Otovo ASA (OTOVO) Earnings Call Transcript & Summary

[Audio Gap] Director of Technology, respectively. And we also have a cohost today, Rohit Kulkarni. He runs our Internet team. And this is going to be a discussion about how Otovo has found ways to really reduce their dependencies and usage of SaaS software. And as a reminder, this is pretty close into Q2 earnings season, they're in a quiet period technically. And so we'll not talk about their financials. They announced on their Q1 call, that they are exploring a potentially U.S. listing. We can't talk through that. So let's just focus the discussion on how they are changing things with their deep usage of AI. With that, Note that this webinar is live being recorded. Here are some of my disclosures, really to have some as well. So I'm going to pause and let him show his screen and then we'll jump over to John and Jack with their deck.

Thank you, Phil, while I pull up my PowerPoint. Welcome Otovo team, looking forward to seeing what you have done with all the AI tokens that you have spent over the last 6 to 9 months and how that's changing the business that you do? And again, would be a proof point of what from the tech investor standpoint, what we see as extremely powerful tailwinds and headwinds affecting more than 200 companies in my comp sheet. So this webinar is live and being recorded, and these are the mandatory disclosures. One Mississippi to Mr. [indiscernible] Thank you. With that, thank you again for doing this. Thank you, John and Jack, I can't make it, who is the son, whos the father from the pictures here, but feel free to jump in. And again, looking forward to the discussion.

Thank you, Rafi. All right. Well, let's get started. We can put -- we've got a slide deck, and then we'll go into Endurance here as soon as at the right time here. So we have our own disclaimers. So I think everything has been disclaimed at this point in time, so we can go to the first slide here. First of all, My name is John Berger. I'm CEO of Otovo, Jack is Head of Software and AI for us at Otovo has done really amazing things. And what I want to get and thought that this would be something very interesting to our shareholders, both the United States, Europe, global. But it's really exciting. It's regardless of industry, no matter what it is, and we'll get into and talk a little bit about Otovo before I turn it over to Jack. But I hear constantly about artificial intelligence. Is it real? How do we do it? Is it really just using a ChatGPT or is it something more than that? And of course, we've all heard about SaaS apocalypse, what's happening with the software, what is real, what is not. We've seen the software companies, including this week, defend themselves and say, no. We also saw IBM just last week, have its worst trading day in its entire history because of concerns around AI and what we're about to show you. So exciting. I think there's a lot of implications that Rohit set in the world. And this is regardless of solar, generators, power, whatever it is. But I think you're going to get a real treat here today. So first of all, on the slide, let's go through an Endurance, if you look at what Endurance is and what it means to us, just the highlights here. We have one operating system, and then we have one confirmed margin engine and then it's repeatable as allowing repeatable M&A. So that's our highlights. This is what we're going to tell you is the summations about why Endurance is important to Otovo. But let's -- what is Otovo. Let's take a look at that. Otovo is essentially an AI-enabled service company roll-up, starting with a platform company of Otovo that was in the solar space was doing origination. We shut that down. Now we're moving and been buying companies at a breakneck pace, 8 acquisitions. We just closed SST in fact, Jack's in that Sun system technologies. Jackson in the Northeast United States, doing the integration. It is within 3 weeks as we close that, I think, July 1 or 2nd Jack. And we are closing on, as we announced previously, we're working on closing on green panel acquisition really bolster our European operations tremendously. So we're looking forward to that. And as we move towards being profitable, real exciting in terms of our plans and what we're doing. But we are really, really executing. Very happy and looking forward to the earnings call. I've got to tell you that. I'll leave it there. So when you look at our company, we have over $1.8 million. This does not count by the way, SST and Green Panel. We have 30,000 customers. These are Q1 numbers. These are all sanitized. So you can imagine this number is larger as we report. And then we see just $5 million in cost savings, which is tremendous. But that's not including SSD. It's not including Green pounds, not including on a forward basis. So this is an annualized number. It would be repeatable every single year, and it's growing materially. And so we're going to talk about that as we get into what the benefits of Endurance are. We did this basically with a very small amount of people. In fact, majority of these ads, if not almost all of them next to Jack was really since May. And so we've done this with very small numbers. You've heard a lot about that AI. We can tell you that, that's real. Again, what we're going to show you is we're going to show you reality. We're going to show you instead of talking about AI and talking about buzzwords, we're going to show you what we've done, and we'll show you the numbers. We've talked about this on the Q1 call, but we're going to be able to show even more real cold hard cash and how much has been saved. When you look at -- in terms of what Otovo is in the next slide here. Let's start first, how do we make money? We make money through service. We are a service company. What does that mean? We're rolling trucks and fixing and tech, and we're fixing generators, solar, batteries, EV chargers, and load managers. We're doing that in Europe, United States and soon to be in the Middle East as well. We have the -- we are the largest behind the meter as soon as we close Green Panel. We anticipate that behind-the-meter power company or service company in the world. So we service both residential and commercial. We make money through memberships signing up for service and then paying us on a per month basis. Repairs, fixing solar systems, batteries, generators, make money on that. Upgrade sales, so think batteries and so forth, retail power and BPP, so that's aggregating power and selling it back in the wholesale system where appropriate, which is all of Europe. Right now, we're doing that in Texas. So that's how we make money. What is Otovo crossroads here? It's 3 things: power. And when I look at power, you look at the space and for 2 different reasons, both Europe and the United States, we all have to -- we all know this has gone through a tremendous downturn in solar. So there's a lot of good service companies available out there at their subscale but they're good -- a very, very good valuations. And so we've been taking advantage of that. It's gone much better than we thought. We've had been very acquisitive, as I said earlier, post even the merger of Otovo, we've done 8 acquisitions, and we were on a tear. We have a big backlog. These are profitable businesses that were coming in and further cutting and yes, Endurance and AI is a big part of those cost cuts and keeping in pushing that operating cost at overhead costs lower. The second thing is service. Service has been terrible in this industry. There's reasons why a lot of people assume that an installer is the same as a service company that built scale businesses in both areas, and I will tell you, installers are good, and it's a project construction business measured in weeks and months. And service is measured in hours and days, and that's a logistics business. So it's 2 very different businesses. And also, there's a lot of bankruptcies that have been happening out there, particularly in the contractor space. And that's left a lot of manufacturers of inverters, batteries, generators, stranded with customers that are looking for service and looking to get their power back on and that has been exacerbated by the huge build-out that we've seen over the last 10-plus years. It's now the chickens, so to speak, are coming home to roost. Somebody is going to go out there and service these customers, both residential and commercial, and that's Otovo. So we're seeing a lot of demand from a lot of B2B customers to come in from the service. Last and that's the purpose of our call today, AI. [indiscernible] be honest, as always, is I fell into this. It's just the right timing. But when you look at a tremendous amount of our costs as an industry, it's actually SaaS software. It's coming in and having to spend the money. And then when you look at the back office, we're talking dispatcher, schedulers, marketing, finance procurement, all of this is a lot of money and a lot of money goes against affordability in solar and behind-the-meter generation, particularly distributed that doesn't have the scale as front of the meter does. This technology, AI and what we're doing with it, so exciting, we're attacking that cost, and we're doing it. We're not going to talk about doing it. We've done it, and we're going to show you that here in just a minute. So as I'll turn the call over to Jack. Jack, I'll say, yes, there is a relationship here as everybody, I think, understands and sees very proud what he's been able to do I'm too old for the technology, really understand I can get by. But you really need to be, I think, in your 20s to really and maybe even younger to really be a [indiscernible] at this and Jack certainly is done a tremendous and very exciting. I haven't seen anything like this out there, period in the economy. So I think this is -- like I said, it's a real treat. And I'll turn the call over to Jack and walk you through Endurance and how -- and what it means for Otovo. Jack?

Hello, everyone. Thank you for coming today. So here what we built out in Otovo is the Endurance Operating System. So what does that mean on a bunch of different cost basis this year. So we have marketing, sales, supply chain operations, all brought into one central operating system for Otovo. When we started out making Endurance the idea and the impetus behind it was not necessarily to make it for AI and just shove AI into everything. In fact, as a company, we do -- obviously, we do a lot of AI now but we wanted to make the best CRM as a basis, of course, with AI and using a lot less developers than before, but not using AI properly in the operating system. Now I believe that we've done that. And over the past few weeks, we've now injected AI deeply into each aspect of these 4 pillars as well. So what you'll end up seeing with the Endurance platform is you're going to have lower acquisition costs, much higher throughput of work orders and appointments that we can send our technicians out on much faster M&A integration. Our average integration time is 3 weeks and massive revenue growth. Just that is independent of our overhead growth. So as we grow our revenue, usually with service businesses, you have a significant problem with the back office increasingly exponentially growing as you do that. And that's not so for Endurance. So today, when we do our live demo, we're going to show off the marketing system, we have a full marketing e-mail, SMS, CSAT CMS system, everything like that, that you would normally pay for or break off into a separate system is all into Endurance. Same thing with sales, commission tracking, pulling up AI sentiment, site reports, everything like that, supply chain, the inventory management and taking requests from partners all the way through the process and automatically ordering these parts all the way through. And then, of course, operations on automatic scheduling and load balancing our technicians in order to increase our margins on those.

Before you go to the output, can you say as of first of December 2025, if you have to run your business, just walk through like people who don't understand how your business works, maybe just kind of just, okay, you get an order, you do this, you do that, you do that. And like what is the time? I just want to get a good quantification of how much time are you saving and how much money are you saving before and after, if you can just pinpoint that.

Yes. So I'll go over this more when I go through the proper platform itself. But the idea here is let's just take SST as we're -- I'm here in New Jersey right now and integrating them into the system, what do they do when they integrate...

Just to be clear, SST is not solid state transformer. So...

Sun system technologies, just for everybody else on the call. So that's one of our recent acquisitions. What they were doing on a significant amount of overhead basis was even if they're handed the lead, no marketing, no nothing, just B2B. They're taking that lead their input, they're getting in their inbox. They e-mail it and they go manually point their CRM system. Okay. Well, now they've got to get somebody to go call them and they call them on a personal cell phone and then they're like, okay, well, let me just put it like increment each time I call them. And then the same person has to call them 3 times because they require 3 contact attempts. But you don't know what was said in the previous call. So you just logged that you called them. It's not in a system. And of course, you can get a SaaS to get it all in your system, then your cost increase once again. So -- and then everything is a 2 monitor system. You got Google Maps in one and you got your open jobs in the other, just praying and hoping you set up the correct route for your like 10 technicians in the area. It's very, very difficult. It's a very, very difficult math problem in general, which is what we've optimized entirely into Endurance. And there's a lot more to it, and I'll show you as we get in here. But that problem, that huge back-office problem following up the customer, sending them the site report saying, hey, this is what we did on site, making sure that they've collected payment, all of that is what -- the SaaS in order to even complete those tasks is already going to be about a 10% EBIT margin. And then on top of the labor savings, we will do much more than 20%, 30%. And margin impact. But we're going to -- we're bringing that more in as we're bringing more AI into the system. So what we've seen is about $2.3 million in SaaS and then at least $1.7 million in SaaS support that we've cut on an annualized basis over the past year. That SaaS support is probably underdone but the old Otovo Europe had already undergone massive cuts before we took them on. So we will -- in reality, the engineering team that built Otovo Cloud, which is their old legacy system was nearing 100 people at the peak in order to actually develop the system. They were down to just less than 10 once we acquired them due to cuts, but that was not a build new features team. That was a maintenance team. And then additional $1 million so far in staffing. So that's cutting out dispatchers, cutting out office space for those dispatchers cutting out a variety of different back-office people that are having to do accounting work. We're doing a lot of integration with our NetSuite and ramp providers that is done much, much quicker than we would have been able to do before. And much...

Okay. Fantastic. And also like maybe a later question, maybe John can... So things that you are doing better, faster, cheaper, much better, like that's one bucket. And I would love to towards the end of this call, I get your feeling of things that you couldn't dream of doing. And now you're able to do, like, for example, you couldn't sit on your phone and get a car and like 2 minutes because now you have Uber there, like 10 years ago, you couldn't dream of that, like you now have 5 million songs in Spotify, for example, like things of that nature that you couldn't dream off a year back, John, like say, by the way, but now we have this technology and now I can do it. Maybe I can acquire 30 companies in a day like whatever that thing could be. I would love to think of like you have 30 minutes to think of be as creative as possible as a public company CEO, and I don't, as a sell-side analyst asking that as it's not a good question. But think of that. Like, I want you to stretch your imagination and think now that you know what this technology is capable of doing. If I can do that, that would be nice and cool. So anyway a demo....

Yes. I've got an example demo for you all set up on exactly that. So here, we have the SaaS graveyard. We've cut a total of about 56 to 100.

Can you go back to the prior slide sorry. Just to put a finer point on the right side here, guys, the margins are going from 15% to 25%. So that's a 10% -- 1,000 basis point improvement right? That's kind of what this $5 million of cost savings translates to. But then there's potentially more beyond that as well. So I just want to make sure that's very well under sorry, Jeff.

That's a good point, Phil. And this is what we've realized. We do see -- you see some other firms out there, General Catalyst, Thrive founders, doing a roll-up strategy in their own service verticals, and they're saying they're seeing at least 10 on just the SaaS alone and then the additional 20 to 30, we can verify that, at least for what we've seen in these companies, we're stripping out at least 10% of the cost, and that goes directly to the bottom line. Yes. Endurance license is $0 for us. So here's our SaaS graveyard. I got some fun Otovo colors in here. This is just a subset that we've put on here. But you can see some heavy hitters here, including AWS, which is kind of interesting. Usually, even people that build their own systems, still rely on an AWS to host the underlying the underlying operating system itself. But here at Otovo, we've actually built our own server architecture by hand. So we actually have our own servers. We own our infrastructure. We have multi-region failover. We have oversight and monitoring over the whole system. And we have an always on team because we're a global company, but we also have an always on team in the form of our AI engineering that we've also built out behind the scenes. So we have an always-on AI engineer as well. I'm going to switch over to Endurance proper now, I believe.

So this is the real system here is what you built. What I would also say is just from my perspective as CEO and goes to a little bit of what Ravi asked me to think about, this is unfathomable to me and I think many other CEOs have seen this about how much has been done. This would take -- first of all, we would again procure to the tune of tens of millions of dollars a year, these software pieces. You saw the graveyard and to build that software that they then sold to us for tens of millions of dollars a year, then you're spending more CapEx like several -- couple of hundred million dollars building out what you want for your business. This is astounding. And the speed at which you can change is just mind blowing. And it's because you own the entire stack and you're pulling it in as you keep going because you can't. The technology is so powerful and you own your entire stack, there's a lot you can do with it. But wait, we'll get into here later about the agents, the Agentic AI, creating the agents. This is their own playground. You don't have to go in and have a lot of blockers because you have all this SaaS stack of 50 to 100 SaaS companies. This is not just a cost play, but this is also an enablement of becoming a truly Agentic AI company in whatever your business is. I can turn walk through.

Yes, so this is Endurance. If you're wondering what the -- the guy in the boat is autos are kind of like company mass and all of our marketing material and things like that. And Endurance was named after Shackleton boat, which if you're not familiar, Shackleton, was an inventor and his -- 1 of his very, very famous boats was the in -- and the idea was to kind of enter any challenge, both in the service industry and through the changes with AI. So here, I'm going to show you probably honestly kind of a random one that I ended up pulling up for this system, but I wanted to show the power of Endurance. So -- we're a global company. We have a lot of different languages. We have a lot of different resources across the globe that is very, very hard to manage. And you'll see pretty clearly here where Endurance becomes really, really powerful in order to be able to manage all of that. First of all, everything in here is translatable. So we can -- so I can work on this despite not knowing the language. There's a lot of languages in Europe. And I don't know most of them. So this is immediately extremely helpful here. So the reason I picked this case for this customer was this is a customer that e-mailed us saying that they had a battery issue from one of our installs. And so I wanted to pull up here. Iris is our AI assistant that we've just deployed recently in the past few weeks. Iris found an e-mail chain from FOX ESS, which is a battery and inverter manufacturer. That said, this client said, "Hey, I'm having a problem. My battery is not working, it's saying it's not charging correctly, anything like that. This is -- so Iris is handling this case right here. And it's handling it in lockstep with our human assistance. So [indiscernible] handle it and then hand it off and then take it back over. very seamlessly, all the way through the system. So in this case, I was particularly like this because FOX ESS e-mailed us saying, "Hey, by the way, this person -- their battery is approved. But they didn't really tell us exactly who it was, but they did tell us the serial number. And they did say, "Hey, this is the person that's -- this is the [indiscernible] number that's approved for a free replacement. Iris went into the system was trying to find out who that is applied to found the install pictures from this person's install on the project that we installed the battery for them and found the serial numbers off the install pictures, linked it back over to this case and said, "Oh, hey, Mr. Customer, FOX ESS has approved this for you. And so you can see the translation right here. The manufacturers decided to replace the main unit, the address provider will be used to ship the replacement module. Once it's been delivered, it will be possible to term the next service steps. That is a perfect example of Iris and our AI inside the system doing a great job in handling the customer's query. This all happens within 5 minutes, which is extremely difficult to do this. This is a huge huge problem in the service industry, being able to respond on time and promptly to these customers, especially as we get new information like this, that is quite pressing to the customer. The customer has a real issue here. So I wanted to highlight that at first, but also show you kind of all the different systems that we have in Endurance that kind of like compound upon each other. So as you saw before, I'm actually going to switch from out of our EU system into our U.S. system here just quickly, you can see all of our monitoring alerts coming into the dashboard as we see as you can see, quite a few of these systems are in active failure. Now all of these are our customers. We have purchased lists and different things like that, that allow us to see a lot of different -- from old bankrupt companies and acquisitions and things like that, that allow us to see quite a lot of monitoring alerts and act on them for these customers and we brought that all into our system here, and that automatically brings that into our lead intake for the system. So as we're going through here, we have all the calls texting e-mails. We have the dialer system that in order for you to dial out, we have our quote system, being able to quote with a bunch of different items going through the system as we're intaking these. Something I want to show off here as well. You'll see we are in taking these work orders from our B2B partners and other things like that and actually quoting everything with AI. Now this isn't -- this is not a simple process by any means. Quoting in general, in the service industry is extremely difficult in large part because it is effectively a fleet get the exact type of conduit, it needs to be electrical resistant, whatever else it is. It's extremely difficult. And what we found is that we have after only 2-week trial period on the system. We've had about a 95% exact match rate with our best estimator at our team. So now we are going to start taking these work orders all the way through the process. and immediately scheduling them for the customer because we know how much they're going to cost for the customer, for the B2B customer or the B2C customer immediately. So you'll see here quote revisions and anything that AI is built on [ here ]. So we can -- and it also brings in the parts required and then we'll actually bring the path all the way through. So as you can see here, the AI has reserved these parts required for the system. Here's our OT numbers, which is just our Otovo inventory numbers. And that is going to bring this copper wire, this EMT fittings, all of this directly into our procurement system and actually send out a request for quote from one of our partners that we've designated are available for these products immediately into our inventory system. So you can see how this kind of like Domino's vary very quickly in terms of getting everything done...

An extremely comprehensive system that's custom created and fulfills a lot of your business workflows and ties together a lot of disparate data streams and workflows as such. I guess maybe just 30 seconds or a minute overview on how you did this in terms of kind of the technologies you used kind of any white coding things that you used or anything like that?

Yes. So here at Otovo, we largely build all of our own agent infrastructure. So we have our own autonomous AI agents that work off of internal and customer requests. So if we have an issue on any different system, we have an autonomous system that will pick it up. We call it Nessy after Nessy the lackness Monster, just the name is just because it's fun. But we obviously use codecs and anthorapic models frequently across the system to build this out, but a lot of it is we really, really love building our own agent loops. We have when you look at cursor or any of these other companies, they have one main agent loop design. They said, "Okay, hey, this is -- we're going to optimize this for this task, it's going to be for coding, it's going to be really good at coating. Here at Otovo, we have about 11 to 18 different ones for each different task. So we have a separate version of Iris for e-mails, for texting, for building out these AI estimates, anything like that. This is mainly for token efficiency and performance. So we get very, very low costs. The month of July has seen us use about $4,500 in total of AI usage costs across the entire company, both Europe and the U.S. on the system. So you're going to see that we've really done a very good job at being AI efficient as well, while also building out the system with codecs within therapic models and things like that.

And what was your peak spend, like you said, 4,500 of run rate. What is your peak spend while creating the system?

So we -- in the month of May, we actually had about $16,000 worth of spend. We've now done more with AI with less spend by just tuning in our AI systems. So that's where you see a lot of companies now overspending on AI, and it's very easy to overspend on AI. But here at Otovo, we make sure that we don't. And we're very, very intentional about making sure that we don't overspend and that's not because we [indiscernible] and we just use less. We use more. We just are very, very smart about how we build our agent loops and how we build our agent systems.

What's the average spend that you expect this year to be on a per month basis?

I expect it to be less than [indiscernible]

So staffing on what Jack fully loaded, everything else, total, total tokens, everything. Anything else that we're spending, which is basically a lot of it's pretty much all of its ours right outside branch, striking NetSuite. That's about $1 million a year total. Total, total. So Jack, you want to go to the dashboard and just keep it there and to show the different dashboard things. Some time but as we answer your question.

Yes. From a -- how can you -- can you confirm or comment on quality, right? Like with speed, a lot of times, it's messy, there bugs, there mistakes, there's just handoffs that are not right between agents or something. So how do you guys ensure the quality of the software is as good or maybe even better than what the incumbent solutions were.

Yes. So here's one of our dashboards that we do actually kind of confirm the ability to do this. So you'll see this is our kind of like Irish management dashboard. And this is what we're doing to reduce handoffs throughout the system and also manage any errors or anything like that throughout the platform. So we have an independent rating AI rating this system in order to like get the star rating effectively up. As you can see, we're really, really reducing our handoffs even throughout this week. As we design the system more and more through this. Of course, no response is not necessarily a bad thing, right? Sometimes people text us a thumbs up or yes, thank you or something like that. So we're starting to get a very significant portion of our e-mails and texts completed with Iris. So we have 24 of these types of dashboards. As you can see on the main system that we consistently ensure quality. So each one of these is we can see the reply, we can see why we didn't reply the star rating of each -- in every single one of these systems here. So I'm constantly in this system, making sure that we can make sure that we have great customer experience. We filter out different SPAM threads and things like that in order to not flood our humans, and we use AI to do that. So it's not like you don't have as many false positives on this system. So quite a lot of -- big companies like that will get quite a lot of unsolicited promotions or different things like that, that we otherwise don't want.

Phil, from the CEO's perspective, my history and my experience has been you have like a big quote tool goes down or big customer service because some SaaS company decided to change something and it didn't quite fit with another SaaS company somewhere in the STACK and you're sitting there trying to run around and figure out what's going on. Here you just go in, you fix it. And the AI endurance in Nessy is constantly looking for faults and then fixing them. So the RSI and that's recursive system improvement that you talked -- that's been in theory. We've been doing it since last fall. And as recently as 60 days ago, basically 5% of the issues that tickets that are put in or faults within the software were found installed by Nessy. Now I think, Jack, that's with the new models, that's approaching 85%. So that kind of change is -- and when you look at the possibilities here, the speed at which you can fix any problems is just -- I mean, I'm still not used to it, and it's unbelievable. So the quality is really, really high.

Yes. Interesting. There are some questions here. First one here, can you elaborate on your qualifications for leading the AI implementation Jack, what experience or expertise are you bringing to the role? Or is this -- or is the approach primarily based on rapidly building AI-powered solutions without a deeper implementation strategy. And then this guy continues. The whole solution looks vibe coated. And then he continues how large, let's see, can Jack talk about its qualifications and why did he get the position?

Yes, absolutely. So I was very, very early on to AI. I was working with OpenAI on a research review called the GPT-3 back before ChatGPT was even a thing. So I've been working with OpenAI and AI long before anybody else was back when the system was kind of not really a thing and even...

What year was that year rougly Jack?

And that was 2022. So began to use that work that primarily my work long before anybody else really did and then even started to use ChatGPT in ways that people really didn't use it at the time, long for anybody else was doing it. So using and developing kind of early versions of Cursor back before it was really a thing that people did. Cursor used to be an e-mail writing assistant, if anyone knew that. Now it's a coding assistant. But -- so honestly, I was just really early. And as for like experience in general, I have about as many much experience with AI coding as anybody else will have long, long, long before anybody else was really into the system. Now on the saying, "Oh, yes, it's vibe coated. Okay. Yes, we got a lot with AI, but it works. The only thing that matters on any part of the system is, do I get a technician out to that customer? Is that customer happy? That's all that matters. That's all we had a too care about. And that's all anyone else should care about, spending engineering resources and time and money on stuff just to make sure that it is somehow human tire has no bearing on what we actually do here at too. from -- for our motto here is relentless, constant pursuit of absolute customer satisfaction. That's it. We want to fix your thing. That's it. If our software gets it to you the fastest, and that's what we want to do.

Can I jump just -- so last 1 when you talked -- you had this -- like opening I posted on the LinkedIn about Otovo. Can you just tell us what was that about? And what you're doing with OpenAI for business and what's the real partnership under the whole?

Yes, yes. So OpenAI posted us on LinkedIn, just acknowledging our kind of extreme advancement in using AI at Otovo? The large part of that is really just we're doing stuff that no one else is. And -- and throughout the day today, we are building new systems and endurance that no one else is really doing. That's really all it is, is that we are at the absolute forefront as we went all in on this system very early on. I think that's going to be very difficult for other companies to do because there's a large bit of hesitance of, "Oh, well, what if something goes wrong, whatever what if this happens, what if this happens. But if the customer -- the quality of the customers experience is the best in the industry, you're going to win every time. And that's what we want to do here at Otovo. It's not -- is a -- you have to take that leap for AI, and I think it's going to be very difficult for existing companies to do so. But...

Can you quantified that customer experience for you guys? Like where it has it been and where is it now with Endurance operating as the baseline or like the your operating system for the company?

Exactly. Yes. So if a customer calls, texts us or whatever else it is at 1 a.m., most service companies don't normally have somebody ready for you. With an AI system and the AI ability to dispatch a technician all the way through, we actually truly have a system where the only human you'll have to talk to is a technician. Why do you care about that? Why don't you care that the AI only went through. One, obviously, our cost can be lower. And what we charge you was much lower. And number 2 is most service companies do not have someone ready for you at 1 a.m. I was in a situation recently where solar system [indiscernible] 1 AM didn't have air conditioning. And that's a major problem. With Otovo, you can text us immediately. We can -- we automatically dispatch a technician all the way through the process with our load balancing system, making sure that we send the closest technician, the most available technician to you same day. So someone can be there at 8 a.m. before the phone lines even open. So that's the real benefit of Otovo. Also, when you are dealing with the sale on anything like this, this is my system, as you can see here. We have an actual like DocuSign integration. Now this link is expired. But actually, no, I can still show it to you. This quote is going all the way through the system, explaining to the customer exactly what is going on. We actually got -- before we started building out these kind of like in-plant English explanations with quotes. We were getting issues where customers were like, "I think this is made with AI, and it wasn't. It was made by humans, but it was very technical, not understanding. They don't understand what they're buying. So this is another thing we bring to the table. We help customers understand what they're buying. We don't want to fleece anybody. We don't want to do anything like that. We want to just provide genuine good service. and that's why we kind of break these down. But writing up each one of these each time is extremely time consuming and very expensive. And so doing that with AI now is quite nice to be able to do so. Also, on a normal one that has not been done here.

But a bigger picture question, like do you have like an overall NPS score. That might be more of a question for John. That where you can show that trend of like improvement. So not only is Endurance as good, it could even be better given all the examples that you gave us, Jack. But it'd be interesting to see it for the entire company. Now maybe you guys don't have it yet, but that might be something that might be very useful...

I'll give an answer and Jack -- so we started looking at our CSAT scores. And I think one that would help answer your question, Phil, is that in Europe where we've had the legacy it was quite poor. There were service response times measured in months. And that, by the way, that's fairly typical in the industry, whether it's U.S., Europe, even to Australia and so forth. It's just a really bad experience. And that -- you see that a lot, and you write about that quite a bit about the media, get regulators in attorney generals in the United States and all that. And so when you look at the U.S., which is just really known Endurance, it's actually well over 4.6 and marching higher. I think it's closer to 4.7, 4.8. So really, good customer service and satisfaction. And as these jobs are coming in from our business-to-business, manufacturing partners and other partners, we're rapidly burning them through and burning in a good way, getting the problem solved for the customer. So it's a dramatically better experience. And this is...

Can you quantify this, John? So for example, like before you guys started with Endurance, what was the average kind of time to service or time to resolution. And then what is it now?

Yes, I can answer some of this. So with Otovo Cloud, kind of a traditional non-vibe coded, no AI in the platform, no nothing and HubSpot in Europe. You'd be lucky if we got to you. This is obviously prior to the merger within the next 3 to 4 months on average. CSAT MPS is sitting was sitting at about 3.3 before we have ripped out the old system.

What is CSAT?

Just like a general metric of customer satisfaction. So customer satisfaction metric. Yes. not good, very bad. We had customers that we hadn't contacted for a year for 4 months for e-mailing us and actually when we put in Endurance into the system, replacing the legacy HubSpot system, which HubSpot's #2 behind sales force, a very, very impressive system in general. We were getting flooded with e-mails. Iris was getting flood with e-mails saying, "Oh, you haven't been able to contact us for 4 months or year or something like this, oh, thank you for finally responding like this is awesome. And we've been able to track our callback metrics, we have been able to get back to customers. Now none of this is an easy process, going from not contacting customers contact with customers is very, very difficult. And the backlog is huge. That's what we're doing with Endurance here is bringing -- is taking these legacy businesses that may have had issues before and then in 3 weeks, refreshing them entirely with a brand-new platform that addresses customer concerns.