1 00:00:00,000 --> 00:00:03,920 Welcome to the Cloud Native in 15 Minutes podcast. If you haven't listened before, 2 00:00:04,040 --> 00:00:08,340 the goal of the podcast is simple, to explain some complex but increasingly important and 3 00:00:08,340 --> 00:00:12,580 even strategic technologies and about the time it takes for a coffee break or a walk, 4 00:00:12,700 --> 00:00:18,000 short walk, a commute, whatever you do in 50 to 20 minutes. So I'm Derek Harris from Pivotal, 5 00:00:18,480 --> 00:00:23,000 and my guest today is Zach Klima from a Detroit-based startup called WaitTime. 6 00:00:23,720 --> 00:00:31,180 And what WaitTime does is it uses imaging and AI to monitor how many people are in line at, 7 00:00:31,440 --> 00:00:36,520 it's focused on sports right now, so how many people are in line at any given concession stand 8 00:00:36,520 --> 00:00:40,040 or how many people are coming in and out of the gates or any number of things. And the goal is 9 00:00:40,040 --> 00:00:44,480 to make a better experience for both, for the fans who can get a sense of like, hey, I should go to 10 00:00:44,480 --> 00:00:48,500 this concession stand or this bathroom line. I'm not going to have to wait as long. And also to give 11 00:00:48,500 --> 00:00:53,520 the venue some sense of traffic and traffic flows and that sort of thing. So it's really interesting, 12 00:00:53,520 --> 00:00:57,120 but specifically, instead of talking about the technology, we talk a lot more about, 13 00:00:57,620 --> 00:01:01,740 you know, building, how Zach went about building this company. And I think it's relevant for, 14 00:01:02,720 --> 00:01:06,220 not just if you're an entrepreneur, it's definitely relevant, especially an entrepreneur based in the 15 00:01:06,220 --> 00:01:13,200 Midwest or based somewhere outside of, you know, the ample access to venture capital and angel 16 00:01:13,200 --> 00:01:17,940 investors, right? So, but also if you're a large company, you know, and especially a large company 17 00:01:17,940 --> 00:01:23,320 based on the coast where you have, you know, a lot more access to technology and a lot more access to 18 00:01:23,320 --> 00:01:28,920 capital is, what are the, what are the ways you might go about looking to get into a new space? 19 00:01:28,920 --> 00:01:33,900 How many go about building out that team? How many go about finding that initial foothold to get 20 00:01:33,900 --> 00:01:38,600 into something new and then expanding it? I think it's from a business perspective, you know, from 21 00:01:38,600 --> 00:01:43,060 startups, even large enterprises, I think it's really insightful. In fact, and one of the ways you'll hear 22 00:01:43,060 --> 00:01:47,980 wait time, got it, got it, got it start from Dan Gilbert, the, of Quicken Loans, who's doing some 23 00:01:47,980 --> 00:01:53,820 stuff, you know, maybe, maybe it's an idea for, if you're an executive for how to start fostering 24 00:01:53,820 --> 00:01:58,580 talent, nurturing, interesting technology in your area with, with some sort of an incubator, but 25 00:01:58,580 --> 00:02:03,260 anyhow, stick around, really interesting. Listen to Zach Klima from wait time now. 26 00:02:05,820 --> 00:02:12,320 Okay, Zach, let's start off with talking about wait time, specifically what is wait time for anyone 27 00:02:12,320 --> 00:02:18,640 that's unfamiliar? Yeah, absolutely. So wait time is an artificial intelligence software company, 28 00:02:19,280 --> 00:02:26,120 focused in sports right now, where we've developed the only patented AI building system technology 29 00:02:26,120 --> 00:02:32,140 that's able to track and record the movement analysis of people in real time. So that's all 30 00:02:32,140 --> 00:02:38,340 concession lines, restroom lines, retail lines. We're also doing ingress and egress, so gate 31 00:02:38,340 --> 00:02:49,540 entrances. And also, um, we just successfully did something with the live monitoring of grandstands. 32 00:02:49,540 --> 00:02:56,200 So basically, you know, the, the seating capacities. So in a nutshell, it's all about the redistribution 33 00:02:56,200 --> 00:02:59,860 of people within an arena or stadium at this point in time. 34 00:03:00,900 --> 00:03:04,080 Very cool. And how'd you come up with the idea? Like what was the conception of this? 35 00:03:04,780 --> 00:03:12,360 Yeah. So I'm a habitually, I'm very impatient. And so, um, I was actually in line at a Detroit 36 00:03:12,360 --> 00:03:18,380 Red Wings game, which is, uh, I'm from Detroit. So the wings are my team. And so I, um, I was in 37 00:03:18,380 --> 00:03:27,540 line, it was a playoff game and it was overtime game seven. And so I, I went in line and to get a 38 00:03:27,540 --> 00:03:33,880 beer or I believe it was to get a beer. Datsuk, Pavel Datsuk, one of my favorite players of all time, 39 00:03:33,940 --> 00:03:39,620 hit a game winning shot. Everyone came running out. There's obviously a sudden death and I'm sitting 40 00:03:39,620 --> 00:03:44,840 there in line, like twiddling my thumbs. And I'm like, you know, you know, son of a gun. If I wish 41 00:03:44,840 --> 00:03:51,040 I would have known what the wait time was before I got up, I would have gone to a separate line and 42 00:03:51,040 --> 00:03:56,580 gotten served faster. So that's where the, like the light bulb went off. And I was like, you know 43 00:03:56,580 --> 00:04:03,860 what? I think that this is a very common problem with everyone. And that goes to sporting arenas 44 00:04:03,860 --> 00:04:09,600 and stadiums. And then also be who likes to wait in line. Like, no, I can, I'll give someone 45 00:04:09,600 --> 00:04:15,500 a ridiculous sum of money that I don't have. If, if they told me and convinced me that they like 46 00:04:15,500 --> 00:04:21,640 way in line. So with those two things, it was kind of a, the stars aligned. I'm okay. This could be 47 00:04:21,640 --> 00:04:26,140 a good idea. And so that's where the initial light bulb went off. 48 00:04:27,220 --> 00:04:30,880 All right. It's interesting. Yeah. I think everyone's been there. I was just at a WNBA 49 00:04:30,880 --> 00:04:35,640 game a while ago and I, and what it got me was I saw people eating better food. I said, well, one, 50 00:04:35,680 --> 00:04:40,320 I didn't even know that thing existed. And two, I only did light for an awful long time with this 51 00:04:40,320 --> 00:04:50,020 nasty pretzel. Yeah. I got to know what's going on here. All right. And when was, and when was this, 52 00:04:50,080 --> 00:04:57,340 when, when did you actually launch the company? So that was in 2000, the, the inception happened 53 00:04:57,340 --> 00:05:05,760 in 2014 and we started to get working, um, 2015. So I had to like, obviously find the right people 54 00:05:05,760 --> 00:05:11,380 to actually build the technology and believe in the vision. So it took me about a year to find those 55 00:05:11,380 --> 00:05:17,360 after I came up with the idea. All right. And 2014. So that was, you know, I'm not sure exactly 56 00:05:17,360 --> 00:05:22,080 what the, what technology you're using, but that was pretty early days for even some of the computer 57 00:05:22,080 --> 00:05:27,860 vision stuff that seems commonplace. Absolutely. Right now. Like, yeah, it was, you know, in processing 58 00:05:27,860 --> 00:05:35,740 power, um, back in those days, um, was not even strong enough to do, as you just said, to do imaging 59 00:05:35,740 --> 00:05:41,340 and, and artificial intelligence in the way that we're doing it. So it wasn't even possible even 60 00:05:41,340 --> 00:05:47,520 before, like, so you talk about perfect timing, right? So it wasn't even possible back then. Um, 61 00:05:47,520 --> 00:05:52,860 but obviously, um, you know, you find the right people. So for example, my, my head of technology 62 00:05:52,860 --> 00:05:58,160 technology is the global leader in imaging. So he owns about half the world market with the 63 00:05:58,160 --> 00:06:04,980 technology he invented about 20 years ago. So his, his, uh, his foresight and his knowledge of how to 64 00:06:04,980 --> 00:06:11,160 make things happen before the really even possible is, uh, it was quite nice. And so, yeah, we, it was a 65 00:06:11,160 --> 00:06:17,300 perfect timing in the market. All right. How, how'd you go about finding talent? I mean, finding your 66 00:06:17,300 --> 00:06:20,940 head of tech maybe, but also finding other people that work a lot. So I know what happens a lot of 67 00:06:20,940 --> 00:06:26,120 times is, you know, anyone who says who has AI in the resume, they, they go off to Google or Facebook 68 00:06:26,120 --> 00:06:30,320 or their companies get acquired by Google or Facebook. And it seems like everyone else is 69 00:06:30,320 --> 00:06:38,640 struggling to, to find talent. Right. So, yeah. So, um, that's a good question. So, um, I had the 70 00:06:38,640 --> 00:06:44,700 opportunity to pitch to, um, the guy who's rebuilding Detroit. His name is Dan Gilbert. 71 00:06:45,060 --> 00:06:52,880 And so Dan put me in his business accelerator in Detroit called wisdom where they accept five 72 00:06:52,880 --> 00:06:59,300 out of like a thousand people to be, to fund their ideas and to kind of like help bring them 73 00:06:59,300 --> 00:07:05,280 to market. And so I did that. I went through this program and I quit my job. I'm an architect 74 00:07:05,280 --> 00:07:12,860 by schooling. I quit my job, which confused my mom, obviously. And I quit my job and I jumped 75 00:07:12,860 --> 00:07:19,220 right in and they take a, I think they gave me like $25,000 and, you know, for a percentage of 76 00:07:19,220 --> 00:07:23,460 your company, you know, like a chunk of your company. And so I was like, great, great deal. 77 00:07:23,540 --> 00:07:29,420 Let's get started. And so, you know, I, I met with all these different entrepreneurs and this network 78 00:07:29,420 --> 00:07:36,120 and I, I listened intently, didn't spend a dime. I listened intently. And so, um, when I did that, 79 00:07:36,120 --> 00:07:41,820 I learned that like, Hey, this is, you know, I think I'm on the right path here. So I met a guy 80 00:07:41,820 --> 00:07:49,920 through that network named Doyle Mosher. So Doyle Mosher is a very well-known entrepreneur in Metro 81 00:07:49,920 --> 00:07:58,840 Detroit. And what his main business is he builds very, very custom high-end homes for very well-known 82 00:07:58,840 --> 00:08:05,800 entrepreneurs and business leaders, um, so on and so forth. So for example, like the Ford family, 83 00:08:05,800 --> 00:08:13,480 the Kennedy family, things like that. And so what he was building a house, uh, quite a large house, 84 00:08:13,480 --> 00:08:20,280 uh, to say the least for a guy by the name of John Mars. So, you know, Doyle started to mentor me 85 00:08:20,280 --> 00:08:25,620 and to kind of like get my pitch deck, right. And, you know, just kind of like the, you know, 86 00:08:25,620 --> 00:08:34,180 the standard stuff. And so, but he was increasingly becoming more interested. And so one day he was 87 00:08:34,180 --> 00:08:38,480 building this house for like five years. And one day he said, Hey Zach, I want to introduce you to 88 00:08:38,480 --> 00:08:43,920 John. Um, I know he made a gazillion dollars in software. I don't know what the software was. 89 00:08:43,920 --> 00:08:50,020 I just want to like run this idea by him that your idea. So I didn't even, I couldn't afford an iPad. 90 00:08:50,020 --> 00:08:56,660 I had a, I literally a binder of Photoshop renderings of my idea. And I'm like, Hey, 91 00:08:56,660 --> 00:09:01,220 this is how it's going to work. We're going to have a sensor above. It's going to track motion 92 00:09:01,220 --> 00:09:06,060 below so on and so forth. So I was explaining to him, I met John, I was explaining my idea to him 93 00:09:06,060 --> 00:09:13,920 and he was kind of finishing my sentences before they're coming out of my mouth. And I was like, 94 00:09:14,140 --> 00:09:19,760 Hmm, I'm gauging interest here. This is good. He's like, Hey Zach, how much money are you 95 00:09:19,760 --> 00:09:25,340 trying to raise? This is at the end of my pitch, quote unquote pitch. And so I'm like, Oh, by my 96 00:09:25,340 --> 00:09:30,240 financial projections, you know, whatever BS they, they teach you at that point in time, which 97 00:09:30,240 --> 00:09:36,020 at that, you know, don't mean anything. And I was like, Oh, I don't know about $3 million. He's 98 00:09:36,020 --> 00:09:40,820 like, okay, forget all that. I'm going to bring on my team that helped me take over the world, 99 00:09:40,820 --> 00:09:46,360 literally. Um, and we're going to, you know, basically I'm going to do this for equity. I'm 100 00:09:46,360 --> 00:09:53,380 going to, you know, um, a mind as beautiful as John's. It's, it's not about money for him. It's, 101 00:09:53,380 --> 00:09:59,180 it's about creating something and you have always has to be creating something. His currency is 102 00:09:59,180 --> 00:10:07,300 creation. And so when that happened, um, things got very real and I was like, okay, well, I, 103 00:10:07,300 --> 00:10:13,580 yeah, that sounds great. You know, there's not much of a sales pitch on his end because I'm like, 104 00:10:13,580 --> 00:10:24,140 clearly this guy can execute. So I was flirting with a lot of very high, um, not, not, not just 105 00:10:24,140 --> 00:10:31,820 network, but like very connected sports individuals that I've been talking to. So for one, um, a guy 106 00:10:31,820 --> 00:10:37,140 named Andrew Craig, who he's really kind of the main advisor of the international Olympic committee. 107 00:10:37,780 --> 00:10:43,080 So he actually has his fifth winning bid, which is Paris, but he negotiates with the cities on how 108 00:10:43,080 --> 00:10:48,840 to win the rights to host the Olympics. And so he, and so, uh, you know, all these people were kind 109 00:10:48,840 --> 00:10:55,300 of for it with me, like, Hey Zach, like great idea. If you can pull this off, like I'm in. And so 110 00:10:55,300 --> 00:11:03,440 when John Mars came on, uh, it became very real. And so at that point in time, that was in 2000 111 00:11:03,440 --> 00:11:11,820 mid 2014. And at that point in time, that's when we officially quote unquote started the company. 112 00:11:11,820 --> 00:11:13,780 I would say when we actually got started. 113 00:11:14,460 --> 00:11:19,240 All right, cool. And where are you at now? How, how, how big is the company? Where do you have 114 00:11:19,240 --> 00:11:25,120 wait time installed? Yeah. So we have about 40 investors now, um, ranging from some of the people 115 00:11:25,120 --> 00:11:30,880 I just talked about to, uh, Michael Jordan's son, his oldest son, Jeff is an investor. So we, we have 116 00:11:30,880 --> 00:11:37,760 some very, um, you know, recognizable figures within the company. And so with that being said, we 117 00:11:37,760 --> 00:11:42,260 internally fund the company. So we didn't take any outside money, um, because of the story I told you 118 00:11:42,260 --> 00:11:47,180 where we were able to internally fund it through our, our CTO is the one that actually can build the 119 00:11:47,180 --> 00:11:54,960 technology. And so, and he's part of the company. So 40 investors were in 12 venues across the world. 120 00:11:55,460 --> 00:12:03,820 So Australia, UK here in the United States, and then soon to be Canada. So three different continents 121 00:12:03,820 --> 00:12:11,600 right now. Um, and the reason why we wanted to kind of grow at a steady pace with the right people 122 00:12:11,600 --> 00:12:18,600 is because we wanted to make the product as perfect as possible and as scalable as possible before we 123 00:12:18,600 --> 00:12:27,340 actually scaled. So with that being said, we wanted to really make sure that everything was bulletproof 124 00:12:27,340 --> 00:12:33,740 and battle tested before we started to really press copy and paste, which we did strategically. 125 00:12:33,740 --> 00:12:41,900 And so now we're at a point in time in the company now where we hit, we do have larger resellers of our 126 00:12:41,900 --> 00:12:48,000 solution, like an IBM to people, uh, other people who are helping position our company across the world 127 00:12:48,000 --> 00:12:56,740 like Cisco, um, you know, within their product set. And so now all of our, you know, me knocking on 128 00:12:56,740 --> 00:13:03,180 doors now has, and it's, it's got a great paradigm shift. A lot of that has changed into a lot of 129 00:13:03,180 --> 00:13:09,620 these leads are now inbound because it's clearly the value proposition is standard across each venue. 130 00:13:09,700 --> 00:13:16,460 Every venue is the same when it comes to this problem. So that's the kind of the point in time 131 00:13:16,460 --> 00:13:17,180 where we're at right now. 132 00:13:17,740 --> 00:13:21,960 All right. And what, what is the user experience? Like what, what does the actual product look like? 133 00:13:22,000 --> 00:13:26,140 I'm, I'm, I'm, my understanding is there's an, there's, if I'm a user, I'm, if I'm going to the 134 00:13:26,140 --> 00:13:30,400 event, I have an app on my phone and then there's software and cameras or sensors set up throughout 135 00:13:30,400 --> 00:13:34,060 the stadium that are, that are basically feeding that app. Is that fair? 136 00:13:34,740 --> 00:13:40,420 Correct. So we mount cameras above every line in the, in the stadium and it basically takes 137 00:13:40,420 --> 00:13:44,840 anonymous screenshots. So we don't see anyone's face, but we take anonymous screenshots from 138 00:13:44,840 --> 00:13:50,540 above. So they're top of their heads, their shoulders and 10 times per second. So those 139 00:13:50,540 --> 00:13:55,960 screenshots are going to our servers that are on site and our servers are custom made that 140 00:13:55,960 --> 00:14:03,660 go on site that process these images at that frame rate of 10 times per second. So that's 141 00:14:03,660 --> 00:14:08,920 how we process the images and get the data from like real time line cows and serve time and 142 00:14:08,920 --> 00:14:16,580 wait time. But then we serve this up to digital signage concourse, digital signage. So that's 143 00:14:16,580 --> 00:14:23,180 where if you walk out of your seat, the first thing that you see is a very large board that 144 00:14:23,180 --> 00:14:28,380 shows you concessions and restrooms in each direction and what the wait times are in that 145 00:14:28,380 --> 00:14:35,460 green, yellow, red spectrum bar analysis. And then also on the team's mobile app. 146 00:14:35,960 --> 00:14:41,940 So we integrate with the team's mobile app. So they're able to see exactly what the wait 147 00:14:41,940 --> 00:14:46,920 times are at their fingertips as well. And that plays into a lot of these teams, mobile 148 00:14:46,920 --> 00:14:52,760 strategies. A lot of these teams are, are really trying to push people to mobile. So that's 149 00:14:52,760 --> 00:14:58,480 a great way to do it is to provide them with information that they need, not even just that 150 00:14:58,480 --> 00:15:04,280 they want. That makes sense. Cool. And so how have you, how have you gone about growing? 151 00:15:04,720 --> 00:15:07,640 Like, like you mentioned, you know, you have, you have a lot more investors now you have, 152 00:15:08,060 --> 00:15:12,180 you've got some critical mass going. What was it, what has it been like growing the team? 153 00:15:12,240 --> 00:15:16,100 Like how big is, is the team you have right now? And how have you, you know, plotted out 154 00:15:16,100 --> 00:15:19,640 growing, you know, an engineering team, right? Or growing, you know, your business. 155 00:15:19,640 --> 00:15:27,280 So the power of John being the foremost leader in imaging is the way that he builds 156 00:15:27,280 --> 00:15:36,140 the technology. So he is, he, it was able to make the technology and automate it as much 157 00:15:36,140 --> 00:15:43,420 as possible. So we actually don't need to build our dev team out really at all, you know, outside 158 00:15:43,420 --> 00:15:51,320 of our core, our core group. So we have about 15 full-time people and we don't really need 159 00:15:51,320 --> 00:15:58,400 to grow as, you know, really much more than that. It doesn't matter if we have 50 venues 160 00:15:58,400 --> 00:16:02,660 or 500 venues, you know, we might grow a little bit more, but we don't necessarily need a lot 161 00:16:02,660 --> 00:16:11,800 of personnel just by the way that John has built the system very intelligently. So yeah, we don't 162 00:16:11,800 --> 00:16:15,760 really need to grow the team out that much. So for us, it's more about strategic partnerships. 163 00:16:16,540 --> 00:16:23,480 So who can help sell and position wait time effectively? That's really where we, you know, 164 00:16:23,480 --> 00:16:24,680 focus most of our energy. 165 00:16:25,520 --> 00:16:32,720 Okay, cool. And then finally, Zach, like what is, I mean, do you have a, do you have an end 166 00:16:32,720 --> 00:16:37,400 goal in mind? I mean, is the end goal like, you know, wait time in every stadium or, you 167 00:16:37,400 --> 00:16:38,940 know, is there an evolution of the product? 168 00:16:39,660 --> 00:16:40,020 Yeah. 169 00:16:40,180 --> 00:16:42,300 Yeah. At some point I'm just curious what we're thinking about. 170 00:16:42,580 --> 00:16:47,520 Yeah. So obviously every stadium, that's the goal. I mean, our, our, you know, the, the 171 00:16:47,520 --> 00:16:54,020 more, the feasible way to get there is to become a building standard. So we, we're now working 172 00:16:54,020 --> 00:17:01,360 with architects and designers, you know, when it comes to speccing our system into these arenas 173 00:17:01,360 --> 00:17:07,240 and stadiums. So we're starting to have those conversations now. So if you go to a stadium 174 00:17:07,240 --> 00:17:11,760 that doesn't have wait time, you're confused, like, Hey, why doesn't this place have wait 175 00:17:11,760 --> 00:17:17,780 time? So that's our, that's our goal when it comes to that, but not even just stadiums, 176 00:17:17,780 --> 00:17:25,140 you know, we have, our AI is so complex and so captivating that there's so much other industry 177 00:17:25,140 --> 00:17:33,600 crossover applicability. So whether it be from retail to, you know, to convention centers, 178 00:17:33,600 --> 00:17:39,980 to you name it, uh, airports, there's a lot of applicability for our software. So, you know, 179 00:17:39,980 --> 00:17:45,800 we might just have the industry that we're in now, which is kind of all pretty much sports. 180 00:17:46,560 --> 00:17:52,100 Um, you know, we see it where there'll be these pillars of the company. So you'll have a sports 181 00:17:52,100 --> 00:17:58,840 division, you'll have a retail division, um, so on and so forth. So that's kind of the way that we see 182 00:17:58,840 --> 00:18:04,560 it going and, you know, acquisition is, you know, is, is probably going to happen down the line, 183 00:18:04,560 --> 00:18:09,660 but not anywhere in the near future, just because we're, we're just scratching the surface on what 184 00:18:09,660 --> 00:18:15,300 we're doing with our technology. And we do have everything protected. We have issued patents, 185 00:18:15,300 --> 00:18:21,920 which is very rare with software, as I'm sure, you know, so that puts us in a good position to win, 186 00:18:22,000 --> 00:18:24,620 um, across a lot of different fronts. 187 00:18:25,920 --> 00:18:29,960 All right. Yeah. And that's really interesting, actually. The, I mean, I got smart, the idea of 188 00:18:29,960 --> 00:18:35,520 branching out because yes, sports is like a limited marketplace. Right. So, so, so you go, 189 00:18:35,640 --> 00:18:39,980 you go elsewhere. Right. And then the idea of the idea of working with architects and doing stuff 190 00:18:39,980 --> 00:18:45,440 at the inset versus trying to retrofit, I think too, like puts that plants, that idea or plants, 191 00:18:45,440 --> 00:18:50,100 that seed at the early stages. Right. So just part of the design. And then it seems more normal, 192 00:18:50,100 --> 00:18:54,640 maybe. That's right. That's right. You know, and, and, um, you know, for us, 193 00:18:54,740 --> 00:19:02,840 you kind of hit on it. It's sports is small, but it's, it's great publicity. So the reason why we 194 00:19:02,840 --> 00:19:08,120 started in sports strategically was to get our name out there. Sports is not the end all be all for 195 00:19:08,120 --> 00:19:14,800 wait time. It's just where you have a captive audience for a nice amount of time. And so with that 196 00:19:14,800 --> 00:19:20,800 being said, it allows us to have basically marketing happen because we get a lot of press with our 197 00:19:20,800 --> 00:19:27,600 solution to get our name out there, to get the attention of other people that can apply our 198 00:19:27,600 --> 00:19:32,840 technology differently in other industries. So that's kind of where, why we started in sports, 199 00:19:32,840 --> 00:19:36,180 which is, um, you know, kind of played out nicely. 200 00:19:36,960 --> 00:19:41,120 All right. Makes sense. Well, with that, we are out of time. Thanks a lot, Zach. Appreciate it. 201 00:19:41,520 --> 00:19:42,600 Awesome. Thank you very much. 202 00:19:43,160 --> 00:19:47,720 All right. There you are. I hope you learned something for more, for more information about 203 00:19:47,720 --> 00:19:52,180 wait time. You can visit its website at, and wait for it. Cause this is not exact. 204 00:19:52,940 --> 00:20:06,380 It's the wait times.com. So T H E W A I T T I M E S.com company's wait time website, the wait times.com. 205 00:20:06,380 --> 00:20:12,180 Okay. And for more information about pivotal and our broad suite of products and services for 206 00:20:12,180 --> 00:20:16,420 building and managing and running cloud native applications, as well as helping you just build 207 00:20:16,420 --> 00:20:21,740 better software, check out pivotal.io. And if you like this podcast and want to keep up with all 208 00:20:21,740 --> 00:20:27,400 things, digital transformation and, and cloud native without, without a lot of sales or product talk, 209 00:20:27,580 --> 00:20:34,980 visit the home of this podcast that is intersect pivotal.io slash intersect. And you can also find 210 00:20:34,980 --> 00:20:39,240 us online at intersect it on Twitter. Thank you.