ChargeMate’s AI Advantage: Designing for Service, Delivering for Drivers

In this episode, host Jason Cortes sits down with Brad Crist, CEO and co-founder of ChargeMate, to explore how AI is transforming EV charging reliability. From real-world road trip frustrations to building an AI-driven support system that bridges the gap between drivers, operators, and field technicians, Brad shares how ChargeMate is redefining service intelligence in the EV space.

Show Notes:
The transition to electric vehicles depends on more than just chargers—it depends on reliable charging experiences. In this conversation, Jason and Brad unpack the challenges behind EV service workflows and the role AI plays in keeping chargers online and drivers confident.

Inside the Episode:

• Brad’s journey from environmental science to leading ChargeMate
• The catalyst moment that sparked ChargeMate’s founding
• Identifying the “service gap” between drivers and charge point operators
• How AI bridges driver-reported issues with actionable insights for service teams
• Smarter dispatching and avoiding unnecessary truck rolls
• Making raw charger data meaningful through context and automation
• Building serviceability by design: what CPOs and OEMs should ask about hardware
• Why “buy vs. build” matters when it comes to AI in charging operations
• The future of EV service intelligence and collaboration across the industry

Listen to learn:
 How ChargeMate is transforming EV charging from a reactive model to a proactive, intelligent, and human-centered experience—and what that means for CPOs, service providers, and drivers alike.

Transcript

0:00

Did you know that one out of every five EV charging sessions are unsuccessful? Drivers get stuck, CPOs start to lose revenue, and service teams are just trying to figure out what's going on to help at the site. On today's episode of Field Frequency, I'm joined by Brad Christ, CEO of Chargemate. We dig into how AI can flip that script by capturing real-time information from the drivers to cut through the noise and to avoid premature truck rolls or even unnecessary truck rolls. It's what's going to give operators what they really need, and that's reliable chargers. This is all about designing for service and delivering for the drivers. Let's get into it. Welcome to another episode of Field Frequency. Today I'm joined by Brad Chris of Chargemate. Brad, so glad to have you today. Yeah, thanks for being on. You are showing up right after some good news of investment in Chargemate. And so I hope maybe you can share a little bit about that with us. But right before we get started, I'd like to... I'd like you to just introduce yourself. us, you know, tell us, give us your professional journey and what led you to where you're at today and how things have come to be with ChargeMate. So give us, us, give us Brad's story and give us ChargeMate's story. Thanks, Jason. Well, I'm Brad, CEO and co-founder at ChargeMate, and I grew up in Kansas, spending a lot of time outdoors. I studied environmental science and energy in undergrad and got really excited about the electrification of the grid and transportation system, both from an environmental and climate perspective and as one of the biggest industrial shifts in our lifetime. And I think there's an inevitable future where we move off fossil fuels. And I realized at some point in my studies that that's where I wanted to take my career. So I've been working now for 12 years in the energy and transportation industries. I'm really fascinated by the consumer behavior and shift that has to happen of electrifying not just cars, but our homes and buildings. And, you know, the average American spends less than eight minutes a year thinking about their electric bill. Um, but it's one of the biggest industries and so foundational to everything we do. before charge made, spent three years at Volta charging where I led development of the driver app, how EV drivers would find start and pay for charging. I guess I saw firsthand that transitioning to electric vehicles requires significant behavior change. And I knew that the mainstream EV driver isn't patient like us EV nerds who are enthusiasts and willing to troubleshoot chargers that aren't starting. I was taking friends on road trips a little over a year ago in a Rivian and they said, know what, EVs are not for us. This charging experience is full of friction. So that exposed for me that the new mainstream driver ever for EVs to really hit this inflection point and reach massive adoption, charging just has to be simple and seamless and ideally as much like a gas station experience in public as it can be. So in some of those road trips, you know, navigating to reliable available chargers can be difficult, but we saw a lot of tools for route planning and navigation. However, when a driver steps out of their vehicle, every charger feels different. And there's a lot of friction there, I think in how to start a charge, dealing with issues that might happen. When we dug into the data, we realized that globally one in five attempts to start a charge will still fail. And at a couple occasions, I spent more than 10 minutes on hold and 15 to 20 minutes on the phone calling a 1-800 number for help and thought, okay, this is really where we should start. And this experience needs to change. When a driver needs help, it shouldn't be a 10 minute wait to serve them. And so I sold the Rivian. was driving friends on road trips in and invested that money in building a tech company. um I have a product management background and my co-founder Brian worked at the design and innovation firm IDEO where he led the data science practice. So our skills are really good fit and we've done a tremendous amount of human centered design work together interviewing more than a hundred charging executives where then we arrived at our wedge into the market being AI driver support. Very good. you you mentioned early on, was still while in school, you foresaw a future where petroleum as a fuel source wasn't there. That's, entered the EV charging base actually within oil and gas far downstream at the retail level and trying to talk to petroleum retailers, petroleum marketers about EV charging as a fuel source was a very sore topic back then. Retailers weren't what they're doing today. So interesting that you had that foresight. I also had that foresight, probably not as early as you did, I was involved in liquid fueling infrastructure, petroleum fueling infrastructure. My view was that that's another form of power, another form of fuel. electrons, uh, there could be space made in, in both retail as well as a commercial context for, for refueling with electrons. And it's just, it's a different experience. So you, your road trip with friends and an EV was, was, was a catalyst to, resolving the friction points that they as a, as a non-adopter of EV saw. And so you saw that, that need, thus, you know, charge made and its solution. So I want to, I want to. get into what ChargeMate does. I want to get into the solutions that you're bringing to market. I want to start off with that service gap. Obviously that friction point that your friends saw on the road trip and we as EV drivers also know it exists. It's not a hidden thing. We don't deny it. We recognize it. em And so in identifying service gaps, from your perspective, what are the biggest gaps today in the EV charging service work? So we've got an EV charger, we've got an EV driver trying to charge their car, and it doesn't always work. That's the reason why companies like ours are field advantages in business, because believe it or not, chargers sometimes don't work, and that's why we exist, is to keep them working. So within that service workflow, from driver experience to work order execution, where... What did you identify as a service gap and what is the solution? Yeah, one of the biggest gaps we've seen today is in identifying and diagnosing the problem. you know, drivers will often struggle to get help, um as well as they don't report issues very often when a charger doesn't work. And so operators then are stuck in very reactive workflows, usually manually triaging emails or combing through charging logs on the back end of their systems. And they'll often miss the driver behavior that results in a fault in the first place. uh We believe at ChargeMate that AI helps bridge that gap by making it easy for drivers to not only understand how to start a charge, resolve common failures with payment and authentication or vehicle or charger faults, but really making it simple for drivers to also self-report damage and then reach some accurate and immediate support. And we turn that context into more actionable insights that then streamlines uh downstream work order management and helps reduce downtime. So you're leveraging AI as that bridge and that service gap. You obviously have a frontline defense and that's the user of the charger, the driver of the EV trying to work with the charger. The driver becomes the first responder in this context. And so you've emphasized that the driver is the first to detect an issue. That's what you just said. They're the ones trying to use the credit card reader. It doesn't work or they're trying to plug in and it's not Seating the charger cables not seating or or you know the HMI the screen is is is blanked out or it's there's other things or maybe it all shows to be connected but Nothing's happening the chart card the car is not getting a charge So the driver is the first to detect that issue because they're the ones trying to use the charger So how can from your view how can drivers real-time experience that those experiences at the charger be translated into actionable Intel for a charge point operator? Good question. I think the old adage picture is worth a thousand words applies here. We found that it's really important to be able to confirm, yes, we've got a broken card reader or damage to the plug, but also differentiating that from what might be user error. A, the plug isn't seating because maybe you forgot the adapter or maybe you need to push in a little harder until you hear the click. And so from our AI support channel that is web-based, it also embeds into the driver applications of charging network operators, will capture more structured data using chat as well as a series of dynamic buttons. And that encourages the conversation to be longer. We've also seen much richer data. And so we're not only trying to save the charging experience for the driver, but use that intelligence to define improvements for the network. And so there's a part of our product that helps automate work orders and support tickets from the AI chats that we're having, as well as now looking at plug share and Google Maps reviews and seeing that drivers are occasionally reporting problems via phone, email, third party platforms like those. But that information is often separate and siloed in many of these larger organizations. So we want to bring that intelligence all into one place. And now we're matching what was the driver telling us with what did we see in the back end from the charge point management system. And we believe that's the real unlock here in being able to have both a real time understanding of what the driver's experiencing and really understanding what's happening in the system as well. So for the listeners that maybe they're not an EV driver and they don't understand that when there's a how that problem is captured for the operator, the charge point operator, the charge station operator, there's that issue, whatever it may be. It's capturing that detail. And you mentioned for a ticket or for service, for a service call. In other words, ChargeMate is taking an AI-driven solution that is bridging the gap between the owner and operator of that charger and the user, the customer that's trying to access the charging session. And it's bridging that gap because when there is a disconnect, ChargePoint operators may not know. The charging station owner may not know what's going on. They're not there in real time. Charging sites are typically unmanned. It's not like you have a concierge. It's not like traditional retail fueling where, you know, there's someone on site that you can go to if you're having a problem. So what happens is when a charging session is not able to go through, you have this gap and you're leveraging the driver with their, with their on-site information to, to integrate information that goes back to the, to the CPO. then they can action. on what needs to happen, whether it's a truck roll, whether it's a remote resolution, whatever that may be. this is all about smarter maintenance, smarter dispatches that result in smarter maintenance or a smarter resolution. so CPOs, they want to avoid wasted or premature truck rolls. They don't want to spend that. For CPOs trying to into the black and out of the red, they're looking for cost containment, they're looking for utilization, they're looking for uptime. And so if there's a problem that could be resolved remotely, they don't want to spend the money to someone out that didn't need to go out. so ChargeMate is leveraging AI to address that for that smarter dispatch. How does ChargeMate address this? What does an ideal decision tree look like in the ingesting of the problem and where does it go from there? Great question. So charge mates at the front end of field service and we believe we can improve its delivery and improve uptime as well as success rates. So maybe an example scenario would help. Let's say a driver or a site partner says that a charger is broken. We don't always have a lot of data by the time that reaches the field service team. And that results in false positives like you mentioned, a truck roll that maybe didn't need to happen. We just needed to send a remote restart or a power cycle. And so we've been able to identify charging stations that needed a power cycle or a remote reboot and then avoid sending a technician prematurely. So that's saving the operator anywhere from 200 to $500 or more on the truck roll and labor. But it's also more immediate in the flow of a driver being able to resolve the issue, ideally, while we still have their attention while they're still there trying to get a charge. And You mentioned, you know, what's the ideal decision tree. think the ideal workflow, you know, says something about a driver who shows up and they cannot charge. They'll activate our AI support assistant either in the charging networks app, or we've used QR code stickers with a call to action. Need help scan here. And that opens then the AI support assistant part of our product uh in a mobile browser. And so let's say the charger looks off to them. We're going to check the OCP logs. Is the station online? Do we see a heartbeat? When is the last time someone successfully charged here? And is this something that we can resolve from a soft reset or do we need to recommend a power cycle? In the cases where we do see persistent issues, We'll create a support ticket or work order. And then we'd like to be able to assign that to a field service technician and even handle downstream up to the point of checking parts inventory and getting that scheduled. All of that happening ideally without a human in the loop. And while we're still serving a driver trying to save their charging experience. Yeah, that's, uh, that's good. You, you mentioned, you know, CPOs having access to their OCPP logs. CPOs often have large data sets, but those data aren't necessarily accessed or, or usable or even translate into actual service items. So you're on the front end of service. You're ingesting those error codes or whatever the problem may be. And, and you're, you're reconciling what the immediate problem is. whether there's an error code attached to it or not, typically there is, but then you're reconciling that as the existing data sets that are there through the OCP logs. so listeners know what OCP means, open charge point protocol, it's a communication protocol that occurs and there's data in there. So obviously data without context is not as meaningful as data with context and an actionable you know, some, some way to action on that. So how does charge make, make raw data meaningful for the owner, an operator of the charger and the service providers that they have in the queue to resolve a need whenever there's a need to resolve. Yeah, the first problem we've observed is that there is a lot of data, but it's often all over the place. And like you mentioned, it may not have the right context. So we'll see, um, issues reported by phone email, some of the third party platforms I mentioned. Um, and that's often in separate systems and different teams. When I worked at Volta and we're building the driver application, we get reported issues via the app. That was a different team that's handling support and maintenance and then you have to aggregate that information with what you might learn from email or what a driver might indicate over social media. So the first thing we're doing is just getting all that information into one place. The next is being able to filter what we'd say is signal through the noise, right? If you have 10 driver tickets submitted, let's identify the one that we need to act on right now. What else can we automate or what might be able to wait a little bit longer? And then to your earlier point about the importance of driver feedback and data, we're appending that to support um conversations and charging logs, which we think is really powerful. So it's like being able to see both the front end experience and the back end with one complete picture. Good. That's good. You you mentioned your, your, experience with Volta. and for the listeners that may be new to the world of EV charging, Volta is is a brand, um, that was a charge point operator, I guess is what their EV space was. Volta was, brought to market a, a unique, you know, a big screen that was, the screen was leveraged for, marketing aspects, but there was charging, typically level two charging. And so you referred to how drivers trying to access the Volta network would have an issue. And that issue would go into a siloed aspect of the business. would go into that customer trying to resolve that issue to get that charging session going. the data didn't flow and the workflow wasn't as streamlined as it should. And so uh You know that obviously goes back to the data without without context AI is is bridging that con is bringing in that context and so the the potential That's there with with your platform to capture driver behavior To capture real-world conditions what's going on with the charger? What's going on around the charger and and even contextual clues that that are going to eclipse? Just some information sitting on an OCP data log or a session log rather There's the, it's going to fall back. How, how do you, how does charge mate see AI reshaping the definition of service intelligence in this charging space? Yeah, great topic. Service intelligence has typically meant analyzing logs, right? Looking at uptime, error codes, potentially matching that with support tickets. But we think that only tells part of the story. And so AI helps us shift from reactive reporting to more proactive problem solving by capturing some real world context. Also a deeper understanding of what hardware skew a driver is trying to start a charge on. What else do we know about that? mean, some of these hardware products have hundreds of unique error codes, which is difficult for anyone human to keep track of. But it's a great fit for AI and a knowledge base, right? And so part of that context is capturing and understanding of the driver behavior, getting any photos or leveraging any interactions via voice as we can. and then looking at conditions on the site. What else is happening in terms of the building and energy load at that location? So that makes the system much more human aware and it also helps us understand charging the way the driver actually experiences it, right? If a charge doesn't start, a driver feels like it's broken. And so how do we go a level deeper to understand, well, it's not broken, let's try to start the charge. ah or if there's a persistent issue, let's make sure that we've got all the information we need before we roll a truck. You know, you mentioned something there about error codes and I first decade and a half of my career was spent in a fleet context. Fleet management role. We were obviously maintaining a large, you know, six to 700 unit fleet with liquid fueling destinations more than one. both petroleum gas and eventually CNG as well. when it got down to working on vehicles, there was error codes that were driven by SAE and other standards, but there was continuity to those error codes. So for instance, check engine light on a Chevrolet pickup, check engine light on a Ford pickup are going to trigger a code. There's typically Not always, but for the most part some continuity to that numbering. So you can recognize, you can see that error code. You plug in an OBD scanner into the vehicle's port and you're downloading the issue. You're identifying that error code. Why is the check engine light? Whether it's a Chevy, whether it's... There's some continuity to that error codes. We need that in this space. It's not that case. So we've got tons of manufacturers. These OEMs have error codes. They have telemetry. um They have all their own data sets and and there's a need for collaboration with this data But the OEMs for you know, IP reasons or whatever it may be They're not always willing or able to share information. So, you know you you the reason I'm bringing that as you touched on Error codes and interpreting that and knowing what to do. What does what do what does a company feel the advantage? Do when there's a problem? What's the path toward better collaboration here? What results when that doesn't happen? When it's disjointed and it doesn't come together. What happens? So what's the path forward? We want to respect other companies desire to keep data, specifically telemetry data private. But at the end of the day, charging manufacturers are successful when their products are reliable. And when that data isn't shared, you often see longer downtime and as a result of higher cost of field service. We're beginning to see more willingness to share data and information like install manuals and data dictionaries, lists of error codes that are unique to hardware SKUs. particularly with trusted partners. So what's worked well for us so far at ChargeMate is we're selling our AI customer experience platform directly to charging network operators. Then we can leverage that trusted relationship to get their hardware vendors on board when they see that our goals are all aligned and just providing a more reliable and trusted charging experience for the end user. Yeah. So talking about, well, let's look at serviceability by design. Whether it's as an EV driver, as a found charge mate, and when the systems are able to experience all your disk experience, know that the hardware isn't always designed with service. I've noted myself, you can open up a modular chart today and see a chart of parts and versions that are some segments in there. You open up a LASIG chart and it just looks like fire. It's crazy. It's just, there's uh lots of disconnect there. uh are hard work on the design with some sort of mind, obviously. Should CPF... It's kind of getting out of our focus where we've been on data and software and AI and all of that. But what lessons, because there's potential CPOs listening to this or prospective buyers or those entering the market, what are the lessons that CPOs need to take to heart when it comes to hardware solutions or selections rather? Yeah, you know, we learned the hard way at Volta with some of our early DC fast charging prototypes that it was really difficult to repair. Not only because we didn't provide accurate spec of all the wiring and information on field service, but we had to staff an internal team and fly about a dozen people all over the country to serve chargers. But they weren't just fixing a charger. They also had a media display. advertising player. And so it was a little specialized and obviously that doesn't scale well when you're flying technicians to multiple states. So if I were selecting vendors at a CPO, I think I'd ask questions like which field service or maintenance groups are already trained on your hardware? What is their scale and what geographies do you have some trained technicians? What's the cost associated with replacing a power module, for example? or a heavy CCS cable? How do you design your chargers to be easily maintained? Is all that information shared with us as the CPO and with other field service partners in your network? um can we see your install and service manuals as well? So I think digging a level deeper into how serviceable are these chargers, not just by internal staff, but by field service firms like Field Advantage as well. Sounds like you've been involved in specing equipment at some point in your life. Yeah, I can tell. It seems like you're answering all the, you're sharing all the right points as far as considerations and hardware selection. So uh kind of zooming out, you know, looking at the market as a whole, you know, if you were just speaking, obviously to potential perspective hardware. buyers or folks in procurement but if you're know if you're speaking directly to to CPO or to an OEM or fleet operator that's listening to this episode then you want them to take away about a US AI driven service intelligence Yeah, thanks, Jason. First is recognizing the value of AI for customer experience. So initially, I was really skeptical of Chatbot being the market entry point. Early Chatbots had really rigid decision trees, right? You've all had frustrating experiences of like, I just want to talk to human. But generative AI has changed that completely. And we We're really surprised with our early deployments to see that three to five times more drivers are willing to chat with AI than the rate that they're calling customer support. And that tells us a lot that tells us a lot of drivers aren't really getting the help that they need from incumbent call centers. Often that's a few minutes hold time, or it's just feels effortful to pick up the phone and go through a number of questions before. you're actually resolving your issue. Or in some cases, a driver might have a question. They might feel embarrassed asking, it's my first time charging. What do I do? Or, hey, I'm seeing the charges a little slow. What's happening there? How much does this cost? You might not pick up the phone to handle some of those service-related questions. And the other thing I'd say is we're not replacing the call center. We're augmenting support and operations teams with AI. So a small team can now handle a massive network with AI tools because they're able to focus on the issues that demand their expertise and leave a lot of the basic tier one issues to us. The second topic is on build versus buy. There's a lot of companies in charging that are also software savvy, but just because you can build AI tools doesn't mean that you should. And there's some value in partnering with experts. MIT recently put out a great report that showed 95 % of AI projects at large corporations fail. It's really enticing, I think, to want to build with AI. It's new and shiny. Many software savvy companies don't necessarily understand or expect like how much is required to orchestrate that system and continue to maintain it. And I'd say, you know, consider your goals. it to have a cool new AI feature or to deliver a reliable seamless experience and become profitable? And so there's a strong business case for buy over build. We think that wins out almost every time. especially when you consider the cost to maintain AI and keep a system running. And software, if it isn't really good, you're going to frustrate drivers. We see companies that talk about, we deflected 50 % of our tickets. Well, for the other 50%, did you make a driver then repeat themselves on the phone and go through a complicated process? That ultimately frustrates drivers and results in churn. So we believe it's most important to look at what tools will drive up the resolution and charging success rate most effectively. I you you mentioned about the churn. I'm thinking of a very personal experience with my first EV, Nissan Leaf. And, you know, I charge more on the Tesla network than I do. I still have my Leaf actually. But my, course, using, when I first got the Leaf, my Leaf, I was living in multifamily community. So obviously, couldn't put a charger in. Eventually moved to a property that I did have access to a parking garage where I could put a charger in there. But point being is, where going with this is I was dependent on public charging. So I would uh get to a site. Of course, I'm having to use the one Chattamo plug on the charger on site. So that's the only charger. That's like my charger because that's the only one. was a row of CCS. uh plugs on chargers, I don't have access. can only use the one with Chattemo. So then I'd get up there and there'd be an issue. so it was, was, it was a pretty much the same issue all the time. I would, I'd recognize what was going on. Charger would need a, you know, a reset. They call in and be like, Hey, it looks like it's, you know, it's just late and the screen just, there's nothing going on. It's not responding. Can you power cycle the unit? And it was all that would, would go through that and they'd power cycle it, come back on. Of course I'm on the phone with support the whole time and they're like, what's the screen doing? I'm like, ah, it's doing this. And they're like, okay, now try it. I'm going to plug in, okay, then charge. And that was a regular occurrence. So I kind of factor that into my charging experience before I even got to the charger. And of course I'm in a Leaf, 48 kilowatts, you know, it's, this is, this is a, it's charging is an experience at this point. And so the reason why I'm sharing all that story is because With ChargeMate, you've got a product where I wouldn't have even had to call in. I would be interfacing with AI and AI would be ingesting. so I'm talking literally, you talked about early adoption, chat bots, rigid experience, not a very clear decision tree, you might even end up on a FAQ page. Not cool when you're an EV driver trying to use a charger. Whereas your solution, it's compelling and that... I'm interacting with an AI and I'm interacting with AI and I'm talking about what's going on here. And maybe I'm even taking pictures from my phone about what's going on. And it's resolving all that. And I don't necessarily even have to talk to anybody or go through that frustrating experience and what's your name and what vehicle are you in? All these questions, it's streamlined. And so I would have loved to have had that experience back then. You know, with that, with that example, mean, what it, what's, don't want you to reveal in secret sauce, obviously behind the product, but, is, is, is the way I've kind of presented charge mate solution, is that what's going on with, the AI driven actions there? That's right. Yeah, we think of ourselves as a driver experience company. It's both a best fit of Brian's and my skills. And we're using AI then to make the user's charging experience more reliable, seamless, and hopefully delightful. I feel your pain and I'm really impressed you've been a patient early adopter and continued to deal with your leaf. I've felt some of the same frustration and I think maybe because I worked in a charging network and have worked in electric cars for a while, I understood that there was some friction. But that isn't going to work for EVs to really take off and reach mainstream adoption. So we're really excited to partner with field service groups like Field Advantage. Ideally, we want to do and AI plus human support and delivery of field service. We think the charging industry is going to win through partnerships. That's been a really big theme this year and was talked about a lot at the Intercharge Conference in Berlin about a month ago. At ChargeMate, we're taking a vertical AI approach to the market. So what that means is we'll expand from customer experience into more operational automation. We're already troubleshooting issues with the vehicle. Sometimes that means we need to know something about the Auto OEMs driver app. Why did we have trouble activating plug and charge, for example? How do we help a driver set that up, maybe for the first time, at the charger? Also a deeper understanding of the battery capacity, what issues can happen on the vehicle side or in the charging equipment, whether that's software or hardware. And so I think in the future, you'll see ChargeMate both in the vehicle and integrating into building systems in the future. Well, this has been a great conversation as we get ready to wrap up here. I'm kind of looking ahead as we close out. Where does ChargeMate go from here? As AI and EV charging are evolving rapidly, what do you see as the next frontier for integrating intelligence, the collaboration in the space that you mentioned, reliability for the driver experience? Where's ChargeMate go from here in the midst of all that? Yeah, great question. I think like many other vendors, we want to see charging be reliable 100 % of the time. So that's a big part of it. We've also seen our customers see a lot of value in the observability and the data that we can provide them. What is the most common issues we're seeing at different sites? How can we change maybe the UI on the screen or improve the experience starting and paying for a charge? So we want to drive more value, not just from saving individual charge sessions, but providing intelligence that helps network operators improve their experience overall. We've also started to see different trends between hardware manufacturers and how that's combined with a backend software system, as well as what are the options for a driver to start and pay. And so it's really that combination of user experience, software, and hardware that is delivering a success or failed charge. So I think, you know, it's a combination of using AI to directly serve a driver, personalize the experience to them, make it ridiculously simple, and make them feel supported, but then equipping network operators um and other vendors to make improvements to their products, ultimately all in pursuit of delivering a reliable and seamless experience. Appreciate that. Brad, I appreciate you coming on Field Frequency to share your story, to share the story of ChargeMate, the problem that ChargeMate is solving in this space, an important solution that you've brought to market. And look forward to future conversations with you. Thank you for being on Field Frequency. Thank you, Jason.