Meeting Title: Uttam <> Shaun—Curri-Data-Chat Date: 2024-05-10 Meeting participants: Shaun Sims, Uttam Kumaran
WEBVTT
1 00:02:44.200 ⇒ 00:02:44.870 Shaun Sims: Hey? What’s up, man?
2 00:02:44.870 ⇒ 00:02:46.399 Uttam Kumaran: Hey! How are you?
3 00:02:46.670 ⇒ 00:02:48.060 Shaun Sims: I’m good. How are you doing.
4 00:02:48.210 ⇒ 00:02:50.730 Uttam Kumaran: Good. I like your room. It’s so nice.
5 00:02:51.120 ⇒ 00:02:57.469 Shaun Sims: My daughter’s room. I usually usually take this down. I just I always forget on my first call today. So I’m like.
6 00:02:57.470 ⇒ 00:03:02.784 Uttam Kumaran: Oh, it looks so pleasant it looks like I don’t know. I feel like relaxed just seeing you there.
7 00:03:03.050 ⇒ 00:03:06.773 Shaun Sims: Yeah, I like it. I I I think it makes me more approachable.
8 00:03:07.060 ⇒ 00:03:12.272 Uttam Kumaran: Yes, yeah. You’re like about to fire someone, but you’re in your daughter’s room.
9 00:03:12.620 ⇒ 00:03:15.129 Shaun Sims: They’d be like dude. That guy’s a real butt head.
10 00:03:17.816 ⇒ 00:03:18.950 Uttam Kumaran: How’s everything?
11 00:03:18.950 ⇒ 00:03:23.669 Shaun Sims: It’s good man. No, it’s good. I I was excited to to chat with you this morning, and I think
12 00:03:23.730 ⇒ 00:03:40.399 Shaun Sims: I I know we pushed it out, but I think we could probably have a better conversation now. Just mo more more progress internally on our side in terms of what we’ve been able to kind of it like in in terms of just like narrowing down the problem right? That we’re trying to solve. So.
13 00:03:40.620 ⇒ 00:03:44.157 Shaun Sims: But no, everything’s good man. I’m still really enjoying working at Curry. It’s
14 00:03:44.430 ⇒ 00:03:45.070 Uttam Kumaran: Grade.
15 00:03:45.380 ⇒ 00:03:47.170 Shaun Sims: Yeah, it’s good. It’s a
16 00:03:47.330 ⇒ 00:03:49.171 Shaun Sims: I like the culture, it’s
17 00:03:49.960 ⇒ 00:04:01.540 Shaun Sims: it. It gets pretty intense, as like, you know, pretty much every startup can be but like it, it’s hard to describe, but it’s like periods of intensity. And then also, like periods where, like, you have a break like it’s like.
18 00:04:01.680 ⇒ 00:04:06.809 Shaun Sims: and I think I think it aligns with, like. Our customers, like most of our customers, are doing like deliveries.
19 00:04:06.860 ⇒ 00:04:13.440 Shaun Sims: you know, starting at, you know, 6 central. But then they start to kind of wind down around like 3 central. So
20 00:04:13.520 ⇒ 00:04:20.370 Shaun Sims: it feels like you can like go home, you know, and like not have to think about things. 7, which is nice.
21 00:04:20.370 ⇒ 00:04:25.279 Uttam Kumaran: And so is it, you mean periods of density like even in intra day periods not? Or is it more like
22 00:04:25.560 ⇒ 00:04:29.409 Uttam Kumaran: we have like a month where it’s like if something new launching.
23 00:04:29.410 ⇒ 00:04:44.425 Shaun Sims: It’s it’s but well, so it’s both. It’s there. There’s that sort of overarching like, Hey, we’re we’re trying to like ship new products, new features. That’s sort of. But then also intra day like it, there’s definitely and part of it, too, is like most of our employees are on
24 00:04:45.000 ⇒ 00:04:47.410 Shaun Sims: like out in California central coast. So it’s like.
25 00:04:47.410 ⇒ 00:04:48.020 Uttam Kumaran: Yeah.
26 00:04:48.280 ⇒ 00:04:52.420 Shaun Sims: You know, when they and and like we’re all on slack. So it just feels like.
27 00:04:52.570 ⇒ 00:04:57.109 Uttam Kumaran: When they wake up you get the yeah slack is the I would say, slack
28 00:04:57.400 ⇒ 00:05:00.740 Uttam Kumaran: is the problem, because I have a big like.
29 00:05:01.020 ⇒ 00:05:06.049 Uttam Kumaran: I have a lot of rules, and like how I use slack like, I don’t have any notifications or anything, because
30 00:05:06.180 ⇒ 00:05:14.250 Uttam Kumaran: I’m someone who like has to go see everything, especially now that it’s like it’s my company. But even before I was running a team and everything and it’s like
31 00:05:14.290 ⇒ 00:05:17.050 Uttam Kumaran: you get so and you don’t, can’t prioritize.
32 00:05:17.428 ⇒ 00:05:31.140 Uttam Kumaran: It’s very, very difficult. And so yeah, I mean, I totally get that. That’s good, though, that you feel like there’s downtime, because I’ve been in organizations where it’s like one thing after another after another. And you basically like, just have to pull the plug
33 00:05:31.480 ⇒ 00:05:34.596 Uttam Kumaran: and something drops. You basically have to just drop a ball.
34 00:05:34.880 ⇒ 00:05:41.220 Shaun Sims: Exactly. Yeah, I don’t know. I yeah, I’m sure we’ll get to that point. I I think it’s also like
35 00:05:41.260 ⇒ 00:05:43.959 Shaun Sims: just the point in my career where I
36 00:05:44.060 ⇒ 00:05:52.943 Shaun Sims: I know, like I’m happy with my productivity. And it’s like I feel like it’s more than most in a lot of cases. So I I just you know it’s
37 00:05:53.240 ⇒ 00:05:57.350 Uttam Kumaran: You do what you can, and you’re like, leave it for tomorrow. Yeah.
38 00:05:57.350 ⇒ 00:05:57.876 Shaun Sims: It’s right.
39 00:05:58.530 ⇒ 00:06:05.503 Shaun Sims: I think I think having a family helps as a forcing function with that. And our factors have families which which helps
40 00:06:06.030 ⇒ 00:06:09.409 Shaun Sims: you know I I not nothing against like young founders, but I think.
41 00:06:09.410 ⇒ 00:06:10.350 Uttam Kumaran: Like no no.
42 00:06:10.350 ⇒ 00:06:18.829 Shaun Sims: Working for like a 20 year old, which was like I was interviewing with several companies. I’m like, when I was 20 I had 0 empathy or sympathy.
43 00:06:18.830 ⇒ 00:06:19.410 Uttam Kumaran: Yeah.
44 00:06:19.410 ⇒ 00:06:22.574 Shaun Sims: And so I’m like, so what that you have a kid? I don’t care.
45 00:06:23.084 ⇒ 00:06:26.495 Uttam Kumaran: I know, I know, but also I just think some people they
46 00:06:26.840 ⇒ 00:06:36.110 Uttam Kumaran: like, if and it’s also hard to shift out of that like I’ve it’s it’s hard to be like that. And then, even when things go well to be like cool, this is when we lay off
47 00:06:36.441 ⇒ 00:07:04.649 Uttam Kumaran: a lot of people like, no, this is what we like. Lay it back on. And I I think that’s also kind of like a San Francis like, it’s definitely like a New York mindset but in in, if you’re in New York, it’s one thing. But in San Francisco, yeah, I just think, like everybody’s like pushing so hard. That’s also why I like move to Austin, because, like lifestyle, wise is so much better. And I’m also I know that there’s periods of time where you need to get something done, or there’s something on fire. But there also is the equivalent time to just like.
48 00:07:04.690 ⇒ 00:07:07.529 Uttam Kumaran: Hey, like, let’s just cancel meetings today, or like.
49 00:07:07.660 ⇒ 00:07:13.889 Uttam Kumaran: you know, you kind of need that even for me. I really, I don’t want to be on the phone all day takes a lot of energy for me. So.
50 00:07:13.890 ⇒ 00:07:14.860 Shaun Sims: It does. It does.
51 00:07:14.860 ⇒ 00:07:15.470 Uttam Kumaran: Yeah.
52 00:07:15.470 ⇒ 00:07:18.469 Shaun Sims: Well, cool man. Well, yeah. Happy to kind of like.
53 00:07:18.870 ⇒ 00:07:19.400 Uttam Kumaran: Yeah.
54 00:07:19.400 ⇒ 00:07:36.004 Shaun Sims: With what we’re doing, and and see if there’s areas where May. Maybe you could plug in let me see where to start. And I I think sharing screen will help to just kind of like visualize it so. But maybe I can just like describe it high level, and then I’ll show you some visuals to maybe help like, bring it in.
55 00:07:36.260 ⇒ 00:07:55.019 Shaun Sims: So okay, so the the problem that we’re trying to solve right? So so actually, before I get there just a refresher on curry right? And who our customers are. So curry today really focuses on last mile delivery within construction and industrial verticals. So what that means is.
56 00:07:55.020 ⇒ 00:08:12.579 Shaun Sims: most of our customers are distributors. So you know, I don’t know if you’ve had a like Hvac issues, or but like th some popular names that you see driving around town, or like stands or radiant. And th those those folks are the ones that like
57 00:08:12.580 ⇒ 00:08:26.624 Shaun Sims: kind of come to your house. They will like install a new Hvac system, for example. So we would actually work with the people that they procure that from or or like, so like the in distributors of that equipment. So not not always the oems.
58 00:08:26.930 ⇒ 00:08:39.020 Shaun Sims: but like oem distributors. And then you know the radiance and stands right. And so basically, we have a network of I don’t know. 10,000,
59 00:08:39.150 ⇒ 00:09:00.350 Shaun Sims: you know, different carriers and or gig drivers that help our customers. The distributors kind of augment their own fleet. So when their own fleets kind of get maxed out right, for whatever reason, like demand outstrips their ability that they’re resourcing, they’ll call curry to like. Say, Hey, I gotta get this out to a customer right? So that that’s kind of like the core business. Now
60 00:09:00.730 ⇒ 00:09:28.189 Shaun Sims: we’re evolving as a company. So this is like part of the like. What I’m leading internally is, we have this like really great marketplace. It’s been running and operating for 5 years. What we’re trying to do now is say, Hey, this software that we’ve built to power our delivery network is also valuable to our customers to help them power their own fleets right? So a lot of these distributors, they have their own trucks right? But they don’t necessarily have the best software for like managing logistics, routing
61 00:09:28.589 ⇒ 00:09:58.090 Shaun Sims: and and so forth. And so one of the specific initiatives that we’re working on. And I’m I’m kind of like starting abstract. And then I’m narrowing down. So one of the specific initiatives that we’re working on is helping them basically plan their routes. Right? So hey, I’ve I’m a I’m a distributor branch and I’ve got. Let’s just keep it simple. Let’s say I’ve got, you know, 5 trucks. Each of them do call it 8 deliveries a day. Right? So what’s the most efficient way for me to sort of like, get those drivers to go? Do those deliveries
62 00:09:58.090 ⇒ 00:09:58.810 Shaun Sims: now?
63 00:09:59.290 ⇒ 00:10:25.485 Shaun Sims: So today, like what they have. They have the option of like they actually like manually create the orders in curry. So they would say, Okay, I’ve got a physical like, pick ticket. Right? That like says, Hey, this is what I like. This is the item, like in the order information. I’m gonna basically transcribe that into curry. And then I’m gonna do that for all 40 deliveries that I have going out for a day, and then I’m gonna drag and drop them and assign them to trucks. Right? So that so that’s how it happens today.
64 00:10:26.320 ⇒ 00:10:35.667 Shaun Sims: where we are. What we’re in the process of is rather than have them do manual order entry. We are basically pulling order information directly from their erp systems.
65 00:10:36.060 ⇒ 00:10:54.959 Shaun Sims: So right now, I don’t know. This is probably irrelevant. But just so you know, we’re working with epicor, have 2 different erp systems that our customers tend to use. One is called profit, 21 or p. 21. For short, the other one is called eclipse, and so those are the 2. We also have a Monday integration as well. So.
66 00:10:54.960 ⇒ 00:10:55.659 Uttam Kumaran: Okay. Great.
67 00:10:55.660 ⇒ 00:11:13.639 Shaun Sims: Some of our customers use Monday, so we’re able to pull that in as well. So now here, here, here, I’m getting to the problem. Right? So the problem is like, what we, what we want to have happen is all of this order. Data comes in from the Erp, and it’s complete and accurate when it comes to things like the products. Wait
68 00:11:13.640 ⇒ 00:11:32.729 Shaun Sims: the dimensions of the product mostly that right? It’s like the weight and dimensions alone is enough. Because, like, why, that’s so important is, it’s not just like when you think about routing and logistics. You’re like, Oh, yeah, it’s traveling salesman problem. Right. But it’s like, Well, there’s actually a problem before that. Which is, how do I take all of these orders? And like play, Tetris.
69 00:11:33.010 ⇒ 00:11:37.230 Uttam Kumaran: So you mentioned that during the dinner, like actually fitting them onto the flatbed? Yeah.
70 00:11:37.230 ⇒ 00:12:02.149 Shaun Sims: A huge problem, right? And it’s like, that’s where, like a lot of inefficiency still lies in logistics and transportation, right? Especially for last mile right? And so that th, the the problem is the order data that we get from the Erp. And then if you go a step further, so that, like the the PIN files, and like the actual product data that they’re getting that feeds their erp. That then, would feed curry is often
71 00:12:02.220 ⇒ 00:12:28.439 Shaun Sims: just incomplete. Right? It. It’s there’s really 2 problems. It’s like, wait dimensions often are missing. If they are included. Often it’s not clear like, is this, for like a palette, like a a palette. Worth of these order items, or is it like one order item? And so I’ll show you in a second, like we got a a PIN file from one of our customers, and I’ll I kind of want to like. Don’t I don’t want to solution necessarily like.
72 00:12:28.440 ⇒ 00:12:29.719 Uttam Kumaran: No. But let’s yeah.
73 00:12:29.720 ⇒ 00:12:53.989 Shaun Sims: I’d be curious what your thoughts are. I have some ideas. But but basically the problem to solve is like, how do you enrich that data right to get weight dimensions. And like, even if you have to kind of like, infer and make some guesses right? Like, just, it’s just like one of those like notorious industry problems that is just really, really hard to solve. But it’s like, if you could solve it, you would. Your product would be completely differentiated in the market.
74 00:12:54.500 ⇒ 00:13:00.249 Uttam Kumaran: And so can you actually. So do you get any information about the actual product? And can you get that from
75 00:13:00.310 ⇒ 00:13:03.000 Uttam Kumaran: the manufacturer like, can you do a lookup.
76 00:13:04.350 ⇒ 00:13:06.749 Shaun Sims: Yeah, so here, let me let me.
77 00:13:06.750 ⇒ 00:13:07.990 Uttam Kumaran: Yeah, let’s take a look.
78 00:13:09.890 ⇒ 00:13:14.519 Shaun Sims: So let’s see, unilog PIN data.
79 00:13:15.000 ⇒ 00:13:20.450 Uttam Kumaran: Because we’re we’re working with a client. We’re getting it directly from the ship shipment providers
80 00:13:20.811 ⇒ 00:13:23.799 Uttam Kumaran: cause I have our intern like I have the clients internal.
81 00:13:24.210 ⇒ 00:13:28.870 Uttam Kumaran: linked with height dimensions, but when they ship it the boxes may be different.
82 00:13:28.960 ⇒ 00:13:31.110 Uttam Kumaran: you know, then, so.
83 00:13:31.110 ⇒ 00:13:34.250 Shaun Sims: Ex exactly right. Here, let me
84 00:13:34.660 ⇒ 00:13:42.169 Shaun Sims: what’s orient to this, and I haven’t spent a ton of time looking at this, but this is a customer of ours insco.
85 00:13:42.180 ⇒ 00:13:46.040 Shaun Sims: And they they sent over this file. So you can see, like
86 00:13:46.650 ⇒ 00:13:49.149 Shaun Sims: in theory, it’s everything you’d need.
87 00:13:49.730 ⇒ 00:13:55.780 Shaun Sims: Here’s dimensions right here, and then here’s wait. But you can see like there’s a lot of.
88 00:13:55.780 ⇒ 00:13:56.970 Uttam Kumaran: Clientele? Yeah.
89 00:13:56.970 ⇒ 00:14:05.580 Shaun Sims: Right but so like it’s not completely hopeless. But it’s it’s very inconsistent, right? And so
90 00:14:06.460 ⇒ 00:14:11.309 Shaun Sims: where I’m wondering if there’s if there. If this is where kind of the opportunity is, it’s like
91 00:14:11.400 ⇒ 00:14:15.369 Shaun Sims: there’s this short description here. So this is an electric heater kit
92 00:14:15.580 ⇒ 00:14:16.335 Shaun Sims: right?
93 00:14:17.300 ⇒ 00:14:19.970 Shaun Sims: there’s a long description description here.
94 00:14:20.670 ⇒ 00:14:25.490 Uttam Kumaran: And it looks like some of those descriptions have some dimension information. Anyways.
95 00:14:25.490 ⇒ 00:14:30.080 Shaun Sims: Exactly. Exactly. So. I wonder like, how much of this is really just like
96 00:14:30.550 ⇒ 00:14:34.689 Shaun Sims: kind of parsing. This right? Is kind of one.
97 00:14:34.710 ⇒ 00:14:36.950 Shaun Sims: And then I guess the second one is kind of
98 00:14:37.000 ⇒ 00:14:42.739 Shaun Sims: to your point, like is there? Can we do like a lookup, somehow or like write a scraping like a python screen?
99 00:14:42.740 ⇒ 00:14:43.690 Uttam Kumaran: Yeah, yeah, yeah.
100 00:14:43.690 ⇒ 00:14:46.649 Shaun Sims: To go scrape like the in manufacturers.
101 00:14:46.760 ⇒ 00:14:48.280 Shaun Sims: Product catalog.
102 00:14:48.763 ⇒ 00:14:52.530 Shaun Sims: But you’re right, it’s true, like some of this stuff does have.
103 00:14:52.830 ⇒ 00:14:53.590 Shaun Sims: So yeah, so.
104 00:14:53.590 ⇒ 00:14:56.259 Uttam Kumaran: These are all the so yeah, a couple of things. One is.
105 00:14:56.290 ⇒ 00:15:15.445 Uttam Kumaran: yeah. The way so dealt with this sort of issue kind of not in this field, but like this is a pretty common thing. Basically, one is like, if you have that in, if you have it in the actual. For example, if you look at Row like 1, 100 or 101, it says 60 by 30, by
106 00:15:15.840 ⇒ 00:15:16.930 Uttam Kumaran: by 2.
107 00:15:16.930 ⇒ 00:15:17.530 Shaun Sims: Yep.
108 00:15:17.680 ⇒ 00:15:24.139 Uttam Kumaran: So in in. Let’s take this situation in in this case, and like in 101, so would that.
109 00:15:24.330 ⇒ 00:15:28.770 Uttam Kumaran: Would that just be what we, what we would take? Or is there any other
110 00:15:28.920 ⇒ 00:15:36.559 Uttam Kumaran: information we need like? Is there any other first class data that would like trap like trump that. Basically, you almost create like a little bit of a
111 00:15:37.069 ⇒ 00:15:43.030 Uttam Kumaran: like a priority of like, can we get information from here? If not, can we get information here? If not, can we get information from there?
112 00:15:43.458 ⇒ 00:15:47.390 Uttam Kumaran: We can even try to take this example, and even try to go to the manufacturer and see.
113 00:15:49.640 ⇒ 00:16:08.769 Shaun Sims: Yeah, I’m the only the only other. So it’s it’s it’s the 2 first class citizens. Here are dimensions and wait. If you have dimensions. Wait, you’re good, honestly. That that’s like 90% of it. I I mean, the only it’s probably honestly, 99% of it. The remaining one would be things like.
114 00:16:09.170 ⇒ 00:16:16.640 Shaun Sims: you know, the material type like if it’s hazardous, for example, like that’s helpful to know right? Because
115 00:16:16.780 ⇒ 00:16:25.200 Shaun Sims: certain trucks with certain driver certifications required. But that’s getting way. A field. I I it’s like the problem here is really just weight and dimension.
116 00:16:25.400 ⇒ 00:16:31.490 Uttam Kumaran: Yeah. So in this example we have, we would take these dimensions. But there’s no wait. So
117 00:16:31.680 ⇒ 00:16:39.299 Uttam Kumaran: like if if would, to find the manufacturers. You would just Google, or take that like Id, and just try to like, basically find that manufacturer.
118 00:16:39.300 ⇒ 00:16:49.640 Shaun Sims: That’s what I was thinking like, I mean, I was kind of thinking like I want, like I’m not. I’m not a big scraper got like I don’t know. I didn’t want to like get banned from Google. But I was like, I think in theory you could write like a python script.
119 00:16:49.640 ⇒ 00:16:56.549 Uttam Kumaran: No, this is totally possible. I I guess one, I guess, because it’s the first time you’re looking at this description is M. And M. And M. Would be
120 00:16:56.650 ⇒ 00:17:00.420 Uttam Kumaran: probably the manufacturer. I mean. I see Mitsubishi electric
121 00:17:00.470 ⇒ 00:17:03.760 Uttam Kumaran: as you roam, so it’s that’s probably the manufacturer.
122 00:17:03.900 ⇒ 00:17:04.569 Shaun Sims: Yeah.
123 00:17:04.819 ⇒ 00:17:07.080 Shaun Sims: I would assume like, I wonder if we just like.
124 00:17:07.089 ⇒ 00:17:08.779 Uttam Kumaran: Let’s just see it. Yeah.
125 00:17:08.780 ⇒ 00:17:09.460 Shaun Sims: Or.
126 00:17:10.300 ⇒ 00:17:13.379 Shaun Sims: Oh, this is funny! So this is our customer right here
127 00:17:13.490 ⇒ 00:17:14.589 Shaun Sims: in sco.
128 00:17:16.089 ⇒ 00:17:19.469 Uttam Kumaran: Okay, let’s see, do they have anything under specs here for the wait.
129 00:17:19.609 ⇒ 00:17:24.099 Shaun Sims: So they have brand name. It’s interesting login. Let’s see spec.
130 00:17:27.179 ⇒ 00:17:31.159 Shaun Sims: So we basically, it looks like we have. We’re kind of working from the same information.
131 00:17:31.269 ⇒ 00:17:35.563 Shaun Sims: But I wonder, like, with these different lookups right like, if you could do.
132 00:17:37.830 ⇒ 00:17:40.799 Uttam Kumaran: Yeah, let’s just go through because I just wanna even see like
133 00:17:45.080 ⇒ 00:17:46.979 Uttam Kumaran: it looks like it was a second one.
134 00:17:47.030 ⇒ 00:17:48.749 Uttam Kumaran: Well, drainage fan.
135 00:17:48.750 ⇒ 00:17:51.913 Shaun Sims: Oh, you’re right, Baker, so Baker would be like another.
136 00:17:52.230 ⇒ 00:17:53.869 Uttam Kumaran: Another, one another, distributor.
137 00:17:53.870 ⇒ 00:17:56.770 Shaun Sims: Yeah. So let’s see if they have.
138 00:17:57.890 ⇒ 00:18:00.009 Shaun Sims: Oh, that’s funny. They have weight. Look at that.
139 00:18:00.010 ⇒ 00:18:00.800 Uttam Kumaran: Okay.
140 00:18:01.300 ⇒ 00:18:09.280 Uttam Kumaran: Alright. So this is like a manageable. I so one is taking it from the description is totally easy.
141 00:18:09.280 ⇒ 00:18:09.830 Shaun Sims: Okay.
142 00:18:10.216 ⇒ 00:18:15.439 Uttam Kumaran: There’s like a number of ways we could do that. It’s also pretty easy now like
143 00:18:15.720 ⇒ 00:18:35.759 Uttam Kumaran: to do this really with an Lm. Directly in Snowflake. We. Just. I’ve been doing this for a client this week, actually, where we’re taking their Zendesk tickets, and they’re back and forth and categorizing them, using openai all within snowflake. So, taking that description and parsing out the different link with heights
144 00:18:35.790 ⇒ 00:18:37.350 Uttam Kumaran: that seems manageable.
145 00:18:37.500 ⇒ 00:18:39.460 Uttam Kumaran: This sort of lookup
146 00:18:40.310 ⇒ 00:18:43.030 Uttam Kumaran: is a little bit of a different process. So one is.
147 00:18:43.714 ⇒ 00:19:00.949 Uttam Kumaran: I know there’s also there’s also commonly like large scale product, catalogs and Granger and things like that where they have everything. This is just from one, I would say like, is there any like one or 2 source of truth websites that typically have everything where we can
148 00:19:01.180 ⇒ 00:19:25.340 Uttam Kumaran: do the search, and it’s in if it’s in the page and we can get it. Googling, and then finding out what to click on is a little bit challenging. But the other thing is you mentioned the first link we clicked on, which is the insco. If it’s if it’s on their site. Then we can, of course, do a lookup. But the second, the thing I would ask is there if there’s like a universal product, catalog or something where we can.
149 00:19:25.340 ⇒ 00:19:25.830 Shaun Sims: Yeah.
150 00:19:26.071 ⇒ 00:19:31.150 Uttam Kumaran: Reference these it it doesn’t have to be all of them. It’s just like again trying to just do 80, 20
151 00:19:31.615 ⇒ 00:19:36.949 Uttam Kumaran: on this whole thing. Second thing is actually looking for this product in historicals.
152 00:19:37.396 ⇒ 00:19:41.309 Uttam Kumaran: So I would be looking at. Did we ever have the wait
153 00:19:41.360 ⇒ 00:19:48.679 Uttam Kumaran: for something like this? Or do we ever have the length of the height for something that that matches? Because you may have it. For from a previous
154 00:19:48.700 ⇒ 00:19:58.250 Uttam Kumaran: distributor previous? And you guys have access to all that data. So that’s one thing I would look at is, look at like, did we ever see this come up in the in the database. And
155 00:19:58.400 ⇒ 00:20:02.010 Uttam Kumaran: are there dimension, you know information about it?
156 00:20:02.353 ⇒ 00:20:06.490 Uttam Kumaran: I guess the other question I would have is like, what’s the cost of getting it wrong?
157 00:20:08.030 ⇒ 00:20:09.410 Uttam Kumaran: and like, is it
158 00:20:09.680 ⇒ 00:20:15.658 Uttam Kumaran: blank versus wrong, or or is it like wrong versus like super wrong like, if you could tell me like what happens.
159 00:20:15.930 ⇒ 00:20:23.980 Shaun Sims: I see. Yeah, it’s actually interesting. Pretty low risk of of meaning, like, not a lot of actual like
160 00:20:24.420 ⇒ 00:20:33.880 Shaun Sims: like, I’m how do I say this? Very low risk in terms of like it’s like, if you got the weight or dimensions wrong.
161 00:20:34.196 ⇒ 00:21:02.820 Shaun Sims: Th. This is still human in the loop, at least, for now, right like for the 4 people feature like there’s gonna be the branch manager dispatcher, and I’ll show you I I can pull it up like that’s actually building the routes. Opportunity to kind of spot check. I don’t think like I think they would see like, oh, this order information like, there’s no way that like that. Wait is completely wrong or like no like, because that’s how it operates today, like, it’s all tribal knowledge. Right? So this is just like, you know.
162 00:21:02.820 ⇒ 00:21:06.849 Uttam Kumaran: And so until that item in particular, do they go? Put that in? Or.
163 00:21:07.420 ⇒ 00:21:14.500 Uttam Kumaran: yeah, like, is there, is it? Do you get like? Do you get that data back when that person? Yeah, I guess if yeah, if you go walk me through this.
164 00:21:14.500 ⇒ 00:21:17.419 Shaun Sims: Yeah, let’s so this is like the route planner product.
165 00:21:18.183 ⇒ 00:21:18.650 Shaun Sims: Here, like.
166 00:21:18.650 ⇒ 00:21:19.809 Uttam Kumaran: Product, looks, good.
167 00:21:20.150 ⇒ 00:21:23.435 Shaun Sims: Yeah, I’m I mean, it’s it’s I’m impressed.
168 00:21:23.800 ⇒ 00:21:29.839 Uttam Kumaran: I’ve seen a lot of these products before. They don’t look good at all. But it’s also a design challenge, because
169 00:21:30.270 ⇒ 00:21:32.530 Uttam Kumaran: there’s a lot of information you have to display so.
170 00:21:32.530 ⇒ 00:21:40.909 Shaun Sims: But that. Yeah, I am impressed by this team like there is so much like just like discrete, hidden functionality which I think is appropriate for this type of product. Right? Like, it’s like you.
171 00:21:40.910 ⇒ 00:21:41.450 Uttam Kumaran: Correct.
172 00:21:41.450 ⇒ 00:22:07.570 Shaun Sims: Users so that way you’re not cluttering the ui but over here let me zoom in. So this is what we call like our order queue. So today, this is mostly like, you know, these are mostly manually created. Right? So you would like add an order right? This is the whole annual process I was talking about. So you’re gonna enter in like, here’s the pickup information. Here’s the drop off information, you know, like, here, here’s like.
173 00:22:07.610 ⇒ 00:22:19.679 Shaun Sims: it’s like a standard palette, right? I’m gonna enter in weights, dimensions, and so forth. So this is mostly what our customers use today. But this is what we’re trying to sort of augment with the erp integration right?
174 00:22:19.680 ⇒ 00:22:20.080 Uttam Kumaran: Yeah.
175 00:22:20.080 ⇒ 00:22:22.389 Shaun Sims: So this order queue here
176 00:22:23.440 ⇒ 00:22:24.804 Shaun Sims: when it loads
177 00:22:26.350 ⇒ 00:22:33.500 Shaun Sims: would automatically kind of be pulling in data from the Erp. And then basically, like he, I’m
178 00:22:34.140 ⇒ 00:22:37.769 Shaun Sims: like, I’ll just build a route. So like, let’s say, Craig.
179 00:22:37.780 ⇒ 00:22:40.370 Shaun Sims: today, it’s gonna be running around on a box truck.
180 00:22:41.870 ⇒ 00:22:43.450 Shaun Sims: So I’ll create the route.
181 00:22:49.870 ⇒ 00:22:59.449 Shaun Sims: So these are like Hq. Auto populates like at the like. Think about it as like a branch or something like that. And then I would just kind of like scroll down and assign
182 00:23:03.600 ⇒ 00:23:05.960 Shaun Sims: these orders to Craig.
183 00:23:08.280 ⇒ 00:23:10.540 Shaun Sims: Where did that go? There? It is. Okay.
184 00:23:11.270 ⇒ 00:23:12.749 Shaun Sims: Is that another one?
185 00:23:17.680 ⇒ 00:23:27.180 Shaun Sims: So you see how I’m like manually building these right like this should be some future state where, like as we pull in Erp, data like it should be able to kind of like build.
186 00:23:27.180 ⇒ 00:23:31.860 Uttam Kumaran: Oh, because it’s doing the it’s doing the priority based on how much space is in the truck.
187 00:23:31.860 ⇒ 00:23:39.719 Shaun Sims: So right now, it’s it’s doing the priority based on the Traveling Salesman problem. Right? So it’s really only looking at
188 00:23:39.740 ⇒ 00:23:40.880 Shaun Sims: kind of like
189 00:23:40.990 ⇒ 00:23:44.590 Shaun Sims: origin destination. So I’ll show you like.
190 00:23:45.600 ⇒ 00:23:51.790 Shaun Sims: This is probably a bad example, because I think these locations are like really far away. But you’ll you’ll still get the point.
191 00:23:51.900 ⇒ 00:23:54.370 Shaun Sims: So I can like, optimize the route.
192 00:23:54.810 ⇒ 00:23:59.880 Shaun Sims: Actually, here this is. Let me show you a better way to like visualize this, so you can see them on a map.
193 00:24:02.260 ⇒ 00:24:04.089 Shaun Sims: Yeah, the I mean, this is not
194 00:24:05.330 ⇒ 00:24:06.779 Shaun Sims: too. You’re too far away. But like.
195 00:24:06.780 ⇒ 00:24:11.919 Uttam Kumaran: Long journey. I see what you mean, though. So you’re saying. Another factor would be
196 00:24:12.700 ⇒ 00:24:14.579 Uttam Kumaran: adding in the weight and dimensions.
197 00:24:14.580 ⇒ 00:24:28.499 Shaun Sims: Yeah, so what wait and dimension does. It’s like, right here, right? Like, when I’m at like assigning it. Like, basically, it’s like, Hey, okay, I know that. You know, Jeffrey is going to be driving a sprinter van today.
198 00:24:28.690 ⇒ 00:24:38.610 Shaun Sims: Right? And so it’s almost like, okay. Now I know the driver and I know the truck and the dimensions, because it’s a sprinter van. Now take into account not just the origin and destination, but also.
199 00:24:38.895 ⇒ 00:24:39.180 Uttam Kumaran: Yes!
200 00:24:39.180 ⇒ 00:24:41.384 Shaun Sims: How many orders I can fit into that sprinter.
201 00:24:41.956 ⇒ 00:24:42.610 Uttam Kumaran: Correct. Correct.
202 00:24:42.610 ⇒ 00:24:44.919 Shaun Sims: So so that that’s what’s really challenging.
203 00:24:46.220 ⇒ 00:25:03.000 Shaun Sims: like the origin destination. Isn’t that hard? I mean, we use like, Google’s like, like they have their like. It’s like what everybody uses right? Now, we can optimize on the edge, for, like our special delivery truck types and things like that. But it’s it’s really just trying to solve that like.
204 00:25:03.130 ⇒ 00:25:04.610 Shaun Sims: which of these orders from.
205 00:25:04.610 ⇒ 00:25:11.500 Uttam Kumaran: But again, you don’t know if this is like a small box, we’re so large box when it’s like you could have done 4, the small ones, and then then the large one.
206 00:25:11.500 ⇒ 00:25:16.620 Shaun Sims: Yeah, no, that’s right. That’s right. So it’s like that. That’s what’s really unsolved. And like a potential like.
207 00:25:16.980 ⇒ 00:25:31.040 Shaun Sims: pretty big differentiator in our product. I’ll show you this just because it’s like fun. It’s not relevant to this conversation. But I think just the power of curry. So like I’m building these routes for my own fleet, right as a distributor. But like, let’s say.
208 00:25:31.040 ⇒ 00:25:50.170 Shaun Sims: like, when I was viewing these on a map, let’s say like, Okay, 3 and 2 obviously don’t make sense for me to do because they’re across the country. I can click this button. And basically this says, Hey, I want Curry to do this delivery for me instead of my internal fleet, so that integration, like with our core marketplace, I think, is really cool and powerful.
209 00:25:50.170 ⇒ 00:25:52.480 Uttam Kumaran: And so who pick? Who ends up picking that up.
210 00:25:53.100 ⇒ 00:25:54.739 Shaun Sims: Curry like our network, right?
211 00:25:54.740 ⇒ 00:25:56.149 Uttam Kumaran: I see, I see.
212 00:25:56.150 ⇒ 00:26:05.040 Shaun Sims: So so. And that’s the other cool part, too. It’s like, if we can get dimensions down, then it’s also like, Hey, you know, you actually don’t have the capacity for this sixth order.
213 00:26:05.040 ⇒ 00:26:05.550 Uttam Kumaran: Yes.
214 00:26:05.550 ⇒ 00:26:07.380 Shaun Sims: Send it to Curry. We’ll take care of it.
215 00:26:07.660 ⇒ 00:26:09.820 Uttam Kumaran: Okay, I can. I see. I see. I see.
216 00:26:10.240 ⇒ 00:26:19.009 Uttam Kumaran: Okay. I mean, I think one getting from the description is really is really manageable. How how are you doing the actual like
217 00:26:19.390 ⇒ 00:26:22.499 Uttam Kumaran: integration with them like you have this flat file. But
218 00:26:22.560 ⇒ 00:26:24.179 Uttam Kumaran: is that all like
219 00:26:24.220 ⇒ 00:26:28.029 Uttam Kumaran: set up now? Or do you know what environment this data is gonna be in.
220 00:26:28.400 ⇒ 00:26:32.909 Shaun Sims: Yeah. Good question. Yes, let me
221 00:26:33.310 ⇒ 00:26:35.449 Shaun Sims: let me see if I can share
222 00:26:36.020 ⇒ 00:26:37.410 Shaun Sims: I can share like.
223 00:26:37.530 ⇒ 00:26:41.310 Shaun Sims: So it’s it’s there’s there’s for Monday. It’s like an Api integration.
224 00:26:41.601 ⇒ 00:26:43.349 Uttam Kumaran: I know the Monday integration. Yeah.
225 00:26:43.350 ⇒ 00:26:45.280 Shaun Sims: Yeah. So we just get all the you know you can like.
226 00:26:45.280 ⇒ 00:26:50.629 Uttam Kumaran: Is that going into Snowflake? Or is that going to like a data warehouse? Or is that going to S. 3 or.
227 00:26:50.630 ⇒ 00:26:57.129 Shaun Sims: Yeah, that’s a good question. I need a I should know the answer to that. My assumption, I would assume. Just it goes into like an s. 3 bucket.
228 00:26:57.130 ⇒ 00:26:57.890 Uttam Kumaran: Okay.
229 00:26:57.890 ⇒ 00:27:03.270 Shaun Sims: Yeah. And then, in terms of the actual endpoints, right?
230 00:27:03.950 ⇒ 00:27:07.890 Shaun Sims: or fields rather, that would be passed. I can like send you
231 00:27:08.040 ⇒ 00:27:12.640 Shaun Sims: an example. But but base, basically, it would be comprehensive of
232 00:27:12.810 ⇒ 00:27:14.859 Shaun Sims: wait amit, like everything we’re talking about, basically.
233 00:27:14.860 ⇒ 00:27:15.600 Uttam Kumaran: Yeah.
234 00:27:15.600 ⇒ 00:27:22.950 Shaun Sims: And to the extent, it’s not right. That’s where I think a service like us. It’s like, okay, we see your order data, and we’re going to enrich it, for you like that is like
235 00:27:23.200 ⇒ 00:27:24.610 Shaun Sims: their minds would experience.
236 00:27:24.610 ⇒ 00:27:34.290 Uttam Kumaran: Yeah, yeah, yeah, yeah. Yeah. But see, you guys have the advantages that you’re in the middle of a lot of these. I’m sure a lot of these items, the especially if it’s like from the Oem, are the same
237 00:27:34.700 ⇒ 00:27:44.999 Uttam Kumaran: right? So I’m so that’s why I wanted to break it down to like couple of the kind of like, where’s the oil? Basically, it’s like one is, if it’s in the description
238 00:27:45.040 ⇒ 00:27:53.169 Uttam Kumaran: great. So what the what? But then, again, you may not have everything. So then there’s a little bit break of second is, can you look up in your own historical database?
239 00:27:53.460 ⇒ 00:28:04.809 Uttam Kumaran: I don’t know how what percentage of that may hits. The third is then going outside. Going outside is going to be the hardest and probably least reliable, unless you have.
240 00:28:05.190 ⇒ 00:28:19.640 Uttam Kumaran: like a direct hookup into like again you do an 80 20 on oems like, I don’t know what the constituency of the products that you guys are shipping, but it’s probably really easy. You’ll get a catalog data set from the top.
241 00:28:20.030 ⇒ 00:28:24.820 Uttam Kumaran: you know, whatever oems, especially if you’re like, we’re working directly with your distributors.
242 00:28:26.030 ⇒ 00:28:34.349 Uttam Kumaran: so in any situation, I would say, number one is getting structured data, any sort of scraping. And then processing is, gonna be tough.
243 00:28:34.741 ⇒ 00:28:46.629 Uttam Kumaran: There’s a lot of like AI companies, things like that trying to do this. It’s like, really, really difficult to find exactly where to go. So one thing I would suggest is one figuring out.
244 00:28:46.860 ⇒ 00:28:59.389 Uttam Kumaran: if you’re like, let’s just try for, like these manufacturers, these set of products based on like some sort of 80 20 analysis. That’d be amazing. Cause you could go directly to the manufacturers and say, Do you guys have a
245 00:28:59.570 ⇒ 00:29:11.799 Uttam Kumaran: product catalog Api, or even if that doesn’t even change that often. Can you just give us like a flat file of everything? I I think they’re gonna be able to do that. And as long as you’re able to
246 00:29:12.359 ⇒ 00:29:24.349 Uttam Kumaran: do a match on that you should be good. It’s clear that they were. There was some sort of probably manufacturer Ids, that you could then look back up with the M. And M. In that in that situation.
247 00:29:24.350 ⇒ 00:29:25.190 Shaun Sims: Yeah. Totally.
248 00:29:25.190 ⇒ 00:29:29.919 Uttam Kumaran: That would be an example. And the this sort of stuff is stuff that we’ve done
249 00:29:30.344 ⇒ 00:29:41.369 Uttam Kumaran: like we we’ve done in a bunch of different scenarios where we we’re basically like, okay, the the take it from the description that’s really manageable wherever your data lives, in whatever language
250 00:29:41.410 ⇒ 00:29:47.960 Uttam Kumaran: the lookups and actually going to the oems and getting that data and making sure it’s all set up is like a little bit more of a challenge. But
251 00:29:48.130 ⇒ 00:29:52.809 Uttam Kumaran: 80 20 everything and find like where the first key value is. And then it’s like a.
252 00:29:53.000 ⇒ 00:29:56.914 Uttam Kumaran: it’s basically like, you’re just long tail of integrations. So.
253 00:29:57.270 ⇒ 00:30:10.618 Shaun Sims: Exactly. Yeah. So I mean, that’s super helpful. I think you know. Just so you kind of understand, like curry and resourcing. So I mean we operate. I almost too lean. In some ways, like we’re we’re super
254 00:30:12.140 ⇒ 00:30:37.030 Shaun Sims: I don’t know if Conservatives right word, I maybe efficient but but like most of our internal engineers, are kind of like to capacity right? And so there is an increasing appetite to leverage like outside consultants, especially for like projects like this, like like another example that we’re we’re investigating. You know. Should we move off of Google Maps and go to oh, gosh, Tom, right maps or something.
255 00:30:37.030 ⇒ 00:30:38.119 Uttam Kumaran: Oh, interesting. Okay.
256 00:30:38.120 ⇒ 00:30:57.039 Shaun Sims: Yeah. And so it’s like we, we’re leveraging like a consultant to help us like, understand. And and some of it’s internal. But like it’s like cost analysis, like pee feature like. So there is. I’d say there’s a lot more appetite to leverage like third party consulting right now than to like, go hire additional internal team members to like do this. So
257 00:30:57.040 ⇒ 00:31:09.889 Shaun Sims: I I mean, I don’t know like what your engagement model looks like. But if you wanna like, follow up Async. I could see it being like, you know, my responsibility would be to kind of like build some internal, you know. Case that says, Hey.
258 00:31:10.120 ⇒ 00:31:13.759 Shaun Sims: this is, we need an outside resource versus like, you know
259 00:31:14.270 ⇒ 00:31:18.649 Shaun Sims: us doing this in the margin. But that’s how I would kind of see it progressing.
260 00:31:19.040 ⇒ 00:31:40.269 Uttam Kumaran: Yeah, I mean again, like, I’m in the consulting business. But I’ve also hired a bunch of data consultants before. My biggest thing is like we would work directly with you, and that basically frees up us getting involved in any other company. Thing. Second thing is like, if you were to hand this to any like a data person. They may not have seen this challenge before, like doing this sort of
261 00:31:40.660 ⇒ 00:31:43.299 Uttam Kumaran: column parsing and going and getting that data like
262 00:31:43.470 ⇒ 00:32:03.940 Uttam Kumaran: if if you gave me an hour I’d call, I call every oem right now, and we get on the phone with it and make that stuff happen. So I think the speed is one thing you could totally sell on. I think the one thing that would be helpful for us to work together is, think of like a very, very initial like, when is like, okay, if we were to set like 4 weeks
263 00:32:03.940 ⇒ 00:32:19.880 Uttam Kumaran: and we’re like we wanna get this piece done that way when we come up on like, oh, this thing’s a little bit harder. This is Bar. We can knock those out and say, like a focus on the 80 20, which is like again, is it a handful of manufacturers? There’s a one key distributor client, is it some like
264 00:32:19.950 ⇒ 00:32:43.990 Uttam Kumaran: Kpi like that like that would be really helpful. Because I’m not gonna the the problem and data is like, I don’t know until I’m in to see like what your systems are and where we can run things. So that’s where I we need a little bit of runway. We do everything on like an hourly basis, but happy to start with, like, you know, like a basket of hours and put something together. But I’m help. We’ve I’ve helped a lot of people like
265 00:32:44.030 ⇒ 00:32:48.590 Uttam Kumaran: like similar just codify what a project plan could look like. Basically like, what is a one month
266 00:32:48.670 ⇒ 00:33:00.389 Uttam Kumaran: kind of like, we just go after this small problem. If you I would love to even like, bring this up to discussion with my team. I’m meeting with everybody in about an hour, do you? Would you mind sharing that
267 00:33:00.660 ⇒ 00:33:06.450 Uttam Kumaran: like that? Google sheets? I just want to talk to a couple of folks on my team of like
268 00:33:06.810 ⇒ 00:33:13.484 Uttam Kumaran: the the challenge and just get everybody’s perspective. And I can send you some notes after that, too.
269 00:33:14.383 ⇒ 00:33:16.230 Shaun Sims: Gonna I’ll paste it in the chat.
270 00:33:16.570 ⇒ 00:33:18.140 Shaun Sims: I don’t think this is like
271 00:33:18.320 ⇒ 00:33:19.209 Shaun Sims: it’s not like.
272 00:33:19.210 ⇒ 00:33:21.289 Uttam Kumaran: It’s just yeah, it’s just
273 00:33:21.440 ⇒ 00:33:22.300 Uttam Kumaran: yeah.
274 00:33:22.910 ⇒ 00:33:25.398 Shaun Sims: Yeah, I don’t. I think it’s totally fine.
275 00:33:27.040 ⇒ 00:33:30.240 Shaun Sims: I mean, I don’t know. Like, maybe just keep it within your team right.
276 00:33:30.240 ⇒ 00:33:38.223 Uttam Kumaran: It’s just that. And again, I’m just looking at like, I’m just looking at the descriptions. And I’m honestly gonna see whether we can do some of this like
277 00:33:38.640 ⇒ 00:33:50.090 Uttam Kumaran: today or on Monday, just to just to call on parsing stuff. But yeah, I think that’s kind of way the way we would go. So let me take a look at this kind of put together, just from what we’ve talked about, like, what are the kind of like?
278 00:33:50.120 ⇒ 00:33:58.464 Uttam Kumaran: Write down things we talked about. One thing from your side would be helpful is like, exactly what is that first win? We could try to drive towards
279 00:33:59.070 ⇒ 00:34:05.012 Uttam Kumaran: and that really helps to be like, let’s go after that, accomplish that. And then if there’s follow on things,
280 00:34:05.400 ⇒ 00:34:07.480 Uttam Kumaran: that’ll help to do the sell for those.
281 00:34:08.230 ⇒ 00:34:15.109 Shaun Sims: Awesome man. I like it. Well, if you don’t hear from me, feel free to, you know. Read, I mean, you know how it is. It’s like it’s not.
282 00:34:15.110 ⇒ 00:34:17.480 Uttam Kumaran: Yes, no yes, yes.
283 00:34:17.489 ⇒ 00:34:22.232 Shaun Sims: Like I’m not like, not interested like I wanna keep the combo going. You’re you’re never gonna bug me
284 00:34:22.469 ⇒ 00:34:30.626 Uttam Kumaran: Cool. It’s just it’s just interesting. Because again, I’ve been working with a lot of the shipping data. Recently, I saw Ltl, we’ve been working directly with their team on a lot of stuff.
285 00:34:31.177 ⇒ 00:34:44.269 Uttam Kumaran: And then we’re starting to work with some of the manufacturers directly, like like one of the clients we work with. They manufacture their own product. So deal with a very similar issue. Even for the reporting on a lot of this stuff like I, what do you guys used to do like?
286 00:34:44.659 ⇒ 00:34:49.519 Uttam Kumaran: What do you use to see the reporting on all this like those questions I even asked to you like, how would you go?
287 00:34:49.539 ⇒ 00:34:50.969 Uttam Kumaran: Just for curiosity?
288 00:34:51.359 ⇒ 00:34:58.760 Shaun Sims: Well, like. So we use metabase. Right? That’s kind of like our core like reporting and analytics.
289 00:34:59.229 ⇒ 00:35:05.674 Shaun Sims: and we’re working on like actually exposing a lot of those metabase analytics back to the customer. So that’s kind of like an thing for us.
290 00:35:06.429 ⇒ 00:35:14.079 Shaun Sims: but yeah, this this is cool. Let me let me chew on like I think I kind of have an idea of like what the quick one would be. It would probably be like
291 00:35:14.179 ⇒ 00:35:17.311 Shaun Sims: working with insco to be like, you know, hey?
292 00:35:17.899 ⇒ 00:35:28.599 Shaun Sims: Or just understanding like, what are the majority of like orders that come through that like you either wanna put on a last mile delivery or and we’re we are moving into Ltl. By the way, too. So.
293 00:35:28.600 ⇒ 00:35:29.460 Uttam Kumaran: Oh, cool. Okay.
294 00:35:29.460 ⇒ 00:35:35.630 Shaun Sims: Yeah. So I think it would just be like understanding like to your point to 80 20 like, if we could just enrich like
295 00:35:35.730 ⇒ 00:35:41.103 Shaun Sims: Hvac system, or you know, it’s like, or just like certain start with a certain manufacturer. Right?
296 00:35:41.470 ⇒ 00:35:43.970 Shaun Sims: I think that feels that that would help kind of.
297 00:35:43.970 ⇒ 00:35:54.348 Uttam Kumaran: And then get the get the pipes hooked up right, you know, especially if and it again, if in scope, is is willing to work with us on the data side. That’s where we may have a little bit of like back and forth.
298 00:35:54.990 ⇒ 00:36:02.579 Uttam Kumaran: and then just one thing that also be helpful, just like the environments you guys work in like, you guys are, what are you guys using for data warehouse? You said Metabase. So that’s fine.
299 00:36:04.260 ⇒ 00:36:06.630 Uttam Kumaran: And yeah, that’d be helpful.
300 00:36:06.880 ⇒ 00:36:10.429 Shaun Sims: Alright, man. Well, I enjoyed it. Let’s let’s stay in touch on this.
301 00:36:10.430 ⇒ 00:36:12.007 Uttam Kumaran: Yeah, I appreciate it. Thanks all.
302 00:36:12.270 ⇒ 00:36:13.420 Shaun Sims: Yeah. Have a Good Friday.
303 00:36:13.420 ⇒ 00:36:14.639 Uttam Kumaran: You too. Bye, bye.