Leveraging AI

300 |💥 AI done right - behind the scenes of the most advanced AI company I work with, with Ari Supran, CEO of Sonance

• Isar Meitis • Season 1 • Episode 300

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What does AI transformation actually look like when it's done right?

After 300 episodes exploring AI's potential, it's time to go behind the scenes with one of the most advanced AI adoption stories we've seen. Not a Silicon Valley software company. Not an AI startup. A manufacturing business with 360 employees that has embedded AI into the way it works, builds, sells, and innovates.

In this special 300th episode, Isar Meitis sits down with Ari Supran, CEO of Sonance, to unpack the real-world journey of transforming an established business with AI. From leadership buy-in and employee training to custom-built applications, internal AI infrastructure, and company-wide adoption, this conversation offers a practical blueprint for business leaders looking to move beyond experimentation and into execution.

If you're wondering how to turn AI from an interesting tool into a competitive advantage, this episode provides a rare look at what's working, what's not, and what comes next. 

In this session, you'll discover:

  •  Why leadership involvement—not delegation—is the foundation of successful AI transformation 
  •  How Sonance grew AI adoption to more than 100 active employees across the organization 
  •  The "orchestrator" role that's creating a new category of business value 
  •  How non-technical domain experts are building powerful internal applications 
  •  Why custom AI-powered tools can outperform expensive off-the-shelf software 
  •  The infrastructure required to scale AI safely across an enterprise 
  •  How AI agents and connectors are accelerating productivity throughout the company 
  •  The role of knowledge graphs, context, and clean data in the next phase of AI adoption 
  •  Lessons learned from three years of experimentation, implementation, and continuous learning 
  •  What business leaders should do today to prepare for the next wave of AI transformation

About Leveraging AI

If you’ve enjoyed or benefited from some of the insights of this episode, leave us a five-star review on your favorite podcast platform, and let us know what you learned, found helpful, or liked most about this show!

Isar Meitis

Hello and welcome to episode 300 of the Leveraging AI Podcast, the podcast that shares practical ethical ways to leverage AI, improve efficiency, grow your business, and advance your career. This is Isar Metis, your host. And as you can imagine, I'm really excited because it is episode 300. But before we talk about that, I wanna thank you, each and every one of you, for listening to this podcast. Some of you have been with me in this journey for over three years now. Some of you are probably just getting started, but I really, really wanna thank you for being a part of this. More or less everything that I do right now, from helping companies, really large companies, really small companies in multiple areas around the world, in different industries, help them with AI adoption, wouldn't happen before or without this podcast. And so again, thank you. But I try every single week to make the best episode that I can, but obviously 300 is a big number that is worth celebrating and doing something special. And I thought a lot of what is that special thing that I want to do for episode 300, and what I decided is I decided that I wanna take you on a tour, show you a glimpse, if you want a backstage pass, to how my most advanced client, the company that I know personally well from all the people that I work with, and that's dozens of companies in the last three years, that are really doing AI transformation right. And what we're going to do is we're going to look at it through the lens with the help of the CEO of the company, and we're gonna cover everything that they are doing, from which people are doing what from an HR perspective, from a training perspective, from a hiring perspective, which technologies they're using, what processes they have in place, what are they using agents for, which concepts drive their decision-making, and so on and so forth. The goal is really to show you what successful AI transformation can look like and what questions does it raise. There's not just only answers. I'm sure there's gonna be a lot of interesting questions that are gonna come up or hesitations about different things. But it is going to show you what the path can look like, and we're gonna talk a lot about the path as well, and the way we both got started. So Ari Suprun, who is the CEO of Sonans and he's the guest of our show today, he- him and I met just over three years ago, I think, and we started working together shortly after because we clicked very much in the way we think and we approach things. And the company that he's running is not a high-tech company. They don't write code. They are a manufacturing business, and they distribute what they manufacture with all the complexities that come with that. And What Ari is going to share with you is all the issues that he faced through these three years and how he thinks about the process, and what he has done that worked and what he has done that didn't work, and what does he would recommend to anybody to start today, and how to do the things right based on what he knows today, which may not be the thing that we're going to say a year from now, but as of right now, it is probably the right thing to do. Again, the process started for Ari and I just about three years ago with just a two-day training to him and his team on how to start implementing AI. And from that moment on, and even before, Ari took over, and really with an incredible combination of, first of all, real passion for AI, but also with lots of management skill and vision to drive this process to where they are right now, and I'm going to let him explain where they are right now because I think it will be a lot more valuable than me sharing their story Ari's ability to really take these concepts and run with them, both on a personal perspective and on a company vision and implementation perspective, are truly inspiring, so I'm really, really excited to have him as a guest on the show today. Ari, welcome to Leveraging AI.

Ari Supran

Thank you. Honored to be here.

Isar Meitis

It's, uh, you know, you and I meet weekly to talk about this stuff, so it's very, very hard to decide, uh, where to get started even. But I would love for you to first of all share a little bit about the company so people get an idea who you are, what you do, how many people, stuff like that.

Ari Supran

Sure. Okay, great. So, um, let's see. We are, Sonance is the primary brand, and we are a manufacturer of architectural loudspeakers for high-end residential as well as commercial applications, um, as our primary business. We also have another brand up here, iPort, that is, uh, iPad accessories for enterprise, as well as a brand called James, which is, custom-built speakers. We have a factory up in northern Nevada, built to order, customized speakers. And so we're, we're primarily a B2B company selling to a s- network of custom installers that do home automation, home theater, that type of thing. they do design and installation, working with architects, interior designers and consumers and end users, uh, globally. And so we're, we're very much geared, our DNA is to be a B2B company that believes in the idea of authentic partnership and giving back to our customers and making them feel like we're a part of their team. And, um, that has, that was all in place. We're a privately held company. We're 43 years in business. We have about 360 employees. And, uh, we've been growing quite, quite fast the last several years. And, uh, AI has really been something that has given us, an opportunity to really transform the way our business processes work, and we're on a journey. And, um, you know, you, you, Isar, you've, you've, uh, certainly been a part of that journey. You've seen it along the way. I'm very proud of where we're at, and at the same time I'm very aware that there's still, uh, we're still on a journey. We're, we're, we have not pro- completely proven to ourselves that the path we're on is the right one, but we have a lot of, uh, a lot of good indicators that it is. And, um, we've got a lot of traction in the company. We have got about, uh, I just looked this morning, 115 employees now with active Claude subscriptions on an enterprise plan, and we're about to kick off, uh, some Claude Cowork workshops. Claude Cowork has been, uh, really the product that has, um, gotten the most traction within our, our sort of everyday business, and our employees are finding all sorts of uses for it that really up-skill them and help them, um, do their job better. and that's kind of where, where we're, we're at on this journey is, uh, building a lot of internal apps- which I can, we can speak a little bit more to, and really leveraging Cowork along with connectors into our, traditional SaaS tools of Microsoft Teams and Outlook and Asana for task management. And that's really been what's propelling our, our current, traction that we're getting, is that our employees have the ability to leverage AI in ways that are go way beyond chat interfaces and are much more into the agentic delegating work and, um, that's exciting

Isar Meitis

Yeah, I, I will say something amazing about what I see in our weekly meeting. So, so Solance has a team of champions that meet every single week, but it's not just champions, and again, I'll let Ari explain how the structure is built. Like, there's actual people in specific roles who lead that part of the organization. But literally every single week there are employees that has never been in the meeting before that come and show different applications that they built that solve actual real business problem, either generate more revenue, drive more time, uh, save efforts that were hard to do before across every aspect of the company. Uh, from manufacturing through sales, marketing, operations, customer service, you name it, uh, we see this coming. And the amazing thing is that it's not coming from three or four or five individuals in the company. It's literally coming from every single department. So I think what will be interesting is if you can talk about specific examples. So we'll start with the end, so people understand why they should stay with us for the rest of the hour and understand how to get there. But let's show a few examples of what people have been building.

Ari Supran

Sure. Yeah. I, I would say what we've really embraced is the idea that, it is a lot easier to build a piece of software, uh, specifically for your own use than it is to purchase a piece of software or, or, or, or, uh, start paying monthly for a piece of software that was designed for the, the world and, and then compromise and wrestle with it to get it to do what you wanna do. And again, I gotta say it over and over again, I, I think we still have a burden of proof to ourselves that this path is the right one, but we are seeing great, uh, indicators that it is. And, and, uh, we're, we're able to... Uh, let me start with this part. we've made the investments over the last about a year and a half, two years ago into a dedicated technical team, and so we've got... We moved a senior executive in our company, Derek Dahl, as Isar you know well, front 15 years with the company running our I-port, product business and, put him in charge of this effort, and he's got a real vision for it and is able to really put a dedicated focus on it. We've built out what we refer to as an orchestrator team. These are people that have a, a day job, so to speak, where they're managing a department, but in addition, they are building tools. Typically, internal apps that we, have built ourselves, a domain expert in the business who may have never written software before is paired up with either a technical resource or the technical team has put things in place so that a domain expert can just go forward with using natural language and build out an application. And we kind of do it in, in, um- I-I-In a collaboration to make sure that we're doing things in a secure, scalable way. but really seeing tremendous value in getting domain experts out in different departments of the business, looking at an opportunity, getting up out of their chair, going to talk to people, figuring out what their problems are, what their pain points are, and we have completely changed, or we are on the process of changing the culture from, "I put a ticket in with IT when I need help, uh, I need a solution built," to, "I'm gonna build it myself with the support of our technology team," which is a combination now of our traditional IT capabilities and our new AI capabilities that are, uh, merging into one team now

Isar Meitis

Just before you dive into showing actual examples, I wanna touch on two very critical things that you said that I think are important for people to understand. One is, and, and those who've been listening to the podcast for a long time heard this many times. I always say that there's two things that are really the key drivers to a successful AI transformation. One is leadership buy-in, and in this particular case, you see that the leadership buy-in is, A, the CEO himself, Ari, is fully vested. Like, he's developing more AI stuff than I do sometimes uh, which puzzles me because I'm like, when does he has the time to do this when he's running, uh, such a large business? But he does, and he's fully committed to the process himself. But also, they think about a business that takes one of the leading people in the company, that has been with the company for a very long time, that has developed a brand to a very large scale, and moving him to a role that manages the AI strategy of the company. That's not an easy decision to make, but that's shows real leadership buy-in. There are l- top talent people in the company that are leading the AI implementation of the business. So that's one aspect of it. The other aspect is continuous education, uh, which is the... I said there's two things. So leadership buy-in and continuous education. And again, you hear- you heard Ari, and again, I'm connecting a few of the dots of things, and 115 people that are using Claude actively, not just have licenses, that are trained and retrained every time there's a new thing that's happening, so they can be more productive and do more things with the assistance of a, let's call it an infrastructure layer, and that infrastructure has both people and processes and tools and so on. So keep that in mind because these really holds the keys or the, if you want, the foundation to everything Ari's going to show you and talk about. And now, yeah, if you c- if you will show us examples, that would be awesome.

Ari Supran

Absolutely. So yeah, like, like you said, Isar, I, I would, I would say that's one mistake that I, I see people making out there, less so these days than a year ago, but just the, the leadership of a company just delegating AI, right? Like sending articles they don't have even necessarily read them themselves and just say, "Hey, IT department, this AI thing, you know, you should, you should go, uh, explore." And I, I think that what I've learned is it takes... It doesn't have to be the founder or the CEO, but a member of a leadership team really having their own, wow moments with AI that they go, "Wait a second, this really solved a problem, and I see tremendous value here." And that then can spread through our leadership team to get the buy-in and the confidence. You know, I don't, I don't just go to the team and say, "We're doing this." I, I influence and get them to, uh, um, align and challenge me. And I think that through the, these efforts over the years, our leadership team has completely bought into this because they've had their own wow moments with it. And quite frankly, it's, uh, I, I say this all the time, it's Claude Cowork that has given most people, uh, in our organization, if they say, "Well, there was this moment that I realized that this is so much more capable and powerful than I had realized," it has been an experience with Claude Cowork. and then on top of that, getting even a step further into Claude Code and building apps. And to full disclosure, uh, I'm well aware, uh, you know, and as I know you are as well, Isar, that, that OpenAI and, and Codex in particular has really come a long way recently. So we... One of the philosophies we have is to be model agnostic, to be frontier, company agnostic, and there's things we're doing, as you're aware, knowledge graphs and data lake houses, that I think are gonna set us up to be more, even more nimble and more agnostic. But at the moment, we're an Anthropic shop, and seeing tremendous benefit in having chosen that, about a year ago. And, uh, we're, like I said, we're about to... You know, I'll, I'll say this, we- we've kind of pushed the ball up the hill. It has clearly crested, and it is rolling down the other side, and we need to catch up with it and put a little more structure in place, more education. Yes, we've got a lot of people who know what they're doing and have figured it out, and many people out of those 115 that probably have a, a license with us and don't yet know what it can do. And so we're, we're kicking that off actually this week on, on Friday, doing a series of workshops. but yeah, it's, uh, it's an exciting time right now, and I'll show you a couple things that we're working on, so. Awesome. This one I'm, I'm particularly, uh, excited about and proud of because the gentleman that really was the domain expert and built this, a gentleman named Eric on our team, lives out in Carolina, is a... He's a speaker guy. He's never written a piece of software in his life, but he knows speaker design and speaker calculations really well. This is a tool that we didn't have. Our competitors have some version of it for the, typically for the professional market, like bars and restaurants. You wanna have some type of speaker calculator that helps you when you put in room dimensions. Here, let me show you. easier Okay, so Eric, our domain expert, was able to pair up with Thomas and team on our technical team to build this application, and, uh, we're launching it in about two weeks at, uh, the InfoComm show. But it's basically a tool where you can put in dimensions of a room here, and once you do that, you can calculate the number of speakers. So you pick a speaker, and it calculates the placement of the speakers in three-dimensional space, and then it does a heat map, because this is all calculatable, what the decibel levels would be. You can see here if I go underneath a speaker, it's 8-87 dB. If I go out to one of the corners here, it drops to 83 dB, and I can... Decibel levels, which is the way we measure sound. Something that architects and designers, and, uh, acoustic consultants can come onto our website and basically do a quick design. We have design services that we offer as a free service to our dealers, where we'll go through a set of plans and do a layout, but a lot of projects don't need that level, and can, can work perfectly well with this. It even goes further and helps choose an amplifier to go with the project. Something really exciting, because again, the gentleman that built this had so much fun building it, and, uh, it took him about three months. I asked him recently, uh, if he started now with everything he's learnt about this, uh, I guess it's considered vibe coding process, how long do you think this would've taken? He said three to four weeks to build this tool. And, um, it's really, really quite exciting, of what he's been able to do, and he's like- What's next, you know? That's his attitude.

Isar Meitis

Awesome. I love this for several different reasons, but the biggest one is a combination of two things. One is, I always say, you know, you can be the biggest AI expert in the world, you don't know what the business actually needs. You don't have 15, 20 years of experience in that field, in your industry. And, but the cool thing is, if you teach the people who have that knowledge, those domain expertise that nobody else has how to build these things, they can do the magic themselves, then they get hooked, and then they can do more and more stuff. So that's one aspect why I love this. The other reason why I love this is because it provides value to everyone. Yes. It provides value to the end users because they understand what they're going to buy. It provides value to your clients, which are kind of like in the middle, that are going to build this and develop this because they can understand what they need to customize for their clients, and provides values to you because it sells more speakers and more amplifiers in a way that will be the best way to everybody else. So i-i-it literally like the best of all worlds, if you can imagine. You took somebody who has the experience and the history and the knowledge of... And, and it happens in every company in every department, right? You have those people who just know because they've been around for so long, and now there's a way to take the knowledge in their head and turn it into something that everybody can benefit from.

Ari Supran

Yeah. And I, I chose this one in particular because, uh, it's just, I love the, the story, the backstory of the gentleman, Eric Welch, that built it, um, along with our technical team, and it's just, it's so emblematic of what, um, I think is possible. You know, this would've been something that we would've had to outsource and hire a, a, a development firm that we would have to teach them all the acoustics. Uh, I've seen some of the competitive products out there. I mean, they look like MS-DOS. You know, it's, it's... This is already better than anything anybody else has. It cost us probably a few, I don't know, a few, $2,000 in tokens to build this once. It's now self-contained. There's no API calls. It's done. and we'll keep ev- evolving it and, and, uh... You know, that's part of what we're, we're working through now is, all right, you make a piece of software, now we need someone to own it long term. And not being a software company by nature, we're still learning these muscles of beta testing and regr- you know, uh, just creating a tight feedback loop. And this one in particular we're putting out there for customers to use, not just internal use, which- Yeah 95%, I'd say, of the apps we're building, maybe 99, are really for internal use, but this one, touches customers as well. So Thought that was an exciting one. It is. Love it. So one of the things our technical team has done also is, uh, built something we refer to as the Cortex. Uh, so the Cortex is, for those that have dabbled in sort of agentic AI, you've seen these connectors or model context protocol, MCPs. These are just the way we can connect AI to the SaaS tools in our business, whether that be Slack or Gmail or Google Drive or for us it's, Teams and SharePoint and Outlook and Asana. So what we've built is a system called the Cortex, which is, I, I like to describe it as a basket of connectors So rather than our employees connecting their Claude accounts to individually to Microsoft, to s- uh, Monday, Power BI, SAP Concur for expenses, Databricks, our data lakehouse, these are all put into one location, um, by our technical team. El- Elliot, uh, as you know, built this, and, um, is able to put it all into one basket so we have one connector to it. And it's not just a convenience factor though, it's more than that. There's also skills that are built in. So for instance, Supabase as an example, is the database tool that we use so that if you're building an app that a user has to enter data into, let's say they log in and they start filling things out, and then they want to come back to it and see their data and only their data, we need a backend database for the app. That's Supabase. So we put it here in the Cortex, but what's, beyond just the fact that it's part of this from a convenience factor is that there are built-in skills or hooks that make sure that when we go to create a database, it's done a very specific way every time. Same thing with committing to GitHub for the code. All of these things are done in a very specific way that provides some guardrails and some, um, just security features that help us enable domain experts to not have to understand how to use software and be able to create these apps and do it in a secure and scalable way.

Isar Meitis

So I wanna say how magical this is because I work with a huge variety of organizations, and literally the biggest problem is getting access to company systems and tools in a secure way with the right governance. So actually connecting the systems themselves are relatively easy, meaning getting access to any tool that has an API, wrapping it as an MCP, connecting it to whatever AI, not a big deal. What is the big deal is Joe versus Jill versus Jack versus, Sheila each need to see different things because they have different access. You don't want everybody being able to see everything all the time, such as people's salaries, such as pricing of competitor websites or whatever the case may be. It has to be governed in a way that every person, despite the fact that they're connecting through an AI tool to build something, can only see the stuff that they're allowed to see. So this tool that again is homegrown- That was built by the people that were hired to help the AI team grow is now available to any employee in the company. So when you go to build either a process, an automation, an application, a chatbot, whatever it is that you wanna build, you can build it on top of every data that sits in any tool the company has access to in a safe and secure way, which by itself dramatically accelerates the ability to do things because that's usually the largest showstopper in large organizations

Ari Supran

Yeah, that's, that's the plan, right? We're still, uh, like I said- Yeah we're, we're in the middle of, of adoption of this, and we're training people on what the Cortex can be used for. we haven't given people You can, you can have access to the Cortex, but then we individually turn on these different connections for people. depending Most people it's gonna be Microsoft 365, which gives them Teams, and Outlook, and Calendar, and email. and then the next thing will be Asana for our task management, and then we have this group of orchestrators that are building, starting to build apps or have built apps. That's where we connect them to, GitHub for storing the code, Supabase for storing the data, and then Vercel for deploying the apps. And I, I,

Isar Meitis

No, I- Go on. No, I want to say something about this. This is another amazing aspect of this because vibe coding is easy from the generation of the code. Doing it correctly in a way that is, has the right architecture, and that is deployable correctly, and that has versions and traceability and rollback and access and logins and all of that's what makes it a lot more interesting. And building an in-house infrastructure that takes care of all of that or most of it- Yeah and having people that can help you in the 10% you do need help with is, again, another amazing accelerator that every company will have in the future, and those who will figure it out faster, uh, will just gain tremendous benefits in the midterm.

Ari Supran

Yeah. I stop here 'cause I wanna show o-one of the, connectors we put into the Cortex is not Microsoft or one of these big names. It's our own brand guidelines. And so, we took our brand guidelines that are typically in a PDF sitting in some SharePoint that unfortunately no one really goes to and, and reads on a regular basis or tries to implement because it's just trying to follow a list of rules. What we did is we put all of that information, our PDF, we turned it into a web application, not for humans to look at on a daily basis. It's to put it into the Cortex so that we can connect everyone's Claude or Claude code to a backend brand MCP or connector that infuses our brand, our logo, our fonts, our colors, as well as a component library so that apps like this all have a consistent look and feel to them. So this is what our Sonance brand, uh, guidelines would do. It injects the logo, the word mark, the fonts, the color scheme so that everything has a consistent look. And this is still, again, a work in progress. We're still evolving, uh, how this works, but it's really been, um- Uh, you know, it's almost magic, right? The employee doesn't even know that it's happening in the background. They just start building, could be as simple as an artifact in Claude, like a simple lightweight app or something more sophisticated like this, and it just comes out looking exactly the way we want it consistently every time without them having to know any of that or really do anything. So that's exciting. Let me skip over to another, So our Eyeport brand, um, selling into enterprise, we have different verticals that we sell into, uh, restaurants, gyms, spas, um, retail, et cetera. And I thought this was a really good thing. Our, our, AI leader, Derek, has his own agent, who does coding for him that he can delegate a project to. And this is a good example of where our, uh, Derek just told me this last week, our marketing department at Eyeport wanted to make a microsite for Eyeport specifically for the restaurant industry, and asked Derek, "Should I use WordPress? How much do you think this will cost?" Um, and he said, "Well, send me your design brief." And the next morning he came back with this microsite for the restaurant industry, and it looks exactly like our Eyeport we- traditional website, but it was designed specifically for the restaurant industry as a little microsite. And what I love is, number one, how beautiful it looks, the animations, everything's so fluid. What's mind-blowing about it is that his Not him, his agent built this in about four hours. But what really blew me away is that he asked his agent to put a CMS into the sys- into the, uh, website as well. So what he can do now is just come in here, just like a PowerPoint slide or a Keynote slide, and make any change you want to any aspect of this site, 'cause his agent built a CMS into the website that I can then change a image just as easy as that. I can change copy as easy as this, and treat this like a PowerPoint slide. And the code is written behind him as he makes changes with this WYSIWYG interface here. And that just starts to really get my, gears shifting of like, wow, we could make microsites per client with our Eyeport business so that we have something very specific to them. We al- we, we already do, custom renderings of their space with our product, but give them a website or a microsite that they could go to. And then when I think about our customers, because we do a lot of AI evangelism in the industry and trying to help, uh, inspire our customers, and quite frankly, I, I can think of 10 to 15 of them that are just doing mind-blowing things, in transforming their businesses and creating internal apps that their business will run on. But one of the challenges in our industry is giving the client, this typically wealthy end user, a proposal. And today it's a series of PDFs and bills of materials that could be As easy as a microsite that can be auto-generated with brand, focus from the integrator to the client, showing all the different subsystems of home automation and all the things that they're doing in a rich way that is so easy to build and then make changes to before sending it out to the client. So I thought those were some good examples to, uh, to share with you of, uh, a gamut of different things, and there's so many other things. You know, I, I think about our, our factory up in Nevada and just have a individual up there that has been building internal apps and, and really building one super app that the factory is, beginning to use to create more transparency of the process and where orders stand within the process between custom engineering, finishing, assembly, et cetera. And just creating more transparency and clarity for our internal team as dashboards and other things to know where we stand in the process, and he's just doing some amazing stuff. And I, I think that's so exciting to me because I think that in the, in the old world, there was sort of two ways to really, um, add value to a company. You could either be this like amazing individual contributor, maybe a, a top salesperson, or ultimately you could be a people leader. And I think in this new world, there's this third avenue that I'm so excited about, which I, I like to refer to as orchestrator, that, like I said, I think the key here is they don't just build for building's sake. They actually understand the business well enough, get up out of their chair, get away from the keyboard, go talk to people, find out what the business pain points are, and understand what's possible, and then they're building solutions that solve problems, and they're not stopping there. This is the key, I think. They understand that the tool they build is only as good as their ability to get people to use it, to know how to use it, and to ultimately create a success factor of are we getting the right business outcome from this, and not stop until we are, and then own it all the way through. And I think that is really exciting because I think that, in the next two to two and a half years, our intention is to completely transform just about every aspect of our business. We may still be selling the same types of products that we were today, but every other part of our business, we plan to transform using AI as well as getting, I think, the two key, points here. These models, and you and I have talked about this before, I, I personally think the models, frontier models today, like Opus 4.8, GPT 5.5- Already more capable than to do just about everything that we'll ever need them to do. So that is not the bottleneck, in my opinion. I think the bottleneck, if anything, is, getting data clean, organized, and mapped in an intuitive way. Our plans there are a data lakehouse with data- Azure Databricks, and we're building that out now. And then secondly is getting context right. I think that is the biggest unlock that anybody can focus on, which is, especially if you want to stay model agnostic, which is to all these systems that ChatGPT and Claude have memories. But, um, we wanna go beyond that and start capturing all of the context in the business into something referred to as a knowledge graph, that we believe will not only capture all that information, but I think the key is that it can inject the right context into everything everybody's doing all the time with AI so that everything's more relevant to our business, everything hits closer to the target, uh, from the get-go. So it might be something like, uh, a good example. We've got an individual building an app for customer onboarding, and we have a lo- very diverse business. We have between, uh, the way we do business in Europe differently than in the U- US with, uh, residential dealers, commercial dealers, enterprise customers. There's so many different nuances to this, and so he built an app or is building an app that will assist in onboarding a customer, which today is a very broken process here of a system of emails going into spam because they're DocuSigns. And we're building an app now that has sort of, we like to refer to as the pizza tracker of where does this stand, whose approval is it waiting on, all in one place. And that app that he built is so, is, is, is being built, is so, powerful and amazing. Yet when he showed it to our sales leaders, they were like, "This is incredible. However, you missed that there's this nuance here. We do things differently here, there," et cetera. And so he's having to go back and make all of these changes. Our belief is in the future when we can connect his Claude code to that knowledge graph, the very first iteration of the product is just gonna be so much closer to accurate and what we need because today, Claude code doesn't know those nuances, nor does the gentleman who's building the app, who's a technical resource and doesn't understand all those nuances of the sales, uh, and go-to-market strategy. But our knowledge graph will, and so we're going through a, a process right now of capturing this knowledge, codifying it in a way into this knowledge graph that I really think between getting data right and getting context right, we-- that's where we really get the unlocks and that's, that's the direction we're heading right now.

Isar Meitis

I love everything you said. We can probably spend the next 10 hours deep diving into each and every one of those, but I'll pick a few. I, I'll start with explaining the knowledge graph and why it's so critical, and, and I'm in the same path with my company as well. the idea of a knowledge graph is connecting the dots, right? Those of you who don't know what that, that means. So if you take a simple example, if you allow the AI to write proposals for you right now by giving it access to, let's say, a transcript of a call. So that's awesome, it has access to the transcript of a call. But maybe there were five calls. Maybe there were 65 emails before that. Maybe there's information in other departments in the company that already worked with this client, and they know stuff from the past. Maybe the technology that they're using is a little different than the average, and it needs special attention. That information, and I'll enhance what Ari said, that this person doesn't have that information. Most likely nobody in the company holds all the information that is required to do this. That information is broken between people's heads and multiple systems. If you build a knowledge graph and give the AI access to it, and there's... It's not magic. Like, there's a process, there's cleaning the data, there's documenting the... Like, there's a process. But if you follow the process, at the end, the AI can figure out where the right data is, pull the right components in without breaking the context window, and still benefiting tremendously with whatever it is that it is trying to do. So that's one aspect, just to clarify on the last point. But I actually wanna go to the point you started with, which is the people, right? And I think both you and I really believe that that's the, the key to everything in a company. Totally. What is the current structure from a people perspective, and also what were the steps to get you there? Because when you and I started, obviously it was you and me, there were no other people that were involved in the process.

Ari Supran

sure, sure. Well, um, let's see. From a people standpoint, the process goes back to about two years ago, making those investments and bringing in technical resources. We brought Elliot Amador in, has a, a lot background in machine learning and, uh, and AI, and has really been the backbone of a technical team. We brought in Thomas, um, recent UCLA grad that has a background in some programming as well as acoustics, which was a really nice find for us, um, who's been instrumental moving Derek into that role. So we've got that core team. We found a, a gentleman named Joshua on our team that was a, an electronics test engineer, or is an electronics testing engineer, but had a proclivity for, uh, AI and has started building tools and so he's kinda, uh, joined that core team. and then we started... You know, we started off with a committee. and I think we realized that committee's not really the right thing for us. we, we didn't really need a, a committee to come together to make decisions. What we needed was a community of people to share knowledge and to, uh, inspire each other and teach each other what's possible. And so that, that led ultimately to this orchestration team. I will say that we, going back two years ago, you know, I remember starting to, maybe it was two and a half years ago, starting to come to our, head of IT at the time and say, "Have you seen this? Have you tried that?" And realizing quickly, and, and, and he and I have a, a really good relationship, that he was so head down trying to keep the lights on of our current ERP and other systems that it just wasn't, wasn't fair really to expect him to also be trying to stay up on, on all the developments in AI. So we built this, technology and innovation team sort of in parallel to our traditional IT team. Uh, I would say that that worked well in terms of getting us the traction that we needed in getting going, and at the same time, I think we let that go as two teams for too long, and we're, we're actively bringing them together as to one team with one set of priorities because there's so much interdependence between the AI efforts and our traditional IT efforts, from security and networking, all sorts of things like that. And we're clearly... I know I keep saying this, but we are on a journey. We are not at the destination. I don't know that there is one. but we're, we're making great strides, and we also are fully recognizing that, we have, we're out there maybe at the- close to the frontier of what's happening, and we're just going off of instinct in some ways. There's really not a playbook here. but we are trying to stay connected, talk to a lot of different peers and companies and customers of what they're doing, and try to stay abreast and be nimble. I think that's the key for us, is to just make sure that we don't lock ourselves into any one provider, model, agent framework. We haven't really touched on agents much in this conversation yet, but that's certainly, uh, something we see in the future of introducing agents as coworkers to our employees in Microsoft Teams. And by the way, I should have mentioned this earlier, all the apps that we'll build, um, internal apps I should say We, all of those will appear to our employees in Microsoft Teams. So what we learned is it's really hard to get your app into Microsoft Teams for the world to see. It's really easy to get your app into only your company, a single-tenant app. To put it into Teams is easy, and that's where agents will show up as well, like I said. As we, we haven't introduced agents, we're, we're using them on an experimental basis. Um, I have one, uh, Derek has one. Et ce- many of my other senior leaders have them. But, uh, eventually we will- we see an opportunity to... We're building a, an agent that essentially, uh, spawns new agents that we have the ability to control what it has connections to, who it answers to, who can talk to it, and what its role is, and lock that in so that an employee can't override that, but they can use that agent to help them get work done. that's exciting, and also very much something that we're keenly aware has a, a change management, human side of it that we need to be careful about. One thing I, I just gotta always go back to is before all this AI stuff started, we had a really healthy culture. We're a privately held company. I can't speak for other companies in the world that, that are publicly traded or private equity and what their motivations are, and, and I don't have this massive call center of 1,000 people doing the same thing. I've got really hardworking, passionate employees that at times feel stuck because the processes and the systems that we've had are inflexible, and they feel like, well, it is what it is. And I think that culture is actively changing right now to say, "If it's not the way we want it to be from the in- the customer experience and the employee experience, we can change that." and we are seeing evidence of that throughout the company right now. And, uh, that's what gets me so excited coming to work every day. and I'm seeing so much from our customers too, that are doing some things that I, I, I- inspire us. Um, and, and there's, like I said, a handful, maybe 10 or 15 of them, that are doing things that, uh, you know, they're really building internal apps to run their entire business on. Uh, from scheduling to proposals to you name it, all into one app. a- and that's exciting as well because we played a, a role in, uh, sharing knowledge with them, learning from each other, and I think that just speaks to our, uh, our pillar of authentic partnership and our ability to help our customers be successful, not just with our brand, but just in general. And so AI education, AI evangelism has been a big part of that, and we're seeing tremendous, exchange of value with our customers as a, as a B2B company that believes in these types of partnerships.

Isar Meitis

Yeah. When I, when I work with businesses and we start by writing, you know, the why. Like, what, why do we want AI? And, and, you know, that's the core for everything. And I always go, at the end of the day, we do what we do to provide value. Yes. But we don't do what we do to provide value to the owners of the company. We do what we do to provide value to the people in the company, to their families. Maybe they can get two more hours a week at home and play soccer with their kids or whatever it is that they like to do. Yes. We want to provide value to our suppliers and distributors and consultants and, like, e- everybody in our ecosystem. And AI really has the ability to do that, and that is very, very rare. You know, there was the old saying, uh, that has been true for years, you know, faster, better, cheaper, pick two. Uh Right. And it's always the third. And it's the first one, the first time ever you don't have to pick You can do faster, better, cheaper, more valuable with less time for the sake of everyone. And as much as there are definitely the negative sides of this, like what is this going to do to the world and relationships and, and, and, and the economy and, and the workplace in general, like there's a lot of open questions that nobody has access to. Yes. But from being able to build value to everybody involved at scale, this is the most exciting time in history. Well- I want to ask you one more thing that I think would be very helpful for people because, you know, y- you live through this literally every single day, every single hour, and you think about this all the time, and you have an incredible team that is involved in that creation, which has created this, you know, snowball effect of just growing and attracting more people, a flywheel effect if you want. But there's a lot of people out there who are just getting started. Mm. Like, they barely know the difference between- Yeah Claude and ChatGPT, if they even heard of Claude. Right. If you are in a leadership position in a company right now and you're just getting started- what are the three to five things that you would say, "Okay, sit down, write this down right now, and do these things to accelerate your success or your chances of success"? Again, you and I don't have a crystal ball. We don't know where this- Right the chances of success, in implementing- Sure yeah, successfully.

Ari Supran

Yeah. I would say first and foremost is, uh, if you're just getting started with the adoption, somebody in leadership, don't delegate it, somebody has to have their wow moment. And, I don't want to sound like a broken record, but I, I think that what I keep hearing people say is things like, "AI is this, AI is that. it's not this, it can't do that," as if it's this monolithic one thing. Um, AI is not one thing and the model matters, but the product that the model, that you, you use the model matters as well. And what we've learnt is that, These coding harnesses like Claude Code and Codex are extremely capable. And while they are coding harnesses for coding, uh, and not everybody in- so I'm supposed to speak here to the, the people that are new, just understand that you don't have to be a programmer to leverage coding because what is behind every spreadsheet and every PowerPoint deck is code. And so what we've figured out is that these systems like Claude Cowork and now the Codex app, not just ChatGPT, but OpenAI's Codex app, are really this gateway into doing knowledge work with AI that, is so much different than chat. And when I say chat, I don't mean ChatGPT. Claude Chat, same thing. This chat idea that I ask a question and get an answer, we are past that. and I think that is the number one thing I would encourage anybody, uh, out there to go experience for themselves is open up Claude's desktop app, go to Claude Cowork, it's on Mac or PC, and point it to something... You know, you don't upload files into it like a chat interface. You point it to a folder, a traditional folder. I'm on a Mac, so that's Finder, it's Windows Explorer, that has a... could have 57 documents in it, four spreadsheets, PDFs, Word docs, it doesn't matter, and ask it to just familiarize yourself with the contents of the folder, ask me questions to make sure that we are on the same page, and then this is what I want you to do. I want you to... A- and those a- and, and it's an action word here. Create something, build something, uh, design something, analyze something, actions, because this is not chat. We're not here to get an answer. We are here to get stuff done, and we are here to delegate to, a model in a product like Claude Cowork. And I think once it starts to analyze the files and starts to ask questions of you, it is that moment that I think most people that I've turned on to this start to realize that this is different. Because what they see is that these questions are no longer generic questions to clarify what you want, but they're incredibly insightful questions that are based upon its analysis of the files in your folder, and so much so that even if you don't know what you wanna do, there's obviously a great technique called reverse prompting, where you simply say, "Given what you see inside of this folder, what do you suggest we do?" And I take that a, I learned recently just take that even a step further and say, "What do you suggest..." Let's say I'm a busy executive and I need to help, um, visualizing this data. What is the suggested prompt that you think I should give you in order to get there? And it writes out the prompt for me. I say, "Go do it." And right in front of my eyes, hands off the keyboard, I see graphs built and tables built, and all sorts of things, uh, that, you know, I can fumble my way through still from my Excel skills, but it just happens magically in front of me. Um, and I think that's the stuff that is most important, is finding this real practical value. And Claude Cowork's been that gateway for our company to see the, the real value, and I've got so many examples throughout our organization of people that are just crushing it, by doing different analysis that they never could have done before Creating dashboards, creating, visualizations to... These aren't necessarily apps, it's just simple stuff that I refer to as or is referred to as knowledge work, and I think that's where we're really seeing the traction. And we haven't even really kicked off our formal Claude Cowork workshops and education that start this Friday. I'm excited to, to really upskill the employees, 'cause back to your question about the why behind this, it's just very clear for us. We, we truly believe that AI is, uh, something that can unlock and upskill our employees to be able to free up their time from the menial tasks that are involved in their job, to free up their time for more value-added activities that help our customers, to help our employees, to help our culture. and we're seeing that throughout our organization. And again, I, I can't stress this enough, that doesn't happen with chatbots. Whether it be Claude or OpenAI, it doesn't matter. It happens with agentic delegation tools like Claude Cowork and Codex that I think are really the, uh... It's really the, the, the foundation of what we're doing right now, which then leads to these dashboards can become apps. So it's sort of the, the gateway, the on-ramp to, um, seeing the potential and power of AI for us has been Claude Cowork, and our employees are by and large seeing it. They get it, uh, and they're coming back to us saying, "Thank you," not, "What are you doing? You're, you're, you're taking away parts of my job." a- and to be clear, with 360 employees, I am sure that we have some employees that are concerned, and heck, I'm concerned over, about AI in the world. I, you know... but I know our company, I know our culture, I know our motivations, and I know why we're doing what we're doing, and I know our founders and our leadership team and who we answer to, and we answer to our employees and our customers with the right intentions of adopting AI to, really leverage this, what I think is a, a total arbitrage moment of intelligence right now, where the people that are using these tools have an ability to differentiate themselves and differ- and companies have a ability to transform and differentiate themselves, in new ways that never existed before and, and that's what we're gonna continue to do. So my, uh, long-winded way of saying my advice is don't delegate this. Have your own, uh, moments. I suggest Claude Cowork or Codex as the, to do knowledge work. And then get that, let that spread organically and get more and more people cr- creating tremendous practical value using these tools. And then from there you've got the traction, you've got the confidence, and you can start to invest. I'll say this, I, we wouldn't be doing a lot of... We wouldn't let domain experts do some of the things that we're doing with apps if we didn't have the technical team behind them, but we wouldn't have had the courage to invest in the technical team had it not been for leaders of the company having their own moments and realizing that there's really something here that we need to be ahead of and start adopting, and I think that's, that's my advice

Isar Meitis

Awesome. I think that's an awesome way to end this. really, really incredible conversation. I truly appreciate you willing to come and share what you've learned with your own, uh, blood, sweat, and tears in the last, three years in the AI journey. I really appreciate our, our partnership and our friendship, through this journey together. Uh, you and your team really inspire me and push me to work harder and do some of the things that I do. Uh, and, and I think that's maybe the biggest thing, is surround yourself with people who are experimenting with this. They don't have to be coworkers. They don't have to be somebody you hire. That's not a bad thing necessarily, but it's not necess- a necessity. Surround yourself with people who are tinkerer and experimenters in this space because like Ari said, there is no playbook, and if there is, it's changing on a weekly basis, so even if there was one, it doesn't matter. I- That's right the amount of times Ari and I said, "Oh, no, no, no, we gotta dive into this or that," and it's just changing all the time, but the concepts, like the concept of agents. So it was OpenClaw, and then it was, ChatGPT, and then it was, uh, you know, whatever open source tool, and then it's, now it's Claude Cowork and Hermes and, like, on- Hermes, yep but the concepts and the experimentation- That's right are what drives this forward, together with something that I, that I love that you pointed because I think is the... If you want the secret sauce, is how do you create real excitement in the organization? And it is starting small and just showing people what's possible, and then the right people get excited, and then they will join, and they will excite more people, and that just organically will grow, and it takes time. Again, it didn't happen overnight. It took three years. but if you don't start, then you're you're not going to get there. Uh- That's right if people want to follow you, learn more about what you're doing with AI or learn about the company or whatever it is, what are the best ways to do that?

Ari Supran

Sure. You're welcome to reach out to me. Um, my email is Ari, so A-R-I, @Sonance, spelled right behind me here, .com. And then you can also reach our whole AI team if you have questions or, just wanna bounce ideas off of us, uh, which is very similar, but ai@sonance.com. So reach out to either one of those email addresses, and, uh, we will get back to you. And, um, love to connect and learn what anyone else is doing out there. We, uh, we're definitely a sponge trying to, continue to, to make sure that we, uh, recognize that, like you said, there's no playbook. We've got plenty to learn, plenty yet to prove to ourselves. and, um- Yeah, it's been, uh, exciting. By the way, one, one thing I forgot to mention, if you're new and you haven't figured out skills and what skills are yet within AI parlance, if that word is just foreign to you, get into Claude Coworker Codex and start building some skills. I think that is a major unlock of capability that really, highlights the difference between chatting and, and really delegating things using skills. So those are, those are sort of the, the entry points that I, I think are best. but reach out. We're happy to help. We're happy to talk and, um, thanks again for having me. Really appreciate it.

Isar Meitis

Thank you. This was absolutely awesome. I appreciate it

Ari Supran

Thanks, Isar. Woo! Thanks for your role in our journey. I appreciate it.

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