may have failed the entire interaction of that conversation and taking the conversation off of a cliff, basically. So it’s an entire business of edge cases and the cliffs surrounding the start and end of the conversation are steep and painful if you don’t get what the customer is saying perfectly.

You brought up a really great point and we talked about the nuance. Even we say, we all speak English, everybody I should say. Even that just the fact the arrogance that I would automatically go to we all speak English. What the challenges is the we’ve got sort of dialect. We’ve got accents, nuances of the human language to then add it to the fact that you’re ordering things that are called like, can I get a double Foogly Moogly? This is not even easy stuff to be able to translate, right?

No. And that’s still on the speech to text side. I mean, there’s other things like, can I have the two for four? It’s like, okay, well, what’s the logic that goes into that? Is there two chili dogs count for that? Is the two the price or the quantity? Is four the price or the quantity? And so there’s innumerable number of amalgamation of how these restaurants will package their food and their condos together and allowing the system to intelligently understand the core basis or principles, rules in every one of those situations.

And then in something like, can I have the two for four? Basically, each of those words in there are super critical. And so if you just miss one word or mistranscribe it, it can wildly change the output of what the customer was actually intending to say to you.

And just even, such a great example is it two four four? Or two for four? Like, there are so many words sets, which I even find that I’ve tried to use speech-to-text with simple dictation. And it just creates this giant run-on sentences. And I often thought there’s got to be some way, some shortcut that can be used to say period, comma.

But when you say them, it writes out the word and you can see. And then what happens is the frustration drives me to feel that the tech is failing, which I know it’s an unfortunate human reaction, but it’s actually, I just haven’t figured out how to best interact with it.

Right. We are seeing I will say that element getting better. I think this job and building this company would have been so much harder, bordering on impossible technology aside, a decade ago, purely from a customer psychology standpoint, that was right around the time that we started seeing Siri, Alexa, and Google Home start to enter into the marketplace. Fast forward today, and there’s hundreds of millions of these units sold. And so everybody in one capacity or another has interacted with one of these systems or likely heard somebody else interacting with one of these systems.

And that is helping to start to kind of train customers a little bit more like in normal communication. We’re extremely fast. We tend to be a lot more vague. There tends to be a lot of nuance. It tends to be a lot of emotion and internal Ty and body language that all feed into our communication with each other. And I think people, as they’ve now gotten more and more used to interacting with these systems, they tend to be a little bit more halting, tend to be a little bit more direct, and ideally, if they can be a little bit louder and a little bit more patient, every one of those systems helps the accuracy of the system in terms of understanding customers.

Such a good point. And so this is a funny story based on that. The platform that I’m recording on, it’s called SignalWire. I actually had Sean Heiney, who is their chief product officer on this. Sean was great. And I started using the platform. One of the advantages is that it allows you to actually stream multiple sources of audio simultaneously, actually multiplexing audio.

The advantage to it is if you have four people on or if you and I talk over each other, we can talk over each other and it continues versus the, I’ll say, other platforms have the problem of digital cut off where as soon as one person starts to talk and then you and then they both start talking again. So this platform gets rid of that. However, when it starts to happen, we naturally accounts for it, like the people I talked to will stop talking if they hear me talk at the same time. I’m like, no, no, no. I was just sort of adding color to it like.

We can all talk at the same time. It’s actually fine.

We’ve learned to behave within systems that are common now. And like you said, no one really doubts. Hey, Siri, do this thing or hey, Google, do a thing. We’ve actually kind of, we’ve normalized it, which is kind of nice.

Yes, I would agree.

Now, on the technology side, you’ve talked, and if you don’t mind, I’d love to dive in. You talked about currently, of course, you’re sending data to the Cloud. That’s the easiest way to do this because you want to make sure is it the most computing powers there create the most viable centralization. It’s a great platform approach. But you talked about the move eventually to do more stuff at the edge. And that is important because we’re going to see more. You know, first of all, just the risk of power loss and data loss and other things could impact it.

But then you really open the doors to interesting, unique use cases once you can have a real full edge presence.

Yeah, it’s really critical. And we’re finding, at least within our industry, there’s definitely a lot of concerns from these restaurants. Some are in major Metropolitan areas and have fantastic high speed Internet, and a lot are in really rural areas with really bad Internet connections and even where we are now almost ready to go into 2022. There’s still restaurants in some cases, I know that are on dialog, and so in those situations, it really precludes you from being able to your product to market if you don’t have it capable on the edge.

So where we’re at right now is we just are starting in the more Metropolitan, more well connected areas, but it opens up basically the entire rest of the industry. If you can push it to the edge and you wait until the middle of the night and you push downloads and updates to the system and things like that to keep it current. And it’s a lot more from a kind of a device. It software management when you’re so distributed like that on the edge versus just having one core platform that’s in the cloud, that’s significantly easier to interact with and to modify, but at least for us and for our industry in our use case, that edge capability is going to be really critical for us in the future.

The other thing that’s interesting is as a founder and knowing that you’ve got to stay focused, how did you maintain that? You talked about, at the start, that you’ve actually had to actively turn away folks that have brought lots of hats? Rob, you’re doing this. What if you just did here? How do you maintain that real Pragmatic approach, especially not just because of you, but your entire team has to ultimately stay aligned on that vision of what you need to get done first before you branch out.

Yeah. I mean, I’d be lying if I said it wasn’t hard, and I think this is a problem that every entrepreneur and business owner faces and kind of determining their model, which is, are we going to have one sort of generic system that’s going to work well or work okay in a lot of different industries? Or do we just want to have an absolutely best in class product, but in the foreseeable future, it’s just hyper focused on one space. And I’m not actually a engineer. So I definitely come more from a business development operations type of background, and it’s hard to turn away a 500 billion dollar company that wants to talk to you about voice AI capabilities.

Generally, what I’ve done, which has been helpful for me, is I just throw out high barriers to entry for them, because for these big companies, it takes nothing to waste a startup time. This could be interesting. Let’s see if all those guys over there want to go and work on this for free or, nearly free for six months or a year, and then we’ll see if we want to do anything with it. So it’s been a bit of a self fulfilling prophecy to stay focused, because I have taken those meetings.

I have talked to those companies, but then generally, I just throw out high price points to them. And then in the back of my mind, I’m like, okay, well, if they pay this, then I can go higher. One, two, three people. They can focus on adapting our platform because at the end of the day, it’s just software, right? So it can be adapted to any industry. But it takes focused time and energy and concentration. And in pretty much every one of those situations, then the companies come back and said, like, okay, well, it’s not that big of a priority for now, and it works out in that way.

And it’s a way where we’re not rejecting them or leaving a bad feeling with them. We just kind of lay out the case, the background, the reason it goes into it and then throw a big figure in front of them and say, hey, if you pay this, we’ll do it. And I think especially right now within the conversational AI space. There’s so many people working on it. There’s so much going on. I think there’s a lot of excitement. There’s a lot of real technology, there’s a lot of hype, there’s a lot of smoke and mirrors.

And so it’s very choppy waters for companies to figure out how they want to navigate this process. And so by throwing that barrier up, it’s pretty much kind of kept everybody out and allowed us to just stay on our sort of happy path from a go to market strategy. That’s just how it made sense for me.

Yeah, it’s great. And when you talk about that, there’s a lot of folks that are talking about the space, and they have technologies versus like yourself, where you’ve literally chosen, you’ve laser focused on a use case, you’re delivering it, you’re growing with Lighthouse customers. You’re doing that really, really strong methods of don’t do B until you’ve succeeded at A versus people that are like talking about A, B and C, and then maybe dabble in D. But they can create a lot of noise for you.

I don’t want to call it competition, but how do you do noise reduction against that stuff? Because eventually your customers will be like, hey, Rob, some other people are approaching us because of course, you go to Google and you look up Valyant. And the first thing that comes up is not Valyant because somebody’s buying ad space above you, which is the first site you’re doing well is when people are buying ad space above you. So Congratulations on that.

Yeah. I’ll tell you what, ironically, we’re in a situation right now where customers are not a problem for us. So it’s nice if we just really don’t have to focus much energy there basically everybody in the market want this technology. And so I think we’ve done a nice job of sort of positioning ourselves out there. And so as I look at the top ten biggest brands in the entire United States, we’re talking to or working with half of them. And so these large organizations or finding their way to us.

And that’s been really helpful, too, because then I’m not trying to work my way up through cold calls or introductions or other marketing efforts and having to kind of work my way up the chain to somebody important that can actually make the decision and sign off on projects and determined to move forward. So I think that portion of it has been extremely healthy for us, but I might need to go look and see who’s bidding against us and put some energy in it.

The other thing is just as a technology side, it’s very easy to look at the wonder of what’s possible. And as you go and you take on like adding new features or adding new customers, and you’ll see the expansion into potential, like taking on this idea of moving more tech to the edge. It’s a real undertaking where you have to invest into it. So when you’re making decisions like that as a founder, what’s your thought process around, where you have to be 100% revenue generating versus how much can I put into the longer term growth and viability?

Yeah, I think, and I’m assuming here a little bit, but I don’t think there’s too many of us that are in this hardcore AI space that are really trying to bust new pathways into markets that have never existed that are hyper profitable because it’s just huge amounts of work and huge amounts of investment into the technology. And you have some level of just sort of carrying costs for every single customer. And so the more you can improve the platform, the more you can bring down those costs and improve your unit economics.

And so something like Edge, your hardware, those are decisions I think bigger decisions are. For how long should I keep trying to drive towards perfection versus focusing more on just trying to be profitable on a per unit basis? And I think at least from my perspective, I really view conversational AI as a true kind of customer service automation capability across dozens or hundreds of markets as a blue sky opportunity. So I would rather keep investing like crazy to get the product as capable as possible and then be able to push into as many additional spaces once we can transition out from a source of strength versus just trying to dig in on the unit economics and staying smaller and trying to make each one of those locations just a little bit more profitable.

So I think it’s a land grab right now. A lot of different companies have grab space in a lot of different industries. We have three to four, I think very real competitors that have good technology in our space that we’re actively competing with to try to grab land in this space. And I think we will continue to see this at minimum, for another five to ten years. And then I would expect conversational AI to start going through a similar type of market consolidation that you’ve seen in a lot of the other industries prior to this.

Yeah. And the interesting thing, of course, is because folks like you and I were a bit more aggressively focused on the the competitor space. And in the end, there’s such a huge consumer environment for this stuff. There really is. If you spend so much time focusing on the competitors, you get lost chasing them instead of chasing your business. And it’s so we always have to be mindful. But of course, the the inner nerd in me is always like, you know, where are we technologically aligned with somebody? And make sure I can always think about differentiation without being stuck on like, they changed their messaging again.

You can’t be attached to folks that are in a parallel space too much.

Yeah, I would agree. And I still think there’s some challenges and some education for the market as well. We recently ran into a situation where a company in our space was telling potential customers like, hey, we’re 90% plus accurate, and they’re just kind of leaving out that. But we have some people in the background that are fixing things on the fly to help us get to that number. And so the customer wasn’t quite as sophisticated enough to ask and the other company didn’t bring it up. And so there is still an element, I think of kind of smoke and mirrors out there.

This is a very unconsolidated, unstabilized market. It’s a bit of the wild wild west. There are no norms, there are no level systems to compare against. There are no independent third parties to verify capabilities and stuff like that. And so we see companies throwing out pretty stretched metrics relative to what we see, both in terms of what state of the art technology and when we test what’s their system actually capable of. And so that’s been kind of an interesting process of bringing this product to market and kind of navigating against the sales and marketing that maybe sometimes there’s somewhere between kind of disingenuous to just sort of withholding information because customer didn’t know what to ask.

Yeah, that’s a tough one. Like you said, especially when it’s a new technology and new space. No one knows that there’s a Mechanical Turk hiding behind the scenes and all that stuff.

Yeah. Google spends billions of dollars developing their Google home system. And I heard a number at one point that said they still have up to 30% of interactions being reviewed by a human. So it is the very dirty secret of the industry of which everybody that’s in it understands crystal clear, and those who don’t understand it and who are trying to figure it out and who are trying to find a way to take advantage of this technology. They often find maybe murky, kind of maybe feel like they were a little misled.

And so I think there needs to be a lot more transparency on our part. And as a technology group as we bring these technologies to market to be real clear about where things work and where things don’t work.

I don’t want to put a limit on the use cases that you’ve got because I’ll say it’s more focused and that you’re less likely to bump into the need to do real deep like sentiment analysis. There’s obviously points where that would come in. I would imagine.

Yeah. For certain.

When someone starts yelling into the speaker like Samuel L. Jackson, you’re probably, time to make sure that somebody taps the headset and get to listen to this like versus some of, like the call center AIs, they’re much more. I feel I’m about to say it, they’re much more challenging to implement because they’re specifically going after doing stuff like continuous sentiment analysis to gauge the health of the call because they’ve been a different long form conversation to attack.

So I don’t mean to say it’s harder. It’s a different challenge that they’re solving. Yours, where do you see the variability and what you can start to do with some of the deep capabilities in NLP and actual analysis?

Yeah. I mean, again, going back to, I mean. We are taking in live conversations on. The vast majority of the conversations we are taking are being handled entirely by the AI, and it took us a long time to get there, but that is a very real product with very real capability. I do believe what we’re doing is exponentially harder than something like sentiment analysis. That is extremely valuable to those companies credits. They’re probably making a lot more money than we are as we’re trying to grind out this hard space, but think about it with that sentiment analysis example.

If it doesn’t work correctly in one to ten cases, does anybody know? Does the end customer know that they care? Does the call center rep on the phone that they know that they really care? Maybe if the sentiment picks up, the call is going really bad, it goes to pull in a manager or they just use it to monitor it after the fact, but it doesn’t stop the core capability from happening. The customer and the call center up still did their call. Could it have been better?

Probably. They still did their call with what we’re doing and with what other companies in our space are doing. If we miss something, the whole call goes off the rails or theoretically can go off the rails if it’s not recoverable and it’s front and center with the customer. So it would be more accurate to say that the call center person is actually an AI trying to carry on a conversation with the customer. That’s much harder than just passively monitoring stuff and tagging it for data or analysis or flagging it to pull somebody in because it doesn’t fundamentally break the core product.

If it doesn’t work, if we go off of one of our edge cases, it fundamentally breaks the product.

Yeah, that’s the interesting thing. And anybody would go through this I just think of the last interaction they had with somebody through an order process at a quick serve restaurant. Odds are the last thing you did. We as humans, made a mistake doing the order or when they do the read, that’s why they do the read back. And I love it. It’s like, do you want to? Actually, no. Let me go with number two instead of number one. And then it’s like, okay, we’ll do that. Is there anything else we can help you with?

Okay. What I’ve got for you now is X and like, that rapid validation and the fact like, there’s so much that can go wrong in the seconds leading up to that, they’ll be like, actually I want number two, not number two, number three. I mean, yeah, number three. Just writing those words down. Yeah. Big deal. You transcribe it. That’s basically a glorified transcript. But actually taking that and turning it into an order.

And responding intelligently in that situation. And maybe you could parse all of that and you got what you needed. But maybe you have to parse all of that. And the customer was still ambiguous. We had a situation when we were working with the restaurant chain here in Denver called Good Times, where we were automating breakfast orders. And so we had a one customer I remember came up. He was like, hey, could I have six sausage burritos? No, no, wait.

Actually, I want three bacon burritos and then sausage burritos. And so it’s like, do you want nine burritos? Do you want six burritos? There’s a lot of ambiguity in there. And so then the system also has to have context. And so that’s an area where we see the company spending billions of dollars, and they’re just scratching the surface of context. Yet for any company that’s trying to do customer service automation, where they’re directly talking to a customer, you have to be able to manage a tremendous amount of ambiguity and related context and then try to respond as we talked about early on with the daisy chain issue perfectly every time.

And you might have a minimum ten turns back and forth, and all you need is just one of those to go wrong. And then the entire thing could be a failure. And so it’s a very painful and exacting process to get to a point where you have a product that is kind of widespread, adoptable and scalable within the industry.

It’s an amazing time to be in this world, though, that we can do this, right? Like to think of the technology that enabled you to do this and that you and the team have chosen to take it on and your succeeding. What a fantastic world, isn’t it?

I love it. I mean, not to be corny, but, I mean, I still get goose bumps when I review sessions, and it’s just perfect all the way through, because I know how hard and painful and grueling that work has been to get to that point. And so when I can sit down and listen to a minute, two minutes, two and a half minute order, and everything flows perfectly throughout the entire order. It’s like, oh, my God, it’s live. It’s real.

It took us a long time. This is a product. It’s such an exciting experience. And truly, I couldn’t be more excited to be in the AI space because this is ultimately going to be the brains of everything. Right? And I think I don’t see it as much as I would like, but there should be a lot more coupling, I think, between robotics companies than AI companies. And if we throw a sort of full circle here, back to the Tesla Bot, there’s maybe one or two Nobel Prizes that’ll be one by an engineering team that can actually pull off what Elon Musk talked about yesterday.

But let’s say that they do. It’s still an extremely capable system that is going to be a paperweight unless it has the brain of an AI behind it. It has to know to be able to carry on conversations with people around it. If it’s about to drop something on somebody and somebody says, stop and yells it at the robot and they’re in an echo-ey warehouse. It’s got to pick that up perfectly the first time and do exactly what was requested. And customers, as we found, just because they’re so ambiguous, they’re not going to write a script for a robot to go and get their mail or go buy them a gallon of milk.

Must talked about like, the system is going to have to be intelligent enough. Somebody’s going to say, Go get me milk. And the robot is going to have to intuitively know what go get me milk means, which is like, turn around, walk to the door, open the door, walk to probably a car, get into the car, drive to the grocery store, walk into the grocery store, go get the milk, pay for it, and then repeat all the steps to get back. And that is where AI lives.

And so it’s just such an exciting time. Industry wide. It’s just in its infancy. It’s going to be really fun to watch this technology evolve over the next 10 to 20 years as it just continues to get smarter, more sophisticated, and starts to proliferate into more places that ultimately, I think, will make our lives better, both as consumers and as employers and his coworkers.

And I want to tap into something that, as technology, amazing. Our place in the world to be able to do this is pretty fantastic. Yeah, I was going to say, what are the risks that we have? But I don’t want to take a dark turn. I want to tap into something else that I saw in your bio. You’re a member of Entrepreneurs Organization, so EO has come up a lot. I’ve had, when you do a couple of hundred of these interviews, you eventually bump into this common things. And EO comes up a lot.

I love to hear. Rob, how did you discover this? And what’s been the value that you found from being a part of that organization?

Yeah. So for anybody listening, who doesn’t know, EO stands for Entrepreneurs Organization. So it’s basically an international networking group organization where entrepreneurs come together. So here in Colorado, we’ve gotten extremely healthy chapter. I think we’re 160, maybe going on 200 people that are in our organization. And every single month, they’re putting on different events. So a couple of days ago, a guy that owns a brewery here in Denver, gave anybody who wanted to a tour of his brewery and gave everybody free beer and talked about the business and the economics of it, things like that.

There was a lady that owned a bunch of restaurants. She gave people tours of her restaurants, explained how they work. She had a very cool kind of collective thing going on where they renovated an old warehouse, and they had, like, a dozen of different restaurants inside there. And you go sit at any restaurant, you can get food from multiple restaurants. Talked about kind of where the evolution that she saw restaurants going. At one point, I think two years ago, we brought in a guy from the military who was the one that found Saddam Hussein.

And he talked about all the work that he had to do to be able to kind of track down where Saddam Hussein was. So it’s just fantastic and intellectually exciting to be around similar people that are trying to grow companies. It’s amazing how many times we all run into the same problems. So to be able to chat through those problems, share experiences of how you’ve overcame those issues, could be partners, can be fundraising, could be legal, can be challenging customers, because ultimately, at the end of the day, it is lonely at the top of an organization.

You don’t want to complain to your direct reports and bring them down. You need to kind of sometimes bottle some of that stuff up, and you just try to keep people kind of excited about the mission and the goals and pushing forward. But then you really do need people that you can lean on have similar experiences that have been what you’ve been through. So the tours, the networking, the speakers, like, those things are fun. But I think the core of EO is what’s referred to as forums.

And so within our bigger chapter of 160 to 200 people, it breaks it down. And everybody gets put into a forum of about five to sometimes ten people kind of on the bigger end of the spectrum. And you get together once a month. And then everybody talks about, like, hey, here’s what I got going on here’s. What’s working here’s, what’s not working. You can give each other experience shares. You can lean on each other. And then even within our forum, we’ll bring in speakers. And it could be speakers to give you education on business, life goals, they could help you with relationships, retirement planning, succession, things like that.

And so it creates this community of people that know what you’re going through that can help you. And that can support you, be it in business or be it in life. And then because it’s an international organization. If you travel to or pretty much any kind of major city, globally, there are chapters of other EO members there, and I’ll regularly get emails of, like, an entire forum that are flying out to Colorado, and they’re like, hey, if there’s anybody local that wants to meet up, let us know.

And you just get to meet all these cool people. I attended one with a group that came up from Costa Rica and really hit it off with a guy he owned a custom software development company. I had just recently left my custom software development company. We connected on everything. And by the end of the night and a bunch of beers, he gave me free access to use this place in Costa Rica whenever I wanted. And so it’s like, what are you going to get those types of experiences in your day to day life when you’re just kind of bumping into people?

And so it’s obviously something that’s near and dear to my heart as I was able to quickly pontificate on it. But I think for anybody that’s running a company, I would just highly encourage you to check it out. It’s just nice to be surrounded and able to interact with just really cool people.

I think I was calling goodness greater policy cameras, last time from Sheets & Giggles. He’s in Colorado, and he was the first one that turned me on to the organization. And then, like I said, probably half dozen other people now. Since then, he brought it up. I’m like, I got to get closer to this. And I’ve actually looked at the organization. It’s good because there’s, like, a minimum as far as the range of folks who can get involved, it’s very targeted. It’s not like a hangers on Reddit group.

This is people who are active. You have to have a certain amount of active revenue. You’re really and truly aligned with a community of people that are doing something. And it’s it’s just so refreshing to me to see that because there’s community for technology, there’s community for so many things. But for founders, it’s a really difficult and lonely spot to be sometimes and have that peer group accessible without having to engage advisors and ultimately, like, everyone wants to give you ideas because they know they can get a hunkier company.

That’s ultimately what a lot of the people that. I want advice from people that are living the life not who just want a taste of mine.

Right. And that is exactly what it is. And I think you also hit on something that was kind of important to me, too. Is it’s not the hanger honors because I went to two or three of the other big kind of national global sort of groups kind of like this, and they just tend to be stuffed with consultants and people that kind of want to live in your orbit. Again, as I go back to my forum, everybody’s roughly in a range from a revenue standpoint, there’s just one guy that’s in the hundreds of millions from a revenue standpoint.

Everybody’s got similar sized organizations in terms of the number of people that they have. And because we’re all living it, we can all collaborate. So in my custom software development company, I crashed and burned with my partners and they bailed out of the company. I’d say at least half of the people that are in my forum, my group of about nine people. Well, probably half of them have had partnership issues since I’ve been in the group, and that’s a lot of experience that I can share.

One guy mentioned that’s in the hundreds of millions from a revenue standpoint, he’s able to give a tremendous amount of advice to us that aren’t at that stage yet that are still growing and building our companies because he’s done a lot of the things that we’ve done. We even have one guy in there that’s managing partner of one of the law firms, and he very kindly, you know, we’ll answer questions and give us some at least sort of direction of where to go from a legal standpoint and things like that.

And so it’s so helpful. And a lot of us will find, we’ll start forum and we’ll just kind of feel like heavy and it’s difficult. And by the time I’m done and we all go get dinner together after forum, I just feel like light and happy and just kind of rejuvenated again. So it’s just sort of good for my soul anyway, to just be around really interesting and exciting people doing cool things. Yeah.

Because like you said, when you go to meet ups and just like general, like event driven organizations, you tend to get a lot of people who are like they’re entrepreneurs. I’m not saying that one isn’t right or one is better or whatever. But you don’t want to be in a group where you’re surrounded by people who just run Shopify. So I know as a guy who runs some Shopify store, I got a successful coffee business, but I don’t have the same thing to bring to the group versus my experience and the advisory and real side.

So yeah, you can see the cut line where.

Plus those meetup groups, they are wonderful. They tend to be a lot more superficial. Might be the best way to put it. You don’t get really deep from a connection standpoint. You might share some ideas here about some cool companies. People come, people go. There’s a lot of transients to it. For our forum, we’ve got real strict requirements on attendance because we really believe that time together, sort of build bonds and build connections. In October, my forum and all of our spouses. We’re all flying to Napa Valley together. We rented a house together.

We’re lining up different wineries that we’re going to go to different restaurants. We’re going to go to in two weeks. We’re all going to meet up at a Lake out here in Colorado, and we’re going to bring our families and our kids. And so it’s a lot, I think, more consistent and much deeper ties than what you might see in some of those other organizations. Yeah.

And it’s finding the group of people who are aligned in a like, it’s tough to find those two things together. You can find a lot of alignment. But then if they’re so disparate in where they are company position wise, it sounds like such a great organization. I’ve heard nothing but really respectful words spoken and folks that are part of it. So I do recommend that. I guess in closing, sadly we lost couple of minutes in the middle because, for anybody that still watching on the YouTube, they’ll see that I’m on a phone instead of on my regular rig here.

Rob, I’d love to get your advice for folks that are getting started, and especially now, COVID and the state of the world means we’re going to be remote longer. It’s a great opportunity, I believe. Are there opportunities to be had? And so for folks that maybe were on the cusp, people that are already remote and thinking, maybe this is my time to start up my entrepreneur mindset. What advice do you have? Kind of today. It’s August of 21. What can the next three months be for somebody who wants to think big?

Yeah. So if you already have your business idea and you know what you want to do, then just get started. It’s the most critical thing. I just finished reading a book called Super Founders, and they talked about what was the number one key to people’s success. And the kind of read it too long didn’t read is past success, which sounds cheesy, but it actually makes sense. So people that have started companies are then more likely to be more successful and are more likely to build a billion dollar companies having done it in the past.

So I think it’s just like anything. You need experience and you need time. I think a lot of aspiring entrepreneurs, they try to make their first company a billion dollar company. So goal one is just our, goal two might be go easy on yourself. Don’t think you have to build the next Uber or next Microsoft with your first company. Think of it in terms of training for a marathon. And your billion dollar company is running to the marathon, right? You need to do things leading up to that.

The easiest place to start a new business is a service based company. There are so many opportunities in this country right now. It’s astounding I think of anything, it doesn’t have to be super exciting. I mean, it could literally be a landscaping company. It could be a house cleaning company. It could be a painting company. People out there are desperate for services. As a quick example, my wife and I are going to remodel our basement. We’re adding a bedroom and a bathroom when we initially got it quoted about 18 months ago to now, not only have prices gone up, about 220%, we had to bring out, like 15 contractors to just find one contractor that wanted to take the project on.

And so there’s huge opportunities out there for people to just start really good service based businesses. Not only I think is there sort of a lot of opportunity from a work standpoint. I think a lot of people out there think that it has to be this big, grandiose thing and it really does not. So start a service based company, get good at it, deliver great customer service. Build a business number one, potentially get yourself out of the rat race. You’re able to create a job for yourself.

You’re able to create income for yourself. Maybe you’re able to then have an exit and sell the business and you use that capital to start your billion dollar company. Or kind of more like I did. I got the service based company to a good place. And then I came up with the idea for my billion dollar product based company. I hired somebody to run my service based company for me. And then I went full time on the product based company. So you open up a tremendous amount of freedom for yourself.

If you just are owning a business and just running a business, just start. Go easy on yourself. Consider service first and focus on coming up with your billion dollar idea while you’re already working for yourself and making money.

That doesn’t inspire people to just sort of take a breath and think about what the possibilities are. I don’t know what is. So, Rob, thank you very much. It’s been a real pleasure. Thank you for writing me out during my technical troubles here today. If people did want to get connected online or elsewhere, what’s the best way they can do so?

Yeah. Feel free to just shoot me an email. It’s rob@valyant.ai or find us online or any of our social media sites.

That’s a beauty. Excellent. Rob. Thank you very much. Lots of great lessons. I’m bullish on the possibility for Valyant. I like what you’re doing. And as they say in the world, you bet on three things the three Ts, team, TAM, and technology. And the reason it starts with team is because you can tell when somebody has potential in something you don’t even need to know where something is, but you know somebody’s got the potential. I would bet on your team.

Thanks, Eric. I really appreciate it.

Excellent. Thanks very much.