The Human Side of Smart Storage

Can AI truly replace the human touch in self-storage?  

Scott Meyers welcomes Mason Levy, founder of Swivl, to explore how artificial intelligence is transforming customer engagement across the self-storage industry. 

From its surprising roots in healthcare and cannabis tech to powering over 4,700 self-storage facilities today, Swivl is revolutionizing the contact center model with its AI-driven platform. 

The conversation dives deep into conversational AI, human-in-the-loop systems, future-proofing tech stacks, and why personalization still matters in an automated world

WHAT TO LISTEN FOR

0:56 The Accidental Storage Tech Founder

5:48 What Makes Swivl Different From Just Another Chatbot?

10:31 Smarter Gate Codes & SMS: Real-Life Use Cases

20:59 Swivl’s Future: Voice AI, Contact Center Suite & More

32:55 The Human Side of Storage: Why Empathy Still Wins

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Chapters

• 0:56 The Accidental Storage Tech Founder
• 5:48 What Makes Swivl Different From Just Another Chatbot?
• 10:31 Smarter Gate Codes & SMS: Real-Life Use Cases
• 22:09 Swivl’s Future: Voice AI, Contact Center Suite & More
• 34:05 The Human Side of Storage: Why Empathy Still Wins

Transcript

Announcer (00:03):

This is the Self Storage Podcast with the original Self storage expert, Scott Meyers.

Scott Meyers (00:12):

Hello everyone. Scott Meyers here, and I am the host of the Self Storage Podcast. And on today's episode, we have none other than Mason Levy with Swivl Mason. Welcome to the show.

Mason Levy (00:23):

Oh, Scott, I'm excited to be here, man. Appreciate you inviting me on.

Scott Meyers (00:27):

Long time coming, long time coming now. We've been a user of your technology, your platform for a little while now, and just thankful that I'm able to share with Storage Nation what it is that you do and what it is that you do for us in the self storage community. So with that, I'm going to turn it over to you to give us a little bit of background on yourself, how you got into the software industry, and then ultimately how that Swivl morphed into the multifaceted platform that it is right now and then dipped into self storage.

Mason Levy (00:56):

Yeah, awesome. I mean, I think how everybody gets into self storage and is kind of a stumbling, people stumble into it and find it. Some people get born into it, but I think we're more of the stumbler here. But if we take a step back, kind of around my entrepreneurial career, I knew really early on in my life that I wanted to kind of go a non-traditional route. And so I left Apple, I was working for Apple straight out of school. I left Apple to jump in the startup world, and the first company was a healthcare tech company. I was the first hire outside of two co-founders that were became large mentors of mine. And ultimately we were working on helping patients communicate with their care teams at scale. And so really early on in my career, I was introduced to conversational ai and I fell in love with just the concept of building machines.

(01:54):

I think this is a human thing, right? Building machines that emulate human action. And this was in 2015, so the technology at that point in time was a little less than what we have today. As much as change, not a lot of still the same, but ultimately I fell in love with just building a business and interacting with customers. And that's kind of been the story of my entrepreneurial journey is just really lean startup, continuing to be curious, ask questions, pivot. And so around 20 16, 20 17, I decided to leave that company and venture out on my own and met some co-founders through that process and founded my second business in the cannabis industry, actually still working on conversational ai, helping people communicate at scale. And ultimately, again, I think at the end of the day, a lot of times I think about falling in love with the problems that you're trying to solve and not necessarily the solutions that you potentially are envisioning.

(03:09):

And that led me to this pathway. And so as you're diving into how do we solve conversational AI problems, whether it be in the healthcare industry and the cannabis industry or at large around just enterprise business, ultimately we kind of found two main problems that we wanted to go and solve. And that was like how do we make these things smarter, faster? And ultimately that's around the data training feedback loop. And then how do we customize and adjust and control these systems? And so we've been working on that for almost a decade now, and that's really what led to the founding of Swivl was just wanting to go and solve these two big hairy problems. We didn't know where we were going to end up, what the customers were going to look like along the way. We had customers like Cox Communication, JB Hunt, and eventually Extra Space Storage actually found us.

(04:05):

Again, you got to be lucky and prepared for luck sometimes, right? But they found us through a marketing agency that they were utilizing. We had no clue exactly what we had stumbled upon at the time, but we worked really closely with their team in 2018 to build our first model for self storage. And we, man, it just really started performing really well and without sitting here and boring everybody about every step, fast forward five years and we're powering over 4,700 facilities, not only with Chatbots, but we've obviously grown up a lot over the last five years. Power voice interactions, text interactions, we do review solicitations, referral solicitations, et cetera.

Scott Meyers (04:53):

Alright, so we could go in a lot of different directions here, Mason. So I do want for the folks at one of those 4,700 that folks that are not utilizing Swivl yet, you are a platform, but we've also heard many software companies call themselves a platform in our industry, and that includes the actual website providers and other ancillary folks. So if you would, let's break it down. Where does Swivl fit in? And for the most part, what we're used to seeing and call the platform is just a website that allows folks to be able, an interactive website that allows folks to be able to rent on online reserve and pay online, but you take it another level. So tell us what the platform looks like and then how it works with an existing facility or if it replaces everything just so that we start from elementary right on through to where we find ourselves today.

Mason Levy (05:48):

Sure. At the highest level, Swivl again is an AI platform for self-storage operators. And what does that mean? Well, we think about ourselves as an intelligence layer, and there's a couple of pieces of this, right? You can think of one side as customer facing, and so this is all the channels that customers might potentially interact with your business and brand. We kind of touched on it, web chat, QR codes via progressive web app voice interaction. So a phone call, obviously web chat sitting embedded on your website. That's our bread and butter. But on the other side of that intelligence layer is data sources. And so we think about the facility management system as a system of record. We think about Google as a system of record, there's a number of data, even your website is a system of record and we're ingesting a lot of that information into our platform.

(06:46):

And then there's two other components. One of them is the actual backend application that we provide operators. And this is where operators have the ability to go in control how these AI performs, set rules, make adjustments so that this agent becomes their own right? Obviously we've got core models that scale across the industry, but we want to give operators the tools to allow this to be their own as well as allow them to make sure that they're meeting regulatory standards in specific states. And so in this platform or in our backend app, you can go in group states or your locations that are in California in a different group than maybe is in Georgia because the collections process might be slightly different or the facilities have different features. And then the last component is really the one where our customers are engaging with the application the most, and that's the human in the loop side of this.

(07:47):

So since day zero, I've always envisioned AI being human a loop at any point in time, whether it's a customer, a business operator, or the ai, somebody can push the stop button and jump in and have a conversation. And so we provide really beautiful interfaces for agents to have not only text-based conversations, but voice-based conversations, send out emails, et cetera. And so that entirety makes up what Swivl is. So end to end, you're looking at again this intelligence layer that plays first line of defense on any channel that a customer could engage with you. It pulls in data from different data sources to make it intelligent and smart, and then it's got a human loop component. So at any point in time a human wants to have a human conversation, they can sit here and say, Hey Scott, how was your weekend?

Scott Meyers (08:36):

Alright, so let's break it down a little more simply, Mason. So let's say that a client comes to you or potential client comes to you and they've got every layer available in self storage on the tech stack prior to say ai, maybe even a couple little chat bots, but then they're looking at your platform and they decide to go with you because they like what they hear. What is the difference? What do they see? What is the actual benefit that you're bringing to the table?

Mason Levy (08:59):

Yeah. Well first of all, we collaborate with a lot of different pieces of the tech stack. We're not trying to replace a facility management system that does your billing and your invoices and houses all your leases and tenant information. We're also not trying to replace your website, your digital landing page, your storefront. There sometimes are overlap and feature sets within that. But at the end of the day, what we are trying to replace is all of the communication stack that you have. And so if you've got a contact center today, we're bringing a next generation contact center to the puzzle. If you've got a reputation management platform, we're bringing a next generation reputation management platform. The big differentiator here is it's powered by what we call our stacked lobe system. That's a really fancy product marketing term for over 32 machine learning models that are purposely built for self-storage.

(09:56):

And they're doing everything from analyzing reviews to responding to your customers or understanding intent from the customer engagement. So that's really it. I'm happy to dig a little bit deeper and break that down. But again, a big differentiator here is it's powered by ai. So instead of just sending out an SMS message where we know 30 plus percent of SMS messages that are sent out to customers, the customer actually responds to and then yesteryear that went to either a human inbox or to nowhere land. Today, an AI agent is sitting there responding automatically, right? It knows after we sent a move-in message and the customer says, Hey, do you have dollies available? Well, we know what location they're at, we know that there are dollies available and we can respond appropriately. We can help with gate codes. So three months later when that same customer forgot their gate code and now needs to get into their facility, we can go in and make sure that there's an account there to factor, authenticate the account and then make sure that they're in good standing. If they're not in good standing, automate a bill payment if they are in good standing, provide that gate code, et cetera. And so it really is this intelligence layer that's helping automate the tedious task that your employees, the team members, you guys don't want to do it. It really frees you up to do more human interactions to really engage on the things that are driving value for the business.

Scott Meyers (11:31):

So Mason, I was out or over in Tokyo a couple of months ago and I was on the main stage give a presentation on how AI is changing self storage, talking about Swivl and how we're using the platform within our own organization. And as you can imagine, there's a host of other folks out there in the hallway that were very anxious for me to about their products as well. And so I did touch on a few prior to giving my presentation. I was there a day before looking through the trade show. And as you can see across the board, AI itself is permeating every facet of well all industries. And we've saw it from the security side now getting at really smart cameras that are detecting faces, let alone the heat mapping and everything else, and then sending it back to the appropriate levels and determining is this an alarm that goes just to the police?

(12:25):

Is this one that goes to the manager? Where does this actually go? And routing smart routing of all types of communication. As you mentioned, we're seeing some platforms that are really not just platforms, but they're just on the sales side. So on the front end, so a chat, call it a chatbot plus to other platforms like yourself, which are like Swivl, which then goes all the way from a sales oriented chatbot into creating the contract, following on through with the same platform, sending out late notices. And then even if we get to the place where there's an issue in payment, some will send it over to another AI based or AI powered auction process. And we're seeing this, we're seeing bundles, we're seeing individual and independent companies that are using AI in either their old platforms or new ones coming into the market right now. I think very quickly we're going to get crowded. So tell me a little bit about what you see if you can, how far do you go out? What's your one year crystal ball look like? Three year crystal ball for the industry and how far you think AI can change it? And then where does Swivl fit into that? And maybe share a little bit about what you're looking to do.

Mason Levy (13:36):

Yeah, I mean, first of all, it's a really exciting time to be a technologist regardless of the industry that you're in. I mean, there's just a lot of tools out there that allow for us to build some really cool products for our customers. And self-storage is really exciting. There's a big need. I think COVID, for better or for worse, pushed the industry forward probably four or five years from a desire of wanting to adopt technology. I know historically self-storage is a laggard industry. They're very slow to adopt. And I think around the time where people started to say, Hey, we can do this unmanned, we can do this hub and spoke, we can do this virtually. It really started to push operators to ask for service vendors to start to create these products. And that's a really exciting thing. So the fact that the market is now becoming, there's more competition and options is just amazing for the self-storage industry.

(14:40):

Competition at the end of the day in any space is good. Having multiple FMSs to choose from multiple website providers to choose from is, I think there are a couple things that I want to touch on is as much has changed in the last three years with the coming on of large language models, GPTs, not much has changed. And so GPT Transformers were invented by Google in 2017. We've been using them since 2017. If we can remember back then we were doing kind of the auto complete and Google Docs. It was just one or two words, it's the same technology. And the big difference that and allowed for the step up, the big step was basically data centers. We started building massive, massive data centers. And this is not magic, it's still a lot of math that goes into these transformer style technologies. And the secret here is that they're still human powered.

(15:44):

Every piece of data that's going into these things is still being labeled by the ghost army of data labelers. And so a lot of these problems are still present from yesteryear to today. And I think the other thing that I want to touch on as I'm geeking out just a little bit around large language models is there's a lot of benefit to them. There's also a lot of drawback to them. And so I give that because they're not always the end all be all for solving a problem. Sometimes old school unquote machine learning model or a logic flow is going to be the right choice to solving a problem specifically from a B2B perspective. There's examples of airlines who put a GPT wrapper in front of customers and it discounted the entire airplane for free. I've seen that with competitors products and Chad, I mean, we're always seeing what's in the market and we've gotten competitors products to give us or to say that they were going to give us 30% off on a unit for two years because we told it that we were a good boy this week and we deserved some type of a reward.

(16:57):

We've gotten them to give us fake gate codes or to give us gate codes that we didn't have. And so I think being grounded in technology that works, technology that has a background and not just the latest shiny stuff is really, really important. So part of the question that you asked was how does the industry adopt things? And I think there's a couple of things here. One's like I hear it all the time. Operators want less tools, not more, right? They want platforms that they don't want specifically in the areas that we're working in where it's like we're communicating with customers. And what I mean is in their business, not necessarily in the market. When they're communicating with customers, they don't want their call center agents and contact center agents to have to go look at the facility management system, go look at the call center software, have to go over to the website, have to go to an internal document, and then come back and answer the question.

(17:57):

And so if I think about all these tools coming into the market and then you go, well, what's say 12 months from now just from a market perspective, my hope is is that there's a lot of collaboration that's happening among these tool sets. How cool would it be for your operating partners to log into a single place and be able to have information from your camera sets populated in here, to have information from your contact center populated in here, to have information from your facility management system, from your Google Analytics, all of it being populated into a single place where you can start to make decisions, a command center of sorts. And so we continually work with partners in the industry to try to find ways to better integrate rightly as a partnership is really great. This is an amazing partnership with us. And we do this with some other website providers, storage pug, et cetera, where we're able to push people through the shopping funnel further than we can with other website providers because we're communicating with their system at a deeper level.

(19:09):

And so I hope that continues, right? We're in talks with a number of facility management systems to continue that as well too. Well, there's information that Swivl has that's going to be valuable for the facility management system, whether that's from a pricing perspective or not. Like if Scott's coming and talking to Swivl four times a month, maybe we should treat him differently than we treat somebody that talks to us once every quarter. And so how do we start to communicate to these billing systems? Maybe that means that Scott is constantly coming here, he's got a business that he is running out of the storage unit. How do we start to draw trends and start to connect those data sets for insights to be smarter? And so I think that's my hope over the next four to five years is I don't think we're going to see this drastic change in what we're actually seeing.

(20:04):

I think that change has kind of already happened now the tools are just coming into the market, so you're going to see more maturity from them. But really where it's going to be a differentiator for operators is when all of the service vendors can really work together and integrate in a further way. The last thing that I'll put here, you kind of asked around what we're working on over the next 12 months. We've been pushing really hard. We've got some really big, I don't know exactly when this podcast will come out, but SSA Vegas in early September. We've got some really big announcements. I don't think it's a secret. We've been deploying voice agents for over six months now. They've been answering the phone for operators. We're engaging selling, doing the whole nine yards, helping move people in. We'll launch a full contact center suite at SSA in Vegas.

(20:59):

And so that's really exciting for us. And then when we think about our, I don't want to say complete features or not feature set, but pillars of our platform, we've obviously got our intelligence layer, we've got our channels, we've got our human in loop contact center, we're doing reputation management with Google and Yelp and listings. Kind of the only missing piece that we see in here is some type of a task and ticketing system. Now the foundation of that has already been built into our platform, but ultimately we want Scott to be able to come in and yeah, he doesn't engage with Swivl as a platform every single day because he's got other people that are doing that. But maybe there's a task that only Scott can answer around some type of a legal question that we might have. And so we want to be able to sign that task to Scott to do that specifically around the sales engine, the marketing engine, who should we be following up with?

(21:57):

Who should we have touch points on? And again, this is all about being human in the loop. Some decisions today still and should be made by the human component of this. And so we're always looking at how do we make that human machine collaboration better? And to us, we've been really focused on what we would consider for the most part, synchronous communication when our AI is immediately engaging and immediately escalating. And so with task and ticketing, now we're thinking about, well, what's asynchronous communication and task look like? So somebody came in, they reported a light out or a gate being broken. Well, how does that create a task or in a ticket that can asynchronously allow for the management team to then go and engage with whoever out in field ops needs to go out and go make that change too. Those are kind of the things that we're looking for. And again, this goes back to integration partners, vendor partners, and making sure that we've got as much information as we possibly can and we're pushing as much information to our partners as well so that we're all working in unison together.

Scott Meyers (23:09):

Well, I have a question and I think it doesn't come from paranoia, but I think as a business owner, I think you also have to have a little bit of a healthy paranoia. And as I look at AI and I look at the ways to be able to implement and incorporate into my many businesses looking at just self storage and say, my facilities, what comes to mind is the Incredibles, the first movie when you look at syndrome and his nemesis, and the goal there was

Mason Levy (23:43):

To create, I love the old school Pixar reference. I love it. Oh, that's

Scott Meyers (23:45):

Fantastic. So ultimately his goal is to make everybody a superhero because then when everybody's a superhero, then nobody is. And so I kind of, for whatever reason kind of harken back to that. And you look at AI that anybody essentially can then now become a superhero by utilizing ai if you know the right prompts to put in certain parts of your business, everybody's using Swivl, everybody's utilizing these learning models and it just keeps getting better and better and better. So how do you differentiate yourself? I mean, you just touched on it a minute ago and says there has to be the human interaction. There's some pieces to that and maybe there is no answer to this question, but I feel like the early adopters are obviously going to have an edge and be able to get some traction in a particular market for everything that the Swivl platform does for folks. But what happens when everybody is utilizing the same thing? How does one differentiate yourself? Are we back to price again just like we were maybe in the 1970s and eighties? What does that look like?

Mason Levy (24:46):

I think that's a great question and verticalization and deep verticalization is the differentiator in one area, but I want to take a trip down memory lane just for half second. We're going down to Pixar, circa the early two thousands, so might as well go back. I mean the same thing was said about the internet and websites, and the same thing was said about mobile phones and apps and you differentiate in a number of ways. One, as a vendor, something we've always hung our hat on is customer support, customer success, providing this amazing experience to our customers that as a software vendor is huge. We also differentiate by the pace of innovation that we continue to deploy in 2024, I think out of 12 months, I think we had close to 36 software releases over those 12 months. So three times a month we're releasing new features.

(25:52):

I think that's a big differentiator for us. The next thing that I want to say is when we talk about machine learning and we talk about large language models and all this kind of stuff, there's a misconception that everybody is going to have the same thing. And that's not true. That how you build these things and how you deploy them is so vastly different. If all you're doing is taking chat, GBT, open ai, anthropic and their foundation models and all you're doing is layering on a prompt, on top of that, you are not doing anything besides having a chat GBT wrapper, right? The deep integration, the ability to say, which again, I go back to our Stack lobe system, we have 32 machine learning models, which model should I be utilizing in order to perform the task? And sometimes that's a large language model, sometimes it's not.

(26:47):

A really good example of this, if I'm using a large language model to identify what language someone is speaking, I'm using the wrong tool. Yes, large language models can do it, it's going to be slower, it's not the right tool for it. So the end customer experience is going to be bad. Let's take another one. If I'm using a large language model to pick out sentiment and review ratings, I'm using the wrong model. Again, it's not the right model. I think using the right tools is going to give people the edges for this Now, and when we think about contact center, when we think about communicating with customer, obviously latency and time and voice and just setting expectations for customers is really big. Design is always a big one too. So in the AI world, conversational design is really big. How do we engage with customers?

(27:46):

What's that workflow look like in order to engage with customers? These are all differentiators that allow for customers. Even we give customers tool sets so they're not one of Swivl a customer and Swivl B customer, yes, we're using the same platform, but they're implementing it completely different. They're not using the same thing. They've got the tools that allow for them to be differentiated. We've got a Southern California brand who is very up Cowabunga dude type of a thing. And that chatbot or that AI agent is engaging different than the AI agent that's kind of a national brand and has a more professional tone. And so we're giving those tools to operators. So the power of that is really big. And then again, I go back to the collaboration with partners. So this integration, how deeply are you integrated with 'em? That allows for both partners to differentiate, that allows for the website partner to market specific features allows for us to market specific features.

(28:53):

So I think there are a lot of ways to differentiate outside of just price. If all we're doing, and lemme say one other thing, large language models are not cheap. And so if all they're doing is competing on price, they're not really trying to provide the best service to you. There's a cost and innovation as well too. And so they're not going to continually push the ball forward. So I think there's a lot of ways for operator or vendors like Swivl, we're constantly thinking about how to be better for our customers, provide more tools, get that feedback. Again, I go back to apps. I mean there's a reason why people choose one app over another, right? There's a reason why. And some of that's intangible. Some of it's some it's feel and there's room for multiple players in the market. That's again, competition's great. You don't need to be everything for everybody. And so we're always constantly going, looking at ourselves in the mirror and going, who are we? What's the core of what we do? And let's continue to surf towards and to continue the surfing analogy, surf towards or ride the wave that is the Swivl wave.

(30:05):

We have a lot of core values that we really lean our heads on,

Scott Meyers (30:10):

And that was the answer that I expected. We've been having these conversations in our mastermind in the self storage mastermind, which I think if the staff hasn't already reached out to you that you're going to be coming here very soon too because we're having these conversations with regards to AI and the comment that was made I think maybe six months ago or so, as we look at our businesses, I have an education and mentoring coaching seminar business that also includes our mastermind in addition to the investing side of the business. And really we're seeing impacts being made, advancements on both regarding ai, but AI is also replacing some of the work that we used to do in the education business because people can find those answers. But at the end of the day, especially in the peer education or say information, if you have a business that's built on that or primarily built on that, the difference is that you know what the owner, the operator, hopefully they care.

(31:12):

And so people can get information, they can get an answer to their question, but does it speak specifically into their situation? AI doesn't care about that person. Whereas again, our organization and certainly our mastermind, everything is catered to and tailored to the individual within not only the group as a whole, but then also the individual. And that's a place where in a community, in a mastermind where that human interaction just can't be replaced because people get to speak into everybody's particular situation because they know them, they care for them, and they understand how they tick. And not every answer is correct. It's not the right prescription for every question that is thrown by way of a prompt into ai. And I would say even the same on the investment side as well. There are folks that have different end goals in mind for their business.

(32:01):

Do they have investors that are coming alongside of them? Private equity? Well, the decisions you make are a little bit different. You're taking fewer risks. You have to preserve their capital and get a return. Whereas if you're a solo dude and you're set, you've got everything set as far as your monthly expenses are covered, you might be swinging for the fences and maybe making a little more risky investments if you will. Not risky, but maybe stretching a little bit. So I think that truly is the difference in any business when you're looking at these, using a model, utilizing this technology, the prompts, whatever anybody wants to call it until they know what they're supposed to call it yet, that is the difference, is the human side and that there should be a human coming alongside of you once you gather that information, that cares enough to be able to speak to your specific situation before you make a huge decision just based on something you get back from a prompt.

Mason Levy (32:55):

At the end of the day, again, going back to this future question that you asked, the next five to seven years is really going to be around this human machine collaboration. And every operator, every business is going to slide a spectrum a little bit to how much of each one we

Scott Meyers (33:17):

Want.

Mason Levy (33:18):

But again, going back to a differentiator, you need to have a tool that allows for you as an operator to do that. And so again, and just to use our system, we have the ability for operators to say every sales interaction, the second that it's identified, I want that to escalate to a human because we believe that humans are going to be able to do that internally. Obviously we're an AI business. I tell our customer experience team, I'm like, I want you to know everyone's birthday. I want you to know what their kids' first names are when their birthdays are. So yes, automation is maybe helping us do some automated outreach or running reports for us and driving insight.

Announcer (34:01):

But

Mason Levy (34:01):

The thing that you can do is say, Hey, happy second anniversary, right? Let's have that human moment. And now, and at the end of the day, humans, we crave social engagement, right?

Scott Meyers (34:14):

Yeah.

Mason Levy (34:14):

It's a really interesting tangent that we could go down on and maybe that some of these things could give us a sense of that and fake us into thinking that we're having social engagement,

(34:23):

But we do want this human element. So again, having a platform and technology that allows for you to make that choice of how much and how little of the thing that you want, it's there. Now, customers, the self-storage industry, we sell a relatively simple product, three balls in a door. I understand there's more complexities than that. There's differentiation even in how you sell it and the type of product that our operators put out there. But at the end of the day, we're talking about people that for the most part, they're putting their self stuff in storage. Historically for the five Ds, typically negative things. I think today it's lifestyle choice,

(35:08):

But I think there's an opportunity to get to know somebody and meet somebody there because of those things. Of course, I literally today, right now for the last four months and the next eight months, my entire home is in self-storage. I've been nomadic and I live that life. This is probably the third or fourth time that I've done that. And so depending on the day of the week, the month, I'm somewhere else. And it'd be really nice if operators knew that about me and could provide me personalized a human touchpoint when I visit the facility, they're welcoming me back to the place that used to be at home. Those are things that are, you can't replicate a machine's not going to replicate, at least not today.

Scott Meyers (35:50):

Yep. Understood. Understood. Well, Mason, obviously we could go on for quite a while and go down a number of different rabbit trails and not even rabbit trails, just different paths. And I mean, this is truly an exciting time and I can't even imagine. It's difficult for me to focus as it is. Well, it's always been difficult for me to focus no matter what as I guess as an entrepreneur. But then now, gosh, you add on AI and all it is able to do, and I no longer sit around and wonder about ways to be able to attack a problem. It always starts with a prompt, the most elaborate prompt that I can put in to at least get me thinking about my next steps. I mean, there's no reason to be stuck in business any longer if the right places to go, as you mentioned, the right model, and then to ask it the right question to get to the answers that you need or the right path or strategy. I mean, there's an it time, it is

Mason Levy (36:41):

Blank page problem is not there anymore,

Scott Meyers (36:44):

Right? No, no, it is not.

Mason Levy (36:46):

And that's awesome. I mean, what a superpower for us to have where regardless of what you're trying to solve, you're redesigning a website, a trade show booth, you're trying to think about something else. You're like, Hey, I've got a couple of little tidbits of ideas. Just help me get started. And then you have a four hour conversation, you end up somewhere where you really love it, that's awesome.

Scott Meyers (37:06):

Or what used to take four hours now is done in 30 minutes or 20 or sometimes five, whatever that is, depending upon how stuck or how the lack of creativity maybe that you've had in the past. So it is exciting times. Well, I have one last question for you, Mason, but before that, how do people get in touch with you and how do they get to, first of all get to see a demo of the Swivl platform, which is amazing by the way.

Mason Levy (37:27):

Yeah, appreciate it. Website is tri Swivl.com. That's T-R-Y-S-W-I-V l.com. Obviously we're a startup. You got to lose a vowel in there. So we lost the E in Swivl. And you can find us on our podcast as well too. The self storage lab. We like interviewing really smart people. Those are probably the two best ways to get in touch with us. A demo, there's a live demo on our website. There's buttons on the website that say live demo, click on it. It's going to be a fake self-storage website that we created for people to go and play with. You can also email meMason@triSwivl.com. We'll set up a time, go through a full voice demo, we'll call one of our AI agents and talk about being laid off and having trouble making a bill payment and play around with the geeking out on that as well too.

Scott Meyers (38:15):

Awesome. Awesome. Thanks Mason. Well, one of the many questions that I ask our guests at the end of the show is regarding books that they're reading, books that they've read that has had an impact. I want to drill down and get a little more specific. You mentioned the nomadic lifestyle, and so is there a particular book podcast person that maybe turned you to or opened your eyes to living the nomadic lifestyle and what was that or who was that?

Mason Levy (38:41):

Yeah, I mean, I think my entrepreneurship is what really led me into being nomadic. I've crossed state lines now 13 times and I think nine years everywhere from Manhattan to California down to Miami and in between Colorado, Texas, North Carolina, Georgia. And so I think early on in my career, it was really just kind of a force of needing to be somewhere. And so I would get up and move and I needed to. As an entrepreneur, sometimes you got to do the hard things, right? So there's a book right there, hard Things about Hard Things. But I think some books that really drove me early on was the Lean Startup. One of the ones, if we talk about the human side of things that I absolutely love is a book by ATIs Grande, called Being Mortal at Towane is a world renowned surgeon and he just talks about how precious human life is and

Scott Meyers (39:40):

How

Mason Levy (39:40):

Our medicine sometimes we need to optimize for quality of life and happiness. Other, I'm an avid reader, so I could go down the thing here. Some other ones that kind of come to mind. Crossing the Chasm is one of my favorite business books. Machine Platform Crowd is a really great one. If you're trying to think about the evolution of technology, life 3.0 is another really great one that's kind of relevant. AI Superpower is another one that's really great for the AI topic, ghost work if you're interested in the data piece of the puzzle behind the scenes. And then my last one that I'll throw out there is Steve Wave, Steve Case, that's the founder of a OL, the Third Wave. I think we're going into the fourth wave right now. So it's really interesting to think about what the previous three waves look like. And typically these things repeat themselves, and so there's repeating patterns that happen there.

Scott Meyers (40:35):

Awesome. Awesome. Well, I know you wouldn't disappoint with that question, so I appreciate that input. Well, storage Nation, you have been hanging out with Mason Levy of Swivl to learn more ways and how to be more efficient to enhance your communication models across all platforms. And quite honestly, just to be a better business owner, entrepreneur, and human with the use of ai. So with that, Mason, thanks so much for your time. Looking forward to seeing you at the Mastermind.

Mason Levy (41:01):

I appreciate it, Scott. Thank you so much for having me.

Scott Meyers (41:03):

Alright, take care now. You too.

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