1 00:00:07,000 --> 00:00:09,600 Speaker 1: Hi everyone, this is Lee Clasgow and we're Talking Transports. 2 00:00:09,600 --> 00:00:13,200 Speaker 1: Welcome to Bloomberg Intelligence Talking Transports podcast. I'm your host, 3 00:00:13,400 --> 00:00:17,520 Speaker 1: Lee Klaskow, Senior Freight Transportation Logistics Analysts at Bloomberg Intelligence, 4 00:00:17,760 --> 00:00:20,680 Speaker 1: Bloomberg's in house research arm of almost five hundred analysts 5 00:00:20,720 --> 00:00:24,120 Speaker 1: and strategists around the globe. A quick public service announcement 6 00:00:24,160 --> 00:00:27,520 Speaker 1: before we dive in. Your support is instrumental to keep 7 00:00:27,560 --> 00:00:31,240 Speaker 1: bringing great guests and conversations to you, our listeners, and 8 00:00:31,320 --> 00:00:34,200 Speaker 1: we need your supports. So please, if you enjoy this podcast, 9 00:00:34,520 --> 00:00:36,040 Speaker 1: share it, like it, leave a comment. 10 00:00:36,400 --> 00:00:37,200 Speaker 2: Also, if you've. 11 00:00:37,120 --> 00:00:39,959 Speaker 1: Got ideas, feedback, or just want to talk transports, I'm 12 00:00:39,960 --> 00:00:42,000 Speaker 1: always happy to connect. You can find me on the 13 00:00:42,040 --> 00:00:44,440 Speaker 1: Bloomberg terminal, on LinkedIn or on x. 14 00:00:44,479 --> 00:00:45,360 Speaker 2: AT Logistics Late. 15 00:00:46,120 --> 00:00:48,559 Speaker 1: Today's episode is something we haven't done before. In this 16 00:00:48,600 --> 00:00:51,120 Speaker 1: episode of Talking Transports, to speak with folks from c 17 00:00:51,320 --> 00:00:56,280 Speaker 1: H Robinson, Ultra Pack Size GOFO, Rebound Returns and bought 18 00:00:56,280 --> 00:01:01,640 Speaker 1: Auto from the Manifest Conference exhibitor hall, where automation dominated 19 00:01:01,720 --> 00:01:08,360 Speaker 1: the discussion. These vendors showcased AI agents, robotics, corrugated box optimization, 20 00:01:08,800 --> 00:01:12,640 Speaker 1: reverse logistics, and autonomous trucking the clear takeaway was that 21 00:01:12,720 --> 00:01:16,520 Speaker 1: supply chain tech adoption is shifting from pilot programs to 22 00:01:16,640 --> 00:01:19,000 Speaker 1: measurable productivity and margin impact. 23 00:01:25,319 --> 00:01:29,840 Speaker 3: It's Lee Glasgow, senior analysts with Bloomberg Intelligence. I'm here with. 24 00:01:30,040 --> 00:01:33,800 Speaker 4: Jim Mancini, vice president of Customer Success for h Robinson. 25 00:01:34,080 --> 00:01:34,399 Speaker 2: Great. 26 00:01:34,959 --> 00:01:37,520 Speaker 3: So we're at Manifest and can you talk about what 27 00:01:37,560 --> 00:01:39,520 Speaker 3: you guys are showcasing today Manifest? 28 00:01:39,680 --> 00:01:41,440 Speaker 5: Yeah, thanks Lee, and this has been a great event 29 00:01:41,480 --> 00:01:42,120 Speaker 5: for us so far. 30 00:01:43,800 --> 00:01:47,280 Speaker 4: What we're really showcasing is how our Lean AI operating 31 00:01:47,280 --> 00:01:51,840 Speaker 4: models coming to life. It's our unique discipline approach to 32 00:01:51,880 --> 00:01:56,160 Speaker 4: applying artificial intelligence to our business. It combines tech expertise 33 00:01:56,200 --> 00:01:59,960 Speaker 4: of our people and the principles of lean continuous improvement. 34 00:01:59,560 --> 00:02:00,600 Speaker 5: In our model. 35 00:02:01,520 --> 00:02:04,120 Speaker 4: It's how we alone use AI to serve our customers. 36 00:02:04,520 --> 00:02:07,880 Speaker 4: And so there's a lot to be said there. What 37 00:02:07,960 --> 00:02:10,639 Speaker 4: we've covered throughout this event is just a lot of 38 00:02:10,639 --> 00:02:13,239 Speaker 4: approof points and values of how this helps our customers. 39 00:02:13,520 --> 00:02:15,600 Speaker 4: So think of things like twenty four to seven service 40 00:02:15,639 --> 00:02:19,560 Speaker 4: capabilities where our agents don't take lunch breaks, they don't 41 00:02:19,560 --> 00:02:21,960 Speaker 4: call in sick to work, they don't have missed opportunities, 42 00:02:21,960 --> 00:02:25,360 Speaker 4: they're always on for us. The speed So if you 43 00:02:25,360 --> 00:02:27,400 Speaker 4: think about all the things that we've done we've talked 44 00:02:27,400 --> 00:02:29,840 Speaker 4: about in the past, or on pricing and taking the 45 00:02:29,919 --> 00:02:33,600 Speaker 4: pricing process that once started to ten minutes to longer 46 00:02:33,680 --> 00:02:35,600 Speaker 4: down to thirty seconds, to be able to return an 47 00:02:35,680 --> 00:02:39,320 Speaker 4: unstructured email with a rate speed to market efficiency and 48 00:02:39,320 --> 00:02:43,360 Speaker 4: how we run our business and delivering productivity gains just 49 00:02:43,360 --> 00:02:47,640 Speaker 4: a better, more reliable output to our customers. We've talked 50 00:02:48,280 --> 00:02:51,880 Speaker 4: yesterday Chris Cutshaw and Cody Griggs talked about the Always 51 00:02:51,880 --> 00:02:54,880 Speaker 4: On Logistics Planner, which is our most recent product we're 52 00:02:54,880 --> 00:02:59,160 Speaker 4: bringing to life, and what they talked about there was 53 00:02:59,639 --> 00:03:03,200 Speaker 4: it's a it's really a digital teammate that sits above 54 00:03:03,240 --> 00:03:06,480 Speaker 4: our purpose built AI agents, our fleet of thirty AI agents, 55 00:03:06,960 --> 00:03:09,679 Speaker 4: and it orchestrates all the complexity and all the workflows 56 00:03:09,680 --> 00:03:11,480 Speaker 4: that go on twenty four to seven in our business. 57 00:03:12,080 --> 00:03:14,280 Speaker 4: It's really valuable right now for our four pl and 58 00:03:14,320 --> 00:03:18,400 Speaker 4: our three PL managed customers. I encourage you, if you 59 00:03:18,440 --> 00:03:20,600 Speaker 4: haven't seen the video, to find the video to take 60 00:03:20,600 --> 00:03:22,200 Speaker 4: a look at it to see some of the specific 61 00:03:22,280 --> 00:03:22,919 Speaker 4: use cases. 62 00:03:23,560 --> 00:03:26,680 Speaker 3: Yeah, the demo that I saw was pretty cool with 63 00:03:26,760 --> 00:03:30,360 Speaker 3: the Walmart loads, just how everything was fully automated and 64 00:03:31,440 --> 00:03:33,640 Speaker 3: not only was a problem solved, but it was able 65 00:03:33,680 --> 00:03:35,880 Speaker 3: to solve at a cheaper rate for the ship er. 66 00:03:35,920 --> 00:03:38,520 Speaker 3: So it was pretty a very pretty interesting use case 67 00:03:38,520 --> 00:03:39,440 Speaker 3: that you guys highlighted. 68 00:03:39,600 --> 00:03:41,720 Speaker 4: Yeah, it goes back to the speed and efficiency that 69 00:03:41,760 --> 00:03:44,760 Speaker 4: I was talking about earlier, where these are things that 70 00:03:44,920 --> 00:03:49,200 Speaker 4: used to take our people minutes, hours, days sometimes that 71 00:03:49,360 --> 00:03:51,520 Speaker 4: now the always on logistics planner can step in and 72 00:03:51,520 --> 00:03:54,120 Speaker 4: solve those in a matter of seconds and really free 73 00:03:54,200 --> 00:03:56,760 Speaker 4: up our people to spend more time working upstream with 74 00:03:56,840 --> 00:04:00,760 Speaker 4: our customers, helping solve more complex problems and more complex challenges. 75 00:04:01,680 --> 00:04:04,240 Speaker 3: And I got to meet a couple of the AI agents, 76 00:04:04,240 --> 00:04:07,520 Speaker 3: So while you guys were demoing Quinn, she seemed really nice. 77 00:04:07,760 --> 00:04:10,520 Speaker 3: She seemed really nice, so maybe we're gonna hear more 78 00:04:10,520 --> 00:04:10,920 Speaker 3: about that. 79 00:04:11,440 --> 00:04:14,640 Speaker 6: Hi, Lee, this is Megan Orth. I'm from H Robinson. 80 00:04:14,680 --> 00:04:16,919 Speaker 6: I'm the senior director of Commercial Connectivity. 81 00:04:17,040 --> 00:04:20,960 Speaker 3: All right, great, can you you know you showcased Quinn 82 00:04:21,040 --> 00:04:23,640 Speaker 3: to me earlier. I thought it was pretty cool. Could 83 00:04:23,640 --> 00:04:25,360 Speaker 3: you talk about the use case for Quinn? 84 00:04:25,480 --> 00:04:25,720 Speaker 2: Sure? 85 00:04:25,839 --> 00:04:28,200 Speaker 6: Yeah, So if you think about the LTL industry, one 86 00:04:28,200 --> 00:04:30,800 Speaker 6: of the biggest problems to solve is mis pickups. So 87 00:04:30,839 --> 00:04:33,080 Speaker 6: you get in in the morning and the shipman should 88 00:04:33,120 --> 00:04:36,200 Speaker 6: have been picked up yesterday. And so when that happens, 89 00:04:36,560 --> 00:04:41,679 Speaker 6: that causes going to websites, calls emails. Right, that takes 90 00:04:41,720 --> 00:04:43,360 Speaker 6: a lot of people a lot of time out of 91 00:04:43,400 --> 00:04:46,120 Speaker 6: their day. So we went and stared down that problem 92 00:04:46,360 --> 00:04:48,080 Speaker 6: and AI was a huge unlock. 93 00:04:47,800 --> 00:04:48,360 Speaker 2: For us there. 94 00:04:48,440 --> 00:04:52,160 Speaker 6: So in the morning we start hitting websites through APIs 95 00:04:52,560 --> 00:04:55,320 Speaker 6: and then we start those calls with Quinn, who you 96 00:04:55,360 --> 00:04:58,960 Speaker 6: got to hear, We get that information, we classify it, 97 00:04:59,200 --> 00:05:02,359 Speaker 6: and then from there, if necessary, we'll send emails to 98 00:05:02,400 --> 00:05:05,440 Speaker 6: the customer letting them know what happened to the shipment 99 00:05:05,520 --> 00:05:08,520 Speaker 6: or when it's been rescheduled. So getting more to that proactive. 100 00:05:09,000 --> 00:05:12,200 Speaker 6: And again this happens within minutes versus something that could 101 00:05:12,240 --> 00:05:14,159 Speaker 6: sit in queues for hours to days. 102 00:05:14,520 --> 00:05:14,680 Speaker 7: Right. 103 00:05:14,800 --> 00:05:18,279 Speaker 3: And when you were showcasing it to me, Quinn called 104 00:05:18,320 --> 00:05:21,160 Speaker 3: a carrier and had a full conversation with one of 105 00:05:21,200 --> 00:05:24,719 Speaker 3: their employees about a miss pickup which was unsolved. And 106 00:05:25,560 --> 00:05:28,200 Speaker 3: you know you mentioned your your AI agents are doing 107 00:05:28,200 --> 00:05:30,880 Speaker 3: one hundreds of these at a time. Uh So the 108 00:05:31,080 --> 00:05:33,680 Speaker 3: the efficiency gains seem pretty incredible. 109 00:05:33,800 --> 00:05:36,880 Speaker 6: Yeah, So ninety five percent of our miss pickups are 110 00:05:36,880 --> 00:05:39,480 Speaker 6: now automated. And a stage is three hundred and fifty 111 00:05:39,520 --> 00:05:42,920 Speaker 6: hours a day, so very impact was your business and 112 00:05:43,480 --> 00:05:44,440 Speaker 6: better sold list. 113 00:05:44,360 --> 00:05:48,039 Speaker 3: Yes, that's a lot of hours in a day, but yeah, 114 00:05:48,080 --> 00:05:50,520 Speaker 3: that's great. Well listen, really want to thank you both 115 00:05:50,520 --> 00:05:53,000 Speaker 3: for your time and have a great Manifest you as well. 116 00:05:53,040 --> 00:05:53,440 Speaker 7: Thank you, Lee. 117 00:05:59,200 --> 00:06:02,480 Speaker 3: This is Lead Class out senior analysts at Bloomberg Intelligence. 118 00:06:02,520 --> 00:06:07,080 Speaker 3: I'm at Manifest. I'm here with Max Freifel, co founder 119 00:06:07,160 --> 00:06:09,839 Speaker 3: of Ultra. All right, and what is Ultra? Because this 120 00:06:09,920 --> 00:06:12,080 Speaker 3: is only audio, there's no videos. So what's Ultra? 121 00:06:12,320 --> 00:06:17,160 Speaker 8: Ultra is a robotics company. We build robots that package 122 00:06:17,520 --> 00:06:20,120 Speaker 8: e commerce orders in warehouses. So if you think of 123 00:06:20,200 --> 00:06:23,839 Speaker 8: like an Amazon warehouse, you know, you're ordering stuff online, 124 00:06:24,320 --> 00:06:26,080 Speaker 8: somebody has to put that into a box or a 125 00:06:26,120 --> 00:06:29,000 Speaker 8: bag and ship it to your door. Our robots drop 126 00:06:29,040 --> 00:06:33,720 Speaker 8: into packstations and we can build boxes, put things into mailers, 127 00:06:33,760 --> 00:06:35,360 Speaker 8: put labels on them, and get them ready to ship 128 00:06:35,400 --> 00:06:35,800 Speaker 8: out the door. 129 00:06:36,000 --> 00:06:36,200 Speaker 7: Yeah. 130 00:06:36,200 --> 00:06:38,080 Speaker 3: So I stopped by your booth because I thought your 131 00:06:38,400 --> 00:06:40,280 Speaker 3: robot was pretty cool. I mean, obviously there's a lot 132 00:06:40,279 --> 00:06:43,440 Speaker 3: of robots here at Manifest. Could you just talk about, 133 00:06:43,480 --> 00:06:45,560 Speaker 3: you know, the market that you're trying to get into 134 00:06:45,600 --> 00:06:47,479 Speaker 3: and kind of where you are right now as a 135 00:06:47,480 --> 00:06:48,520 Speaker 3: company in your growth. 136 00:06:49,200 --> 00:06:52,359 Speaker 7: So we just released our second generation system. 137 00:06:52,680 --> 00:06:57,120 Speaker 8: Our robot is called Operator, and Operator is really focused 138 00:06:57,120 --> 00:07:00,440 Speaker 8: and just designed on e commerce order packaging. So at 139 00:07:00,480 --> 00:07:03,880 Speaker 8: these packout stations there's about one hundred thousand stations in 140 00:07:03,920 --> 00:07:07,839 Speaker 8: the US at warehouses across the country, we can pack 141 00:07:08,080 --> 00:07:12,400 Speaker 8: a variety of items into boxes, bags, mailers, and I 142 00:07:12,640 --> 00:07:14,520 Speaker 8: you know, focusing on that market is about a two 143 00:07:14,560 --> 00:07:17,520 Speaker 8: to three billion dollar market. We're at the beginning of 144 00:07:17,560 --> 00:07:19,960 Speaker 8: our phase. So we have pre orders for our first 145 00:07:20,000 --> 00:07:22,800 Speaker 8: fifteen operators and we're hoping to deploy those over the 146 00:07:22,840 --> 00:07:26,000 Speaker 8: next couple months, with the last one going out in April. 147 00:07:26,560 --> 00:07:29,120 Speaker 3: And who are your like your key customers that you're 148 00:07:29,160 --> 00:07:31,440 Speaker 3: like targeting, Like, what kind of companies are you targeting? 149 00:07:31,640 --> 00:07:35,000 Speaker 8: Yeah, we focus on e commerce three pls, So there's 150 00:07:35,720 --> 00:07:39,640 Speaker 8: a couple thousand, you know, three pls all over the country, 151 00:07:39,680 --> 00:07:45,160 Speaker 8: but a subset of those really focus on e commerce, storage, retrieval, packout. 152 00:07:45,160 --> 00:07:46,600 Speaker 7: And that's our bread and butter right now. 153 00:07:46,680 --> 00:07:50,440 Speaker 3: And the big ones are like GXO, DHL, lot of 154 00:07:50,640 --> 00:07:52,400 Speaker 3: a lot of the big ones are here, you know 155 00:07:52,480 --> 00:07:55,040 Speaker 3: at this conference. DHL has a big arm that does this. 156 00:07:55,160 --> 00:07:57,640 Speaker 3: GXO does a lot of this. A lot of the 157 00:07:57,680 --> 00:08:00,240 Speaker 3: bigger companies do omni channel as well well. 158 00:08:00,320 --> 00:08:03,200 Speaker 8: Right, So you might walk into a GXO warehouse and 159 00:08:03,280 --> 00:08:05,920 Speaker 8: you know, you'll see wholesale and retail pack out going 160 00:08:05,920 --> 00:08:08,640 Speaker 8: to different stores. You'll see an e commerce section that 161 00:08:08,880 --> 00:08:12,600 Speaker 8: you know, really picks up during peak season. And then 162 00:08:12,720 --> 00:08:15,480 Speaker 8: there are some warehouses that are just focused on e 163 00:08:15,520 --> 00:08:17,800 Speaker 8: commerce and this is actually starting to pick up a 164 00:08:17,840 --> 00:08:20,560 Speaker 8: lot with like TikTok and Instagram, there's a lot of 165 00:08:20,600 --> 00:08:21,640 Speaker 8: direct online orders. 166 00:08:21,760 --> 00:08:23,760 Speaker 7: Yeah, and there's warehouses that only do that. 167 00:08:24,240 --> 00:08:26,160 Speaker 3: My son just bought like, I think, one hundred dollars 168 00:08:26,200 --> 00:08:27,600 Speaker 3: worth of shampoo from a TikTok door. 169 00:08:27,680 --> 00:08:28,560 Speaker 5: There you go, There you go. 170 00:08:28,640 --> 00:08:29,360 Speaker 7: Did he get it yet? 171 00:08:29,480 --> 00:08:30,120 Speaker 5: He did get it? 172 00:08:30,160 --> 00:08:30,360 Speaker 2: Great? 173 00:08:30,560 --> 00:08:30,800 Speaker 5: Great? 174 00:08:30,880 --> 00:08:32,520 Speaker 7: I hope he liked it. Yeah. 175 00:08:32,559 --> 00:08:37,240 Speaker 3: So you know this is I'm watching your robot behind me. 176 00:08:37,320 --> 00:08:38,360 Speaker 3: He's building a box. 177 00:08:38,840 --> 00:08:39,000 Speaker 8: Uh. 178 00:08:39,240 --> 00:08:42,800 Speaker 3: It's it's very very cool. You know, where where do 179 00:08:42,880 --> 00:08:46,360 Speaker 3: you see the technology going? You know, you're in your 180 00:08:46,400 --> 00:08:49,080 Speaker 3: third or fourth iteration, and I would suggest you might 181 00:08:49,120 --> 00:08:51,120 Speaker 3: want to call it the logistically as opposed to the 182 00:08:51,160 --> 00:08:52,920 Speaker 3: operator as a name. 183 00:08:53,040 --> 00:08:53,760 Speaker 2: Just a suggestion. 184 00:08:54,280 --> 00:08:56,520 Speaker 7: Thank you, Lee, we'll we'll we'll. 185 00:08:56,360 --> 00:08:58,920 Speaker 3: Consider it all right, great, So where do you see 186 00:08:58,920 --> 00:09:00,920 Speaker 3: this technology going then five years? 187 00:09:01,480 --> 00:09:03,680 Speaker 8: You know, we think we're really at the early phase 188 00:09:03,720 --> 00:09:06,400 Speaker 8: of this. There's a lot of horizon in the future 189 00:09:07,360 --> 00:09:10,120 Speaker 8: to improve the speed, the throughput of what we're doing 190 00:09:10,600 --> 00:09:13,560 Speaker 8: by focusing, you know, for us, by focusing on a 191 00:09:13,600 --> 00:09:17,280 Speaker 8: relatively narrow application, we can focus on performance. So the 192 00:09:17,320 --> 00:09:19,880 Speaker 8: next year for us is all about performance. We want 193 00:09:19,920 --> 00:09:23,000 Speaker 8: to meet and exceed human level performance in terms of 194 00:09:23,040 --> 00:09:28,120 Speaker 8: speed and quality. We've gotten there with bagging, so we're 195 00:09:28,160 --> 00:09:31,480 Speaker 8: packaging bags at two hundred orders an hour. With boxes, 196 00:09:31,520 --> 00:09:34,360 Speaker 8: we're in the forty to fifty range, and so we're 197 00:09:34,400 --> 00:09:37,720 Speaker 8: starting to see that number creep up. The reason that 198 00:09:38,240 --> 00:09:41,839 Speaker 8: kind of happens is, you know, our robot learns through doing, 199 00:09:42,280 --> 00:09:45,400 Speaker 8: and so we record all of the work that we're doing, 200 00:09:45,640 --> 00:09:48,240 Speaker 8: and we can take all of the fastest orders that 201 00:09:48,280 --> 00:09:51,600 Speaker 8: we pack and use that to retrain our model. And 202 00:09:51,640 --> 00:09:54,520 Speaker 8: the AI model gets faster over time as we train it. 203 00:09:54,840 --> 00:09:57,880 Speaker 8: So the next year is about speed. Then we're focusing 204 00:09:57,880 --> 00:10:01,880 Speaker 8: on expanding to other applications outside of order packing. You know, 205 00:10:01,960 --> 00:10:06,040 Speaker 8: the technology as a whole, there's thousands of applications for 206 00:10:06,520 --> 00:10:10,080 Speaker 8: AI powered robots. You know, it's a new way of 207 00:10:10,160 --> 00:10:14,320 Speaker 8: programming robotics. I think the question will be like where 208 00:10:14,320 --> 00:10:17,320 Speaker 8: are the big chunks of work that kind of get 209 00:10:17,360 --> 00:10:19,559 Speaker 8: picked up early, and we think e commerce sort of 210 00:10:19,600 --> 00:10:20,560 Speaker 8: packaging is one of those. 211 00:10:20,800 --> 00:10:23,640 Speaker 3: All right, Maxwell, I really appreciate your time and insights 212 00:10:23,640 --> 00:10:24,680 Speaker 3: and have a great conference. 213 00:10:24,679 --> 00:10:25,080 Speaker 7: Thanks Lely. 214 00:10:30,720 --> 00:10:30,840 Speaker 9: Hi. 215 00:10:30,840 --> 00:10:34,600 Speaker 3: It's Lee Klaskow, Senior Transportation Logistic salils a Bloomberg Intelligence. 216 00:10:34,600 --> 00:10:37,280 Speaker 3: I'm here at Manifest and I'm standing next. 217 00:10:37,080 --> 00:10:41,520 Speaker 9: To Chris Gross with Pack Size, Enterprise sales manager here. 218 00:10:41,559 --> 00:10:44,160 Speaker 3: All right, so this is an audio podcast so people 219 00:10:44,200 --> 00:10:46,200 Speaker 3: can see what is pack size What do you guys do? 220 00:10:47,000 --> 00:10:49,560 Speaker 9: So at pack Size we make equipment that allows people 221 00:10:49,559 --> 00:10:51,800 Speaker 9: to ship every item or every order in a perfect 222 00:10:51,840 --> 00:10:54,280 Speaker 9: size box. We have a bunch of different pieces of 223 00:10:54,320 --> 00:10:57,760 Speaker 9: equipment that we can place hardware, we have the software 224 00:10:57,760 --> 00:10:59,960 Speaker 9: that can run it, and we also sell the core 225 00:11:00,120 --> 00:11:01,040 Speaker 9: get the runs through it. 226 00:11:01,120 --> 00:11:03,920 Speaker 3: Probably people listening to the podcast they probably can relate 227 00:11:03,960 --> 00:11:06,800 Speaker 3: to when you get that Amazon box with like, you know, 228 00:11:06,960 --> 00:11:09,720 Speaker 3: a toothbrush in it, and it's really a really big box. 229 00:11:09,760 --> 00:11:12,840 Speaker 3: So you guys are trying to cut down on waste 230 00:11:12,920 --> 00:11:16,920 Speaker 3: from an environmental standpoint and also helping shippers reduce costs 231 00:11:16,640 --> 00:11:19,800 Speaker 3: on the boxes that they use. Yep, exactly. 232 00:11:19,920 --> 00:11:22,160 Speaker 9: So the nice part of our pack size is we 233 00:11:22,240 --> 00:11:25,200 Speaker 9: kind of hit both the operational savings and sustainability impact 234 00:11:25,240 --> 00:11:25,880 Speaker 9: on the environment. 235 00:11:25,920 --> 00:11:27,959 Speaker 3: Could you give any stats about, like, you know, what, 236 00:11:27,960 --> 00:11:30,800 Speaker 3: what your machines are kind of doe for the industry 237 00:11:31,000 --> 00:11:31,840 Speaker 3: or for shippers. 238 00:11:32,240 --> 00:11:35,000 Speaker 9: Yeah, so it can be a little bit variable depending 239 00:11:35,040 --> 00:11:37,600 Speaker 9: on the industry, but I mean, for the most part, 240 00:11:38,040 --> 00:11:41,560 Speaker 9: I would say we typically save around like twenty six 241 00:11:41,640 --> 00:11:45,680 Speaker 9: percent reduction in corgate use. Probably between sixty and seventy 242 00:11:45,720 --> 00:11:48,319 Speaker 9: percent is the average on void fill use, so the 243 00:11:48,640 --> 00:11:51,000 Speaker 9: paper or plastic filling the space in the box. And 244 00:11:51,040 --> 00:11:53,560 Speaker 9: then on shipping that's where it can get really variable 245 00:11:53,559 --> 00:11:56,480 Speaker 9: if it's larger, small items, probably anywhere you know, five 246 00:11:56,520 --> 00:11:58,360 Speaker 9: to ten percent of I would say it's the average 247 00:11:58,360 --> 00:11:59,040 Speaker 9: that we would see. 248 00:11:59,080 --> 00:12:02,120 Speaker 3: And so I'm a shipper. Do I lease your machines? 249 00:12:02,160 --> 00:12:04,240 Speaker 3: Do I buy your machines either? 250 00:12:04,320 --> 00:12:06,960 Speaker 9: We have a really flexible business model that really is 251 00:12:06,960 --> 00:12:09,400 Speaker 9: designed to help meet customers where they are. You know, 252 00:12:09,520 --> 00:12:12,000 Speaker 9: if a lease model makes more sense, we can look 253 00:12:12,040 --> 00:12:12,280 Speaker 9: at that. 254 00:12:12,480 --> 00:12:15,559 Speaker 3: We also do can seller quick and can you tell 255 00:12:15,559 --> 00:12:16,960 Speaker 3: me just a little bit about the company you gots 256 00:12:17,000 --> 00:12:18,199 Speaker 3: private public. 257 00:12:18,760 --> 00:12:20,880 Speaker 9: Yeah, pack SLID's privately held starting in two thousand and 258 00:12:20,920 --> 00:12:23,079 Speaker 9: two and has been in kind of hyper growth mode, 259 00:12:24,120 --> 00:12:26,560 Speaker 9: you know, for the past twenty five years. 260 00:12:26,720 --> 00:12:27,720 Speaker 5: And where are you guys based? 261 00:12:28,120 --> 00:12:30,120 Speaker 3: Based in Salt Lake City, U tak Okay. And do 262 00:12:30,160 --> 00:12:32,360 Speaker 3: you guys manufacture the machines here in the US? So 263 00:12:32,360 --> 00:12:33,480 Speaker 3: are you importing them in. 264 00:12:33,640 --> 00:12:34,520 Speaker 7: A little bit of both. 265 00:12:34,600 --> 00:12:37,400 Speaker 9: So, but we do have a very large facility in 266 00:12:37,400 --> 00:12:40,000 Speaker 9: Louisville that we just opened in the last year, so 267 00:12:40,040 --> 00:12:41,280 Speaker 9: we're all very excited about that. 268 00:12:41,320 --> 00:12:43,280 Speaker 3: All right, great, And could you just talk about like 269 00:12:43,520 --> 00:12:45,760 Speaker 3: how many machines are deployed roughly? 270 00:12:46,320 --> 00:12:49,200 Speaker 9: Yeah, I mean of thousands throughout the US and Europe, 271 00:12:49,559 --> 00:12:51,400 Speaker 9: but deploying more every single month. 272 00:12:51,480 --> 00:12:53,880 Speaker 3: All right, Well listen, Chris, I really appreciate you taking 273 00:12:53,920 --> 00:12:56,240 Speaker 3: the time in speaking with me. I thought the video 274 00:12:56,280 --> 00:12:58,760 Speaker 3: that you guys behind had behind you of the machines 275 00:12:59,080 --> 00:13:01,160 Speaker 3: creating the boxes, it's pretty interesting, so I wanted to 276 00:13:01,160 --> 00:13:02,080 Speaker 3: share that with the listeners. 277 00:13:02,400 --> 00:13:10,120 Speaker 10: Yeah, awesome, Thanks so much for the interview. Hi, It's 278 00:13:10,200 --> 00:13:15,760 Speaker 10: Lee Klaskal from Bloomberg Intelligence. I'm here with highly Vendomodel, 279 00:13:15,800 --> 00:13:17,840 Speaker 10: here with Gopho. I'm the Chief sales officer. 280 00:13:18,280 --> 00:13:20,760 Speaker 3: All right, great, uh, I was walking past your booth. 281 00:13:20,760 --> 00:13:23,240 Speaker 3: It's quite a nice booth. I like the colors, and 282 00:13:23,280 --> 00:13:25,640 Speaker 3: I never heard of gophos. So could you talk about 283 00:13:25,920 --> 00:13:29,160 Speaker 3: what is gofo? Where are you guys located, and like 284 00:13:29,440 --> 00:13:31,240 Speaker 3: what what kind of services do you provide? 285 00:13:31,679 --> 00:13:35,640 Speaker 11: Golfo is a national last mile service provider specifically focused 286 00:13:35,679 --> 00:13:39,760 Speaker 11: on the e commerce small parcel space. We're fast growth, 287 00:13:39,880 --> 00:13:42,600 Speaker 11: you know, high growth company. You know, a bit of 288 00:13:42,600 --> 00:13:44,640 Speaker 11: a disruptor if you want to call us that, who 289 00:13:45,400 --> 00:13:49,000 Speaker 11: is challenging the national service providers like a FedEx or 290 00:13:49,000 --> 00:13:53,400 Speaker 11: a UPS or maybe a USPS, but specifically focused on 291 00:13:53,400 --> 00:13:55,760 Speaker 11: on small parcel e commerce. 292 00:13:56,000 --> 00:13:57,600 Speaker 5: So you know verticals like. 293 00:13:57,600 --> 00:14:03,040 Speaker 11: Apparel, health and beauty, you know, vitamins, supplements, small consumer 294 00:14:03,080 --> 00:14:07,679 Speaker 11: package goods, small consumer electronics. So we bring to the 295 00:14:07,720 --> 00:14:13,520 Speaker 11: market a more competitive overall solution from from coverage which 296 00:14:13,559 --> 00:14:15,960 Speaker 11: is right now, you know, right around eighty three hundred 297 00:14:16,040 --> 00:14:20,000 Speaker 11: zip codes, which represents about seventy percent of the US population, 298 00:14:21,840 --> 00:14:24,800 Speaker 11: and then we couple that with very aggressive rates and 299 00:14:25,000 --> 00:14:28,360 Speaker 11: strong service to address you know, kind of the the 300 00:14:28,560 --> 00:14:32,560 Speaker 11: growing margin pressure from a lot of these etailers. 301 00:14:31,880 --> 00:14:34,160 Speaker 3: And merchants and brands that are out there. 302 00:14:34,640 --> 00:14:36,120 Speaker 5: We help a lot of three pls. 303 00:14:36,680 --> 00:14:40,240 Speaker 11: These are companies that do fulfillment for e commerce sellers 304 00:14:40,280 --> 00:14:43,120 Speaker 11: and brands and whatnot and just help them to be 305 00:14:43,160 --> 00:14:47,640 Speaker 11: more competitive, win more business, win more merchants. Obviously, while 306 00:14:47,680 --> 00:14:51,160 Speaker 11: while you know, servicing the growing e commerce demand for 307 00:14:51,640 --> 00:14:53,840 Speaker 11: direct to consumer that specific market. 308 00:14:54,080 --> 00:14:55,880 Speaker 3: I was talking to one of your colleagues and he 309 00:14:56,000 --> 00:14:59,120 Speaker 3: was just describing kind of your network. Can you just 310 00:14:59,280 --> 00:15:01,360 Speaker 3: talk about a you know, your your you said your 311 00:15:01,400 --> 00:15:04,040 Speaker 3: asset light, but you do own some assets and you 312 00:15:04,080 --> 00:15:05,000 Speaker 3: do have employees. 313 00:15:05,080 --> 00:15:05,400 Speaker 10: We do. 314 00:15:05,520 --> 00:15:09,000 Speaker 11: We we we run all of the induction facilities, so 315 00:15:09,160 --> 00:15:12,640 Speaker 11: you know, we're doing the scanning, the sorting. We run 316 00:15:12,680 --> 00:15:15,760 Speaker 11: all the line halls to connect all the facilities so 317 00:15:15,800 --> 00:15:18,440 Speaker 11: where you know, again you can think of there's kind 318 00:15:18,440 --> 00:15:21,600 Speaker 11: of two versions, right. There's a true regional player that 319 00:15:21,960 --> 00:15:25,200 Speaker 11: maybe covers one specific part of the country or one 320 00:15:25,240 --> 00:15:28,040 Speaker 11: specific region like a metro or maybe a couple of metros. 321 00:15:28,520 --> 00:15:31,160 Speaker 11: We're more of a national last mile provider where we 322 00:15:31,320 --> 00:15:34,560 Speaker 11: cover forty nine of the fifty top metros. But everything 323 00:15:34,640 --> 00:15:38,880 Speaker 11: is everything is interconnected, so we're managing dedicated line halls 324 00:15:38,920 --> 00:15:42,560 Speaker 11: that connect these regions you know, from from let's say 325 00:15:42,680 --> 00:15:46,640 Speaker 11: LA to Chicago or Dallas, or is that your capacity 326 00:15:46,680 --> 00:15:49,840 Speaker 11: that you're doing the line hall it's contracted line hall, 327 00:15:49,880 --> 00:15:52,200 Speaker 11: but it's dedicated line haulight, right, So that's you know, 328 00:15:52,240 --> 00:15:54,520 Speaker 11: again plays back into that sort of asset light model, 329 00:15:55,880 --> 00:15:59,960 Speaker 11: but it allows us to again to offer a solution 330 00:16:00,120 --> 00:16:02,840 Speaker 11: into the market that is very much in high demand 331 00:16:04,520 --> 00:16:09,600 Speaker 11: and offer a service with a performance that is highly competitive, 332 00:16:09,600 --> 00:16:12,000 Speaker 11: but at the same time bring it to the market 333 00:16:12,160 --> 00:16:15,160 Speaker 11: at at you know, typically rates and pricing that is, 334 00:16:15,960 --> 00:16:18,680 Speaker 11: you know, usually better than many of the other options 335 00:16:18,720 --> 00:16:20,680 Speaker 11: that are out there, right. And the person doing the 336 00:16:20,720 --> 00:16:24,760 Speaker 11: final delivery is that a GOFO employee or is that 337 00:16:24,840 --> 00:16:27,200 Speaker 11: into been a contract. Our model is what we refer 338 00:16:27,320 --> 00:16:30,320 Speaker 11: to as a DSP model, So we are contracting with 339 00:16:30,720 --> 00:16:34,680 Speaker 11: delivery service providers and this is a very common model 340 00:16:34,720 --> 00:16:37,880 Speaker 11: if you think of even even like a FedEx ground 341 00:16:37,880 --> 00:16:40,440 Speaker 11: model or an Amazon model or something like that, where 342 00:16:41,200 --> 00:16:44,720 Speaker 11: you know they are reliant upon DSPs that they contract with. 343 00:16:44,840 --> 00:16:49,160 Speaker 11: Those DSPs either employ on a W two basis or 344 00:16:49,200 --> 00:16:52,400 Speaker 11: maybe a ten ninety nine basis a pool of drivers 345 00:16:52,840 --> 00:16:57,600 Speaker 11: that gives access to delivery capacity. And that's how we 346 00:16:57,680 --> 00:17:02,080 Speaker 11: run our specific point of delivery component. 347 00:17:02,160 --> 00:17:05,280 Speaker 3: Of the network, and so you know, it looks like, 348 00:17:05,320 --> 00:17:07,760 Speaker 3: you know, there's a map behind us of all your locations, 349 00:17:08,600 --> 00:17:11,560 Speaker 3: where aren't you guys? And then I guess where where 350 00:17:11,640 --> 00:17:13,119 Speaker 3: is the next place of growth for you? 351 00:17:14,200 --> 00:17:17,159 Speaker 11: We go where the population density is, right, I mean, 352 00:17:17,200 --> 00:17:19,800 Speaker 11: that's that's very common if you look at you know, 353 00:17:19,880 --> 00:17:24,520 Speaker 11: other similar types of models wherever there's delivery density, you know, 354 00:17:24,560 --> 00:17:27,400 Speaker 11: which is predominantly on. 355 00:17:27,400 --> 00:17:29,280 Speaker 3: The coasts, right east coast, West coast. 356 00:17:29,280 --> 00:17:31,400 Speaker 11: But then in the major markets, I mean we cover 357 00:17:32,800 --> 00:17:35,080 Speaker 11: you know again eighty three hundred and growing. We'll have 358 00:17:35,119 --> 00:17:37,840 Speaker 11: another we'll probably add another thirty five to four thousand 359 00:17:37,960 --> 00:17:40,359 Speaker 11: zip codes this year, which will bring us up to 360 00:17:40,520 --> 00:17:43,320 Speaker 11: north of eighty percent of the population. But it's the 361 00:17:43,400 --> 00:17:45,920 Speaker 11: major metros, you know, if you think of the big cities, right, 362 00:17:46,000 --> 00:17:49,240 Speaker 11: you know, kind of West Coast, La and so Cal, NorCal, 363 00:17:50,440 --> 00:17:56,240 Speaker 11: you know, the Texas market, the Chicago market, Chicago Land obviously, 364 00:17:56,280 --> 00:17:59,520 Speaker 11: the northeast you know, spanning the mid Atlantic and the 365 00:17:59,560 --> 00:18:01,440 Speaker 11: south the way up through the Northeast. 366 00:18:02,640 --> 00:18:04,679 Speaker 5: But those are the you know, kind of core markets, 367 00:18:04,720 --> 00:18:05,160 Speaker 5: if you will. 368 00:18:05,240 --> 00:18:07,199 Speaker 3: Yeah, and so you know you mentioned that, you know, 369 00:18:07,280 --> 00:18:09,399 Speaker 3: you're able to provide a cheaper product than some of 370 00:18:09,440 --> 00:18:11,160 Speaker 3: the larger national and we don't like to. 371 00:18:11,200 --> 00:18:14,200 Speaker 5: Use the word cheap, but but more more cost effective. 372 00:18:14,400 --> 00:18:17,600 Speaker 3: Do you have any like data on like, like what 373 00:18:17,720 --> 00:18:19,920 Speaker 3: percentage are you saving shippers? 374 00:18:20,440 --> 00:18:21,440 Speaker 5: I would say, I. 375 00:18:21,359 --> 00:18:24,359 Speaker 11: Mean, that's a sort of a little bit of a random, 376 00:18:24,720 --> 00:18:26,800 Speaker 11: you know, kind of I give a very random answer. 377 00:18:26,880 --> 00:18:28,920 Speaker 11: But if I was the sort of ballpark it, yeah, 378 00:18:29,000 --> 00:18:30,879 Speaker 11: I would say it would range anywhere from you know, 379 00:18:30,960 --> 00:18:33,200 Speaker 11: fifteen to as much as fifty or more. 380 00:18:33,200 --> 00:18:33,560 Speaker 5: Percent. 381 00:18:33,720 --> 00:18:37,479 Speaker 11: Wow, so very significant depending on the on the spend 382 00:18:37,520 --> 00:18:39,560 Speaker 11: of the of the shipper, whether it's a brand or 383 00:18:39,880 --> 00:18:43,440 Speaker 11: a three pl you know, it could be it could 384 00:18:43,480 --> 00:18:46,160 Speaker 11: be seven, eight digits or more even right, I mean 385 00:18:46,240 --> 00:18:49,840 Speaker 11: there are some very very large e commerce shippers that 386 00:18:49,920 --> 00:18:54,960 Speaker 11: have tremendous spend and obviously those types of shippers you'd 387 00:18:54,960 --> 00:18:58,119 Speaker 11: see a much higher, you know, percent of savings versus 388 00:18:58,119 --> 00:19:01,399 Speaker 11: say a smaller Can you talk about you know, the 389 00:19:01,440 --> 00:19:05,680 Speaker 11: ownership of GOFO. Gofo is a is a New York 390 00:19:05,760 --> 00:19:08,080 Speaker 11: you know, US based New York founded company with ven 391 00:19:08,119 --> 00:19:11,000 Speaker 11: in business since twenty twenty three. Again, you know, high 392 00:19:11,080 --> 00:19:16,240 Speaker 11: growth company. I can tell you that that we're north 393 00:19:16,240 --> 00:19:18,760 Speaker 11: of two million parcels per day, that we're servicing now, 394 00:19:18,760 --> 00:19:23,720 Speaker 11: which is significant certainly and growing fasts. We're seeing a 395 00:19:23,760 --> 00:19:26,280 Speaker 11: lot of demands. You know, there's a lot of interest 396 00:19:26,320 --> 00:19:29,440 Speaker 11: in GOFO again, be it from from you know, a 397 00:19:29,440 --> 00:19:32,080 Speaker 11: brand or a merchant side or or a retail or 398 00:19:32,119 --> 00:19:35,080 Speaker 11: etailor to a lot of the three pls that are 399 00:19:35,080 --> 00:19:35,919 Speaker 11: out there that are. 400 00:19:35,760 --> 00:19:38,000 Speaker 5: Doing e commerce fulfillment for those brands. 401 00:19:38,080 --> 00:19:41,240 Speaker 3: And are you a venture capital, back, private equity, a founder, 402 00:19:41,400 --> 00:19:43,240 Speaker 3: just founders, there's some there's. 403 00:19:43,080 --> 00:19:46,760 Speaker 11: Some private, there's you know, different different investments from some 404 00:19:46,880 --> 00:19:50,240 Speaker 11: different groups that are that comprise the funding overall, and 405 00:19:50,280 --> 00:19:54,360 Speaker 11: then there'll be some additional you know, probably announced funding 406 00:19:54,720 --> 00:19:56,399 Speaker 11: in the near future. 407 00:19:56,520 --> 00:19:58,520 Speaker 3: Okay, great, well, Vincent, thanks so much for your time. 408 00:19:58,560 --> 00:20:01,600 Speaker 3: It was great learning more about. 409 00:20:05,720 --> 00:20:05,800 Speaker 9: This. 410 00:20:05,880 --> 00:20:09,160 Speaker 3: Is Lee Lascow, senior analysts from Bloomberg Intelligence. I'm alive 411 00:20:09,200 --> 00:20:09,879 Speaker 3: at Manifest. 412 00:20:09,920 --> 00:20:10,639 Speaker 5: I'm here with. 413 00:20:11,000 --> 00:20:14,520 Speaker 3: Ilko Is on the megazine director Rebound returns. All right, 414 00:20:14,600 --> 00:20:18,439 Speaker 3: so rebound returns. Obviously you're in reverse logistics. Can you 415 00:20:18,440 --> 00:20:20,600 Speaker 3: talk a little bit about your company. Yeah, sure, we're 416 00:20:20,640 --> 00:20:22,159 Speaker 3: a company specialized in returns. 417 00:20:22,200 --> 00:20:25,000 Speaker 12: They just say it's only ten returns, So anything that 418 00:20:25,080 --> 00:20:28,480 Speaker 12: comes back from eat consumers or retail stores, we handle 419 00:20:28,560 --> 00:20:32,760 Speaker 12: that for brands and different retailers to reduce costs, avoid 420 00:20:33,440 --> 00:20:37,680 Speaker 12: long shipping distances, and with that's also reducing the CO 421 00:20:37,920 --> 00:20:40,440 Speaker 12: two E footprints CARBA footprints. 422 00:20:41,000 --> 00:20:43,440 Speaker 3: Right, And can you talk about so your your customers 423 00:20:43,440 --> 00:20:47,159 Speaker 3: are major apparel brands retailers? Is that that this is 424 00:20:47,200 --> 00:20:47,800 Speaker 3: your customers? 425 00:20:48,040 --> 00:20:52,719 Speaker 12: So, I mean in apparel and foodwear returnerate talk quite high, 426 00:20:52,880 --> 00:20:58,000 Speaker 12: like easily thirty five. And I mean we work with 427 00:20:58,040 --> 00:21:03,960 Speaker 12: brands like Crocs, Michael Course, Hella Hanson, Columbia, So mainly 428 00:21:04,040 --> 00:21:07,399 Speaker 12: kind of sportswear, fashion also some high end fashion. 429 00:21:07,920 --> 00:21:09,840 Speaker 2: And what we can do. 430 00:21:09,760 --> 00:21:13,080 Speaker 12: There is help them with getting their returns back in 431 00:21:13,160 --> 00:21:16,040 Speaker 12: stock asap so they increase their availability. 432 00:21:16,520 --> 00:21:19,040 Speaker 2: And yeah, I mean that's what we do. 433 00:21:19,520 --> 00:21:21,640 Speaker 3: Yeah, So could we talk about the process a little 434 00:21:21,680 --> 00:21:23,600 Speaker 3: bit if you will. So let's just say, buy a 435 00:21:23,640 --> 00:21:26,320 Speaker 3: pair of cocks or too big, I want to return them. 436 00:21:27,040 --> 00:21:28,040 Speaker 3: How do you guys step in? 437 00:21:28,240 --> 00:21:31,159 Speaker 12: Well, first of all, depending on where the consumer sits 438 00:21:31,240 --> 00:21:35,240 Speaker 12: right or is located. So we have thirty five warehouses 439 00:21:35,240 --> 00:21:37,480 Speaker 12: across the globe where we can handle products. 440 00:21:38,520 --> 00:21:41,359 Speaker 2: So whether the consumer sits in New Zealand. 441 00:21:41,480 --> 00:21:46,879 Speaker 12: In Norway or in Alabama, we based on dynamic routing 442 00:21:46,960 --> 00:21:51,200 Speaker 12: we ship that product to the right warehouse. We open boxes, 443 00:21:51,240 --> 00:21:54,440 Speaker 12: we expect items. We can do repairs, we can do 444 00:21:54,480 --> 00:22:00,200 Speaker 12: spot cleaning, steam cleaning, repackaging, just to make sure that 445 00:22:00,240 --> 00:22:03,080 Speaker 12: the item is resellable and in perfect states. 446 00:22:03,960 --> 00:22:05,360 Speaker 2: And that's why brands love us. 447 00:22:05,400 --> 00:22:07,640 Speaker 5: I always wondered that when I returned his shirt, like. 448 00:22:07,600 --> 00:22:10,440 Speaker 3: Do they see you you clean them before you resell them? 449 00:22:11,160 --> 00:22:14,200 Speaker 2: We can do so again based on brand preferences. 450 00:22:14,400 --> 00:22:17,879 Speaker 12: If it's like an almost untouched items and through verification, 451 00:22:17,920 --> 00:22:19,800 Speaker 12: why I didn't find there's no need to invest in 452 00:22:20,119 --> 00:22:21,040 Speaker 12: the refurbishments. 453 00:22:21,600 --> 00:22:22,280 Speaker 2: There's no needs. 454 00:22:22,720 --> 00:22:26,760 Speaker 12: But yeah, we can go as far as steam cleaning, refolding, roning. 455 00:22:27,240 --> 00:22:30,919 Speaker 3: You know, the whole aspect of reverse logistics is not 456 00:22:30,960 --> 00:22:34,600 Speaker 3: only can like save the seller money, but it also 457 00:22:35,080 --> 00:22:37,280 Speaker 3: probably helps the environment a little bit. Can you can 458 00:22:37,320 --> 00:22:38,880 Speaker 3: you talk about you know what you guys do? 459 00:22:39,440 --> 00:22:39,720 Speaker 2: I mean? 460 00:22:39,800 --> 00:22:43,080 Speaker 12: First of all, we try to work with local carriers 461 00:22:43,080 --> 00:22:46,880 Speaker 12: as much as possible in order to keep goods locals. 462 00:22:47,040 --> 00:22:50,080 Speaker 12: We're also invested in the development of our carrier network, 463 00:22:50,560 --> 00:22:55,560 Speaker 12: finding ways to to work with to reduce our couple 464 00:22:55,560 --> 00:23:02,280 Speaker 12: of footprints, work with electrical vehicles in certain cities, and 465 00:23:02,320 --> 00:23:06,600 Speaker 12: that's why brands appreciate our kind of milk carrier network. 466 00:23:07,840 --> 00:23:10,199 Speaker 12: I think another big benefit of working locally is a 467 00:23:10,280 --> 00:23:13,320 Speaker 12: quick refund. So consumers like to get their money back 468 00:23:13,480 --> 00:23:17,040 Speaker 12: but after their return item, and with our setup, we 469 00:23:17,080 --> 00:23:22,120 Speaker 12: can actually enable refunds within a few days, while global 470 00:23:22,119 --> 00:23:25,960 Speaker 12: brands may may struggle with debts in case the ship products. 471 00:23:25,600 --> 00:23:26,600 Speaker 2: All across the globe. 472 00:23:26,920 --> 00:23:28,960 Speaker 12: So I think our local network is really one of 473 00:23:29,000 --> 00:23:32,320 Speaker 12: our unique selling our selling points. 474 00:23:32,400 --> 00:23:35,439 Speaker 3: And what is else is unique with rebound versus your 475 00:23:35,440 --> 00:23:37,480 Speaker 3: competitors out there in this a similar space. 476 00:23:37,359 --> 00:23:41,440 Speaker 13: I'd have to say our tax stack is well advanced, 477 00:23:42,680 --> 00:23:46,800 Speaker 13: so we do a lot of logistics and transportation, but 478 00:23:47,119 --> 00:23:51,520 Speaker 13: we're technology company in the ends, and through our great technology, 479 00:23:52,000 --> 00:23:54,320 Speaker 13: we can steer the supply charea a very efficient way. 480 00:23:55,320 --> 00:23:58,200 Speaker 13: We integrate well with both brands as well with suppliers 481 00:23:58,320 --> 00:24:03,320 Speaker 13: like logistics firms, so it's quite seamless for brands, and 482 00:24:03,600 --> 00:24:09,240 Speaker 13: we work provider agnostic, so we could work with multiple 483 00:24:09,240 --> 00:24:12,760 Speaker 13: different logistics companies or transportation companies. Well for the brand, 484 00:24:12,840 --> 00:24:16,920 Speaker 13: it's just one system, one transportation network. And then yeah, 485 00:24:16,960 --> 00:24:17,639 Speaker 13: I think I think. 486 00:24:17,480 --> 00:24:19,800 Speaker 3: That makes us quite unique, right, And can you talk 487 00:24:19,800 --> 00:24:22,480 Speaker 3: a little bit about your parent company The ownership of it. 488 00:24:22,680 --> 00:24:24,720 Speaker 2: So we're owned by Economy. 489 00:24:25,440 --> 00:24:29,760 Speaker 12: Economy is a two billion firm with a third of 490 00:24:29,920 --> 00:24:34,440 Speaker 12: the revenue coming out of the US. We are folks 491 00:24:34,520 --> 00:24:38,560 Speaker 12: a circularity, so it's all about all the portfolio companies 492 00:24:38,600 --> 00:24:39,080 Speaker 12: are based on. 493 00:24:39,280 --> 00:24:43,000 Speaker 2: Are looking at how to use output. 494 00:24:42,600 --> 00:24:48,080 Speaker 12: Materials as input materials, and that can go for apparel, foodwear, 495 00:24:48,160 --> 00:24:55,359 Speaker 12: but also medical waste and even toxic toxic waste. So 496 00:24:55,400 --> 00:24:59,960 Speaker 12: we're always finding finding ways to create a circular supply check. 497 00:25:00,320 --> 00:25:03,639 Speaker 3: And for rebound, what is the biggest driver for growth? 498 00:25:03,800 --> 00:25:07,240 Speaker 3: Is it just e commerce? Is it share gains because 499 00:25:07,240 --> 00:25:09,960 Speaker 3: of you know, your anti ant to end solutions? What 500 00:25:10,520 --> 00:25:11,600 Speaker 3: kind of fuels the growth? 501 00:25:12,640 --> 00:25:15,080 Speaker 2: I mean there's a couple of growth pillars for us, 502 00:25:15,680 --> 00:25:17,119 Speaker 2: I mean e commerces. You have to stay. 503 00:25:18,040 --> 00:25:19,720 Speaker 12: What we've been seeing in the last couple of years 504 00:25:19,720 --> 00:25:21,960 Speaker 12: the retails really coming back brick and mortar. 505 00:25:22,880 --> 00:25:24,760 Speaker 2: Hence we've been investing quite a bit of our. 506 00:25:24,720 --> 00:25:29,320 Speaker 12: Retail retail solutions, so we we do a lot of 507 00:25:29,400 --> 00:25:33,400 Speaker 12: B t B pickups, so we help brands to keep 508 00:25:33,400 --> 00:25:37,160 Speaker 12: their assortments up to date. We pick up goods from stores, 509 00:25:37,359 --> 00:25:42,040 Speaker 12: bring them back and sell them in other channels. So 510 00:25:42,200 --> 00:25:45,240 Speaker 12: we have border solutions, so buy online, return and store. 511 00:25:45,680 --> 00:25:50,560 Speaker 12: That works very well here. And so we see ecommerce 512 00:25:51,280 --> 00:25:55,040 Speaker 12: developing towards like a marketplace dominated space. Yes, like easily 513 00:25:55,040 --> 00:25:59,120 Speaker 12: seventy percent of all e commerces so via marketplaces. So 514 00:26:00,040 --> 00:26:02,320 Speaker 12: what we're currently working, So we're working with the largest 515 00:26:02,320 --> 00:26:04,920 Speaker 12: marketplaces to build returns integrations. 516 00:26:05,400 --> 00:26:05,800 Speaker 2: So as a. 517 00:26:05,800 --> 00:26:10,240 Speaker 12: Consumer, you still have a seamless returns experience. You don't 518 00:26:10,280 --> 00:26:13,840 Speaker 12: need to work with like multiple parcels being sent back 519 00:26:13,840 --> 00:26:18,040 Speaker 12: to different brands because the marketplace doesn't wanna wanna touch 520 00:26:18,080 --> 00:26:21,400 Speaker 12: the item. Right, So yeah, we are the returns partner 521 00:26:21,440 --> 00:26:22,680 Speaker 12: for marketplace returns. 522 00:26:23,040 --> 00:26:26,400 Speaker 3: All right, great, well listen, I really appreciate the insights 523 00:26:26,400 --> 00:26:28,080 Speaker 3: in your time and have a great conference. 524 00:26:28,200 --> 00:26:28,960 Speaker 7: Thank you very much. 525 00:26:35,160 --> 00:26:39,640 Speaker 8: Hey Slee Glasgow, I am here with Robert Brown named Botato. 526 00:26:40,119 --> 00:26:43,159 Speaker 3: All right, great, So bodado, what is it? 527 00:26:43,400 --> 00:26:44,280 Speaker 7: What old is new? 528 00:26:44,960 --> 00:26:48,560 Speaker 8: We are a self driving truck company asset heavy operating 529 00:26:48,600 --> 00:26:51,520 Speaker 8: transportation as a service for very large shippers. 530 00:26:51,080 --> 00:26:52,080 Speaker 5: And three pls. 531 00:26:52,359 --> 00:26:55,480 Speaker 3: Okay, could you talk about like where you are because obviously, 532 00:26:55,760 --> 00:26:58,600 Speaker 3: uh you know they're not running all over the country. 533 00:26:58,880 --> 00:27:01,800 Speaker 3: Where are you operating, how are you operating and who 534 00:27:01,880 --> 00:27:03,560 Speaker 3: are you operating? For if you can. 535 00:27:03,640 --> 00:27:04,240 Speaker 5: Talk about that. 536 00:27:04,840 --> 00:27:07,600 Speaker 8: I have a few that I can mention publicly. But Lee, 537 00:27:07,680 --> 00:27:09,560 Speaker 8: as we've known you tother for a long time, it's 538 00:27:09,560 --> 00:27:11,879 Speaker 8: a very exciting Thank you for having me on. We 539 00:27:11,920 --> 00:27:15,239 Speaker 8: are based in Houston. Headquartered in Houston. One thing we've 540 00:27:15,320 --> 00:27:17,679 Speaker 8: learned from previous life experiences, I have everyone in the 541 00:27:17,680 --> 00:27:19,720 Speaker 8: boat rowing in the same direction. So that's why we 542 00:27:19,760 --> 00:27:22,600 Speaker 8: moved the start of the company in Houston. And we 543 00:27:22,640 --> 00:27:26,600 Speaker 8: operate between San Antonio and Dallas on the Texas Triangle. 544 00:27:26,960 --> 00:27:31,000 Speaker 8: And and we are a you know, level four technology developer, 545 00:27:31,040 --> 00:27:34,000 Speaker 8: but this time around, we are a transportation company. 546 00:27:35,040 --> 00:27:36,680 Speaker 7: One of our public customers is JB. 547 00:27:36,800 --> 00:27:40,120 Speaker 8: Hunt and their customer Steves and Son out of San Antonio. 548 00:27:40,160 --> 00:27:44,240 Speaker 8: They a large door manufacturer that the sixth generation company, 549 00:27:44,280 --> 00:27:45,840 Speaker 8: and they want to make it to the seventh generation 550 00:27:45,960 --> 00:27:48,560 Speaker 8: and embracing automation is a key component of that. 551 00:27:48,920 --> 00:27:52,679 Speaker 3: So could you talk about so so your some of 552 00:27:52,680 --> 00:27:54,160 Speaker 3: your trucks are fully automated. 553 00:27:54,160 --> 00:27:56,879 Speaker 8: There's there's no there's no driver. Could you talk about 554 00:27:56,880 --> 00:28:00,760 Speaker 8: that evolution? It's really exciting. I mean, and Auto is 555 00:28:00,800 --> 00:28:03,840 Speaker 8: doing this with you know, a very small team. Compared 556 00:28:03,840 --> 00:28:06,960 Speaker 8: to our competitors, we're less than eighty people total, less 557 00:28:07,000 --> 00:28:10,719 Speaker 8: than fifty engineers. And we did, you know, humanless operations 558 00:28:10,760 --> 00:28:13,320 Speaker 8: in and around Houston last year and this year. Our 559 00:28:13,880 --> 00:28:17,600 Speaker 8: goal is to do commercial operations with these humanless trucks 560 00:28:17,600 --> 00:28:20,280 Speaker 8: and actually start making money. And someone that I know 561 00:28:20,320 --> 00:28:22,800 Speaker 8: you've covered this space a long time, is like, it's 562 00:28:22,840 --> 00:28:25,000 Speaker 8: cool to do a humanless operation, it's cool to have 563 00:28:25,080 --> 00:28:27,480 Speaker 8: these pilots, but who's going to make money actually doing this? 564 00:28:28,000 --> 00:28:30,920 Speaker 8: And that's why Shouty and myself and the whole team 565 00:28:30,960 --> 00:28:33,520 Speaker 8: is obsessed with cost per mile and our goal is 566 00:28:33,520 --> 00:28:35,760 Speaker 8: to get that cost per mile in that two dollars 567 00:28:35,840 --> 00:28:37,720 Speaker 8: range where you can start squint and start seeing a 568 00:28:37,760 --> 00:28:38,880 Speaker 8: real business model around this. 569 00:28:39,120 --> 00:28:40,960 Speaker 3: Right, And can you talk about the ownership of the company. 570 00:28:41,000 --> 00:28:42,840 Speaker 5: Are you venture back? Pe back? 571 00:28:43,200 --> 00:28:45,840 Speaker 7: Yeah, we're private, privately held, venture backed. 572 00:28:46,360 --> 00:28:49,000 Speaker 8: We're about to kick off our a round, so if 573 00:28:49,040 --> 00:28:51,360 Speaker 8: any listeners are interested, please reach out on LinkedIn. 574 00:28:52,880 --> 00:28:53,720 Speaker 7: Very excited. 575 00:28:54,840 --> 00:28:57,360 Speaker 8: You know, give kudos to our some of our competitors, 576 00:28:57,400 --> 00:29:00,320 Speaker 8: Wabbi and Kodiak, They've been a good job. I think 577 00:29:00,400 --> 00:29:02,840 Speaker 8: I don't know if it's quite twenty eighteen nineteen with 578 00:29:02,920 --> 00:29:06,040 Speaker 8: the hype cycle, but people, I think I've seen that 579 00:29:06,200 --> 00:29:09,640 Speaker 8: autonomous vehicles are happening, and now it's about the business 580 00:29:09,640 --> 00:29:11,440 Speaker 8: model and then the cost per mile. So I think 581 00:29:11,480 --> 00:29:14,440 Speaker 8: from a market perspective, folks are getting more and more 582 00:29:14,440 --> 00:29:16,920 Speaker 8: interested again in autonomous trucks. 583 00:29:16,640 --> 00:29:19,280 Speaker 3: Right, And I'm assuming the cost per mile decreases the 584 00:29:19,440 --> 00:29:20,600 Speaker 3: longer the length of haul. 585 00:29:20,800 --> 00:29:23,320 Speaker 8: Is that, yeah, And the key component of courses around 586 00:29:23,320 --> 00:29:26,080 Speaker 8: the cost per mile is regularly removing the human driver 587 00:29:26,200 --> 00:29:29,920 Speaker 8: from that component, and then the operational moneies that go 588 00:29:30,000 --> 00:29:32,960 Speaker 8: into supporting that. Of course, your bomb costs on your 589 00:29:32,960 --> 00:29:36,160 Speaker 8: censor suite and compute all those things. Shout out to 590 00:29:36,200 --> 00:29:39,440 Speaker 8: Boston consulting group that put together like an auditible cost 591 00:29:39,480 --> 00:29:41,480 Speaker 8: per mile structure that not just us, but the whole 592 00:29:41,480 --> 00:29:44,200 Speaker 8: industry is starting to use for you folks like yourselves 593 00:29:44,240 --> 00:29:45,600 Speaker 8: to kind of compare apples that. 594 00:29:45,920 --> 00:29:48,680 Speaker 3: Right, And so in Texas you're allowed to operate with 595 00:29:48,720 --> 00:29:52,280 Speaker 3: that without a driver. Are you allowed to operate without 596 00:29:52,280 --> 00:29:53,959 Speaker 3: a driver anywhere else in the United States? 597 00:29:54,120 --> 00:29:56,640 Speaker 8: Yes, pretty much. We have a green field every state 598 00:29:56,680 --> 00:30:00,520 Speaker 8: that touches Ien from Florida minus my old home state 599 00:30:00,560 --> 00:30:03,120 Speaker 8: of California. So all the things of pretty much all 600 00:30:03,160 --> 00:30:07,640 Speaker 8: the southwest southeast are are open and welcoming to autonomous trucks. 601 00:30:07,640 --> 00:30:12,560 Speaker 8: So the regular regulations is much further along than actually 602 00:30:12,560 --> 00:30:13,840 Speaker 8: even the technology at this point. 603 00:30:14,200 --> 00:30:16,360 Speaker 3: And like, you know, obviously you'd love to be growing 604 00:30:16,520 --> 00:30:20,000 Speaker 3: like a million percent every day, but like what is 605 00:30:20,000 --> 00:30:22,200 Speaker 3: the growth trajectory because this is like, you know, it's 606 00:30:22,240 --> 00:30:26,480 Speaker 3: a new technology. You're you're kind of really really like 607 00:30:26,720 --> 00:30:30,880 Speaker 3: changing the way trucking companies operate to be incredibly transparent. 608 00:30:30,920 --> 00:30:33,000 Speaker 8: We have twelve trucks, so we're not, you know, a 609 00:30:33,000 --> 00:30:34,360 Speaker 8: major carrier, but we're growing. 610 00:30:34,480 --> 00:30:36,880 Speaker 3: It's twelve more than May. Yeah, we'll get the twenty 611 00:30:36,960 --> 00:30:37,360 Speaker 3: or thirty. 612 00:30:37,600 --> 00:30:39,200 Speaker 8: What we've learned in the past is we don't want 613 00:30:39,240 --> 00:30:41,360 Speaker 8: to be the micro Scott paper company where every load 614 00:30:41,400 --> 00:30:43,880 Speaker 8: we're losing our shirt, you know, and you can't make 615 00:30:43,880 --> 00:30:44,600 Speaker 8: it up on volume. 616 00:30:44,680 --> 00:30:44,840 Speaker 2: Right. 617 00:30:45,640 --> 00:30:48,480 Speaker 8: So, and we've learned all these like interesting and fun 618 00:30:48,560 --> 00:30:51,600 Speaker 8: lessons in the past. Is like before, you know, solve 619 00:30:51,680 --> 00:30:54,200 Speaker 8: the problem of cost a mile before you scale. And 620 00:30:54,240 --> 00:30:56,960 Speaker 8: then once we've solved that, that's when we scale, tap 621 00:30:57,000 --> 00:30:59,280 Speaker 8: public markets and grow this technology nationwide. 622 00:30:59,560 --> 00:31:02,040 Speaker 3: And right now, now, what is the best use case 623 00:31:02,120 --> 00:31:05,320 Speaker 3: for an autonomous truck with no driver at it? 624 00:31:05,920 --> 00:31:09,240 Speaker 8: Anything with high density and volume and consistent. The robot 625 00:31:09,400 --> 00:31:11,600 Speaker 8: likes to do something over and over again. That's what's 626 00:31:11,680 --> 00:31:14,960 Speaker 8: really good about. So, you know, Texas Triangle is great, 627 00:31:15,000 --> 00:31:16,920 Speaker 8: but obviously we would love to get up beyond hours 628 00:31:16,960 --> 00:31:20,240 Speaker 8: of service, you know, open markets like Atlanta and Memphis. 629 00:31:20,240 --> 00:31:23,640 Speaker 8: You know from Houston, Laredo is a great market as well. 630 00:31:23,720 --> 00:31:26,240 Speaker 8: So just like those longer links, to haul that tweet 631 00:31:26,280 --> 00:31:29,120 Speaker 8: er freight over four hundred miles is obviously ideal for 632 00:31:29,160 --> 00:31:29,920 Speaker 8: a robot to do. 633 00:31:30,280 --> 00:31:32,800 Speaker 3: And you know I asked you just earlier, but like 634 00:31:33,040 --> 00:31:37,080 Speaker 3: you know, so from a liability standpoint, could you just 635 00:31:37,120 --> 00:31:40,640 Speaker 3: talk about, like you know, God forbid something happens, who's 636 00:31:40,680 --> 00:31:41,160 Speaker 3: on the hook. 637 00:31:41,440 --> 00:31:43,360 Speaker 8: And that's a beauty of our model is we are 638 00:31:43,440 --> 00:31:45,720 Speaker 8: a We operate under our own dot authority, just like 639 00:31:45,760 --> 00:31:49,320 Speaker 8: any other trucking company would. We're a carrier and so 640 00:31:49,360 --> 00:31:51,640 Speaker 8: we we actually announced it a kind of a collab 641 00:31:51,680 --> 00:31:53,680 Speaker 8: with marsh Or I'm sure, and you know we work 642 00:31:53,720 --> 00:31:56,760 Speaker 8: with our underwriters, so that helps us when we're talking 643 00:31:56,760 --> 00:32:00,600 Speaker 8: to customers is like we're not outsourcing or giving them 644 00:32:00,640 --> 00:32:03,680 Speaker 8: a software product for them to operate and maintain. Our 645 00:32:03,800 --> 00:32:06,120 Speaker 8: KPIs are just like any other trucking company. But our 646 00:32:06,160 --> 00:32:08,360 Speaker 8: superpower is you know, we don't have a human in 647 00:32:08,400 --> 00:32:09,440 Speaker 8: the truck, right. 648 00:32:10,040 --> 00:32:12,480 Speaker 3: But but they're also you know, your robots don't have 649 00:32:12,480 --> 00:32:15,040 Speaker 3: to worry about non domicile CDLs or anything like that 650 00:32:15,160 --> 00:32:18,240 Speaker 3: or and so you know what would happen if, you know, 651 00:32:18,520 --> 00:32:21,880 Speaker 3: if one of these trucks blew a tire, Like you know, 652 00:32:21,960 --> 00:32:24,320 Speaker 3: I don't know everything, but like I know, like when 653 00:32:24,320 --> 00:32:26,720 Speaker 3: a truck has to pull over, they have to put 654 00:32:26,720 --> 00:32:30,959 Speaker 3: out cones. From a safety perspective, So what does an 655 00:32:31,000 --> 00:32:33,880 Speaker 3: autonomous truck do that has no driver in the cab, 656 00:32:34,280 --> 00:32:35,520 Speaker 3: you know, if it gets a flat. 657 00:32:35,720 --> 00:32:38,560 Speaker 8: Yeah, so we have sensors both on tractor and trailer 658 00:32:38,720 --> 00:32:42,400 Speaker 8: to help solve that problem. And then the most famous 659 00:32:42,440 --> 00:32:44,800 Speaker 8: regulatory hurdle of all time the who's going to put 660 00:32:44,800 --> 00:32:45,600 Speaker 8: the cones out? 661 00:32:46,040 --> 00:32:49,280 Speaker 7: This administration's FMCSA, through. 662 00:32:49,120 --> 00:32:51,440 Speaker 8: Working with what Aurora and WEIMO did and also the 663 00:32:51,440 --> 00:32:56,320 Speaker 8: Autonomous Vehicle Industry Association created us a path to basically 664 00:32:56,360 --> 00:33:00,440 Speaker 8: do a safety prevalency of that. So any you've talked 665 00:33:00,440 --> 00:33:02,240 Speaker 8: to actually human driven trucking companies, some of the most 666 00:33:02,320 --> 00:33:03,760 Speaker 8: dangerous thing you can do is get out on the 667 00:33:03,800 --> 00:33:06,000 Speaker 8: highway and had that poor driver put out those cones. 668 00:33:06,280 --> 00:33:09,680 Speaker 8: So having a lighting alternative that actually increases safety, not 669 00:33:09,720 --> 00:33:12,360 Speaker 8: just for autonomous trucks, but even for human driven trucks. 670 00:33:12,400 --> 00:33:14,360 Speaker 3: And so when people think of your company about auto 671 00:33:14,480 --> 00:33:17,880 Speaker 3: like what what is what do are you guys just 672 00:33:18,120 --> 00:33:20,720 Speaker 3: the software? Are you like the things that are on 673 00:33:20,800 --> 00:33:23,360 Speaker 3: the truck to make it self driving? Those are things 674 00:33:23,400 --> 00:33:26,400 Speaker 3: you're buying from third parties? Or do you manufacture these things? 675 00:33:26,440 --> 00:33:28,719 Speaker 3: Like talk about like what makes it a uh you 676 00:33:28,720 --> 00:33:29,520 Speaker 3: know what are your truck? 677 00:33:29,640 --> 00:33:29,840 Speaker 5: Yeah? 678 00:33:29,880 --> 00:33:33,680 Speaker 8: What makes a bout auto unique is as a transportation company, 679 00:33:33,920 --> 00:33:36,240 Speaker 8: we obviously upfit the trucks with all the sensor sweet 680 00:33:36,320 --> 00:33:38,960 Speaker 8: those are all from you know, commercial off the self 681 00:33:38,960 --> 00:33:41,760 Speaker 8: the type of purchase. We of course develop the virtual driver, 682 00:33:41,840 --> 00:33:45,480 Speaker 8: the bought auto driver, which is our core competency, and 683 00:33:45,520 --> 00:33:47,920 Speaker 8: then operate those trucks like any other trucking company would 684 00:33:47,960 --> 00:33:48,760 Speaker 8: without the human in it. 685 00:33:49,080 --> 00:33:53,560 Speaker 3: And so for the autonomous trucking in your view, when 686 00:33:53,600 --> 00:33:57,040 Speaker 3: do you really think it really penetrates the market where 687 00:33:57,080 --> 00:33:58,719 Speaker 3: you get to see the growth because you know, we've 688 00:33:58,760 --> 00:34:02,400 Speaker 3: been talking about autonomous show for a long time. You know, obviously, 689 00:34:02,400 --> 00:34:05,560 Speaker 3: I think a lot of people believe in the technology. 690 00:34:06,160 --> 00:34:08,839 Speaker 3: H it's just the adoption of the technology, So could 691 00:34:08,880 --> 00:34:12,799 Speaker 3: you talk about you know, are we talking about you're 692 00:34:12,800 --> 00:34:14,880 Speaker 3: not going to see a lot of autonomous trucks in 693 00:34:14,920 --> 00:34:17,200 Speaker 3: the next two years five years to you like what? 694 00:34:17,320 --> 00:34:20,040 Speaker 7: Yeah, I mean, it depends on what everything is relative. 695 00:34:20,120 --> 00:34:23,200 Speaker 8: Right when if we become a twenty thousand truck carrier, 696 00:34:23,360 --> 00:34:25,920 Speaker 8: we're still talking less than one percent of market share, 697 00:34:26,200 --> 00:34:28,480 Speaker 8: but that's again a multi billion dollar company. 698 00:34:28,560 --> 00:34:31,040 Speaker 7: So and I think it's you know, similar to Weymo. 699 00:34:31,120 --> 00:34:32,759 Speaker 8: And if someone's been in this industry a long time 700 00:34:32,800 --> 00:34:34,279 Speaker 8: that you know, people used to clown on m oh 701 00:34:34,320 --> 00:34:37,160 Speaker 8: they're in a suburb of Scottsdale, and then all you know, 702 00:34:37,200 --> 00:34:38,520 Speaker 8: and they're in the Bay Area, and then they're in 703 00:34:38,640 --> 00:34:40,359 Speaker 8: LA and then there's you know, and then like all 704 00:34:40,360 --> 00:34:42,600 Speaker 8: of a sudden, now they're in a ton of cities. 705 00:34:42,640 --> 00:34:45,080 Speaker 8: And I think you'll see that same adoption for trucking 706 00:34:45,080 --> 00:34:48,400 Speaker 8: and be certain lanes, certain states and certain types of 707 00:34:48,400 --> 00:34:51,000 Speaker 8: loads and and then you know, fast forward ten years 708 00:34:51,040 --> 00:34:53,160 Speaker 8: from now, they'll be ubiquitous and be normal, just like 709 00:34:53,320 --> 00:34:54,600 Speaker 8: the weymos are in those cities. 710 00:34:54,680 --> 00:34:56,600 Speaker 3: All right, Well, you know, we see each other of 711 00:34:56,600 --> 00:34:59,320 Speaker 3: a year at Manifest, So hopefully I'll see in the 712 00:34:59,320 --> 00:35:00,160 Speaker 3: next ten years thank you. 713 00:35:01,200 --> 00:35:02,480 Speaker 1: I want to thank you for tuning in and I 714 00:35:02,560 --> 00:35:06,080 Speaker 1: hope you enjoy these diverse conversations I had at Manifest. 715 00:35:06,120 --> 00:35:08,480 Speaker 1: If you liked the episode, please subscribe. 716 00:35:07,960 --> 00:35:08,800 Speaker 5: And leave a review. 717 00:35:09,120 --> 00:35:11,400 Speaker 1: We've lined up a number of great guests for the podcast, 718 00:35:11,440 --> 00:35:16,080 Speaker 1: so please check back to your conversations with Ceascreet executives, shippers, regulators, 719 00:35:16,120 --> 00:35:18,960 Speaker 1: and decision makers within the freight markets. Also, if you 720 00:35:18,960 --> 00:35:22,200 Speaker 1: want to learn more about freight transportation markets, check out 721 00:35:22,200 --> 00:35:24,600 Speaker 1: our work on the Bloomberg Terminal at big and on 722 00:35:24,640 --> 00:35:27,719 Speaker 1: social media. This is Lee Klasgal signing off and thanks 723 00:35:27,760 --> 00:35:29,000 Speaker 1: for talking transports with me. 724 00:35:29,200 --> 00:35:29,839 Speaker 5: Talk to you soon.