speaker-0: Well, let's jump in. So welcome everybody back to another episode of the Chief Customer Officer podcast. This is your host, Jay Nathan, and I'm joined today by friend, Aurelia Parlay. Did I say it right? Perfect. Okay. I got the pronunciation. Okay. Great. Yay.

speaker-1: Yeah, perfect. It's French. You're in trouble. ⁓

speaker-0: I don't know about that. I need a little more coaching before we get there. so, uh, Aurelia works for car parts.com. It's a publicly traded retailer of you. You guessed it. Car parts, um, big organization. Uh, she's been posting a lot of LinkedIn recently and I came across these posts and there's some really interesting stuff that she was talking about. So I reached out and asked you if we could do a quick call and you, you reluctantly said yes, who's this strange, weird man reaching out to me randomly? I'm sure you get that from time to time with posting on LinkedIn. know I do from time to yeah, the cool is sometimes it it ends up in really cool relationships that turn into long-term friendships. so I'm ⁓ glad we've know I hope so too. I'm glad we got the opportunity to meet. But you've been You've been with Car Parts, how long?

speaker-1: for almost three years.

speaker-0: almost three years you all have done some really amazing stuff which we're going to talk about today. You've gone farther with AI than probably ⁓ I've heard yet and we'll get into what that means. in very specific way, which ⁓ I give it away, I won't let you tell the story, but it's very cool and this podcast ⁓ focuses lot on how customer-facing teams, customer experience teams are using AI. So I'm excited to dig into that with you. ⁓ Tell us just a little bit about yourself. What did you do before Carparts? And then we'll dive in.

speaker-1: So, you know, I fell into customer experience by chance, I like to say. I'm an engineer, I'm a mechanical engineer by trade. So I was not necessarily destined to a customer experience career. And I worked for 15 years for a luxury good company. That's how I came from France to the US. And then we fell in love with the country. So we decided to stay. And, you know, 10 years later, we stayed. 20 years later, we're still here, but 10 years later now we're Americans. And then I had the chance to go in ⁓ industries, B2B, nonprofit, a little bit of everything. But now I'm ⁓ back to my roots little bit, more ⁓ mechanical engineering at CarParts.com. like you said, we sell car parts. for the US market.

speaker-0: And in your role, you are vice president of customer experience. Now that means a lot of things to a lot of different people, right? When you think about B2B, there's B2C. So tell us a little bit about what that is for carparts.com specifically, because I think it ties in your engineering background a little bit as well.

speaker-1: A little bit. So the way it was designed by our CEO, which I love, is really, I'm in charge of the end-to-end customer journey. So, you know, from acquisition ⁓ the contact center to ⁓ programs, we have a membership ⁓ we launched last year. And so it's really looking at it as a whole. And how we make sure there's no friction during that journey? And when we find some, how do we collaborate with my peers, technology, marketing, data science, operations, to not only try to improve it, but also adding more value. And that's something that I'm very passionate about making sure it's a win-win. So when we look at something or redesign or change, it has to be good for the customer, but it has to be good for the company because we're not a charity. when you see it through that lens, it's very interesting because you're not just fixing a return process. How do I add value to that return process? ⁓ it changes the conversation. So been very interesting. We worked on many different projects ⁓ from membership, I mentioned. We just launched a credit card. We launched a shipping and product protection program. So a lot of different things where think I'm acting as a project manager, trying orchestrate those initiatives with all my colleagues. So, you know, connective tissue. That's how I like to describe it.

speaker-0: Yeah, absolutely. And everything you do, maybe a little bit of a, in contrast to B2B organizations that serve a smaller number of large customers. seems like everything you do really has to be at scale, whether it's a membership program or

speaker-1: And that's a challenge of its own. So coming from the luxury industry where I would know the name of the first 100 VIP customers, like you would know that. Here it's impossible. We ship about 50,000 orders a week. So when you look at that, it becomes a little difficult to scale things. So it's easy to say, you know, do this on a Post-it and an Excel file. When you, you know, have that many customer service, that's a different ball game.

speaker-0: Absolutely. And it's even harder to add value at that scale. A lot of companies, you can tell in the way that you interact with them as a consumer. I'm speaking from a consumer perspective here is that they just get it done, right? They're just trying to handle the volume. They're not necessarily adding value. So I'm curious, you mentioned adding value to everything, every touch point. Give me an example of something where... you've had to like the return process, you mentioned, I don't if that's a good one or not, but like, how do you add value at scale in the return process or a similar process?

speaker-1: So one thing that we noticed is we had a lot of lost and damaged packages and stolen, right? So the pirate's porch, it's a real thing. It's happening. And it's for a company like ours, where I think it's true for every e-commerce company, like returns and damaged. And this is so costful for us. It becomes ⁓ So one thing that we were looking at is how do we get out of this without telling customers where? I don't care. Someone stole your package. ⁓ got damaged. Not my problem. ⁓ We to partner with a company that does shipping protection. And so if you decide that want the protection, then you get your money right away. like this in an instant with three questions online and you get your money back. So people have been really happy with that because a solution that we can provide. You don't want it, you don't have to take it, but you're covered for everything that happens from the moment this package leaves our door.

speaker-0: Yeah. it sort of naturally sets the expectation with the client too, that when the package leaves, it's sort of out of your hands at that point. So that's really cool.

speaker-1: Yeah, there's a, so it's like I said, it's a win-win, right? So we make a little bit money on our own and then customer gets value on their end as well.

speaker-0: Absolutely. Win, win, win customer partner and vendor. Yeah. All right. So the, let's get to that. I'm sure everybody's waiting here now to hear about the cool AI work that you have, have done. But so in our pre-call, you were telling me about a really key system that you built from the ground up using AI. talk to us a little bit about that.

speaker-1: Yeah, this case All started with, we had a chat bot that we didn't like, that was not very, you know, it felt old school chat, but you know, with pre-recorded answers. And so we wanted to take advantage of AI and use AI to access our systems and be able to give the information that are available to our customers right there. then why not 24 seven, any language you want. why not tell them where their packages are or if they have a question about a return, we can tell them that. So we built it and we built it from scratch and the team, took three months for the team to make it happen. And I was blown away how fast they did it. And it's fairly good, even the first ⁓ iteration, obviously we had many iterations after that. But then we were like, okay, now that we have this AI that we created, can we use it for something else? And we are a seasonal business. when it's tax returns is actually our Christmas. I didn't know that either before working for Carparts. And so when you have, you know, seasonal business and you have an influx of calls or emails, you cannot necessarily flex your business to be able to answer those. we're like, okay, can we

speaker-0: Interesting.

speaker-1: Can we help that? And so we created a ticketing system from scratch. And at first, I thought we were crazy. I had, you know, the back of my mind, I'm if it works, great. If it doesn't work, well, we tried. But it worked. And it was so amazing that we kept on adding different agents. So we have one agent that helps with tracking. We have one agent that helps with returns. We have one agent that helps with question on payments. And so each of them have their own little category of expertise. And then we realize, ooh, but we can do even more with that because now we have the capabilities through our ticketing system to understand emails that are coming to us that previously a human had to read to take an action. Now we don't need the human to read and say, Disorders canceled, please tell your customer, right? Because we have vendors. Or I want to cancel this order. So all of these things now, we can trigger through the email and an API to our system. And it's done automatically without us having to intervene. Before, if I had wanted to do that, I would have asked to integrate two systems with an API, which is expensive. Our systems are Most of them are legacy systems. So that's very difficult to do. It's costly and it takes longer than we care to admit. So that's we started seeing all the things we could do in the backend that would benefit the customer because not only it's speed, but it's efficiency. And so you free people to do things that matter and not being, you know, clicking on a button. day long, which unfortunately I think we had.

speaker-0: Yeah, that's right. And I think there's a lot of talk about, about AI taking ⁓ jobs away. But ⁓ way I see it, the way it's working in my company is it's actually creating a lot more work for us. We're able to get a lot more done, right? So it's not like we need fewer people. need people that know how to use these tools ⁓ and do more, you know, and sort of orchestrate the work that they do across all these automations that are now in place.

speaker-1: That's for sure. And this is where I think work is continuing. ⁓ we put those AI, they're and they're working, but now how do you maintain them? How do you keep on feeding them, updating them, improving them? This is a lot of work. But to go back to your comment earlier, I think that... Having the AI is complementing our agents that are on the phone and responding to email. And now they have the time to concentrate on the cases where you need empathy and you need to listen to the customer and understand. And sometimes it's complex. Sometimes, you know, there's problems with the system or with a carrier or a part. And so there's less pressure, ⁓ know, now they can take more time and We know they're working on the ones that are difficult and complex. And then we leave AI for where's my tracking? Where's my order?

speaker-0: Absolutely. don't even realize how much time we've spent over the past decade since computers really enter the workplace doing mundane tasks to feed the computers information, ⁓ Filling out forms, inputting It's like all that goes away. And I think gating factor now for us is how do we use, to your point, how do we use our humans? That's the capacity constraint, right? And the humans actually will become the constraint again and we'll need more of them because it's a very unique role in my opinion that our people feel. And I also think, I'm curious how this lands on you, AI as a cost cutting method ⁓ very short-sighted because the real advantage is product innovation, doing things differently and better for the client or the customer that you serve. versus just trying to make it cheaper to do that thing that you did before, right?

speaker-1: Totally. Now it opens door into this creativity you didn't know ⁓ had before. And it's funny because the more we think, ⁓ what else? the more we find use cases or things we could do with it. And ⁓ being freeing to be able to do that, where before we had all those legacy systems and it was, yeah, we could put it on the next roadmap, but it's going to... Obviously everybody has things they want to do. So then you have to compete with your peers and you don't want to do that. I mean, it, ⁓ it's actually blowing my mind what we're able to do and imagining in the future, instead of having a reactive experience for the customer, you could have a proactive experience because now you can, ⁓ was impossible before with the volume I was telling you about, like, how can you monitor all those orders? and say, ⁓ we have a problem. What do we do with this? But now we'll be able to do that. also gathering the insight from everything that's happening is being really complicated, right? And now it's easy to gather the insight and use it because of AI. And so we really have no excuses if... we don't take advantage of this and understand, you know, at what point the friction is. And maybe some of the friction is not as painful than others, but maybe they are low hanging fruits and you can still, you know, take care of those friction points where you will probably have focusing on the other, the big ones first. Well, maybe not. Maybe you, you cut out all the noise and then ⁓ what's left.

speaker-0: Yeah. And you're talking about friction points in the customer experience as it pertains to the use of your product, waiting on the orders.

speaker-1: Well, from ordering on the website, right? Is it easy to find the right part? does it, you know, do you get the part that you were expecting in term of quality, the packaging, then were you able to use it, right? Because most important thing. And then you happy with it after you actually installed it? So along that journey, you can capture in different ways. One of the ways for me is listening to calls. So now you can gather all this insight from the calls. And that's going to be amazing. I'm looking forward to that.

speaker-0: We just implemented inside of our company, centralized data. We use a call recording platform as well. Everybody should be these days. If you're not, you're missing, like that's where the magic is happening. In my opinion is on these calls, whether it's with a high touch customer or a low touch to your point. but we just implemented a central database ⁓ where, then we put an MCP server on top of it so that when we work in Claude, we can just ask Claude about any one of our clients and it brings back. the call transcripts, it'll use skills that we've created in Claude to go and create discovery summaries or requirements documents. We're a consulting firm. So those are the kind of deliverables we create. They're basically all created from the content that's shared in these meetings. But one of the things that I literally started working on this over the weekend, I'm like you, like every time I see something, I'm like, oh, I see something else beyond that. And you just keep going and you keep going and going. And then before you know it, you have these. pretty elaborate systems that are highly customized to yourself. But one of the things I did was, ⁓ took all those call transcripts. Cause we have transcripts of all those calls had it build a knowledge base about ⁓ our consultants are talking to our clients about. Not one that we had to come up with ourselves, but it sort of built the structure and the design and the content for the knowledge base. And then it started linking things together. And then we've set it up so that every time a new call transcript goes into this system, an agent takes it out, processes it, and updates information all over the knowledge base with that new piece of information. Now you could add some checks and balances in there and do other things to make it more.

speaker-1: I'm gonna that from you, Jay. Is that okay?

speaker-0: do. I think, you know, there are certain things that I think are going to be like we're all going to have to do them because everybody your competitors are going to be doing all these types of things. So I got the idea because I read it on LinkedIn. Somebody was describing they had built a knowledge base based on all the their their existing content. So but yeah, ⁓

speaker-1: The idea of having it dynamic based on what's happening at the moment. Yeah. That's pretty cool, I have to say.

speaker-0: Well, the insights, so let's go back. You talked about gathering insight. To me, when you're in a CX role or in sort of the B2B world, maybe even more of a customer success role, one of those powerful roles that you can play for your organization is like the having your ear to the ground on what's actually happening with the customers. So I'd love to hear more about like how you're starting to gather insights now that you have all these tools in place. ⁓

speaker-1: We're just playing like you, we all ⁓ moved to Claude and so everybody's So Insight is great, but it's all about what you do with the insight. So I don't see my role as a listener then a regurgitator to the rest of the company. I want to understand what we can do. ⁓ I ⁓ what my company promise is, I know what we're trying to deliver as an organization. So how do we tie that insight to what we're trying to do this quarter, this year, and propose things to my and say, hey, can we work on that? What do you think? And building whatever it is together. ⁓ So. Yes, of course I could give, you know, hey, marketing, this is the feedback that people are saying about, but is that really helpful if we're not doing anything with it? So I see my role going a little further ⁓ not just telling or sharing, but doing ⁓ ⁓ rest of the team. And so when you flip this, you know, it's ⁓ more powerful, way more interesting than just providing insight.

speaker-0: Yeah. You just hit on something really powerful there. And then I want to come back to this, how you made the decision about the, ⁓ support platform, but it's really powerful idea in general, because you're following a strategy you've set, you know, what you want to go do to grow the business. You've set a strategy for the year for the, you know, next two or three years on how you think you can get there. And you're going after it. A lot of times, I will run across customer success leaders or CX leaders who, you know, they're surfacing all kinds of insights to your point. And there it's almost like it's noise because they're putting out everything that's wrong with the organization or the customer experience. And we all know that there are problems, right? And we have to prioritize what we're doing about it. But if it's not aligned with the direction of the business, it's hard to, it's hard to prioritize those things. ⁓

speaker-1: Well, then you become the chief complaint officer and that's not the I want to have. ⁓

speaker-0: Well, and it's, not really helpful to anybody either. Right. And, know, those people, frankly, probably are getting maybe laid off right now. Right. Not, not, they're not being promoted and they're not a core member of the executive team in my opinion. So, okay. Really, really interesting insight. We can have a whole podcast on that at some point. We'll do that for our next, our next one, but let's go back to the, to the support platform. So you, you had some aging technology that was behind your, ⁓ that was behind your, your support system. And decided that you wanted to go build from scratch. Like, ⁓ take inside that decision of how got there. How did you make that decision?

speaker-1: Well, so you look at all those tools and then they're created for different customers, not for you, right? And you have all those bells and whistles, but we're a very simple company. We ship a part, you receive it, you install it, we're done. It's not a very complex industry, right? So we have all those bells and whistles that we don't use, but what we needed was not there. And then seeing how... AI was developing, you're like, how can we not have AI answering those emails that are just informational email? We have the information in our systems. Why do we need to have someone doing this? And with the success of the chatbot, because it started with the chatbot, we're like, well, it works for the chatbot. We can apply the same AI to our ticketing system. And obviously, not you know, UX designers of a software. So it was a little bit of a, how do we do this? But between, you know, a couple of talented people and I, UX designer that design our website, we're able to create something that's simple and works for us. But now we can tweak it every time that we need, we can add more agents, we can add more interface. And we, we have the entire call center now being on that platform. Where before we're looking at how many seats is that going to cook? You know, can I attend people? That's, that's the cost, right? So we had some people that didn't have access to the ticketing system before, like the sales team. we sell on also over the phone they didn't have access to the email. What? So now we can give. The cost. You know, and they are on the phone.

speaker-0: because of a cost, because of cost.

speaker-1: selling. They don't necessarily need to have access to an email all the time. But sometimes it's helpful. So that's how it started. And it was almost like a bet, you know, like, can we do this? we, so I, ⁓ know, it changed my entire perspective on AI. And I thought this was something that only if you, you know, you had a lot of resources you could do. And that's not true. You just need to get started and then it's going to trickle down. So whoever has not started, just start with one thing, right? Something simple. But you can.

speaker-0: And it'll lead to more is your point. So initiated this? Did this come from, ⁓ CEO say, Hey, like we're going to, we're going to do this. Or was it more of a bottoms up like, Hey, I think we can do this. I'm going to take a stab at it. ⁓ did it, where did it originate in the organization?

speaker-1: Well, I recall properly, I think it came from ⁓ the chat bot were really unhappy. that was the, let's do this. ⁓ I don't know if it was our CEO or CEO that said, but why can't we replace the whole thing? And how it started. And then our data science team, they're geniuses. They're like, yeah, sure. Of course we can do this. So it started like that, like a casual conversation. Why don't we? And then they said, Yeah. So here we go. I was a little reluctant, I have to say, at first. I'm like, OK, unknown territory, but you'll figure it out.

speaker-0: Yeah, absolutely. Now, were there people in, I assume you have a team in your part of the organization as well that works on various CX engagements or How were they involved with the people that were actually engineering the solution?

speaker-1: Actually, for this particular project, was three data scientists, myself, and then someone ⁓ at call center. Of course, also helped us because the chatbot is on e-comm, but it was a relatively small team. That's it. That's what it to do a chatbot. I told you they're geniuses.

speaker-0: That's great. Um, I like what you said, you know, think a lot of people are looking at the buy versus build kind of decision, all kinds of tools right now. Um, and even some of the agent platforms that they're, they're looking at and where you said it was really powerful. A lot of the tools that you looked at were not made for your company, carparts.com and the things that you needed that will, they had too many features that weren't for you.

speaker-1: For boys.

speaker-0: and then they had not enough features that were for you and it was very simple what you actually needed.

speaker-1: And you look at the cost, So always that question of build or buy. And I think that every company is different. I don't think we would build a payment processor, right? So there's still some things that it's to buy for your company and you need to assess what it is. If you're a small company, maybe you don't have three data scientists you can dedicate to a project like this. Certainly worth asking the question.

speaker-0: Yeah, absolutely. All right. So when you started out on this journey, I'm sure there were, there were some interesting, learnings along the way. Did you ⁓ any learnings about building these agents or the chat bots that, that you can talk about?

speaker-1: Yes, yes. So there's ⁓ a couple of funny stories as we build those agents and obviously we're building the plane as we're flying it. So we don't know what we don't know. And so we build this agent called Harper and Harper is ⁓ doing and she's helping with We give them names because it was easier to... you know, to connect with them. And ⁓ Harper ⁓ decided that it was okay to tell customer that they could cancel the order and she would keep track of their order and email them back. it's like, no, you cannot do that yet. Like we're not giving you the ability to cancel orders. Now, we can. But at the time we told the AI you have to be helpful and you have to help customers. And so Harper was being helpful. Let me help you do whatever. you know, very, ⁓ conciling, very, ⁓ nice, never say no. we had, ⁓ launched it. We had to go back and look at all the orders and all the customers. She promised things that we couldn't do and then ⁓ them back saying, sorry. Thank it was not that many, but this is when you realize, okay, it's it, it has a life of its own. and you need to understand and put guardrails. Yeah, and the guardrails are difficult sometimes because if you put too many guardrails, then now you have a robot, right? Not an AI. And you're limiting its creativity of what it can do. So it's a very subtle adjustment of that toggle to leeway so it can resolve things, but not letting it go crazy and...

speaker-0: drills.

speaker-1: hallucinates and it happens. So you have to monitor it. You cannot just say, we're done. We did it.

speaker-0: Yeah, think with people

speaker-1: But you would with humans, right? You would coach them and them and audit them, you know, to make sure that they're doing what you want them to do.

speaker-0: Yeah. Yeah, that that's right. And if they're, you know, young teenagers or kids, they would have never known about those constraints or guardrails. Like they might have just done what they thought was right. Just like an LLM. So one of the things I think that we all have a major misconception over is, this whole word intelligence, because at the end of the day, there is no, there's no actual intelligence in these things. I know that sounds weird. Maybe it's the wrong words I'm using, but The intelligence is not, it's just sort of raw and un, mitigated It's not, it doesn't have common sense. The common sense is what you have to get it. You have to give it guardrails. You said that's a great word. And I think that's like a very common word. ⁓ we're trying to do, I was telling you about that solution that I built to sort of put all of our calls into a centralized database. Well, we classify them because some calls they're, they're more Confidential right you have one-on-ones with team members talking about compensation you're interviewing people You have leadership team meetings. You don't want all those exposed through your MCP server for everybody to query, right? Well, I noticed the same thing you did which is when you coach it you the coaching you provide has to be Specific it has to be specific to issues that occurred but not too specific Because if you make it too specific, it'll just blindly follow that rule and that rule may not always apply so I think there's a very, you're something there with like the nuanced nature of what it actually looks like to train an agent on what you needed to actually do.

speaker-1: And we keep on tweaking, you know, the prompt, we're actually looking at it again. And you cannot foresee all the scenarios, right? It's impossible. have to find the right language to tell it. You know. If you don't know, or if it's not specifically said that you can, then cannot. So it's little bit of a interesting, you know, wording, but it's it's been. It's been amazing to see how it interacts back and forth in a very seamless way with Kassars.

speaker-0: very cool. It's very cool. Well, my niece's name is Harper. So I'm a fan of your naming convention for Harper there. It's pretty cool.

speaker-1: It's hard for her, know, she tracks orders. So, you know, we had some remember each agent, you know, there's a little rhyme.

speaker-0: Harper for what? ⁓ okay. Oh, I see. Okay. Well, it's good. And you know, the agents were building, they should have personas because they're doing jobs like

speaker-1: Well, do have personas because, ⁓ for example, Penny is for payment. Penny doesn't have a lot of leeway and ⁓ didn't need Penny to be very helpful and friendly. We want Penny to just, you know, this is about payment. This is what happened. And that's it, right? Not being over explaining, over apologizing. they ⁓ each their little personality for sure.

speaker-0: Just like somebody in finance. You want them to be pretty, cut and dried, good with a...

speaker-1: You know, you have a question about payment. I'm not going to put more words around something that doesn't need it.

speaker-0: That's right. Not going to sugarcoat it. That's why I'm not in finance by the way. well, very cool. So what an incredible journey. Like what's, what's next? What do you think is next for you? Is it just incremental or do you have your eyes on some other system in your, in your platform stack that you want to go after next?

speaker-1: ⁓ I think I really want to stabilize it because we've been iterating, but I think we go into a different phase now where it's built, but how do you maintain it? Because anyone can build something, right? We know the hard part is the maintaining. So I really want to see this through and team just built us an interface where we can ourselves change the prompt, which They just delivered it this morning or yesterday. So because now, you know, they have to move to other projects too. So how are we self-sufficient in maintaining our own system, our own agents? There are agents, like human agents, we're going to take care of them. And so it's, you know, it's doing that work now to make sure that we can ⁓ it every day and improve it. Because if not, it's going to become stale. I mean, you have You can change policies. You have new questions for customers. We have new programs, so new questions, new problems. So you need to update it constantly. Like you do with your agents. You send them, hey, by the way, now it's a new policy. Hey, go to training. You need to learn about this new feature, this new product. Same. We have the ability to do it, some of it ourselves.

speaker-0: So. ⁓

speaker-1: They put some guardrails for us too, to not mess up with the AI. So I appreciate that. Cause it feels like apprentice sorcerer a little bit, a little bit of that, a little bit of this.

speaker-0: Yeah. Amazing. And so it seems like the skill set of your team is probably evolving in parallel with this. Is that true? Is that fair to say?

speaker-1: ⁓ absolutely. think there's nobody, I think in the company right now that's not looking at AI and how it can help their everyday work from, ⁓ mean, anybody, not just a operation or technology or data science. And ⁓ think amazing. It's all scary at the same time, right? ⁓ To see what it can do. And we need to be cautious too, right? Because it could give you wrong information. It could give you stupid answers. And so you still need to have the ability to take a step back and say, okay, you're asking me to jump from the roof. Maybe I won't do that. But it could, right? So I don't know. I feel like this is an amazing tool for a company like ours, a mid-sized company that necessarily doesn't have big budget for innovation and we can innovate at every level of the company. And it's amazing. Now we can keep up with the rest of competition that maybe ⁓ of dollars to spend and we don't. So yeah, it's fair game now. I like it.

speaker-0: I think ⁓ maybe having billions of dollars to spend might be a disadvantage in this because it's very easy to overthink it. And to your point, very small teams can do really amazing things. And sometimes constraints are good for creativity and building things that are effective, Not overly frankly.

speaker-1: And that's how we, know, earlier in the call, we're talking about how I work with the other teams. And usually that's what happens is if we're working on shipping protection, then we have different people from different team. We're meeting every day or every week, whatever is needed. We do what we have to do. And then everybody goes back to wherever they were. So you have many teams working on different projects all the time. And it's been very, it's working well for us.

speaker-0: That's great.

speaker-1: But now we're on top of it.

speaker-0: Yeah, that's right. Filling in the cracks. That's awesome. right, cool. Well, great conversation. ⁓ you have any, ⁓ advice would you give to our listeners that have maybe not even taken the first step yet, or maybe who are just starting to dabble in to figuring out like, okay, where can we really take this in our company? Who would you tell them?

speaker-1: Well, try whatever AI you want, whether it's cloud or whatever you want. I have to say cloud is pretty powerful. And then just go to a tutorial, listen to it. What can you do and start with ⁓ thing, ⁓ little thing that you can do. What are the repetitive tasks that your team is doing every single day? And what can you do with that? Or what is your friction point right now? Can you work? on this particular friction point, whether you're customer facing or not, doesn't matter, but start with one little thing. And then, like learning any skills, like you need to start with something and just, you have to dip your toe in the, at the end of the pool to see what's temperature and then you can jump in.

speaker-0: That's right. Very good. Well, this has been awesome. I appreciate you taking some time out of your day to chat about this and share. think, you know, I think you all felt like you were behind. I feel like you're ahead in a lot of ways now based on what I see.

speaker-1: I feel like we're surfing finally with I will not be hiding anymore. Right. So that's the cool feeling.

speaker-0: Yeah, you're on the way. Well, it's really exciting. And so maybe we'll check in in a couple of months and see what else you guys are up to and what, what do you have? Yeah, I'm sure, I'm sure you will cause you're surfing on the wave. So, well, I really thank you for your time and we'll talk again soon.

speaker-1: Thank you.