Electric vehicles are supposed to represent the future of transportation. Cleaner. Smarter. More connected. More efficient.
But for many drivers, the future still gets stuck at a broken public charger.
That tension is exactly what Brad Crist, co-founder and CEO of ChargeMate, is trying to solve. After spending years in climate tech and EV infrastructure, including work at companies like Accenture, Faraday Future, Volta, and Spring Free EV, Brad saw the same problem again and again: the industry was great at deploying chargers, but not nearly as good at making sure they actually worked when drivers needed them.
The result is a massive trust problem. EV adoption is not just about getting more cars on the road or installing more charging stations. It is about whether a driver can pull up, plug in, and confidently get back on the road.
Right now, that experience still breaks too often.
The Hidden Bottleneck in EV Adoption
Brad’s founding story started with a very human moment: a road trip in his Rivian.
He had been an early EV adopter and was excited to show friends what a luxury electric vehicle could do. Instead, the trip exposed the frustrating reality of public charging. New apps. Slow chargers. Damaged equipment. Confusing payment flows. Stations that appeared to be online but did not actually work properly.
That experience sharpened the problem ChargeMate is now focused on: the gap between charger “uptime” and real driver success.
A charger may show up as available in a system. It may technically be online. But from the driver’s perspective, the session can still fail because of payment issues, app problems, charger-vehicle handshake errors, slow charging, connectivity failures, or confusing user flows.
Brad noted that more than 20% of charging attempts fail, a brutal number for an industry trying to convince mainstream consumers that EVs are ready for everyone.
That is not a minor inconvenience. It is a category-level adoption blocker.
ChargeMate’s Bet: AI as the Operating Layer for EV Infrastructure
ChargeMate is not just building another customer support chatbot.
The company is building an AI-powered operating layer for EV charging networks. Its platform uses chat and voice agents to help drivers in the moment, while also integrating into the backend systems that manage chargers.
That matters because fixing the experience requires more than answering basic questions.
ChargeMate can check whether a charger is online, identify faults, inspect transaction status, and in some cases take remote actions like rebooting a unit or releasing a stuck plug. The goal is not just to respond faster. It is to actually resolve the issue.
That is the core wedge: using AI to turn fragmented, unreliable charging support into something closer to real-time infrastructure management.
Why Generic Support Tools Are Not Enough
A natural question comes up: why can’t Zendesk, Intercom, or an incumbent charging network just build this?
Brad’s answer is that EV charging is not normal customer support.
This is a messy intersection of software, firmware, hardware, payments, vehicles, field service, and physical infrastructure. One ChargeMate customer has dozens of hardware products to manage, and one hardware SKU alone has hundreds of unique error codes.
That complexity is exactly where vertical AI has an advantage.
A generic AI support system can answer questions. ChargeMate is designed to understand the specific failure modes of EV charging: the charger, the vehicle, the network, the transaction, the driver behavior, and the operational workflow behind it.
The more hardware types, vehicles, networks, and failure modes ChargeMate sees, the better its resolution engine can become. That creates a potential data advantage that broad horizontal tools will struggle to match.
The Business Case: Better Support, Better Margins
EV charging operators are under pressure to prove that their networks can become profitable businesses.
That is hard when support and operations costs are high, charging sessions fail, and customers abandon the experience. Brad described customer support and operations as a major cost burden for operators, especially when calls can cost $10 to $15 each.
ChargeMate’s early results are meaningful. Brad said the AI can resolve roughly 50% to 70% of calls without involving a human. He also pointed to one client seeing a roughly 5.5% lift in charging success rate, which can translate into millions of dollars of margin at larger network scale.
That is the real investor-relevant insight: ChargeMate is not selling “AI support.” It is selling recovered revenue, lower support cost, better asset utilization, and improved driver retention.
In infrastructure markets, reliability is margin.
The Pivot That Made ChargeMate Work
ChargeMate did not start exactly where it is today.
The original idea was closer to a consumer product: helping EV drivers find available, working chargers near desirable stops like coffee shops or clean bathrooms. The problem was real, but the go-to-market path was ugly.
Competing with Google Maps or trying to become a consumer endpoint would have required massive distribution. Accessing vehicle data would have been difficult. Monetization would have been uncertain.
The sharper wedge was on the operator side.
Charging networks were already paying for failed sessions, expensive support calls, unhappy drivers, and fragmented operations. ChargeMate could solve a painful B2B problem with direct ROI.
That pivot matters because it reflects one of the biggest lessons in startup building: the best product idea is not always the best business. ChargeMate became more interesting when it moved away from broad consumer convenience and toward a painful operational problem with budget attached.
Voice May Be the Real Unlock
One of Brad’s more interesting reflections was that ChargeMate may have started too heavily with chat.
When a driver is stranded at a charger, frustrated, and trying to get moving, the natural behavior is not always to open a chat window. It is to call.
That is why ChargeMate is now investing in voice AI as a major interaction point. Voice fits the urgency of the moment. It also lets ChargeMate take over the first line of support while escalating to humans when necessary.
This is where the company’s hybrid model becomes important. ChargeMate combines AI with human call center partners, creating an AI-enabled service layer rather than a purely software-only experience.
That is likely the right architecture for messy infrastructure markets. Full automation is attractive, but trust is built by solving the problem. Sometimes that means AI. Sometimes that means a human. The winning system routes intelligently between both.
Where the Market Goes Next
Brad sees EV charging as the beachhead, not the full opportunity.
The larger idea is that AI can become the operating layer for energy infrastructure. Chargers are just one class of distributed physical assets that need monitoring, support, diagnostics, and coordination.
Customers are already asking whether ChargeMate’s AI can help manage other systems, including batteries, building management systems, and broader site-level energy assets.
That points to a bigger future: self-healing infrastructure that can detect problems, communicate with humans, coordinate workflows, and resolve issues before they become expensive failures.
For EV charging, that future cannot arrive fast enough.
The Takeaway
The EV industry has spent years racing to deploy more chargers. That was necessary, but it was not sufficient.
The next phase is reliability.
Drivers do not care whether a charger is technically online. They care whether it works when they pull up. Operators do not just need more stations. They need better uptime, better support, better diagnostics, and better economics.
ChargeMate is betting that AI will become the connective tissue between drivers, chargers, operators, vehicles, and field teams.
That is a sharper thesis than “AI for customer support.” It is AI for physical infrastructure reliability.
And if EVs are going to move from early adopters to the mainstream, that may be one of the most important layers still missing.
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Chapters:
00:01 – Brad Crist, ChargeMate, and the EV Reliability Gap
00:34 – From Utilities to EV Charging Startups
01:16 – The Rivian Road Trip Problem
02:39 – Tesla, Non-Tesla EVs, and Market Fragmentation
04:07 – Why Public Charging Fails
05:55 – ChargeMate’s AI Support Layer
06:18 – Why Incumbents Struggle with Reliability
08:09 – AI-Enabled Support and Call Deflection
09:33 – The First Design Partner Breakthrough
11:16 – The Pivot Away from Consumer Route Planning
13:39 – Why Zendesk and Intercom Are Not Enough
15:38 – Complexity, Protocols, and Charging Standards
16:42 – Autonomous Vehicles and Future Infrastructure
18:11 – Natural Language Interfaces for Energy Assets
19:25 – Early Decisions That Nearly Killed the Company
20:55 – Contrarian Beliefs About EV Infrastructure
21:37 – Enterprise Sales Challenges
22:38 – Starting with Voice First
Transcript
Brian Bell (00:00:57): Hey everyone, welcome back to the Ignite podcast. Today we’re thrilled to have Brad Crist on the mic. He is the co-founder and CEO of Chargemate, an ai platform tackling one of the biggest bottlenecks in EV adoption: unreliable charging infrastructure and broken driver experiences. Prior to Chargemate, Brad spent over a decade in climate tech and helped scale EV charging networks at Volta from hundreds to thousands of stations globally. Thanks for coming on, Brad. Good to see you again would love to get your origin story. What’s your background for the audience?
Brad Crist (00:01:26): Absolutely. So as you introduced us, we spent a lot of time working in the energy industry. I started my career at Accenture with utility clients before moving into EVs and EV charging at startups like Faraday Future, Volta and Springfield. for EV and I was a patient early adopter and early reservation holder of a Rivian which I was excited then when it finally came out to take my partnered friends on road trips thinking I would impress them with this luxury electric car and it seems like every time we’ve I visited a public charger there was some hang up I was downloading a new mobile app to start a charge on a foreign network we were troubleshooting a slow charger reporting damage or wound up in the middle of nowhere and I had been charging electric cars for quite a while but maybe too patient to some of the challenges that exist for the mainstream driver and that road trip really exposed the challenges for us so We focused on solving for the discrepancy between uptime, charging assets look like they’re online, and then the actual experience drivers have is very different and more than 20% of attempts fail. So that’s what we’re after fixing.
Brian Bell (00:02:33): That’s crazy. I mean, one out of five attempts fail. And I love this visceral story. of your brand new shiny Rivian, you know, and like you’re driving around and it’s the R1S, you know, the SUV.
Brad Crist (00:02:45): That’s right.
Brian Bell (00:02:46): So it’s a luxury SUV, right? It’s like a $100,000 car and you pull up to some charging station, you know, you’re down to 20%, 30%. I got to charge and one out of five times that’s not going to work and everybody I think anybody listening who has a non-Tesla anything Neve doesn’t start with the letter T has experienced this problem and even me like I had my first EV was an Audi at the little A3 and Experienced this problem so much and I was so happy to finally get a Tesla. You don’t have that problem but what percentage of EVs out there are non-Teslas now?
Brad Crist (00:03:18): Great question. Tesla has about 40-50% of the market but that’s shrinking. Yeah. And we’ve actually seen the Tesla experience is starting to get worse as they open to non-Tesla vehicles. There’s also something interesting happening where they’re franchising Tesla for third parties. So we’re really curious what that means from a quality perspective. You’ve got a lot of other smaller hosts using Tesla equipment with a lot of other non-Tesla vehicles.
Brian Bell (00:03:44): I’m guessing if you’re a Tesla owner and you pull up and I see a bunch of Rivians parked in all the spots, I’d be pretty mad. Yeah, there’s a little bit of...
Brad Crist (00:03:53): This is ours, like loyalty to the brand. And so there’s some locations that are open to non, like multiple vehicles, others that are Tesla only, which adds a little bit of wrinkle on like, well, where can I visit?
Brian Bell (00:04:05): Yeah. And so what is it about how ChargeMate works? So we get the problem, right? One out of five charging experiences fail initially so that’s a hair on fire problem right for both the ED owner but also the various charging infrastructure providers and then you have the story of like having to download an app every time you stop to charge like a new app a new like my credit card and like oh like Chase now wants to make sure it’s actually my credit card and blah blah blah blah blah so maybe you could talk through like how Chargmate is solving that and yeah some of the facts and figures behind that
Brad Crist (00:04:36): Absolutely. So what we found was contrary to how the media might portray the problem of a lot of physical damage, that really only made up a small segment of the issues. It was really about user error, payment problems, app issues, glitches between between the handshake of the vehicle and the charger and sometimes like occasional faults like in the equipment or loss of power or connectivity. So what we built is first a system that would solve for the driver facing issues that we thought were unaddressed. And this came from our own experience getting stuck at a public charger, spending 10 minutes on hold with a 1-800 number large networks and it reminded us that this is not only a lousy experience for a customer whose first help is a 1-800 number but that there wasn’t really much visibility that the network had either because their call centers were often offshore third parties that were divorced from their operating system so a big part of what we do is using chat and voice agents to handle the customer facing side on the back end integrate into what’s considered like the network operation center or the charge point management system. And a couple ways that then we’ll check the status of the charger. Is this online? Do we see any faults? Are the charger showing available? What are we seeing now in the transaction processing? And that also allows us to take some commands so we can remotely reboot a unit in some cases. We can force like a plug to be unstuck, which can be a tricky issue. So we’re taking on more advanced automation, basically running the asset on the ground through remote commands and AI.
Brian Bell (00:06:11): So this is interesting. So it’s almost like this AI powered SaaS customer service platform, if you will. And you’re kind of solving it in a vertical way for this very particular use case. Why can’t the incumbents just handle this on their own? Like that would be like the main investor question. It’s like, okay, cool. But isn’t that like their job?
Brad Crist (00:06:30): Good question. So there’s a focus right now in the industry of deploying new infrastructure. And we have seen that then operating that making sure it’s reliable and a reliable seamless customer experience is usually a lower priority and some of that came from reliance on grants and trying to win the kind of land grab and plant a flag where you have ownership of the property or lease agreement for a charger in a parking lot, you know, high traffic locations. And what that’s led to then is these teams are really set up to be acquiring new locations, real estate and infrastructure businesses. They’re not really classic So that’s been one challenge is like even if they have the software team, there’s a lot of existing infrastructure to roll out to maintain. The other side of that is like we’ve seen some companies will build their own AI tools, but They tend to be a little bit narrowly focused on just what one operator sees. Whereas what we’ve observed is there might be issues between vehicles and chargers that that single operator hasn’t even seen yet. So there’s an advantage of for us being able are able to set hardware and software agnostic and start to really see the anomalies that exist between different makes models and and asset types. Then the other thing I’d say is like most companies are not in the business of like running customer experience or a call center function. These are typically set up to be kind of BPO. So now we’re coming in and combining our AI with a human call center partner from Ford, Percepta, where we can actually add the AI and human service end to end. So starting to look more of like an AI enabled BPO option as well.
Brian Bell (00:08:10): Very common in business now, especially over the last few years since ChatGPT came out, is these kind of hybrid service models where it’s almost like all businesses now are kind of these AI-enabled agency business, agent businesses that it’s like, hey, why... I have a business and I have this like repeatable problem and I would typically hire somebody and some call center and wherever to deal with this and now you can onshore a lot of that through AI and deflect I mean what’s your deflection rate on like the human deflection rate I guess would be the question
Brad Crist (00:08:40): From calls, we’ve seen about 50 to 70% resolved by the AI. And that is higher when we can also kind of manage some of the policies. But in cases where, hey, any refund should escalate to human or how do we handle sort of the customer’s choice of channel.
Brian Bell (00:08:58): And AI is as bad as it’s ever going to be. And it gets, you know, 10x better, 5x better, depending on, you know, the intelligence per token per unit of whatever. Right. Every year. And so that number is just going to creep up and up and up and up over time.
Brad Crist (00:09:11): What was that first like aha moment?
Brian Bell (00:09:12): Like we got something. I know you come from industry, right? So you knew the problem was hair on fire. But like, what was that turning point in ChargeMates history where you’re like, wow, this is going to work?
Brad Crist (00:09:21): Great question. I think the first feeling of like relief was we had gone through a bunch of interviews with Charge Executives.
Brian Bell (00:09:28): It is relief, isn’t it?
Brad Crist (00:09:29): it is yeah the first the first like contract was like I cried I was like oh my gosh this is like got a contract is real right exactly so so we were actually working with a large publicly traded network who’s a design partner of ours and now we’re finally talking scale so I can’t quite mention yet who they are but I think hearing enough people say like light up or okay I get it you’re gonna kind of fill this gap that we haven’t even been able to measure or our team is kind of chasing their tail running yeah
Brian Bell (00:09:57): we’re spending so many like they’re like what percentage of their revenue are they spending on customer service I mean it’s got to be significant right super high
Brad Crist (00:10:05): when we look at just OpEx it’s like 80 to 90 percent for some of these larger operators
Brian Bell (00:10:10): That’s crazy and that that flows through and the cost of kilowatt hour right they have to build that into the cost right and you know they can’t just charge you whatever they’re getting off the grid they have to like throw in a bunch of margin to pay for all this customer service and maintenance and so you’re you’re basically taking a huge percentage and contributing back gross margin saving the money saving them time solving a problem creating better customer experiences so obvious thank
Brad Crist (00:10:34): you thank you we think it’s inevitable too
Brian Bell (00:10:36): Yeah, that’s why we invested, if anyone’s wondering. So what did you get wrong in your early versions that you had to pivot away from or reiterate on?
Brad Crist (00:10:45): So the initial vision that we started working on part-time was ways for EV drivers. so partly inspired by the road trip experience you should be able to find an available working charger and how great would it be if that could co-locate with something desirable coffee shop clean bathroom you know you there’s so many options of places is to stop with gas stations where you don’t have the same kind of convenience yet with charging. And what we found there was like, while it’s an important problem of navigating and making the like discovering and kind of education easier, there was really hard I think replacing a Google Maps seeing some way that we would be an endpoint you know in their data set since they have such massive distribution and then realizing that the path to like have any kind of data in the vehicle was also a challenge as a third party like the Auto companies are very guarded about that kind of relationship with their driver and they should be. But what we didn’t see was anyone really helping the driver that feels stranded at this charger that the auto company doesn’t control, that the charging network is dealing with so many fragmented vendors in their own ecosystem as well. Our first chat based product. So we piloted with just putting rogue QR code stickers that fed us some survey data. And then we said, what if we could just start helping people generically with advice? Could we start to get specific to like the equipment? and we needed to really know something about the hardware and the asset. And you’re really only effective if you can also see the status of that charger. So I think the early prototypes were very good at giving us like what are the issues people face, but it was taking down the problem. It wasn’t necessarily resolving it. We might deflect or learn, which was really valuable insights, but there’s only so much you could do without really seeing what is chargers this user in front of. What are we seeing in terms of its status? Do we have some ability to write commands or update a work order log? So I think that was the big thing is realizing this is much more than just a chat bot. This has to be a deeply integrated system.
Brian Bell (00:12:50): Let’s talk about, you know, why doesn’t, you know, an existing, I don’t know, like Zendesk or Intercom or something like that combined with some AI stuff, just replicate this quickly and easily.
Brad Crist (00:13:01): Yeah, you know, it’s something we thought a lot about. And I think Intercom is focused on a more kind of B2B commerce focus on Desk obviously has their support platform. No one’s really knowledgeable of the systems, the intricacies of like integrating software with with firmware and hardware. To give you an idea, like one of our clients has 45 hardware products that they have to manage, different SKUs. One of those SKUs has 722 unique error codes. So really challenging for anyone human to grapple with. but a good fit for AI that’s thoughtfully designed and I think that’s the other thing is like some people will decide to build on their own right this is kind of a big question of build or buy and now that AI and software is easy and plentiful but our bet is that you know it is still expensive to build quality products and maintain them. And so as new vehicles are getting the market, as there’s new hardware and new systems, that’s exactly what we’re keeping up with. And so we see some network effects of like the more vehicles, the more hardware, the more resolution rates, that are using the more failure modes we can solve, the higher the resolution rate, the more likely we’ll be able to serve customers. So yeah, I think it’s a bet that diversity of data, the kind of need to integrate deeply of the systems and workflows. And the other component is like Like we’ve been thoughtful about tying into human teams. I mentioned the call center partner also now working with some field service folks around automating work orders, kind of matching driver feedback against backend telemetry. And I think that human reinforcement loop is really what drives a moat as well for anyone that’s like working in an AI, a vertical AI business.
Brian Bell (00:14:35): Yeah, and I think the EV charging system and infrastructure is as simple as it’s ever going to be right now. We’re just going to have more vehicles, more protocols, more vendors. I mean, maybe over time it kind of, you got, you know, some of the big ones, but yeah, there’s going to be a complexity going forward that ChargeMate’s uniquely suited to kind of handle, right? I hear that the industry’s moving over to the Tesla version of plugs. Like Rivian’s already starting to do this and maybe Lucid as well. They are.
Brad Crist (00:15:03): Yeah. Yeah.
Brian Bell (00:15:04): I had one I had one of those adapters I have one in my Tesla as well just in case I’m somewhere where I can’t use the Tesla charger and I’m very familiar with having to use that so what are you excited about in the future you know look out a year five years ten years kind of taken three guys the industry
Brad Crist (00:15:18): She’s really excited about autonomous cars. I think that’s something that that those of us have been working in energy and electric vehicles realized quickly is that this ushers in, you know, connected vehicles, autonomy and sharing. So I think we’re going to see electric And so that’s exciting from just a big industry tech shift perspective. It’s safer, but it also means tremendous growth in infrastructure. and I don’t think we’re at a point yet where these are going to be robotically charged there’s still very much a coordination problem with humans and depots but there’s also a lot of speculation about like new wireless charging technology much
Brian Bell (00:16:01): the way we can kind of charge a cell phone you drive over the plane and wirelessly exactly charges yeah what was that Israeli was it Israeli company Better Place or what was it called that had the swappable battery packs and raised like 500 million dollars yeah I remember that
Brad Crist (00:16:19): There’s a few few battery swapping technologies that have took off in China but we
Brian Bell (00:16:24): haven’t had the scale really here in North America yeah we’re becoming a Europe in a way in some cases what else what else over the next five or ten years are you excited about
Brad Crist (00:16:34): Yeah I think our bet is that humans are going to interact with machines increasingly through natural language right through chat and voice and so I think our big picture view is that physical infrastructure will be self healing will be capable of communicating in a more natural And I think energy has historically felt like something we don’t think about, or it’s confusing, and being able to make that like a really simple, understandable concept for people. I think what I’m excited about, at least in our industry, is that these charging operators now under huge pressure to be profitable and as you mentioned they’re selling a commodity with like a low margin electricity so that is a lean team that’s like automated and AI driven and so we really are part of helping companies move to profitable with new automated tools so I think there’s kind of both ways what’s happening within these companies to manage lots of assets with a smaller, leaner team and prove that that can be a profitable, thriving business. And there’s kind of the broader just like interaction with physical infrastructure and AI that gets us excited.
Brian Bell (00:17:36): That’s awesome. Well, let’s wrap up with some wrap-up questions. What’s a decision early on that almost killed the company? Hmm, that’s a great question.
Brad Crist (00:17:44): I was pretty close to building out like this kind of Waze-like route planning feature with... some fairly expensive like contractors. And I realized quickly like, no, this is not something I can do as a single founder. Like I need a partner that is equally invested. So I was really grateful to meet Brian Lang, my CTO, who has a background in natural language processing. and had a really strong interest in energy and had worked in automotive as well. So one was finding a great co-founder, but I think the other was finding a paying customer, like a design partner pretty quickly. And the move from a B2C product where we felt like we’re going to spend tens of thousands of dollars to build and acquire users with a hope of monetizing later, instead going B2B and solving for a pain that The operators paying $10 to $15 a call. Let’s start there and then find all the other kind of related costs in operations, support, maintenance that now we can expand to. So I think finding the right painful wedge and building from there was a good learning.
Brian Bell (00:18:44): What’s a belief you have about EV infrastructure that most people would disagree with?
Brad Crist (00:18:49): I mean this is becoming clearer now but like that there’s it can it can be really simple and easy for folks that can charge at home that have public charging and so I have to be careful how much I point out hey here’s problems with charging because I don’t want to scare my own friends and family away right but like there’s a some growing pains so I think that’s something that’s constantly on my mind what’s the
Brian Bell (00:19:09): single hardest lesson you’ve learned selling into this market
Brad Crist (00:19:13): Candidly, I think sales cycles are challenging with larger enterprises and like going to some of the larger operators where we knew we would have scale and be able to make an impact, we quickly realized was slower to get into a roadmap to feel like this would be a scalable deployment. So that meant for us like proof points with smaller enterprises, smaller growing charging companies that were less well known. But it also meant like making the product really easy to get started, finding easier ways to integrate with backend systems, and then making it easy to scale. Now that we are live with voice, we can take on the call center and that’s sort of the first interaction point with the end user. And then it makes some of the scale up smoother for us.
Brian Bell (00:19:55): So if you had to start over today, what would you do differently in the first six months?
Brad Crist (00:20:00): I think we would and this was a challenge with like the AI catching up but like we made the decision to work with chat as an interaction point but it’s really voice and like the kind of natural disposition to like pick up a phone and call and so maybe that would have been where we started first was like focus on kind of the like verbal interaction yeah I think that’s probably the right answer makes sense I
Brian Bell (00:20:22): mean if you think about the user experience too working your way back from how are people going to react when the charging things not working they’re not going to just sit there in their car and chat they’re gonna call they’re like what is going on what’s a what’s a metric uh you pay attention to that’s kind of the most important for your business so
Brad Crist (00:20:38): resolution rate like how many issues do we fix without following a human the you know natural engagement rate of like how are people interacting with AI relative to to like a human call center and I think contrary to popular belief like we don’t just want to to talk to a human in a customer technical support capability. We want to solve our problem. So we’ve seen engagement rates sometimes two or three times higher with the automated channels compared to waiting for a human operator, which has been a good insight. People do engage, especially if it’s effective. So yeah, the engagement resolution rate. And then we’re really focused on proving, hey, this is recovering lost revenue. So for one of our clients, we saw lift in their success rate by about five and a half percent. When we extrapolate that across like a larger network at scale, that’s a couple million dollars in margin, which for these companies is really meaningful. So now just like finding the right opportunity to measure that at scale and then also measure improvement and satisfaction retention for the driver.
Brian Bell (00:21:36): Yeah, that makes sense. So if reliability, if you solve reliability and charging, right, or at least that customer service is taken care of, where is the value shift next? Where should investor be investing is another way of asking that question.
Brad Crist (00:21:49): Yeah, I think there’s a lot to automate the enterprise, like beyond these kind of our vertical wedges support, we’re now seeing opportunities to get into automating sales, installation, commissioning, as well as some of the operations and maintenance. So I think like looking at broader functions and capabilities that that can be automated where AI moves next beyond like call centers and customer support being the low hanging fruit and I think in our industry seeing AI as this sort of like integration layer operating layer that can help bridge gaps between disparate systems and what does that look like now when you’re interacting with lots of different assets that’s that’s pretty interesting to us nice any final thoughts on
Brian Bell (00:22:30): charge mate before I let you go
Brad Crist (00:22:32): Yeah, thank you so much for your support from Team Ignite Ventures. We’re still raising, so would love the opportunity to meet other investors. I think, you know, we’ve talked a lot about EV charging, but we see this as a larger opportunity. We have clients that would ask if our AI can also manage not just chargers but health of the network the battery or building management system other on-site assets so we see this as the first kind of wedge and first beachhead segment by a much larger opportunity for AI to provide a better customer experience and reliability for all sorts of energy assets yeah and where
Brian Bell (00:23:07): Where can folks interested in both customers and investors find you online?
Brad Crist (00:23:11): Were at chargemate.ai and on LinkedIn Bradford Crist
Brian Bell (00:23:16): All right Brad well thanks so muchfor coming on. Really enjoyed it.
Brad Crist (00:23:22): Thanks, Brian.
