1 00:00:01,840 --> 00:00:04,080 Matt, welcome to the Evolved Radio podcast. 2 00:00:05,680 --> 00:00:09,520 Thanks for having me, Todd. Happy to be here today. All right, so 3 00:00:09,520 --> 00:00:13,360 we'll get started as we usually do. Kind of give me a bit of 4 00:00:13,360 --> 00:00:16,880 a background on yourself, kind of where you've come to in the MSP 5 00:00:16,880 --> 00:00:20,640 industry, bit of your background and we'll jump into it from there. 6 00:00:22,560 --> 00:00:26,240 Yeah, definitely. So my background, I wasn't as an 7 00:00:26,240 --> 00:00:30,030 MSP operator at first. I've been a software engineer, worked in 8 00:00:30,030 --> 00:00:33,750 the sphere in different roles, mostly in operations in the end. And then 9 00:00:33,750 --> 00:00:37,390 I joined an MSP four years ago now 10 00:00:38,270 --> 00:00:41,870 and just as a CEO operation director, helping them 11 00:00:41,870 --> 00:00:45,630 scale and really going into nitty gritty and learning the trade 12 00:00:45,710 --> 00:00:49,430 I guess by doing lots of it. And that's how I came into 13 00:00:49,430 --> 00:00:53,190 the MSP sphere. So really by doing everything 14 00:00:53,190 --> 00:00:56,510 from tickets to trying to manage and scale operations in the, 15 00:00:57,020 --> 00:01:00,540 I would say lower, smaller to mid size MSP if we were growing. 16 00:01:00,860 --> 00:01:04,500 Okay. And current role kind of being a bit different as 17 00:01:04,500 --> 00:01:07,660 well. Yeah, definitely. So 18 00:01:08,460 --> 00:01:12,180 this MSP adventure led us to realize 19 00:01:12,180 --> 00:01:15,820 that we were well positioned to develop an AI agent that 20 00:01:15,820 --> 00:01:19,180 could help solve some of the issue we were trying to solve at first 21 00:01:19,420 --> 00:01:23,140 through human labor, through processes and in the end we ended 22 00:01:23,140 --> 00:01:26,790 up developing Mizo and that's now I am CEO of Mizo. So we're really 23 00:01:27,430 --> 00:01:31,230 deploying AI agents for our customers, helping them scale their 24 00:01:31,230 --> 00:01:35,070 operations with digital labor. All right, so, and this 25 00:01:35,070 --> 00:01:38,230 touches on one of the things I find really interesting about the MSP 26 00:01:38,470 --> 00:01:42,230 software industry is I feel like most of the 27 00:01:42,230 --> 00:01:45,830 really sort of darling success stories of the industry and probably 28 00:01:46,070 --> 00:01:49,830 50 to 70% of the software out there 29 00:01:49,990 --> 00:01:53,710 really sort of develops out of some MSPs need. Right. 30 00:01:53,710 --> 00:01:57,470 Like I had front row seat to the development of IT glue and 31 00:01:57,470 --> 00:02:01,190 this was sort of a product internally that we needed as an 32 00:02:01,190 --> 00:02:05,030 msp. And every time we had a strategic session we talked about our, our 33 00:02:05,030 --> 00:02:08,630 strengths as an organization. Our documentation platform was always one of those. It's 34 00:02:08,630 --> 00:02:12,310 like there's an opportunity here, like this is good for us. There's, there's 35 00:02:12,310 --> 00:02:16,110 definitely an opportunity for others to kind of leverage the same strength. So you 36 00:02:16,110 --> 00:02:19,820 know, the, the software in the MSP industries is 37 00:02:19,900 --> 00:02:23,260 so much driven out of MSPs solving their own needs. 38 00:02:23,660 --> 00:02:27,260 I'd love to hear you kind of talk about how you guys identified that 39 00:02:27,260 --> 00:02:30,860 and how I guess sort of three stage 40 00:02:30,860 --> 00:02:34,540 process. A very long question, but I'll let you work through it 41 00:02:34,540 --> 00:02:37,420 and ask me if you need me to re prompt you on this as well. 42 00:02:38,700 --> 00:02:41,900 So how did you identify that this was something you guys needed to do, 43 00:02:43,020 --> 00:02:46,660 then determining you should do it yourself. And 44 00:02:46,660 --> 00:02:50,340 then when you sort of realize like, hey, there's a market opportunity, we should 45 00:02:50,340 --> 00:02:53,960 actually start selling our own solution, how did you guys sort of work through 46 00:02:53,960 --> 00:02:57,800 that process? Yeah, definitely. So 47 00:02:57,960 --> 00:03:01,720 our goal at first wasn't to get into the AI 48 00:03:01,720 --> 00:03:05,320 software or the MSP software company. Our goal was to 49 00:03:05,640 --> 00:03:09,080 fix our problem internally. So we were scaling, 50 00:03:09,640 --> 00:03:13,120 we had good traction in MSP. We were growing 50 to 51 00:03:13,120 --> 00:03:16,890 100% annually for two, three years. So that meant revenue 52 00:03:16,890 --> 00:03:20,290 growth was great. Operation growth has its challenge. 53 00:03:20,610 --> 00:03:24,330 So we sort of tried everything and not everything. I 54 00:03:24,330 --> 00:03:27,970 mean there's a lot of things we could have tried too, but just 55 00:03:28,530 --> 00:03:32,290 trying to always hit the same nail the same 56 00:03:32,290 --> 00:03:36,050 way doesn't fix the same issue. And we were seeing that as 57 00:03:36,050 --> 00:03:39,770 we scaled. Adding more bodies to the 58 00:03:39,770 --> 00:03:43,010 problem, adding more people internally didn't get us the 59 00:03:43,170 --> 00:03:46,680 efficiency we were aiming for. So the 60 00:03:46,680 --> 00:03:50,320 realization was really we were at the conjuncture 61 00:03:50,320 --> 00:03:54,080 of AI agents or it wasn't even agents back then, it was 62 00:03:54,160 --> 00:03:57,520 AI or chatbots or the hyperscale of this world 63 00:03:57,680 --> 00:04:01,280 were getting more, I would say commoditized. 64 00:04:01,520 --> 00:04:05,080 ChatGPT had been around for a year or two and people 65 00:04:05,080 --> 00:04:08,920 were starting to see the value in that. We saw that technology as 66 00:04:08,920 --> 00:04:12,750 something that could help us. And that was really the, the moment where we 67 00:04:13,070 --> 00:04:16,830 thought internally let's try to do something out of it and let's try to 68 00:04:16,830 --> 00:04:20,590 fix some of the problems we have. And the first one we 69 00:04:20,670 --> 00:04:24,470 started with was, I guess the obvious one was triage and 70 00:04:24,470 --> 00:04:28,110 dispatch where we saw we spent a lot of time, we 71 00:04:28,110 --> 00:04:31,950 were one of those MSPs which probably you wouldn't recommend, but 72 00:04:32,030 --> 00:04:35,710 having one of the level 2, level 2.5 tech doing the 73 00:04:35,710 --> 00:04:39,550 triage and dispatch because we thought we needed that high level person 74 00:04:39,550 --> 00:04:43,400 to understand issues and be able to know who can 75 00:04:43,400 --> 00:04:47,200 work on that, how should they solve that issue. So, and this 76 00:04:47,200 --> 00:04:50,600 was obviously very costly. That person, we aimed her, 77 00:04:51,240 --> 00:04:53,000 that person to be sort of a 78 00:04:54,760 --> 00:04:58,360 service delivery manager, have service delivery manager, have 79 00:04:58,360 --> 00:05:01,160 dispatcher. It was just too much they couldn't do 80 00:05:03,160 --> 00:05:06,320 was more than a full time role. And in the end all that person ended 81 00:05:06,320 --> 00:05:09,450 up doing was tickets like the so, 82 00:05:10,410 --> 00:05:13,850 so the, the idea came from that if we had that problem we, 83 00:05:13,930 --> 00:05:17,650 we tried with processes to fix it. And we thought maybe the 84 00:05:17,650 --> 00:05:21,290 way to fix this is just to externalize that function and 85 00:05:21,290 --> 00:05:24,970 instead of hiring an admin to do it, we can do it through an AI 86 00:05:24,970 --> 00:05:28,730 agent. And that was really the start. It was, 87 00:05:29,210 --> 00:05:32,810 I guess more than two years ago. And we worked on the product 88 00:05:34,900 --> 00:05:38,620 for about six to seven months internally as an MSP and 89 00:05:38,620 --> 00:05:41,860 just iterating on it, starting with really basic 90 00:05:42,020 --> 00:05:45,660 categorization, renaming, just very basic stuff and 91 00:05:45,660 --> 00:05:49,300 seeing can we have a value of that. And 92 00:05:49,860 --> 00:05:53,140 it was like very, I wouldn't say hacky, but 93 00:05:53,460 --> 00:05:57,180 very low level integration with the PSA we were using back 94 00:05:57,180 --> 00:06:00,940 then, which was Halo and getting those 95 00:06:00,940 --> 00:06:02,580 features on and getting those, 96 00:06:04,820 --> 00:06:08,500 those replacement on or delegation on. And what we saw is that 97 00:06:08,740 --> 00:06:11,860 our back then dispatcher, level two 98 00:06:12,020 --> 00:06:15,860 dispatcher was able to delegate those tasks and we 99 00:06:15,860 --> 00:06:19,380 had even better results than humans sometimes. 100 00:06:19,860 --> 00:06:23,380 So I say humans are 101 00:06:23,380 --> 00:06:27,140 flawed in many ways. And what we saw is that 102 00:06:27,300 --> 00:06:30,920 the operations we did were often better from an 103 00:06:30,920 --> 00:06:34,400 ITIL perspective, from a standardization perspective and what our 104 00:06:34,400 --> 00:06:35,960 dispatcher would have done in that case. 105 00:06:38,040 --> 00:06:41,000 So after that six months we sort of 106 00:06:42,360 --> 00:06:46,200 stopped and said what did that project cost 107 00:06:46,200 --> 00:06:50,000 us and what did it give us? And our conclusion was that even 108 00:06:50,000 --> 00:06:53,560 though there was a lot of R and D investment, it's obviously expected and 109 00:06:53,640 --> 00:06:57,080 we knew about that, there was definitely a lot of value 110 00:06:57,240 --> 00:07:00,980 we got out of it. And we, I think we saw that it was just 111 00:07:00,980 --> 00:07:04,700 getting started. We as a company, as a software were just getting started. But also 112 00:07:04,700 --> 00:07:08,260 the hyperscaler, the AI capabilities on the model 113 00:07:08,260 --> 00:07:11,820 side and the product were also very early. 114 00:07:12,060 --> 00:07:15,740 I think we still are in many ways. So that was 115 00:07:16,300 --> 00:07:19,900 that point, that was December 2024 116 00:07:20,060 --> 00:07:23,740 when we decided, yeah, let's try to make a product out of this. 117 00:07:23,900 --> 00:07:27,140 We had great results for ourselves. Let's try to see if others in the 118 00:07:27,140 --> 00:07:28,640 ecosystem could benefit from it. 119 00:07:31,270 --> 00:07:33,830 So we did that and we went into the market, 120 00:07:35,190 --> 00:07:39,030 went to other MSPs in our peer groups, other MSPs we knew and 121 00:07:39,350 --> 00:07:43,030 asked them do you guys have that problem? And the 122 00:07:43,030 --> 00:07:46,070 conclusion was a lot of people ended up having the same issues 123 00:07:47,750 --> 00:07:51,590 and we tried it out, developed some more integration 124 00:07:51,590 --> 00:07:55,430 with new PSAs, new softwares, just adapting what we had 125 00:07:55,890 --> 00:07:59,410 and we saw some good results there. So this 126 00:07:59,810 --> 00:08:03,010 brought us all the way here I guess more than 127 00:08:04,130 --> 00:08:07,930 a year later, a year and a half later. But I 128 00:08:07,930 --> 00:08:11,650 think I'm missing one part to your question. So we had the, I 129 00:08:11,650 --> 00:08:14,970 think you got it is like why, how did you do it? And then the 130 00:08:14,970 --> 00:08:17,170 pivot basically. I am curious though, 131 00:08:19,410 --> 00:08:22,720 how much of this was people being 132 00:08:22,720 --> 00:08:25,680 attracted to the solution based on what you had versus like 133 00:08:26,320 --> 00:08:30,160 I think we have something that we could market, right? Because like I've seen both 134 00:08:30,160 --> 00:08:33,160 of those where like a lot of people are going to peer groups or they're 135 00:08:33,160 --> 00:08:37,000 just talking to sort of like peer MSPs in the industry and 136 00:08:37,000 --> 00:08:40,560 you know, you're like, oh, you're doing this. Like, how are you doing that? Oh, 137 00:08:40,560 --> 00:08:43,760 like, can you show me this? Oh, this is really neat. Like, can I have 138 00:08:43,760 --> 00:08:47,480 this? Like before it's a product, was there an element of that or was 139 00:08:47,480 --> 00:08:50,920 it sort of a conscious decision? Before it was really sort of public to peers 140 00:08:50,920 --> 00:08:54,150 and other people in that you guys had in peer groups and stuff? 141 00:08:56,380 --> 00:08:58,300 I think it was a bit of both. So 142 00:09:00,140 --> 00:09:03,900 coming from having other businesses 143 00:09:03,900 --> 00:09:07,700 before, I've always liked branding. So we sort of thought of a 144 00:09:07,700 --> 00:09:11,260 name for the product and logos and I mean we started 145 00:09:11,420 --> 00:09:15,060 ironing on that of creating that company. But the first 146 00:09:15,060 --> 00:09:18,780 few MSPs we talked to, they were just seeing us as like, yeah, their 147 00:09:18,780 --> 00:09:22,300 friend developing something nice and sort of their in house development 148 00:09:22,380 --> 00:09:25,340 team just helping them do more. So I think, 149 00:09:26,350 --> 00:09:30,190 and it's a great relationship to have with your customers too, that proximity. But 150 00:09:30,750 --> 00:09:34,390 it was a bit of both. We thought about it as a product, about having 151 00:09:34,390 --> 00:09:38,110 that company, creating company out of it. But I think the first customers were really 152 00:09:38,110 --> 00:09:41,310 like, yeah, I want to use this too and show me how you're doing it 153 00:09:41,310 --> 00:09:44,790 and get it in my environment. And this is the problem I'm having too. And 154 00:09:44,790 --> 00:09:48,550 then you get a list of problems that you're having to which you can 155 00:09:48,550 --> 00:09:51,960 help solving. So that was really great. Cool. Okay, great. 156 00:09:53,720 --> 00:09:57,240 That also lends to. The other thing I wanted to explore here is like, I 157 00:09:57,240 --> 00:10:00,760 am continuously shocked. I've talked about this on other podcasts and 158 00:10:01,080 --> 00:10:04,280 all over the place because as I was traveling last year and 159 00:10:04,680 --> 00:10:08,520 late this year as well, about how 160 00:10:08,520 --> 00:10:12,120 we, the people that are leading edge on sort of AI and automation 161 00:10:12,600 --> 00:10:16,360 are pretty far ahead of, I think the industry average. So you guys 162 00:10:16,360 --> 00:10:19,080 were, I think, way ahead of the curve in the fact that you were developing 163 00:10:19,080 --> 00:10:22,880 this in house and with enough time to be able to then turn around 164 00:10:22,880 --> 00:10:26,500 and start or as a separate product. But I'm still 165 00:10:26,500 --> 00:10:29,780 shocked by the number of MSPs that are not on 166 00:10:29,940 --> 00:10:33,700 AI in a meaningful way. Right. And I see a couple of 167 00:10:34,260 --> 00:10:38,100 points of pushback about this. And you guys, 168 00:10:38,100 --> 00:10:41,860 I think like having a lot of touch points with potential client 169 00:10:42,100 --> 00:10:45,740 prospects for the solution, probably see a lot of 170 00:10:45,740 --> 00:10:49,540 this. But you know, the couple of points of pushback that I see 171 00:10:49,540 --> 00:10:53,140 are like, people just don't have the time to know that the solutions are available. 172 00:10:53,220 --> 00:10:56,720 Like I put out this, this is the one I've sort of 173 00:10:56,960 --> 00:11:00,560 banted on a Lot about is I put out this call out to 174 00:11:00,800 --> 00:11:04,640 a group of MSPs and said, if you had an AI 175 00:11:04,640 --> 00:11:08,040 army to build a solution for you, what would it be? And 176 00:11:08,040 --> 00:11:11,880 invariably, nine times out of 10 people described exactly what you 177 00:11:11,880 --> 00:11:15,200 guys do and for that matter, several other solutions in the market. 178 00:11:15,440 --> 00:11:18,880 I'm like, come on you guys, what you're asking for 179 00:11:18,880 --> 00:11:22,160 exists. Go get it. So I'm partly 180 00:11:22,870 --> 00:11:26,670 flabbergasted by the fact that these solutions are not as prevalent as they 181 00:11:26,670 --> 00:11:30,070 probably can and certainly should be in the, 182 00:11:30,550 --> 00:11:34,310 in the wider ecosystem. And the other part 183 00:11:34,310 --> 00:11:37,950 that I see is, you know, people feel that it will somehow 184 00:11:37,950 --> 00:11:41,630 change something tangible about the human connection. And I see 185 00:11:41,630 --> 00:11:44,950 this maybe as an extension of a lot of owners are really 186 00:11:45,430 --> 00:11:49,070 sort of precious about live answer to a point where it 187 00:11:49,070 --> 00:11:52,770 becomes actually problematic for the MSP where like we have to have a 188 00:11:52,770 --> 00:11:56,330 live answer, you know, we don't want, you know, it has to go straight to 189 00:11:56,330 --> 00:11:59,970 the tech, you know, like we can't have anything go to voicemail, blah blah, blah, 190 00:11:59,970 --> 00:12:03,570 blah, blah. And that becomes problematic over, over time. And I don't think it's as 191 00:12:03,570 --> 00:12:07,250 important as people think it is. And maybe it's sort of related. Like you said, 192 00:12:07,409 --> 00:12:11,250 you actually had better results utilizing the AI than you did with 193 00:12:11,250 --> 00:12:14,530 human labor in a lot of those cases. Right. So maybe if, 194 00:12:15,010 --> 00:12:18,610 again, kind of a long, long question, but just exploring that idea of like, 195 00:12:18,880 --> 00:12:22,720 why isn't this more prevalent yet, considering how we should 196 00:12:22,720 --> 00:12:26,440 be more technically a bleeding edge in this industry and 197 00:12:26,440 --> 00:12:29,720 AI has been around long enough that it sort of blows me away that it's 198 00:12:29,720 --> 00:12:33,440 not more prevalent in a lot more msps right now. 199 00:12:35,600 --> 00:12:38,800 Yeah, it's, it's actually a great question. And I mean it's, 200 00:12:39,360 --> 00:12:43,000 it's something we, we often ask ourselves. I think one 201 00:12:43,000 --> 00:12:46,730 of the, one of the 202 00:12:46,890 --> 00:12:49,130 issue or one of probably 203 00:12:50,650 --> 00:12:54,410 something that's slowing down this AI adoption is the hyper 204 00:12:54,410 --> 00:12:57,610 customization of most MSPs. 205 00:12:58,090 --> 00:13:01,810 I feel what we see is that no 206 00:13:01,810 --> 00:13:05,570 processes are the same. We often hear like that's my secret sauce and 207 00:13:05,570 --> 00:13:09,410 that's how I'm doing it. And it's also 208 00:13:09,410 --> 00:13:12,170 my, I want to keep it for myself. I don't want to share that secret 209 00:13:12,170 --> 00:13:15,520 sauce necessarily, but I think a lot of 210 00:13:15,520 --> 00:13:18,840 MSPs have been built on hyper 211 00:13:18,920 --> 00:13:22,200 customization or hyper specification of 212 00:13:22,200 --> 00:13:26,040 processes where everything is very specific to their 213 00:13:26,040 --> 00:13:29,240 operations and their company and their context and build 214 00:13:30,520 --> 00:13:34,040 around that. Most people probably feel that AI 215 00:13:34,040 --> 00:13:37,760 wouldn't be able to understand that 216 00:13:37,760 --> 00:13:40,760 or to adapt to those situations. While it's completely 217 00:13:41,560 --> 00:13:44,980 the Inverse. If there's something that's good at getting 218 00:13:44,980 --> 00:13:48,100 context and getting an answer out of it, it's no, 219 00:13:48,580 --> 00:13:52,260 it's good at being adaptable to adapt to any context. 220 00:13:52,900 --> 00:13:55,620 So I think that's one of the 221 00:13:56,500 --> 00:13:59,460 things that's slowing down adoption. 222 00:14:00,180 --> 00:14:01,620 The other one is probably 223 00:14:04,020 --> 00:14:07,780 maybe, and this is really speculation my part, but MSP 224 00:14:07,780 --> 00:14:11,500 is being really at the leading edge of technology. I think they've been 225 00:14:11,500 --> 00:14:15,140 the first to see the problems with AI. It was 226 00:14:15,140 --> 00:14:18,980 probably two years ago, like there was some hallucination you would ask ChatGPT 227 00:14:19,540 --> 00:14:23,380 whatever question it would probably give you something wrong and for, 228 00:14:23,700 --> 00:14:27,420 for many different reasons. This happened back then. And I think 229 00:14:27,420 --> 00:14:31,100 a lot of the hyperscalers have worked on that. The AI labs have 230 00:14:31,100 --> 00:14:34,700 worked on that for, from their perspective. Also the prompting side on 231 00:14:34,700 --> 00:14:38,260 the agent side, there's a lot of improvement that were done 232 00:14:38,580 --> 00:14:42,380 but I feel like sometimes people are still stuck there. Yeah, 233 00:14:42,380 --> 00:14:46,100 I'm giving it something and I get AI slot out of it. 234 00:14:47,780 --> 00:14:51,420 This is maybe something we're scared about and it ties into 235 00:14:51,420 --> 00:14:55,020 the service quality. I feel like most 236 00:14:55,020 --> 00:14:58,820 MSPs want to keep their service quality at the highest level possible 237 00:14:59,220 --> 00:15:02,980 and feel like having a conversation with a badly 238 00:15:02,980 --> 00:15:06,700 trained AI agent with their customers would lower 239 00:15:06,700 --> 00:15:10,420 their service quality. But while it's 240 00:15:10,420 --> 00:15:14,260 inverse, if you have something really good that is fine 241 00:15:14,260 --> 00:15:18,100 tuned to how you work as an msp, you get those results much 242 00:15:18,100 --> 00:15:21,660 better. And people would, I think would rather 243 00:15:21,660 --> 00:15:24,700 chat with an AI agent, have a conversation that's 244 00:15:25,180 --> 00:15:29,020 tickets all very fast and they have a human in the 245 00:15:29,020 --> 00:15:31,460 loop where it needs to be and still be able to talk to a human 246 00:15:31,460 --> 00:15:35,120 if they need to while instead of waiting for a human 247 00:15:35,120 --> 00:15:38,600 to be able to solve it and then having that really inconsistent service quality. 248 00:15:39,080 --> 00:15:42,760 So these are my takes. I mean there's probably 249 00:15:42,760 --> 00:15:46,480 more to it and I'm curious to get maybe your impression how 250 00:15:46,480 --> 00:15:50,160 you feel about that. I think you're right, the quality does matter. 251 00:15:50,160 --> 00:15:53,960 I'm not saying that people are sort of misguided 252 00:15:54,840 --> 00:15:58,640 in wanting that obviously better quality service, especially at the front line 253 00:15:58,640 --> 00:16:02,440 is important. It's a service based industry and if your first interaction with the 254 00:16:02,440 --> 00:16:06,180 help desk is terrible, then that sets a really bad tone for 255 00:16:06,260 --> 00:16:09,860 that relationship as a whole. But I think to your point, like I had 256 00:16:10,420 --> 00:16:14,220 Megan Giholy on I guess a couple of years ago now, 257 00:16:14,220 --> 00:16:16,980 like it was a long time ago and we were talking about AI agents, right, 258 00:16:17,540 --> 00:16:21,300 like customer service agents and she said, you know the problem, like AI 259 00:16:21,300 --> 00:16:25,140 agents are actually really good. The problem is most of them are terrible. So like 260 00:16:25,140 --> 00:16:28,940 our expectations are so low because like the implementation of them are bad, but 261 00:16:28,940 --> 00:16:32,420 when they're done well, they're amazing. And that's sort of like it's the quality 262 00:16:33,780 --> 00:16:37,300 of the service that you provide, both in a human interaction but also in 263 00:16:37,620 --> 00:16:40,420 an agentic interaction I think matters. Right. 264 00:16:41,300 --> 00:16:45,020 And to some extent, I think a lot of the MSP industries kind of run 265 00:16:45,020 --> 00:16:48,460 off their feet and they look for cool solutions around 266 00:16:48,460 --> 00:16:52,100 automation, but they don't really have the time or the 267 00:16:52,100 --> 00:16:55,860 bandwidth to capitalize on those things. And I think it's maybe just sort of 268 00:16:55,860 --> 00:16:59,700 the same thing. Right? So yeah, those are some of the big 269 00:16:59,700 --> 00:17:03,420 ones that I tend to see as sort of the sticking points for 270 00:17:03,420 --> 00:17:07,160 this. But the other point that you make I think is actually 271 00:17:07,160 --> 00:17:10,680 really important for how you guys are a bit different than a lot of the 272 00:17:10,680 --> 00:17:14,520 other solutions in the industry is that so from a 273 00:17:14,520 --> 00:17:18,360 philosophy standpoint, like you guys are much more facing the technician 274 00:17:18,360 --> 00:17:21,640 than it is facing the client. So you guys don't really have those 275 00:17:21,640 --> 00:17:25,240 problems. I mean right now, depending on what your roadmap looks like. 276 00:17:25,240 --> 00:17:29,040 But right now a lot of the agentic interaction is 277 00:17:29,040 --> 00:17:32,800 with the tech, like trying to make them more expedient, providing 278 00:17:32,800 --> 00:17:36,570 them context and information rather than trying to front end the 279 00:17:36,570 --> 00:17:40,210 conversation with an AI and then sort of creating that risk 280 00:17:40,290 --> 00:17:43,930 of a bad interaction between an AI and an end 281 00:17:43,930 --> 00:17:47,650 user, I guess, right? Yeah, definitely. And 282 00:17:48,370 --> 00:17:52,050 we really see the value, and I 283 00:17:52,050 --> 00:17:55,890 mean the value of technicians are into solving hard problems to solve 284 00:17:55,890 --> 00:17:59,610 and also creating that customer relationship. You have an 285 00:17:59,610 --> 00:18:03,440 MSP as an SMB. You do business with an MSP 286 00:18:03,440 --> 00:18:07,280 because they are your IT department, you know them probably by name 287 00:18:07,440 --> 00:18:11,120 or you have a relationship with them. And that's the value for 288 00:18:11,120 --> 00:18:14,720 technicians in the msp. And we see ourselves as 289 00:18:14,960 --> 00:18:18,680 just helping those technicians do more. And for 290 00:18:18,680 --> 00:18:22,480 us the future is about having technicians manage fleets 291 00:18:22,480 --> 00:18:26,320 of agents and mostly delegating most of their tasks, 292 00:18:26,480 --> 00:18:30,140 if not all their tasks to AI agents and just being able 293 00:18:30,140 --> 00:18:33,900 to have them in the loop where they need to be, if there needs to 294 00:18:33,900 --> 00:18:37,620 be human contact for some reason, if there needs to be an approval for some 295 00:18:37,620 --> 00:18:41,340 risky operation. But our goal and our 296 00:18:41,340 --> 00:18:45,060 philosophy is to have those technicians perform better and reduce the amount of low 297 00:18:45,060 --> 00:18:48,860 value tasks and non rewarding tasks they do. And if you 298 00:18:48,860 --> 00:18:51,980 ask a technician what they do on a daily basis and what they like doing 299 00:18:51,980 --> 00:18:55,660 on a daily basis, I mean it's that Venn diagram isn't 300 00:18:55,660 --> 00:18:59,420 that big. And they like to solve problems, issues and they don't 301 00:18:59,420 --> 00:19:02,660 like to create reports and document 302 00:19:02,660 --> 00:19:06,020 resolutions and send customer requests 303 00:19:07,460 --> 00:19:11,260 for a meeting or whatever. So all those lower value tasks that 304 00:19:11,260 --> 00:19:15,100 are not, first of all they have low value for 305 00:19:15,100 --> 00:19:18,820 customers, they have low value for technicians. It's something we can easily help them 306 00:19:18,820 --> 00:19:22,020 with and also elevate those technicians to 307 00:19:23,220 --> 00:19:26,550 higher tests that devalue more. So this is really 308 00:19:26,550 --> 00:19:30,190 philosophy we have and all the interactions we're 309 00:19:30,190 --> 00:19:33,950 having are always transparent. So even though we have interactions 310 00:19:33,950 --> 00:19:37,350 through the PSA with some of our, with end 311 00:19:37,350 --> 00:19:41,069 users, everything is done on behalf of the technicians. So 312 00:19:41,069 --> 00:19:43,910 we're just helping those technicians do more and 313 00:19:44,470 --> 00:19:47,990 reduce the amount of work they do by themselves 314 00:19:48,310 --> 00:19:52,070 for those interactions. Okay, great. I guess the other thing 315 00:19:52,070 --> 00:19:55,820 I wanted to touch on here is as people may have, may have picked up 316 00:19:56,220 --> 00:19:59,180 with your, your fantastic accent is. 317 00:19:59,740 --> 00:20:03,380 You're a Canadian. French Canadian. And this is another 318 00:20:03,380 --> 00:20:06,980 aspect of the MSP industry that I find really fascinating. And like there's a long 319 00:20:06,980 --> 00:20:10,739 history to this. Like I obviously, you know, it Glue and 320 00:20:10,739 --> 00:20:14,580 Scalepad, fairly recognizable Canadian brands. Also 321 00:20:14,580 --> 00:20:18,140 Passportal. But even all the way back to like Enable, 322 00:20:18,540 --> 00:20:22,220 you know, being out of Ottawa, like a Canadian company. There's a really 323 00:20:22,220 --> 00:20:25,820 long history of MSP software in Canada which is not a 324 00:20:25,820 --> 00:20:28,200 hu, especially relative to the us. 325 00:20:29,720 --> 00:20:32,400 I mean you guys must have thought about this. But like why do you think 326 00:20:32,400 --> 00:20:36,040 that is that there's, you know, as Canadians we tend to punch above our weight 327 00:20:36,040 --> 00:20:38,200 in the MSP industry when it comes to software. 328 00:20:40,600 --> 00:20:41,960 It's a great question. And 329 00:20:43,960 --> 00:20:47,600 there's, there's probably two parts to it. I think 330 00:20:47,600 --> 00:20:51,000 the, the first part is the, the 331 00:20:51,400 --> 00:20:55,190 SMB rich ecosystem in Canada. So a large part 332 00:20:55,190 --> 00:20:58,950 of the Canadian economy is based on SMBs. Like it's 333 00:20:58,950 --> 00:21:02,510 probably higher than most Western countries. So this 334 00:21:02,510 --> 00:21:05,470 means more SMBs, more MSPs to serve them. 335 00:21:06,670 --> 00:21:10,470 So this is definitely something that we see 336 00:21:10,470 --> 00:21:14,230 that there's a lot of MSP and this is probably a lot, there's even 337 00:21:14,230 --> 00:21:17,710 much more in the United States, but there's many MSPs in Canada. 338 00:21:17,870 --> 00:21:21,680 So as a, as a Canadian 339 00:21:21,680 --> 00:21:25,160 company or a Canadian msp, you have much, 340 00:21:26,520 --> 00:21:30,120 you have a lot of ground to test your product on different 341 00:21:30,600 --> 00:21:34,360 customers. And so that's, I think that's one of the 342 00:21:34,360 --> 00:21:37,960 first one. And what we see is that In Canada most 343 00:21:37,960 --> 00:21:41,720 MSPs will have smaller clients than what we see in the United States. 344 00:21:42,200 --> 00:21:45,720 Less co managed. So they have larger client bases, 345 00:21:46,630 --> 00:21:48,470 meaning that they have well, larger 346 00:21:50,150 --> 00:21:53,830 amount of clients or count of clients which means that they have 347 00:21:53,830 --> 00:21:57,350 more diversity to test their ideas. 348 00:21:57,510 --> 00:22:01,310 I think that might be one of the first one just being 349 00:22:01,310 --> 00:22:03,270 like ASMB fertile ground. 350 00:22:05,270 --> 00:22:07,830 The other one might be just related to 351 00:22:09,990 --> 00:22:13,440 innovation savviness in Canada. I think 352 00:22:14,400 --> 00:22:15,520 as Canadian 353 00:22:18,320 --> 00:22:20,800 we're much less risk prone than 354 00:22:22,240 --> 00:22:26,000 United States. And you see this in VC world, you see this in any 355 00:22:26,160 --> 00:22:29,360 startup world and that's why we have such a deficit probably 356 00:22:30,560 --> 00:22:34,160 in productivity and in innovation. But 357 00:22:34,960 --> 00:22:38,600 launching a product in the Canadian market is probably much 358 00:22:38,600 --> 00:22:42,320 higher bar to launch because people are very, very demanding. 359 00:22:42,870 --> 00:22:46,350 I think since they are less prone to innovation, Kinean 360 00:22:46,350 --> 00:22:50,150 MSPS will want to have a product that's much higher quality. 361 00:22:52,070 --> 00:22:55,870 So this might be something just in having the 362 00:22:55,870 --> 00:22:59,350 philosophy in how canium companies build product they want to build. 363 00:22:59,350 --> 00:23:02,870 And it's always a challenge when you're building a startup but you 364 00:23:03,110 --> 00:23:06,910 can never launch too early probably and if you feel like you've launched at 365 00:23:06,910 --> 00:23:09,430 the right time, it's because it's too late. But 366 00:23:10,790 --> 00:23:13,750 I feel like this is something that Kenyan companies 367 00:23:15,030 --> 00:23:18,470 might be more inclined to having that higher standards, higher bar for product 368 00:23:18,710 --> 00:23:22,470 quality and that might lead them to creating better products. 369 00:23:23,590 --> 00:23:27,230 But this is honestly just 370 00:23:27,230 --> 00:23:30,830 our take on it and speculation. I mean you guys are a Canadian 371 00:23:30,830 --> 00:23:34,630 software development company, so your opinion matters in this matter. 372 00:23:36,630 --> 00:23:40,460 Just curious, did you guys leverage like shred for those not 373 00:23:40,460 --> 00:23:43,620 familiar and especially those not in Canada, this is scientific research and 374 00:23:43,620 --> 00:23:47,420 experimental development. It's like a, like a tax incentive program that 375 00:23:47,420 --> 00:23:51,140 the Canadian government has for, you know, anything scientific, but it also 376 00:23:51,140 --> 00:23:54,860 lends to software development and process innovation. Was that something you guys were able 377 00:23:54,860 --> 00:23:58,700 to leverage? Yeah, definitely. So as 378 00:23:58,700 --> 00:24:02,300 you mentioned, there's shred, but there's many other governmental 379 00:24:02,300 --> 00:24:05,460 programs to accelerate. Yeah, 380 00:24:05,820 --> 00:24:08,540 Iraps one of them too that you can. 381 00:24:09,500 --> 00:24:12,940 So yeah, we leverage all of those actually. So 382 00:24:13,500 --> 00:24:16,940 as Canadian also we have that advantage of being able to 383 00:24:17,580 --> 00:24:21,020 subsidize most of our development R and D, 384 00:24:22,540 --> 00:24:24,220 I wouldn't say subsidized, but 385 00:24:26,220 --> 00:24:29,500 get those tax returns for it helps, right? 386 00:24:30,780 --> 00:24:34,220 Yeah, definitely. It does make a big difference. That paired with 387 00:24:34,540 --> 00:24:37,800 having great talent pool is probably something that that 388 00:24:38,040 --> 00:24:41,800 helps a lot. For those again, 389 00:24:41,800 --> 00:24:44,840 not familiar with Canadian sort of markets and 390 00:24:45,560 --> 00:24:49,400 you guys based in Quebec. There's a lot of software development like 391 00:24:49,400 --> 00:24:53,000 Ubisoft and a lot of the Canadian software development houses. 392 00:24:53,000 --> 00:24:56,360 EA is Canadian west coast. But Ubisoft being huge 393 00:24:56,680 --> 00:25:00,440 in your region, that's the one that sort of comes to mind for 394 00:25:00,440 --> 00:25:04,210 me. But I'm sure there's a ton of other sort of companies 395 00:25:04,210 --> 00:25:07,770 that tend to create a bit of a gravitational force for good talent in the 396 00:25:07,770 --> 00:25:11,330 region, right? Yeah, definitely. And I think 397 00:25:11,410 --> 00:25:15,170 us being based in Montreal Montreal has the longest survey with 398 00:25:15,170 --> 00:25:18,690 AI being one of the first cities to have AI labs from 399 00:25:18,690 --> 00:25:22,490 Meta that have been here for a while now. Google also has an 400 00:25:22,490 --> 00:25:26,250 AI practice in Montreal. This AI I think 401 00:25:26,250 --> 00:25:29,980 there was a good movement around AI five years ago generating 402 00:25:29,980 --> 00:25:32,620 a talent pool in Montreal and generating 403 00:25:34,540 --> 00:25:38,140 those various deep research on AI 404 00:25:38,540 --> 00:25:42,340 development in Montreal. And this obviously shifted a lot 405 00:25:42,340 --> 00:25:46,060 to applied AI now as the fundamental 406 00:25:46,060 --> 00:25:49,580 research is mostly taken care of by the big labs. But 407 00:25:49,820 --> 00:25:53,620 I think we have that talent pool that stayed there that has been doing 408 00:25:53,620 --> 00:25:57,420 AI before AI if you want. I mean even Geoffrey Hinton, 409 00:25:57,580 --> 00:26:00,540 the godfather of modern AI from Toronto, right? 410 00:26:02,600 --> 00:26:06,440 Yeah, exactly. So we have a lot of. So we have a 411 00:26:06,440 --> 00:26:10,280 lot of those talent in Canada that have been at the forefront of the 412 00:26:10,280 --> 00:26:14,080 research before it got before it scaled as it has. So 413 00:26:14,080 --> 00:26:17,760 I think that talent is really leverageable 414 00:26:17,760 --> 00:26:21,480 to apply those principles and start from first principle 415 00:26:21,480 --> 00:26:24,920 and not just learn about how ChatGPT works from 416 00:26:26,600 --> 00:26:29,680 reading the API doc, but really understanding the fundamentals, 417 00:26:29,910 --> 00:26:33,110 fundamentals of models and being able to really 418 00:26:33,990 --> 00:26:37,670 fine tune the usage to how it should be used. Yeah, 419 00:26:37,750 --> 00:26:40,790 cool. The other piece of this kind of lends to 420 00:26:41,430 --> 00:26:45,190 small upstart David and Goliath 421 00:26:45,190 --> 00:26:48,550 type approach. I'm curious sort of how you think about your 422 00:26:48,550 --> 00:26:51,910 opportunity as a small development company relative to 423 00:26:52,550 --> 00:26:55,830 a lot of the PE led companies, 424 00:26:56,350 --> 00:26:59,070 you know, the big giants in the industry. 425 00:27:00,030 --> 00:27:03,630 I personally feel like there's a strong and movers advantage for 426 00:27:03,630 --> 00:27:06,750 smaller companies to be able to iterate and innovate and improve 427 00:27:07,150 --> 00:27:10,910 upon those platforms certainly at a faster cycle and than 428 00:27:10,910 --> 00:27:14,630 some of the larger companies. I assume you think that that's true as 429 00:27:14,630 --> 00:27:17,550 well. But I'm be curious kind of how you feel like you guys have a 430 00:27:17,550 --> 00:27:20,950 competitive advantage as a smaller entity being able to 431 00:27:20,950 --> 00:27:24,380 capitalize on on sort of market opportunities and be a bit more 432 00:27:24,380 --> 00:27:27,780 nimble. Yeah, I think 433 00:27:29,140 --> 00:27:32,820 we try to do what 434 00:27:32,980 --> 00:27:36,820 we preach really internally and I feel one of our main advantages 435 00:27:36,820 --> 00:27:40,620 being an AI native company and what we define as 436 00:27:40,620 --> 00:27:44,020 an AI native company, and there's probably a lot of buzz around it, is that 437 00:27:44,420 --> 00:27:47,820 even though we're a small team, we have agents working for us doing all sorts 438 00:27:47,820 --> 00:27:51,310 of tasks and on the marketing side, on the development side, 439 00:27:51,310 --> 00:27:55,150 obviously on the account payable size 440 00:27:55,150 --> 00:27:58,710 on the accounting side. So we deploy our own AI agents 441 00:27:58,710 --> 00:28:01,870 for many tasks internally so we can leverage that technology 442 00:28:02,270 --> 00:28:05,550 and we can also create 443 00:28:05,550 --> 00:28:09,190 processes around using those AI agents and not having 444 00:28:09,190 --> 00:28:12,830 to rethink already scaled 445 00:28:12,830 --> 00:28:16,190 processes to how we should use AI internally so we have 446 00:28:16,750 --> 00:28:20,460 the opportunity of leveraging AI everywhere. We need, and this is 447 00:28:20,460 --> 00:28:24,140 really, I think one of the main advantage and it leads to, as you 448 00:28:24,140 --> 00:28:27,940 mentioned, faster iteration cycles. And I think we have iteration cycles 449 00:28:27,940 --> 00:28:31,620 that you can match 450 00:28:32,020 --> 00:28:35,820 in any industry. And I mean we try to stay on top of 451 00:28:35,820 --> 00:28:39,460 that, but we ship multiple times a day. And this is something that 452 00:28:40,180 --> 00:28:43,780 with such a small team that we can do as an AI native 453 00:28:43,780 --> 00:28:47,220 company that a lot of the incumbents wouldn't be able to do. 454 00:28:47,780 --> 00:28:51,580 And I think even starting five years ago, you still 455 00:28:51,580 --> 00:28:55,380 have a lot of that gap to bridge 456 00:28:55,380 --> 00:28:58,900 because you've built your processes and you hired people and you build 457 00:29:01,060 --> 00:29:04,900 your company processes into working how they should work around 458 00:29:05,460 --> 00:29:09,300 people. And we are building our processes into 459 00:29:09,460 --> 00:29:13,260 how we should work around agents and how humans can intervene in the 460 00:29:13,260 --> 00:29:15,940 right place in the loop through agents. 461 00:29:17,190 --> 00:29:20,230 So this is, I think it's definitely a fundamental shift that just 462 00:29:20,550 --> 00:29:24,310 creates more faster iteration cycles and in the end better 463 00:29:24,310 --> 00:29:26,950 product quality for the customers. That sort of reminds me of 464 00:29:28,230 --> 00:29:32,030 reminiscing back in the good old days of Connectwise when 465 00:29:32,030 --> 00:29:35,830 Connectwise again they were building their own software for themselves 466 00:29:35,830 --> 00:29:39,470 as an msp. So it sort of speaks to this kind of building to scratch 467 00:29:39,470 --> 00:29:43,230 your own itch. But I think part of what made them successful in the 468 00:29:43,230 --> 00:29:46,870 very early days was they were building it for themselves and being able to 469 00:29:46,870 --> 00:29:50,350 test the things that they needed, solving for their own problems. And I think because 470 00:29:50,350 --> 00:29:54,030 you guys were born out of an MSP and still have 471 00:29:54,030 --> 00:29:57,230 sort of that, that high touch point of like what do we need, what do 472 00:29:57,230 --> 00:30:00,950 we see internally, what's working and then sort of iterate from there. It gives you 473 00:30:00,950 --> 00:30:04,550 that, that higher fidelity understanding of what's 474 00:30:04,550 --> 00:30:08,110 required to make this work in an msp, right? 475 00:30:09,790 --> 00:30:13,610 Yeah, definitely. And I think one of those advantage also is that 476 00:30:13,610 --> 00:30:17,330 we're not afraid to change things. We 477 00:30:17,330 --> 00:30:20,890 built something that didn't work, we'll just scratch it and start again. And 478 00:30:20,890 --> 00:30:24,570 that's something we can do because we have that proximity 479 00:30:24,570 --> 00:30:28,410 and we can create that iteration cycles, but we also have that velocity 480 00:30:28,410 --> 00:30:32,250 of developing it. So where I think as a larger company you 481 00:30:32,250 --> 00:30:35,650 have to plan ahead and create that big roadmap and then you launch and hopefully 482 00:30:35,650 --> 00:30:39,450 it works and you do all that product led development all 483 00:30:39,450 --> 00:30:43,010 around. But I think the processes are so much larger 484 00:30:43,380 --> 00:30:46,260 that you end up probably 485 00:30:47,220 --> 00:30:50,580 launching a product a little too late where it doesn't exactly fit 486 00:30:50,820 --> 00:30:54,660 the need where it's at now. So being in 487 00:30:54,660 --> 00:30:58,100 an MSP and also having that evolution speed allows us to 488 00:30:58,260 --> 00:31:01,980 continuously adapt and our customers are changing on a day to day basis. 489 00:31:01,980 --> 00:31:05,140 And we talked earlier about how they 490 00:31:05,460 --> 00:31:09,300 are starting to adopt AI. But AI will obviously 491 00:31:09,780 --> 00:31:12,780 create a lot of process change for our customers. So we need to be at 492 00:31:12,780 --> 00:31:16,360 the forefront of that and being able to adapt to what they are currently 493 00:31:16,440 --> 00:31:20,200 doing and will be doing in a month or in a year. Yeah, but 494 00:31:20,200 --> 00:31:24,000 lends well to a question. Before we started recording I was like is 495 00:31:24,000 --> 00:31:27,760 this worth asking? But I think you had a good answer to this. So we 496 00:31:27,760 --> 00:31:31,080 can kind of go down this road and it sort of lends from that is, 497 00:31:31,240 --> 00:31:35,040 you know, the future of AI. Right. And totally recognizing to 498 00:31:35,040 --> 00:31:38,760 your point. I always joke that the MSP industry and IT in general has a 499 00:31:38,760 --> 00:31:42,440 six month shelf life. Right. And now like I would say with 500 00:31:42,520 --> 00:31:45,720 sort of the cycles of AI and how quickly things change, it's like 501 00:31:46,220 --> 00:31:49,820 maybe three to six week shelf life. Like things are moving so 502 00:31:49,820 --> 00:31:53,660 fast. Right. And I'm curious sort of how you think about, you know, planning 503 00:31:53,660 --> 00:31:57,500 for the future for in an industry that is subject to 504 00:31:57,500 --> 00:32:00,780 such radical change within a six month period. 505 00:32:03,420 --> 00:32:06,860 Yeah, it's. I think it's a great question. 506 00:32:07,100 --> 00:32:10,940 I feel like the, when you look at the fundamentals of 507 00:32:10,940 --> 00:32:14,530 the industry, they won't be changing like and the MSP 508 00:32:14,530 --> 00:32:17,930 industries are all about service quality. It's all 509 00:32:18,090 --> 00:32:21,650 about providing service, first of all service quality. And there's a lot of 510 00:32:21,650 --> 00:32:25,210 probably uncertainty about how the business will evolve. 511 00:32:25,370 --> 00:32:28,769 And I think PAX8 and a lot of players are pushing for that 512 00:32:28,769 --> 00:32:32,490 MIP which is obviously really great into how the 513 00:32:32,490 --> 00:32:36,250 MSPS can evolve into being strategic advisors to their 514 00:32:36,250 --> 00:32:40,050 customers, into uptake technology which obviously includes a lot 515 00:32:40,050 --> 00:32:43,470 of AI. But I feel like 516 00:32:45,310 --> 00:32:48,910 this is a direction where we're going in and this means that 517 00:32:49,150 --> 00:32:52,630 all the tasks to be done will remain the same. It's just that our 518 00:32:52,630 --> 00:32:56,270 customers will want to focus on tasks that have a higher value for them 519 00:32:56,430 --> 00:33:00,030 and this will be all the strategic advisorship for their customers. 520 00:33:00,030 --> 00:33:03,710 They will want to have their best tech players and their best technicians 521 00:33:03,710 --> 00:33:07,310 into advising and upskilling them into advising their own 522 00:33:07,310 --> 00:33:11,010 customers into how to take that AI 523 00:33:11,010 --> 00:33:14,490 turn and leverage AI as much as they can internally. So 524 00:33:14,570 --> 00:33:16,090 we have that opportunity 525 00:33:18,490 --> 00:33:22,050 of having them delegate all their lower value tasks to us and all their service 526 00:33:22,050 --> 00:33:25,890 desk. And this comes into all those agentic 527 00:33:25,890 --> 00:33:28,890 level one, just doing the full level one 528 00:33:29,450 --> 00:33:32,650 agentically and doing a level two in the same ways and really 529 00:33:32,970 --> 00:33:36,480 removing all those lower value tasks so that the msps can focus and where do 530 00:33:36,480 --> 00:33:38,840 they deliver the most values and change 531 00:33:40,200 --> 00:33:44,000 that part from their P and L of the support team or the help 532 00:33:44,000 --> 00:33:47,800 desk from being cost center to being just a cost 533 00:33:47,800 --> 00:33:51,560 of doing business. And they will generate a lot of good revenue out of 534 00:33:51,560 --> 00:33:55,280 that and increase their capacity to generate even more 535 00:33:55,280 --> 00:33:59,120 revenue through the advisorship. So yeah, I certainly think that 536 00:33:59,120 --> 00:34:02,880 is the direction of the industry is sort of a joke that 537 00:34:02,880 --> 00:34:06,440 we're kind of going back to the 90s where there's a lot more consultative work 538 00:34:06,440 --> 00:34:09,900 that's happening where you know the agents can take 539 00:34:10,380 --> 00:34:13,580 care of the a lot of the rote work that 540 00:34:14,060 --> 00:34:16,380 needs to happen still in a lot of environments. 541 00:34:17,820 --> 00:34:21,660 I know you and I have talked about back in the day when working 542 00:34:21,660 --> 00:34:25,180 on compact computers and we had like a, like a self 543 00:34:25,180 --> 00:34:28,860 healing floppy disk that we put into it and this has always been the dream 544 00:34:28,860 --> 00:34:32,460 of like telemetry tells us the things that we need to do. Computers take care 545 00:34:32,460 --> 00:34:35,880 of it by themselves. Right. But, but we're almost there so 546 00:34:36,280 --> 00:34:39,960 it's exciting times for sure. This has been great. Matt, 547 00:34:40,520 --> 00:34:44,040 anything we haven't touched on or any other sort of last minute 548 00:34:44,040 --> 00:34:46,600 topics you want to hit on before we wrap? 549 00:34:48,040 --> 00:34:51,880 No, I think that sums it up. Thanks for that conversation. Thanks for 550 00:34:51,880 --> 00:34:55,680 having me today and I'll. Link to you and Meso in 551 00:34:55,680 --> 00:34:59,240 the show notes as well. Just a quick call out 552 00:34:59,800 --> 00:35:03,000 if people want to hear more about what you do or connect with you. What's 553 00:35:03,000 --> 00:35:05,450 the best place to connect with you and do that? 554 00:35:06,890 --> 00:35:10,650 Yeah, of course you can reach out on LinkedIn or email me at 555 00:35:10,650 --> 00:35:14,370 Mattizl Tech and I'll answer. So happy to chat with 556 00:35:14,370 --> 00:35:17,970 anybody, happy to have conversations around AI, around how to 557 00:35:17,970 --> 00:35:21,570 deploy it in your msp. So looking forward to that. Thanks 558 00:35:21,570 --> 00:35:24,170 Matt. Thanks to you Todd.