Meeting Title: Zoom Meeting Date: 2025-03-07 Meeting participants: Aakash Tandel, Nicolas Sucari
WEBVTT
1 00:00:11.270 ⇒ 00:00:11.860 Aakash Tandel: Hey!
2 00:00:11.860 ⇒ 00:00:12.600 Nicolas Sucari: Hey, guys.
3 00:00:13.560 ⇒ 00:00:14.329 Aakash Tandel: How’s it going.
4 00:00:15.210 ⇒ 00:00:16.819 Nicolas Sucari: Doing good. How about you?
5 00:00:17.000 ⇒ 00:00:19.550 Aakash Tandel: Not too bad. I had my 1st
6 00:00:19.975 ⇒ 00:00:24.749 Aakash Tandel: retro with the data team. It was good learned a lot about kind of how things are working.
7 00:00:25.620 ⇒ 00:00:30.960 Nicolas Sucari: Nice. Okay, great yeah. Data team is is being growing this last
8 00:00:31.090 ⇒ 00:00:33.099 Nicolas Sucari: couple of weeks. So yeah, a lot.
9 00:00:33.220 ⇒ 00:00:35.590 Nicolas Sucari: I think there’s a lot to talk about there. Yeah.
10 00:00:35.740 ⇒ 00:00:55.409 Aakash Tandel: Yeah, awesome. Yeah. So I just kind of wanted to chat just to get to know you and like, learn a little bit more about Brainforge and some of the stuff that we’ve been working on. But yeah, I mean, I I know that you used to do some Pm stuff. You’re kind of moving towards operations. Did you work on specific projects? Like clients.
11 00:00:55.920 ⇒ 00:01:13.730 Nicolas Sucari: Yeah, I was mainly with pool parts. And Javi, I haven’t. Yeah. Those 2, the other ones I didn’t work on Eden are stock plates. Yeah, I was not involved in that one. I was just for pool parts and Javi for a couple of yeah months, maybe.
12 00:01:13.920 ⇒ 00:01:19.059 Aakash Tandel: Okay, cool. What do you guys do for those? What was like the project engagement kind of overview.
13 00:01:19.250 ⇒ 00:01:28.139 Nicolas Sucari: So pool parts is kind of our oldest client utens been working with them. Like, yeah, I think more than a year now.
14 00:01:28.783 ⇒ 00:01:46.126 Nicolas Sucari: So it’s for for them we are. We were doing like a lot of analysis on the shipping stuff on their side, and they are an e-commerce business that they sell or pull parts across the the Us. And pull accessories across the Us. They have
15 00:01:47.369 ⇒ 00:01:58.389 Nicolas Sucari: an online store. But yeah, the they have, like an organizational structure, a bit complex. Because we focus on pool parts. But
16 00:01:58.670 ⇒ 00:02:13.259 Nicolas Sucari: the owners of pool parts are also the owners that kind of import all of these kind of pumps and pool accessories, and so and sell also to other vendors here, in there, in the in the Us. Okay.
17 00:02:13.937 ⇒ 00:02:28.962 Nicolas Sucari: but yeah, focuses on on pool parts. We did a lot of different analysis. For example, we helped them reduce their yeah, shipping rate with Fedex ups. And yeah, some others through pls,
18 00:02:29.530 ⇒ 00:02:56.019 Nicolas Sucari: yeah, that was really good. We make them yeah. Well worked on that one. And yeah, we make them. Yeah, just reduce a lot of their their costs. There we help them analyze, for example, where to open a new warehouse. We did kind of a center of gravity analysis. Because in in the Us. What I understood is, you have like, different kind of areas regarding shipping like in
19 00:02:56.140 ⇒ 00:03:00.239 Nicolas Sucari: like different. Yeah, I don’t know. Like different steps, right?
20 00:03:00.240 ⇒ 00:03:01.040 Aakash Tandel: Happens.
21 00:03:01.570 ⇒ 00:03:28.930 Nicolas Sucari: Yeah, exactly. And if you are like, near to one of the warehouses like zone, one zone, 2 zone, 3. And that’s how like the price goes on on in terms of shipping so we analyze, like all of the orders where they were going and where they were like, where they were sending them from. And and yeah, we help them to open a new warehouse and and reduce kind of that shipping cost, too. We’ve been helping on marketing stuff, too.
22 00:03:29.210 ⇒ 00:03:37.559 Nicolas Sucari: We have like 2 points of contact with their team. And then, like the CEO and the Cfo one is the
23 00:03:38.008 ⇒ 00:04:02.060 Nicolas Sucari: it’s called Chuck Chuck Gross. He’s the responsibility for all of the kind of operations side. He’s the one that work with us for all of the shipping stuff, and he knows exactly everything about how to ship, where it’s going, the stuff, how to help with those kind of orders and help us with that information. And then on the marketing side, there is a girl called Kim.
24 00:04:02.350 ⇒ 00:04:30.724 Nicolas Sucari: and yeah, she we we tried to do some kind of Ab testing on some campaigns. Try to like, reduce a price. And yeah, just like, increase the price of the same product and see which one was responding better but they were a little bit skeptical on, hey? We changed the prices, and we are kind of losing a little bit of sales, so they kind of get rid of that test. And yeah. But mainly it’s it’s all of that. We’re trying to help them.
25 00:04:31.100 ⇒ 00:04:42.729 Nicolas Sucari: giving them yeah information about marketing, shipping, and we are now kind of doing a project on cleaning all of their skews like they wanna have like a master sku list.
26 00:04:43.039 ⇒ 00:05:05.929 Nicolas Sucari: They have, like a lot of different skills that they are selling across different platforms. And they are using a lot of different platforms to manage all of these processes. And yeah, kind of the skew stuff is kind of a mess they don’t have like the actual cost for for each skew. Well, kind of identified in in all of these platforms. So, for example, if they want to calculate cogs
27 00:05:06.317 ⇒ 00:05:22.680 Nicolas Sucari: on what they are selling, shopify has a value. But then they are like missing. Or it’s different from like a main sheet that they have for calls. And yeah, that’s kind of our. I think that’s kind of the main focus right now. Maybe you you heard about that in in the meeting.
28 00:05:23.050 ⇒ 00:05:34.409 Aakash Tandel: No, I I haven’t gotten the weeds, so that’s all. Everything you said was very helpful. In terms of the analysis. Where were you all conducting, that is, that, like in databases they have, or.
29 00:05:34.770 ⇒ 00:05:43.947 Nicolas Sucari: Yeah, so all of the analysis. So we are using snowflake as data warehouse. We are ingesting the the data, we using 5 tran.
30 00:05:44.801 ⇒ 00:05:54.459 Nicolas Sucari: But yeah, Snowflake is the data warehouse. We have that data warehouse. I can. I can add you there if you wanna go. I don’t know if you’ve you’ve used Snowflake before, I think. Yes, but.
31 00:05:54.460 ⇒ 00:06:00.499 Aakash Tandel: Yeah, I’ve used snowplay before. And I remember 5 Tran, I have not worked with 5 Tran specifically. But I remember people.
32 00:06:00.500 ⇒ 00:06:04.689 Nicolas Sucari: You. You don’t need to know anything about fivetran or like, we’re using
33 00:06:04.920 ⇒ 00:06:24.680 Nicolas Sucari: 3 different like ingestion tools to gather the data automatically, to like to connect with each data source and bring that data into Snowflake. One is 5 trend, another, one is portable, and the 3rd one is polytomic. So depending on, they have like different ways on how they approach pricing.
34 00:06:25.040 ⇒ 00:06:35.939 Nicolas Sucari: And and yeah, which connectors they have available for different platforms. So we kind of decide which one we we use in terms of that for pool parts. I think we’re using all 5 turn
35 00:06:36.786 ⇒ 00:06:41.249 Nicolas Sucari: for Javi. We’re we’re more. We’re leaning into portable.
36 00:06:42.016 ⇒ 00:06:50.549 Nicolas Sucari: Because portable has a fixed cost per connector, not per, like, active role of data that we are ingesting. So
37 00:06:50.820 ⇒ 00:07:09.679 Nicolas Sucari: that’s what we’re doing for Javi, but we don’t have, like all connectors available in portable. So we’re still using 5 for Amazon, for example. Right? But you don’t you like you. You don’t need to understand anything. It’s just like once you set up the connector that that Uton works, and that almost all the time.
38 00:07:09.970 ⇒ 00:07:16.200 Nicolas Sucari: Once you set that up, you just start receiving the data in Snowflake with some frequency. Okay.
39 00:07:16.400 ⇒ 00:07:17.640 Aakash Tandel: Cool, that make sense.
40 00:07:18.230 ⇒ 00:07:27.930 Nicolas Sucari: And then for yeah, for for modeling we’re using. Dbt, like Dbts are, are the main platform for modeling everything we have D lab repo for each project.
41 00:07:28.130 ⇒ 00:07:45.080 Nicolas Sucari: I can give you access to that. I need just to ask. I I was trying to give you access yesterday to that. But we were running out of seats. So I’m gonna ask Utam if we can. Yeah, purchase one more so that you can access where we can. Yeah, maybe I don’t know if everyone there needs to be in there. But.
42 00:07:45.080 ⇒ 00:07:45.600 Aakash Tandel: And.
43 00:07:46.131 ⇒ 00:07:52.237 Nicolas Sucari: Yeah, I’m gonna just look into that. And then, yeah, for visualization. We are using real for pool parts.
44 00:07:53.380 ⇒ 00:07:55.619 Nicolas Sucari: I think, yeah, it’s only real, for now.
45 00:07:55.870 ⇒ 00:07:56.480 Aakash Tandel: Gotcha
46 00:07:57.005 ⇒ 00:08:06.469 Aakash Tandel: did when you were working with the marketing team? Did they use any marketing platform like like Google analytics or Google ads type of thing, or anything like that.
47 00:08:06.470 ⇒ 00:08:15.659 Nicolas Sucari: I think, yeah, I think yes, I’m not sure which one they’re using. But I think Google analytics. Yes, they were using also intelligence.
48 00:08:16.010 ⇒ 00:08:23.540 Nicolas Sucari: and let me see if I have anything else. What? What they are using in my notion that
49 00:08:24.570 ⇒ 00:08:31.900 Nicolas Sucari: yeah, I can remember now. But yeah, maybe they were using some other, some other tools.
50 00:08:32.200 ⇒ 00:08:33.190 Aakash Tandel: You, too.
51 00:08:33.190 ⇒ 00:08:34.099 Aakash Tandel: Okay, cool.
52 00:08:34.340 ⇒ 00:08:37.550 Aakash Tandel: That’s super helpful kind of getting an overview of
53 00:08:37.830 ⇒ 00:08:46.899 Aakash Tandel: how that I’m I’m basically just trying to understand, like all of the capabilities that we have, and like the way that our projects are currently run. So I can. You know.
54 00:08:47.290 ⇒ 00:08:49.470 Aakash Tandel: hop on to one, or also, you know.
55 00:08:49.590 ⇒ 00:08:54.831 Nicolas Sucari: No, no, that’s fine. Totally. Yeah. Ask any questions. I’m gonna try to to help you there.
56 00:08:55.140 ⇒ 00:08:56.480 Nicolas Sucari: What about Joby?
57 00:08:56.850 ⇒ 00:09:03.640 Nicolas Sucari: That’s full parts. And Javi, we started working with them also like to yeah, help them.
58 00:09:04.040 ⇒ 00:09:27.239 Nicolas Sucari: have like better accuracy on on their data. We started using Fivetran to ingest, like all of the the data sources. But the costs were spiking really, really quickly. So we moved to Portable. So everything right now is in portable except for that Amazon data that we don’t have the connector available there. We already we already linked
59 00:09:27.240 ⇒ 00:09:28.479 Nicolas Sucari: kind of their
60 00:09:28.877 ⇒ 00:09:58.229 Nicolas Sucari: shopify, I think. Gorgeous or kendo recharge north beam data. And they have, like some spreadsheet for cogs. And yeah, we’re helping them with a bunch of different reports right now. They they use amplitude. They were using amplitude for all of their reporting, and we are moving. What we are trying to do is to move everything away from amplitude and into Meta base. Because they were not using any data warehouse. Right? So we set up
61 00:09:58.250 ⇒ 00:09:59.370 Nicolas Sucari: Snowflake
62 00:09:59.968 ⇒ 00:10:17.249 Nicolas Sucari: with the amplitude data. We kind of went directly to gather all of the the data directly for each platform and not to bring everything from amplitude. And we started to. Yeah, build our own data warehouse with all of the data from each platform and build some dashboards in metase.
63 00:10:17.770 ⇒ 00:10:44.130 Nicolas Sucari: But yeah, they have. They? They are still using both. Amplitude, like they have a bunch of reports in amplitude. And now that we are starting using to, we’re starting to use Meta base we are kind of building some reports there. So you you’re you. Maybe you heard about the net margin dashboard, or the Amazon dashboard that we are building. Those are in Meta base kinds of what we shared. I think Robert shared that yesterday to the client.
64 00:10:46.148 ⇒ 00:10:49.670 Aakash Tandel: Okay, cool. So one.
65 00:10:49.670 ⇒ 00:10:53.469 Nicolas Sucari: Javi, yeah, I can explain a little bit what Javi coffee does if you want.
66 00:10:53.470 ⇒ 00:10:54.109 Nicolas Sucari: Sure, yeah.
67 00:10:54.574 ⇒ 00:11:09.450 Nicolas Sucari: so they sell, you can access their website also and and figure that out. But they sell kind of coffee concentrates and protein coffee and yeah, syrups and everything regarding coffee.
68 00:11:09.590 ⇒ 00:11:12.849 Nicolas Sucari: And they say, Oh, yeah, online, cool with those ones.
69 00:11:12.850 ⇒ 00:11:35.490 Aakash Tandel: Yeah. So I’m kind of thinking about this in kind of 2 phases, and tell me if this is right or wrong, in we we’re gonna be doing some sort of building, some sort of pipelining, some sort of data warehousing. And then on the back end, we’re gonna be doing some sort of reporting in a dashboard, and then maybe doing some analysis. Is that a split that you feel like is kind of correct.
70 00:11:35.940 ⇒ 00:12:01.700 Nicolas Sucari: So right now, kind of when we start working on on each client like each client has has different steps, right? We have, like all of the like architecture, part of of of the of the project where we kind of set up the data warehouse we set up like these kind of ingestion tools. Once we have, like the raw data, it’s it’s like the second step when we start like modeling all of that data so that we can then use those
71 00:12:01.700 ⇒ 00:12:15.359 Nicolas Sucari: those tables or that information into reports. And once we have the reports, yeah, we start the analysis. And and yeah, just sharing with the client what we have or what they want us to be working on in.
72 00:12:15.800 ⇒ 00:12:20.990 Nicolas Sucari: So yeah, those are kind of the 3 different parts that each project has.
73 00:12:21.457 ⇒ 00:12:31.229 Nicolas Sucari: But yeah, kind of the the 1st part of this is that engineering part with the architecture stuff. It’s kind of the 1st always is the same. And we are trying, like, yeah, to
74 00:12:31.693 ⇒ 00:12:50.529 Nicolas Sucari: speed that up as as much as possible, because that is something that we usually cannot share with the client. Right? It’s not so visual and like the deliverables, are not so easy to share with the client, because, like, they are not seeing anything right? Right? They wanna see analysis and dashboards most of the time.
75 00:12:50.530 ⇒ 00:12:52.710 Aakash Tandel: Yeah, yeah, they don’t care how you’re kind of.
76 00:12:52.710 ⇒ 00:12:53.740 Nicolas Sucari: Exactly. Yeah.
77 00:12:53.740 ⇒ 00:12:58.530 Aakash Tandel: You get the answer, yeah, that makes a little sense. Cool.
78 00:13:00.500 ⇒ 00:13:04.736 Aakash Tandel: I had another question. I’m kind of blanking on what that was,
79 00:13:06.560 ⇒ 00:13:11.689 Aakash Tandel: how long does it typically take for us to do kind of that data engineering piece is that like.
80 00:13:11.840 ⇒ 00:13:13.679 Aakash Tandel: that’s very variable? I’m assuming.
81 00:13:14.040 ⇒ 00:13:25.109 Nicolas Sucari: So yeah, it depends on the amount of like data sources or stuff that we need to bring in. But I’ll say, like it. It’s it. It needs to take
82 00:13:25.240 ⇒ 00:13:30.870 Nicolas Sucari: no more than 2 weeks actually like in a week in in one week you should be able to set up
83 00:13:31.210 ⇒ 00:13:59.160 Nicolas Sucari: like the snowflake, and like the ingestion tool, and then bring the data in right. If there is a huge amount of data, for example, on Javi has, like really large sets of data on each platform it took it took. It took long to just bring everything in. But once we have that, it’s just something that keeps running on its own. And we don’t need to do anything right. We just then need to model all of the that raw data into
84 00:13:59.160 ⇒ 00:14:18.849 Nicolas Sucari: the models that we already know how they work. And we and we kind of are learning each project, each new project, if we need like. If we have, like a new project now, and we need to model the shopify data. We already did that with other clients. So it should be kind of the same right, so we should be able to speed that up.
85 00:14:19.710 ⇒ 00:14:21.976 Aakash Tandel: Okay, yeah, that makes sense.
86 00:14:22.610 ⇒ 00:14:33.639 Aakash Tandel: would. Are we doing any sort of like upfront planning or like meeting with a client asking them how like what they want to see in the data like how they want to see the reports. That type of thing.
87 00:14:34.220 ⇒ 00:14:52.159 Nicolas Sucari: Yeah. So each client has kind of a weekly meeting with us where we kind of share updates and and talk about like these new requests. We try to plan like the next week, and and that stuff with javi like before starting the project. The only ones that kind of talk
88 00:14:52.160 ⇒ 00:15:10.799 Nicolas Sucari: to the clients are Robert and Utam. So they kind of gather all of the requests, and and kind of create. Yeah, and and try to, just before closing the client. Try to sell a little bit what we do and how we can help. And once that is ready, yeah, the team starts to just working on
89 00:15:11.234 ⇒ 00:15:25.569 Nicolas Sucari: any request that the client had as a priority. Yeah, cool. But every week the idea is that every week. We have, like a touch point with the client where we can share. What we did. And yeah, gather and discuss new requests for the future
90 00:15:26.440 ⇒ 00:15:34.267 Nicolas Sucari: and for like for planning meeting. I think Uten is hosting the planning meeting with the entire data team on Mondays.
91 00:15:35.060 ⇒ 00:15:41.650 Nicolas Sucari: I think so. I I don’t know if that’s happening. I think he started to do it, but I don’t know if he’s still doing it.
92 00:15:41.960 ⇒ 00:15:44.869 Aakash Tandel: Yeah, I see a weekly kickoff. It’s probably that one.
93 00:15:44.870 ⇒ 00:15:48.799 Nicolas Sucari: No, the weekly kickoff is kind of yeah. The entire team meeting.
94 00:15:48.800 ⇒ 00:15:52.150 Nicolas Sucari: Okay, Monday’s bad. Let me see.
95 00:15:53.380 ⇒ 00:15:56.849 Nicolas Sucari: I’m not on those calendars anymore. But
96 00:15:57.150 ⇒ 00:16:02.440 Nicolas Sucari: yeah, if not, it’s in the in the daily meeting on Mondays, probably.
97 00:16:02.600 ⇒ 00:16:02.960 Aakash Tandel: Yeah.
98 00:16:02.960 ⇒ 00:16:03.660 Nicolas Sucari: Yeah.
99 00:16:03.660 ⇒ 00:16:07.570 Aakash Tandel: Okay, yeah, I’ll take a look at that. Okay, cool.
100 00:16:07.690 ⇒ 00:16:15.429 Aakash Tandel: That’s yeah. That’s a lot of that’s a lot of helpful context. And it’s honestly, just easier to kind of interview.
101 00:16:15.430 ⇒ 00:16:16.770 Aakash Tandel: Yeah, yeah, I know
102 00:16:16.770 ⇒ 00:16:29.849 Aakash Tandel: documents. Because the narrative, I think, helps a lot with kind of how the things are flowing through a given project. But that’s a lot of good information. Do you have any questions for me? I don’t know. That’s irrelevant.
103 00:16:29.850 ⇒ 00:16:34.105 Nicolas Sucari: Oh, but maybe I can tell you a little bit about the other clients.
104 00:16:34.560 ⇒ 00:16:51.831 Nicolas Sucari: that I know. So ABC is an AI client, as I think you know, so don’t know if you’re gonna be participating in any of that. Then the the 2 biggest clients right now that we have, I think, are Eden and Javi. So those are the ones with more movement
105 00:16:52.310 ⇒ 00:17:08.160 Nicolas Sucari: most of the time. Like Eden, they are requesting a lot. Robert is handling all of the engagement and conversations with the client. And for Javi, yeah, they are asking also, like a lot of stuff we have, like our main point of contact. That is, Aman. A man?
106 00:17:08.584 ⇒ 00:17:28.245 Nicolas Sucari: He’s kind of yeah. Vp of, I think it’s a technology or data or something like that. But we also like Robert also meets with the CEO and Cfo of the company. So we kind of have, like different requests from different people. And I think like that’s like a big
107 00:17:28.920 ⇒ 00:17:44.219 Nicolas Sucari: opportunity that we need to work on, and how we translate what Robert Utam or anyone talking with the client knows and what the client request and how we can translate that into tasks for the team. That’s yeah. We we’ve been struggling a little bit on that one.
108 00:17:44.570 ⇒ 00:17:52.369 Aakash Tandel: Yeah, yeah, taking kind of the I’m assuming, like business logic and converting that to like actual like engineering and data analysis.
109 00:17:52.370 ⇒ 00:17:55.299 Nicolas Sucari: Yeah, exactly. Exactly. Yeah. This this past
110 00:17:55.340 ⇒ 00:18:22.589 Nicolas Sucari: 2 weeks, I think, Kyle, and we’re working on having like a spreadsheet with how the structure of the like, the the modeling part works like which tables we are creating. And if you have a question on yeah, I don’t know. I need to know the exact amount of sales. Okay, we have these tables. We have these. And if you need any change as an analyst, okay, you just let us know or comment on this sheet, and we can try to model that work for you.
111 00:18:23.389 ⇒ 00:18:45.420 Nicolas Sucari: I think that’s been useful this last week. But yeah, maybe you should, yeah, ask, or anyone on the data team about that. Because, yeah, kind of yeah, we we received before we received like the the like, the analyst question. And we needed to build back all of the modeling and things that we will need. And we’re trying to work that the other way around.
112 00:18:46.022 ⇒ 00:18:55.059 Aakash Tandel: Cool. No, that makes total sense. Yeah, I think there’s i’m meeting with both robert and item today, so i’ll definitely discuss that stuff with them. Yeah, I think the like.
113 00:18:55.603 ⇒ 00:19:12.229 Aakash Tandel: It sounds like we’re good at tactically doing the things that like there are asked of us. But getting the the people who are obviously not like data experts and translating like, what we’re doing to them is a thing that we can improve. Yeah.
114 00:19:12.230 ⇒ 00:19:12.670 Nicolas Sucari: Yeah.
115 00:19:12.670 ⇒ 00:19:13.100 Aakash Tandel: That’s good.
116 00:19:13.100 ⇒ 00:19:13.889 Nicolas Sucari: Yeah. Yeah.
117 00:19:14.150 ⇒ 00:19:15.030 Nicolas Sucari: Totally.
118 00:19:15.420 ⇒ 00:19:16.319 Aakash Tandel: Cool. Yeah.
119 00:19:17.010 ⇒ 00:19:19.850 Nicolas Sucari: What about you? Where? Where are you based in the Us.
120 00:19:19.850 ⇒ 00:19:31.689 Aakash Tandel: I’m based in Charlottesville, Virginia, which is about 2 h south of DC. So I used to live in DC. For a long time, and now I’m in Charlottesville. It’s a smaller town, but it’s not too bad. It’s nice still.
121 00:19:31.690 ⇒ 00:19:32.220 Nicolas Sucari: Okay.
122 00:19:32.220 ⇒ 00:19:32.830 Aakash Tandel: Yeah.
123 00:19:33.600 ⇒ 00:19:34.240 Nicolas Sucari: Great.
124 00:19:34.705 ⇒ 00:19:37.629 Aakash Tandel: Do you watch any soccer? Do you? Do you follow football at all?
125 00:19:37.630 ⇒ 00:19:38.370 Nicolas Sucari: Yeah.
126 00:19:38.370 ⇒ 00:19:40.019 Aakash Tandel: Yeah, okay, I.
127 00:19:40.020 ⇒ 00:19:45.050 Nicolas Sucari: I’m I’m a big fan of River Plate. I don’t know if you know the team here in Argentina.
128 00:19:45.701 ⇒ 00:19:48.749 Aakash Tandel: No, I’m not familiar with that one. I
129 00:19:49.360 ⇒ 00:19:50.670 Nicolas Sucari: I’m familiar with Boca.
130 00:19:50.950 ⇒ 00:19:52.406 Aakash Tandel: Boca, yes. Yeah. Yeah.
131 00:19:52.770 ⇒ 00:19:53.200 Aakash Tandel: Wow.
132 00:19:53.750 ⇒ 00:19:57.809 Nicolas Sucari: That’s our our, like, yeah, our opposite. Yeah, yeah.
133 00:19:57.810 ⇒ 00:20:09.460 Aakash Tandel: Yeah, yeah, I I primarily watch the Epl. And I watch Chelsea. So Enzo Fernandez is. Exactly. Yeah. Yeah. He’s definitely on
134 00:20:09.680 ⇒ 00:20:10.320 Aakash Tandel: the.
135 00:20:10.320 ⇒ 00:20:14.610 Nicolas Sucari: And so for. And so Fernandez was from my home team from yeah.
136 00:20:14.830 ⇒ 00:20:15.510 Aakash Tandel: Nice.
137 00:20:15.510 ⇒ 00:20:18.680 Nicolas Sucari: It’s the one with the white and red T-shirt. Yeah.
138 00:20:18.680 ⇒ 00:20:21.220 Aakash Tandel: Okay. Okay. Nice. Yeah.
139 00:20:21.220 ⇒ 00:20:28.010 Nicolas Sucari: And yeah, and this year we were gonna be, we’re gonna be playing there for the Club World Cup.
140 00:20:28.010 ⇒ 00:20:29.779 Aakash Tandel: Oh, yeah. Yeah.
141 00:20:29.780 ⇒ 00:20:34.270 Nicolas Sucari: It’s there. It’s gonna be in the Us. It’s gonna be super super cool. I think I don’t know.
142 00:20:34.750 ⇒ 00:20:38.169 Aakash Tandel: Yeah, I is this the 1st one they’ve done or no? It’s yeah.
143 00:20:38.170 ⇒ 00:20:40.149 Nicolas Sucari: Yeah, it’s gonna be the 1st edition. Yeah.
144 00:20:40.150 ⇒ 00:21:01.499 Aakash Tandel: Yeah, cause I was like, I’ve never heard this thing before. And I how did I miss this? And I, yeah, it’s yeah. I’m excited. There’s a lot of good even. We have the World Cup coming up in like, yeah. And I’m like, really excited about that. I don’t know if I’ll be able to go to any matches because I have a young baby. I had a my wife and I had a baby last September, so he’s only 6 months old.
145 00:21:01.500 ⇒ 00:21:02.120 Nicolas Sucari: Nice.
146 00:21:02.120 ⇒ 00:21:02.930 Aakash Tandel: He’s a little young to.
147 00:21:02.930 ⇒ 00:21:03.850 Nicolas Sucari: Now. But
148 00:21:04.050 ⇒ 00:21:10.399 Nicolas Sucari: you’re gonna be able. That’s fine. Yeah, here in Argentina people just crazy. And they they take their babies.
149 00:21:10.600 ⇒ 00:21:11.060 Aakash Tandel: Yeah.
150 00:21:11.060 ⇒ 00:21:19.119 Nicolas Sucari: Yeah to the match. But yeah, I mean, the World Cup is. Next year I went. I went to the Last World Cup in in Qatar, in Doha.
151 00:21:19.270 ⇒ 00:21:19.620 Aakash Tandel: Just.
152 00:21:19.620 ⇒ 00:21:24.449 Nicolas Sucari: Crazy. Yeah, it was crazy. Yeah, it’s a great experience.
153 00:21:24.660 ⇒ 00:21:37.529 Aakash Tandel: Yeah, I definitely wanna make a I was bummed because, there’s the I think the closest stadium to me is in New York. When Washington, DC. And Baltimore both have pretty good stadium. So I was like, Oh, man, they didn’t. They didn’t win any of the the
154 00:21:38.070 ⇒ 00:21:43.939 Aakash Tandel: but I’ll definitely still have to make a make a trip to one of them, because it it doesn’t come to your own country
155 00:21:44.050 ⇒ 00:21:45.410 Aakash Tandel: regularly. It’s not all.
156 00:21:45.410 ⇒ 00:21:56.760 Nicolas Sucari: Yeah, I mean, if you can. If you if you can go to see like an Argentina much, it’s crazy like the the ambience the people.
157 00:21:56.890 ⇒ 00:22:12.969 Nicolas Sucari: Yeah, everything is crazy, like Argentina, Mexico. I think they are like most the the people are like, yeah, where where the fans go to the most matches, the rest of the the rest of the teams. They you don’t feel like that
158 00:22:13.363 ⇒ 00:22:28.259 Nicolas Sucari: environment in the stadium. But but yeah, I mean, obviously, it’s it’s great. And if you have the World Cup there, you should go to any match. I’m still. I’m still thinking about going next year for the World Cup. Yeah.
159 00:22:28.260 ⇒ 00:22:48.899 Aakash Tandel: Yeah, yeah, definitely. Yeah. Another thing I wanna do is I wanna see a inter Miami game, just because to see Messi live, I think would be super cool. The local team closest to me is like the worst in the League for Mls, so it’s like their tickets are always so cheap. But then, when they play, obviously someone like Inter Milan, it’s like, or inter Milan inter.
160 00:22:48.900 ⇒ 00:22:49.620 Nicolas Sucari: Something like that.
161 00:22:49.890 ⇒ 00:23:00.430 Aakash Tandel: It’s it’s a lot more expensive. So I definitely wanna put that on my to do list, because, you know, he’s not gonna play forever at inter inner Miami. So might as well get that one.
162 00:23:01.430 ⇒ 00:23:22.599 Nicolas Sucari: It’s really good. Yeah. I mean, it’s totally different to see him in, like in the club or in the national team. But yeah, I mean, if you have the opportunity, go there and see. It’s great. You’re gonna see something that it’s like. If you are into soccer you can see like whatever he, when whenever he touches ball, is something magic.
163 00:23:22.930 ⇒ 00:23:28.029 Aakash Tandel: Yeah, exactly. Yeah. And especially in the Mls where it’s like he’s miles away from anyone.
164 00:23:28.030 ⇒ 00:23:28.450 Nicolas Sucari: Yeah.
165 00:23:28.450 ⇒ 00:23:30.189 Aakash Tandel: Else there. So yeah.
166 00:23:30.190 ⇒ 00:23:34.770 Nicolas Sucari: But yeah, and do you like other sports? Or are you just into soccer? Right now?
167 00:23:34.770 ⇒ 00:23:38.827 Aakash Tandel: I’m probably primarily into soccer. I watch a little bit of basketball.
168 00:23:39.140 ⇒ 00:23:39.710 Nicolas Sucari: Nba.
169 00:23:39.710 ⇒ 00:23:51.740 Aakash Tandel: Yeah, Nba, but I follow the wizards, and they’re terrible. So yeah, it’s primarily, it’s mostly soccer. Mostly Chelsea. And then the Nba, yeah, yeah.
170 00:23:51.740 ⇒ 00:23:55.379 Nicolas Sucari: Okay, that’s great. Great, yeah, super interesting.
171 00:23:55.380 ⇒ 00:24:00.357 Aakash Tandel: Yeah, yeah, man. Well, it was good catching up. Thanks for taking the time to meet
172 00:24:00.650 ⇒ 00:24:01.380 Nicolas Sucari: Yeah, of course.
173 00:24:01.380 ⇒ 00:24:09.600 Aakash Tandel: Alright. Yeah, I’ll let you know if I have any other questions. But yeah, I’m just trying to meet like everyone on the team and just get a lay of the land. And then, yeah, hopefully can help out working.
174 00:24:10.160 ⇒ 00:24:15.100 Nicolas Sucari: Yeah, just let me know if you have any question. Just DM, me, I can help you with anything I know. Okay.
175 00:24:15.100 ⇒ 00:24:17.309 Aakash Tandel: Okay. Sounds good. Thanks, Nico. Have a good day.
176 00:24:17.310 ⇒ 00:24:18.619 Nicolas Sucari: Thank you. Bye, bye.
177 00:24:18.620 ⇒ 00:24:19.190 Aakash Tandel: Bye.