Meeting Title: Friday Brainforge Demos & Retro Date: 2025-11-03 Meeting participants: Mustafa Raja, Samuel Roberts, Rico Rejoso, Casie Aviles, Hannah Wang, Uttam Kumaran, Amber Lin, Demilade Agboola, Zoran Selinger, Gabriel Lam
WEBVTT
1 00:01:31.160 ⇒ 00:01:32.380 Uttam Kumaran: Hello?
2 00:01:33.120 ⇒ 00:01:34.190 Amber Lin: Hello.
3 00:01:34.720 ⇒ 00:01:40.329 Amber Lin: Are we running this like the Friday meeting where we have icebreakers, or what’s the plan?
4 00:01:40.330 ⇒ 00:01:43.580 Uttam Kumaran: Yes, but I’m planning something…
5 00:01:43.580 ⇒ 00:01:44.110 Amber Lin: Okay.
6 00:01:44.110 ⇒ 00:01:51.679 Uttam Kumaran: So I have two things, I can just wait till everybody joins. And then, Rico, can we make sure Gabe is here? I would love to intro him.
7 00:01:52.110 ⇒ 00:01:54.630 Uttam Kumaran: And then, yeah, we can probably run this for the first…
8 00:01:55.040 ⇒ 00:01:59.519 Uttam Kumaran: I just wanted to spend maybe the first 30 minutes or so, and then,
9 00:02:00.060 ⇒ 00:02:08.059 Uttam Kumaran: I also have another sort of activity I wanted to share that I think will be kind of productive. I wanted to share with you guys this one sales call that I did.
10 00:02:50.130 ⇒ 00:02:51.960 Uttam Kumaran: Okay, let’s see who else is on.
11 00:03:03.840 ⇒ 00:03:07.929 Uttam Kumaran: I know, Ryan from Marketing is off this week.
12 00:03:14.450 ⇒ 00:03:16.479 Samuel Roberts: Okay, I feel like we have everybody.
13 00:03:16.480 ⇒ 00:03:19.000 Uttam Kumaran: So I wanted to start with one…
14 00:03:19.610 ⇒ 00:03:23.479 Uttam Kumaran: sort of, icebreaker, and I’m gonna see how I can do…
15 00:03:24.850 ⇒ 00:03:30.179 Uttam Kumaran: Breakout rooms, we have 1, 2, 3, 4, 5, 6, 7, 8, 10…
16 00:03:46.750 ⇒ 00:04:02.699 Uttam Kumaran: Okay, so I have a breakout room question, and so a lot of what I’m going to be trying this week, and I’m actually ringing on some more assistants, I had a great conversation with Demolade last week about trying to build more,
17 00:04:03.060 ⇒ 00:04:12.279 Uttam Kumaran: team camaraderie, and so I’m thinking about a couple of ways to make this meeting a little bit more, a little bit less like every other meeting.
18 00:04:12.440 ⇒ 00:04:21.249 Uttam Kumaran: I still want to talk a little bit about some broader company stuff, but I wanted it to be more of, like, folks get to spend time with each other. Additionally, I think
19 00:04:21.370 ⇒ 00:04:30.469 Uttam Kumaran: I wanted to share… do something else unique after this, which is, like, review a sales call with everybody. So, we’ll do this little…
20 00:04:30.820 ⇒ 00:04:35.249 Uttam Kumaran: game to start, so I’ll be creating breakout rooms,
21 00:04:36.360 ⇒ 00:04:43.360 Uttam Kumaran: And so, if you go ahead and join your room, I’m gonna send…
22 00:04:43.910 ⇒ 00:04:47.660 Uttam Kumaran: there is a scenario here that I’ll be sending to everybody, and then…
23 00:04:47.850 ⇒ 00:04:51.799 Uttam Kumaran: I’ll have everybody join back in, like, 5 minutes. That’s fine.
24 00:04:56.720 ⇒ 00:04:58.790 Uttam Kumaran: And I’m gonna join my room.
25 00:08:44.270 ⇒ 00:08:46.200 Samuel Roberts: Now in the main session, okay.
26 00:08:51.480 ⇒ 00:08:54.010 Samuel Roberts: I guess it would have just taken us back, maybe, I don’t know.
27 00:08:54.530 ⇒ 00:08:55.520 Amber Lin: Yeah, that’s okay.
28 00:08:55.520 ⇒ 00:09:01.750 Samuel Roberts: Alright, well, we did it faster than everyone else, and hopefully, hopefully we didn’t miss anything obvious.
29 00:10:14.630 ⇒ 00:10:19.210 Uttam Kumaran: I feel like I… I’ve, I, I like… Thinking about.
30 00:10:19.650 ⇒ 00:10:22.730 Samuel Roberts: Stranded on the island movies, and, like.
31 00:10:23.180 ⇒ 00:10:27.660 Uttam Kumaran: I feel like… and I’ve also… I’ve been watching Alone, on,
32 00:10:28.690 ⇒ 00:10:32.299 Uttam Kumaran: on Netflix, which is, like, they put people on…
33 00:10:32.410 ⇒ 00:10:38.089 Uttam Kumaran: an island, and you have to survive the longest person to survive, and they’re all solo. It’s like a very pure survival.
34 00:10:38.090 ⇒ 00:10:38.940 Samuel Roberts: Oh…
35 00:10:38.940 ⇒ 00:10:39.579 Uttam Kumaran: reality TV.
36 00:10:39.580 ⇒ 00:10:40.420 Samuel Roberts: Oh, wow.
37 00:10:45.030 ⇒ 00:10:45.930 Samuel Roberts: Wow.
38 00:11:02.660 ⇒ 00:11:05.400 Uttam Kumaran: They, like, they, they have… so it’s, like, maybe…
39 00:11:05.790 ⇒ 00:11:16.129 Uttam Kumaran: 15 people, they put them in all different parts of, like, Alaska, and then you don’t know… the last one to survive wins the prize, but you don’t know who else is also surviving.
40 00:11:16.130 ⇒ 00:11:16.950 Samuel Roberts: Right.
41 00:11:17.120 ⇒ 00:11:20.120 Uttam Kumaran: And so, someone survived for, like, 100 days.
42 00:11:22.000 ⇒ 00:11:28.460 Samuel Roberts: And, like, the second place was, like, 10 days, and he’s just out there for, like, 90 more days, just, like, trying to win.
43 00:11:29.600 ⇒ 00:11:31.830 Samuel Roberts: That’s crazy, not knowing is nuts, yeah.
44 00:11:31.830 ⇒ 00:11:33.230 Uttam Kumaran: Yeah, yeah, yeah.
45 00:11:34.030 ⇒ 00:11:35.310 Samuel Roberts: 100 days.
46 00:11:35.830 ⇒ 00:11:40.079 Samuel Roberts: Is it… is this, like, his… is he, like, a professional survival guy? Like, who… who does that?
47 00:11:40.080 ⇒ 00:11:44.000 Uttam Kumaran: So most… most of the people are professional survival people.
48 00:11:44.000 ⇒ 00:11:49.930 Samuel Roberts: Okay. Or they’re, like, wilderness experts. That’s what I mean, yeah, like, he knows what he’s doing, he’s not just some rando off the street.
49 00:11:49.930 ⇒ 00:11:52.060 Uttam Kumaran: Yeah. Yeah, yeah, yeah, yeah, yeah.
50 00:11:52.410 ⇒ 00:11:57.390 Gabriel Lam: Is this a show where, like, you send a bunch of people out, and the last person to stay out.
51 00:11:57.390 ⇒ 00:11:58.380 Uttam Kumaran: Yeah, alone.
52 00:11:58.380 ⇒ 00:11:59.939 Gabriel Lam: Yeah. Yeah, yeah.
53 00:12:00.530 ⇒ 00:12:01.170 Samuel Roberts: Wow.
54 00:12:01.170 ⇒ 00:12:02.980 Uttam Kumaran: I love that show, it’s so good.
55 00:12:03.420 ⇒ 00:12:06.479 Uttam Kumaran: Okay, cool. Everybody’s back. So…
56 00:12:06.600 ⇒ 00:12:14.029 Uttam Kumaran: Who wants to go first? I guess if we can have one person from every room go, that would be amazing. Maybe, Gabe, you can go first.
57 00:12:15.540 ⇒ 00:12:17.890 Gabriel Lam: Well, Anna and I were just like…
58 00:12:18.570 ⇒ 00:12:22.419 Gabriel Lam: What are the 3 things that you probably need to worry about, which is…
59 00:12:22.540 ⇒ 00:12:25.090 Gabriel Lam: Where to live, what to drink, and…
60 00:12:26.200 ⇒ 00:12:33.830 Gabriel Lam: And everything else, so we just went with a knife, a tent, and a life straw, which is basically, like, a water filter that’s a straw.
61 00:12:34.240 ⇒ 00:12:37.860 Gabriel Lam: Cuts… covers all the bases.
62 00:12:38.270 ⇒ 00:12:41.920 Gabriel Lam: Maybe a bit of a cough-out with the tent, but we’re like, it’s fine.
63 00:12:42.550 ⇒ 00:12:46.580 Uttam Kumaran: That’s funny. Okay, nice.
64 00:12:47.080 ⇒ 00:12:50.139 Uttam Kumaran: Yeah, Zoran, you wanna go?
65 00:12:50.140 ⇒ 00:13:07.390 Zoran Selinger: Sure, sure. I mean, the first thing always is the water. That’s… we have the least amount of time without water, so that’s the first thing. Anything to clear the water, so whether… are those tablets or the straw is… I think that’s really, really important.
66 00:13:07.390 ⇒ 00:13:08.060 Uttam Kumaran: Yeah.
67 00:13:08.550 ⇒ 00:13:10.320 Zoran Selinger: But then,
68 00:13:10.650 ⇒ 00:13:30.420 Zoran Selinger: starting a fire. Like, for food, you have… you have a little bit of time to… to find food, you’re not gonna die immediately. But the elements can really hurt you. So, you’ll find materials to build a shelter, I think that’s fine, we don’t have to bring that, but starting a fire, if you’re not… if you don’t practice it.
69 00:13:31.500 ⇒ 00:13:32.170 Uttam Kumaran: hard.
70 00:13:32.390 ⇒ 00:13:37.529 Zoran Selinger: is really hard, so I think a fire starter is really good, and then anything really sharp.
71 00:13:37.670 ⇒ 00:13:49.429 Zoran Selinger: To help you with, with basically the trash you’re gonna find on the beach, to mold into whatever you need is gonna be… is gonna help a lot. So, yeah, that’s the three of them.
72 00:13:50.020 ⇒ 00:13:55.099 Uttam Kumaran: Nice. Yeah, I guess we didn’t do, like, a bowl, but for me and Rico, we did…
73 00:13:55.290 ⇒ 00:13:58.829 Uttam Kumaran: Matches, fishing line, and then an axe.
74 00:13:59.050 ⇒ 00:14:06.179 Uttam Kumaran: But I guess, you’re right, like, we’ve said, like, oh, we can boil water, but I guess we don’t have anything to boil it in, so we have to
75 00:14:06.600 ⇒ 00:14:10.429 Uttam Kumaran: Prey on finding, like, a bull… Or, like, a pan.
76 00:14:11.160 ⇒ 00:14:16.239 Zoran Selinger: I think you can do it… you can do it even in a plastic container.
77 00:14:16.860 ⇒ 00:14:18.839 Zoran Selinger: You can boil water in a plastic container.
78 00:14:18.840 ⇒ 00:14:19.740 Uttam Kumaran: Really?
79 00:14:19.740 ⇒ 00:14:21.369 Zoran Selinger: Weird, yeah, you can do it.
80 00:14:21.730 ⇒ 00:14:24.029 Uttam Kumaran: And you just keep it, like, pretty high up above the flame.
81 00:14:24.030 ⇒ 00:14:28.699 Zoran Selinger: I’m not 100% sure how it works, but I’ve seen it multiple times.
82 00:14:29.340 ⇒ 00:14:31.469 Zoran Selinger: So, I think you’ll be good there.
83 00:14:31.890 ⇒ 00:14:32.990 Uttam Kumaran: Okay, alright.
84 00:14:32.990 ⇒ 00:14:34.680 Zoran Selinger: domestic everywhere.
85 00:14:34.680 ⇒ 00:14:45.630 Uttam Kumaran: And yeah, the biggest thing for me is, like, get fishing line, because you can repurpose it, but then we can fish easily. You find a stick, you find that, you can make a little lure, and then Axe was, like, yeah, cutting anything, so…
86 00:14:45.840 ⇒ 00:14:46.400 Samuel Roberts: enough.
87 00:14:46.680 ⇒ 00:14:50.329 Uttam Kumaran: Nice. Okay, Mustafa, what about your team?
88 00:14:51.050 ⇒ 00:15:09.609 Mustafa Raja: So, me and then Medaria came up with a list of what we need. We need fishing equipment for food, then we… then we would want some, water filters to filter out the water, and then satellite phones to get some help and get out of there.
89 00:15:11.330 ⇒ 00:15:18.149 Demilade Agboola: Like all of you, we were thinking of how we can’t stay there forever, so we needed something to get us out of there, so…
90 00:15:18.150 ⇒ 00:15:21.060 Uttam Kumaran: I said this is my new home.
91 00:15:21.060 ⇒ 00:15:22.530 Samuel Roberts: Yeah, exactly.
92 00:15:22.720 ⇒ 00:15:36.840 Demilade Agboola: No, we’re… we want the satellite phone that… you know, because, like, they… I mean, obviously, satellite phones just need satellite access, and we… obviously, they don’t take as much power, because they’re meant to be, like, outdoor survival phones, so…
93 00:15:36.840 ⇒ 00:15:38.430 Uttam Kumaran: Okay.
94 00:15:40.420 ⇒ 00:15:41.420 Uttam Kumaran: Nice.
95 00:15:42.330 ⇒ 00:15:45.020 Uttam Kumaran: Now, you guys will be back at home in no time.
96 00:15:45.530 ⇒ 00:15:54.149 Demilade Agboola: Give us, give us 7 days. We just… we just need the water and the fishing equipment to survive the 7 days, but we’ll be fine, we’ll be fine.
97 00:15:54.510 ⇒ 00:15:56.499 Uttam Kumaran: Yeah, yeah. Nice.
98 00:15:56.860 ⇒ 00:15:58.889 Uttam Kumaran: Okay. Who else?
99 00:16:00.030 ⇒ 00:16:09.409 Samuel Roberts: Ember and I came up with very similar things. We thought water, but I specifically wasn’t sure what was on the island, so I was worried about desalination of ocean water.
100 00:16:09.580 ⇒ 00:16:11.170 Samuel Roberts: I want something to…
101 00:16:11.170 ⇒ 00:16:12.280 Uttam Kumaran: Hmm…
102 00:16:12.280 ⇒ 00:16:18.480 Samuel Roberts: not just filter the water, but desalinate. And I was looking it up real quick, there are portable versions, so I would bring.
103 00:16:18.480 ⇒ 00:16:19.080 Uttam Kumaran: Nice.
104 00:16:19.080 ⇒ 00:16:22.030 Samuel Roberts: We then said,
105 00:16:22.230 ⇒ 00:16:28.269 Samuel Roberts: We were worried about fire, but we were worried about how long we’d be there, so we didn’t want just, like, a box of matches or something. We went with flint and steel.
106 00:16:29.010 ⇒ 00:16:36.960 Samuel Roberts: A little… little set, fire starter set, and then an axe for not just cutting down things, but protection from whatever else is on the island, potentially.
107 00:16:37.640 ⇒ 00:16:38.860 Uttam Kumaran: Nice, okay.
108 00:16:40.070 ⇒ 00:16:46.500 Samuel Roberts: And then we’ll… yeah, we’d build our lives there, because we would… didn’t have a way to get off, wasn’t even thinking about getting off!
109 00:16:47.270 ⇒ 00:16:55.339 Samuel Roberts: Honestly, one thing that could be… another better idea is you bring a little offline AI to ask questions on how to, like, do everything, you know? Yeah, that’s right, yeah.
110 00:16:56.040 ⇒ 00:16:59.540 Uttam Kumaran: Yeah, I would bring, like, a little, like, Raspberry Pi.
111 00:16:59.540 ⇒ 00:17:02.759 Demilade Agboola: Of course, of course, Otam’s suggestion is offline AI.
112 00:17:03.390 ⇒ 00:17:11.129 Uttam Kumaran: Well, dude, I don’t… I would just be like, hey, I have, like, a plastic jug, I have, like, the side of an airplane.
113 00:17:11.490 ⇒ 00:17:13.360 Uttam Kumaran: what can I do with this?
114 00:17:13.369 ⇒ 00:17:14.619 Samuel Roberts: Fiverr GPT.
115 00:17:14.619 ⇒ 00:17:17.639 Uttam Kumaran: How do I eat this?
116 00:17:18.000 ⇒ 00:17:19.730 Demilade Agboola: I’ll be like, I learned GPT.
117 00:17:20.329 ⇒ 00:17:20.879 Samuel Roberts: Yeah, yeah.
118 00:17:20.880 ⇒ 00:17:23.560 Uttam Kumaran: than GPT.
119 00:17:24.780 ⇒ 00:17:28.209 Uttam Kumaran: It’s nice. Okay, did we do… did we get everybody?
120 00:17:31.850 ⇒ 00:17:32.960 Gabriel Lam: I think so.
121 00:17:32.960 ⇒ 00:17:33.550 Samuel Roberts: Yeah?
122 00:17:33.830 ⇒ 00:17:39.320 Uttam Kumaran: Okay, cool. So one thing I wanted to do that was a little bit,
123 00:17:39.490 ⇒ 00:17:44.299 Uttam Kumaran: unique today, but I’ve been,
124 00:17:44.590 ⇒ 00:17:50.269 Uttam Kumaran: I think some of us on the team are sports fans, and I’ve been watching, every…
125 00:17:50.500 ⇒ 00:18:04.249 Uttam Kumaran: year on HBO, they cover one of the football… the NFL teams, and, like, they do, like, a behind-the-scenes. And, one of the things that they do on sports teams is they review, like, tape.
126 00:18:04.470 ⇒ 00:18:12.649 Uttam Kumaran: And, one of… and one… I was thinking a little bit about, like, okay, how do I start to decrease the distance between people
127 00:18:12.850 ⇒ 00:18:15.850 Uttam Kumaran: On the team, kind of, like, to…
128 00:18:16.110 ⇒ 00:18:23.960 Uttam Kumaran: between them, you know, everyone here, and the client. And one thing that I thought would be really helpful for everybody here is to honestly just, like, watch
129 00:18:24.210 ⇒ 00:18:26.610 Uttam Kumaran: One of our sales calls.
130 00:18:26.710 ⇒ 00:18:33.330 Uttam Kumaran: With me. And we can sort of watch it live, and sort of talk through
131 00:18:33.860 ⇒ 00:18:45.980 Uttam Kumaran: like, how we sort of pitch our services. I had a great call with the team at Element. Element is an electrolyte powder. If you’re into running, or if you’ve…
132 00:18:46.610 ⇒ 00:18:52.089 Uttam Kumaran: They’re just, if you’re no CPG, or for vitamins or nutrition, Element is a huge brand.
133 00:18:52.220 ⇒ 00:19:01.890 Uttam Kumaran: And we are in conversations with them to do some work with them. I had a great conversation with someone that’s coming on to lead business operations there.
134 00:19:02.010 ⇒ 00:19:13.609 Uttam Kumaran: And I think it was a really good end-to-end wrap of, like, how we pitch Brainforge, and how we talk about next steps, and take the prospect through the process.
135 00:19:14.560 ⇒ 00:19:20.309 Uttam Kumaran: like, I just pressed play even for, like, 5 seconds, and it’s extremely embarrassing to watch me…
136 00:19:21.000 ⇒ 00:19:22.270 Uttam Kumaran: Talk through this.
137 00:19:22.580 ⇒ 00:19:26.799 Uttam Kumaran: But I do think that I want to…
138 00:19:27.400 ⇒ 00:19:32.800 Uttam Kumaran: Spend time each week showing something that affects our client or a prospect.
139 00:19:32.950 ⇒ 00:19:47.350 Uttam Kumaran: And I think longer term, ideally, I would even love for a client to even come to these meetings and share a little bit, you know, about what they do, how we’re helping them, what we could do better. It’s something that we did at my last company… two companies ago, and
140 00:19:47.370 ⇒ 00:19:54.740 Uttam Kumaran: although it was very awkward sometimes where we had messed up for clients, I think it brought us really a lot closer to
141 00:19:54.770 ⇒ 00:19:57.199 Uttam Kumaran: You know, the ultimate person that we’re trying to help.
142 00:19:57.370 ⇒ 00:20:08.620 Uttam Kumaran: So one thing that I’d maybe like to do, is just share, and does that all… does that feel like a good use of time for folks? Like, I was originally thinking of
143 00:20:08.740 ⇒ 00:20:12.880 Uttam Kumaran: At doing it with a smaller group of people, and people watch this on their own, but…
144 00:20:13.280 ⇒ 00:20:20.889 Uttam Kumaran: I was like, I’ll just play it on 1.5 speed, and we’ll watch it together, and I’ll press pause and ask questions of everybody. If everybody’s…
145 00:20:21.060 ⇒ 00:20:24.719 Uttam Kumaran: Feels good about that, like… I think it could be productive.
146 00:20:26.530 ⇒ 00:20:27.690 Zoran Selinger: Yeah, that’s good.
147 00:20:28.660 ⇒ 00:20:30.290 Uttam Kumaran: Okay, cool.
148 00:20:36.260 ⇒ 00:20:45.680 Uttam Kumaran: Okay, so I’m not gonna play the beginning, like, small talk, because it’s so… it’s just the worst. I really can’t listen to myself,
149 00:20:46.240 ⇒ 00:20:54.450 Uttam Kumaran: Like, I really can’t listen to myself do that, but, I will share from… like…
150 00:20:54.810 ⇒ 00:20:57.580 Uttam Kumaran: 4 or 5 minutes in. Is this clear to everybody?
151 00:20:58.440 ⇒ 00:21:04.959 Uttam Kumaran: Yeah. And maybe, Sam, I can ask you if, like, I’m gonna press play, if you could just thumbs up if the audio needs to go higher or lower.
152 00:21:04.960 ⇒ 00:21:15.879 Audio shared by Uttam Kumaran: But then I was, like, I was on Amazon, like, I’m gonna poison myself. By accident, it’s okay. That’s good. Keep buying. What, what health were you, what health stuff were you in before? I was working at Brave Health last, which was, like, a virtual mental health…
153 00:21:15.880 ⇒ 00:21:32.150 Uttam Kumaran: So, just to pause, I’m gonna get a little bit of backstory. So, we got connected through, like, a friend of the company. She is gonna talk about, like, her past job, and then, as you can tell, like, I don’t… I don’t start any of our sales calls with anything on the screen.
154 00:21:32.150 ⇒ 00:21:49.429 Uttam Kumaran: I usually start with questions. And so our process is to discover, you know, what the client is here for, what their needs are, and to sort of start to dig deep. And as you can tell, I only have, like, 30, 40 minutes to get there, and so there’s a timer in my head, typically. I’m like, okay, we have to get to these amount of questions.
155 00:21:49.430 ⇒ 00:22:12.959 Audio shared by Uttam Kumaran: healthcare company. Okay, we, we do… one of our clients is Ellie Mental Health. Yeah. And my girlfriend worked for an ABA therapy telehealth company before, so very familiar with that world. So I, like, when I was there, I was overseeing BizOps, and then BI kind of rolled up to me, and then after I left, the head of data, like, started rolling up to tech, which I think was, like, a natural progression, and it works fine.
156 00:22:12.960 ⇒ 00:22:37.189 Audio shared by Uttam Kumaran: But I learned a lot about, like, when I came in to that business, it’s like, we had a bunch of Tableau reports with, like, definitions that varied from report to report, right? Like, your status. So I, like, learned about, like, the merits of, like, doing a dbt layer, and, like, I, like… Great! Solid. Yeah, yeah, yeah. So then I’m coming into Element, where we have a totally different, you know, it’s like, there’s Shopify, Amazon, it’s more e-commerce plus retail, there’s some data that we get about our retail stuff from, via, like, Emerson. I don’t know if you’re, like, familiar with, but then it’s, like, in a snowflake warehouse.
157 00:22:37.230 ⇒ 00:23:00.430 Audio shared by Uttam Kumaran: Cool. And then some people over here are using Looker for something, some people here are downloading Excel spreadsheets and, like, putting manual data in. We have QuickBooks, but we’re gonna transition to NetSuite. So it’s like, there’s a lot in flux, but I’m kind of like, cool, the financial modeling is really manual, the, like, the understanding of, how our retailers are performing, like, that’s not very structured right now. Our supply chain inventory stuff, again, that’s, like, manual data pulls to understand how much inventory is on hand. Cool. So I think it’ll all get better, like, also when we implement NetSuite and things like that.
158 00:23:00.430 ⇒ 00:23:11.560 Audio shared by Uttam Kumaran: But what I’m trying to get ahead of is, like, saying, what is the modern data stack that we need as a business? And so, you know, I might be more familiar with, like, what we had at Brave, which was Fivetran dbt, which is now obviously merged, Fivetran dbt, Snowflake.
159 00:23:11.560 ⇒ 00:23:21.590 Audio shared by Uttam Kumaran: And we used High Touch to, like, push things back, okay? And, like, coefficient reports then, and, like, Google Sheets kind of thing. Perfect. So, like, that was, like, what we had at Brave. We don’t have to mimic that. Maybe we’ll look something, like, something different here.
160 00:23:22.300 ⇒ 00:23:29.849 Uttam Kumaran: So I just want to pause there. This is a great example of someone that actually, up front, knows a little bit about this world.
161 00:23:30.060 ⇒ 00:23:44.719 Uttam Kumaran: this is not that common. Most of the people that we call and talk to know very little about what they want, they just know that, like, there is some burning issue, like, I tried to create a report last week and it didn’t work, and so I, like, need help, or…
162 00:23:44.900 ⇒ 00:23:47.160 Uttam Kumaran: I’m running the whole business on Google Sheets.
163 00:23:47.290 ⇒ 00:23:49.380 Uttam Kumaran: we need some support. For her.
164 00:23:49.870 ⇒ 00:24:02.639 Uttam Kumaran: you may not be able to see it on my face in the meeting, but I’m extremely happy, because she’s outlined the exact architecture that we typically develop, which is a data warehouse, dbt.
165 00:24:02.640 ⇒ 00:24:20.519 Uttam Kumaran: ETL tool, and then BI. She has experience at another company doing it, so she’s probably familiar a little bit with the cost, a little bit with, like, the time it takes to develop these things. So, the calculations I’m doing in my mind right now are like, okay, she has familiar with all this. Okay, so, like.
166 00:24:20.720 ⇒ 00:24:36.740 Uttam Kumaran: what… if she… so typically clients, they don’t know what it is that they want, they don’t know how much it costs, and they don’t know how much time it takes. So at least she knows, like, how much… what it is. So then my job is to understand what is the timeline, and what is the budget here.
167 00:24:36.850 ⇒ 00:24:44.929 Uttam Kumaran: So, one thing that we learned in sales early on is you cannot leave a call without understanding that there… there is a need.
168 00:24:45.280 ⇒ 00:24:52.689 Uttam Kumaran: there is urgency, and there’s budget. All three of those have to be there, right? Like, there have been clients we worked with, there’s urgency.
169 00:24:52.920 ⇒ 00:24:55.870 Uttam Kumaran: They’re like, want to do something here, there’s budget, but then…
170 00:24:56.040 ⇒ 00:25:02.489 Uttam Kumaran: the data piece is, like, not that important. And we’ve gone in, we’ve done a bunch of work, and then they’re like, actually, like.
171 00:25:03.040 ⇒ 00:25:12.370 Uttam Kumaran: whatever, we’re gonna cancel our contract, because it’s not a priority. So I have to make sure that all three of those are there, and so we’ve checked one box at this point, and this is, like.
172 00:25:12.870 ⇒ 00:25:16.640 Uttam Kumaran: this is the kind of mental math that I’m doing, sort of sitting here, listening.
173 00:25:16.640 ⇒ 00:25:31.370 Audio shared by Uttam Kumaran: And so, I think I’m… I just, like, posted in a healthcare chat, and I spoke with Ashley, and she’s like, we really do healthcare, and I was like, yeah, like, but she recommended you for more CPG. I looked at your website, there’s, like, an AI-leaning, like, offering, and then there’s, like, this, like, data stack offering, and so I would explore, like, the basics, kind of.
174 00:25:31.800 ⇒ 00:25:38.980 Uttam Kumaran: And so this is a good point for, Hannah and, like, marketing, is you can tell she got a referral to us, and she went to the site.
175 00:25:39.120 ⇒ 00:25:41.789 Uttam Kumaran: And her takeaway was, okay, there’s AI and data.
176 00:25:42.180 ⇒ 00:26:00.920 Uttam Kumaran: Okay, like, not bad, right? I would be curious to… to… once… if we… if we end up working with her, I think it would be great for us to hop on with her and ask her, like, what exactly she saw, or what convinced her. Yes, this is a recording, Robert. I would like to hop on and ask her,
177 00:26:02.680 ⇒ 00:26:09.319 Uttam Kumaran: what she saw on the website that convinced her, but… okay, so, like, the website, at least, roughly, is working.
178 00:26:10.660 ⇒ 00:26:30.289 Audio shared by Uttam Kumaran: Right now. Yeah, so this is, like, a pretty, like, clear lens where we do a lot of work. So typically, we come into companies where they’ve either taken a crack at something and, like, built a data team, or they have, like, random data people, or they’re, like, kind of starting from fresh, but usually it’s a very similar situation, and, like, I’ll probably just flash a diagram up so I can use this kind of, like, when we kind of go through things, but this is, like, this is, like, a sample e-com, like, architecture that we typically do. And so, of course.
179 00:26:30.610 ⇒ 00:26:31.470 Uttam Kumaran: So…
180 00:26:31.840 ⇒ 00:26:50.060 Uttam Kumaran: the reason why I’m even able to show this architecture is she’s already outlined that she knows this process, but she’s probably never seen it in, like, a clear diagram like this, and so for me, it was perfect. I would say the problem is, and what you don’t see behind the scenes, is I’m scrambling to go find this
181 00:26:50.150 ⇒ 00:26:55.710 Uttam Kumaran: Fucking diagram. Because it’s not in our, data deck.
182 00:26:55.800 ⇒ 00:27:10.359 Uttam Kumaran: And so there is a mini version of it in the data deck, and I’m like, oh god, I need, like, the bigger version. So I… I… I downloaded it last week, and I found it in my downloads. And I was doing that kind of in, like.
183 00:27:10.480 ⇒ 00:27:17.959 Uttam Kumaran: right as she was finishing, I was like, oh shit, I need to go find this diagram. So another piece of feedback for marketing is…
184 00:27:19.210 ⇒ 00:27:32.889 Uttam Kumaran: as you can see on these calls, I sort of don’t know what kind of the journey is going to be until we’re starting to talk, and we need to have everything available somehow. Whether it’s the decks, whatever deck, whatever slide, we just need to have
185 00:27:33.290 ⇒ 00:27:42.650 Uttam Kumaran: up front, because Robert and I certainly sometimes can’t go, like, spend 30 seconds of finding things, we just have to go. And so, luckily, I had this,
186 00:27:42.650 ⇒ 00:27:44.170 Audio shared by Uttam Kumaran: What do you have on the left side? You have…
187 00:27:44.170 ⇒ 00:28:05.810 Audio shared by Uttam Kumaran: Shopify, maybe you’re selling on Amazon or Walmart, you have a bunch of marketing sources, right? You have… if you guys are doing, like, if there’s subscriptions, right, which I know is a big deal, maybe you’re using Loop or something else, you may have, like, something for, refunds and for customer service. Of course, you have your ERP, and so there’s just a bunch of these things. Yes, commonly, people are either spreadsheeting it up, or someone’s, like, at some point has something in S3 and has, like, a tool somewhere. Most of the people will be within these tools, and whatever the report…
188 00:28:05.810 ⇒ 00:28:13.739 Audio shared by Uttam Kumaran: Exactly. Like, marketing is using, like, their own… Triple Whale or Northbeam or something. I don’t know, they have their own, like, data consultancy to try to understand the marketing attribution, right? Yeah. Okay.
189 00:28:13.810 ⇒ 00:28:18.159 Audio shared by Uttam Kumaran: So then, and then, so, yeah, basically the first thing we come in and do is kind of, like, wrangle all this.
190 00:28:18.160 ⇒ 00:28:25.319 Uttam Kumaran: So we’re getting a lot of yes, yes, yes, right? I’m aware, that’s what we’re like to see, right? Okay, I’m aware of this, this sounds right.
191 00:28:25.320 ⇒ 00:28:30.810 Audio shared by Uttam Kumaran: a little bit, like, usually what this… it kind of takes us, like, two to four weeks to sort of, like, see everything, and then our typical.
192 00:28:30.810 ⇒ 00:28:33.739 Uttam Kumaran: So that’s the first time where I’ve made a timeline commitment.
193 00:28:34.120 ⇒ 00:28:44.979 Uttam Kumaran: Right, where I’ve said roughly… and what do I go back to? One of our core offerings is an audit, which we typically say takes 2 to 4 weeks, and I’m about to probably go through the spiel of, like, what it is.
194 00:28:44.980 ⇒ 00:29:07.860 Audio shared by Uttam Kumaran: is, like, we sort of do, like, a two to four week, like, audit, where we come in, and then we help with a couple different ways. So, one, we look at all your tools, we have pretty good documentation on how we structure, like, here are all the tools you have. We propose, like, how do you need to ingest it, right? So, you guys use Fivetran. There are some now, better, lower-cost options that we would totally recommend. Again, but when we recommend tools, it’s a lot from, like, your budget, who’s going to be using it, and, like, things like that. So, yeah, go ahead, were you gonna say something? Yeah, no, no, Fivetran is, like,
195 00:29:07.860 ⇒ 00:29:11.229 Audio shared by Uttam Kumaran: Somebody was just telling me the name of one, instead of the…
196 00:29:11.400 ⇒ 00:29:15.149 Audio shared by Uttam Kumaran: Well, there’s Fivetran, there’s, like, Portable, there’s Polytomic, there’s Estuary, there’s, like.
197 00:29:15.360 ⇒ 00:29:22.000 Audio shared by Uttam Kumaran: There’s a lot. A ton of these, yeah. But also, like, only some of them have really great support, which, like, if you’re using NetSuite, or, like, if you have, like.
198 00:29:22.020 ⇒ 00:29:37.629 Audio shared by Uttam Kumaran: for example, you mentioned you may have a random marketing tool or, like, something that you guys built. You need a tool that kind of, like, will support that, and, like, build you more connectors, so we have some good recommendations of folks that we work with. Also, that will cut you, like, a very good deal. Yeah, they just said the word Matillion to me. Matillion? Yeah, it’s… Matillion is, like, the Power BI of this world, like.
199 00:29:38.290 ⇒ 00:29:57.299 Audio shared by Uttam Kumaran: like, old. But they do… they do this stuff, but it’s not… I would say if you’re thinking about this, you should consider Polytomic. Very, very good, great team, great, like, their support is, like, the number one, and then second, their pricing is actually also pretty competitive. 5 Train is, like, the name brand, but they’re the most expensive, worst support, and I’ve used Fivetran for, like, almost 10 years now, and it’s gotten worse over time. I also have a lot of friends that work there, and, like.
200 00:29:57.350 ⇒ 00:30:04.889 Audio shared by Uttam Kumaran: Yeah, I mean, they also agree, so I don’t know. This is where, like, we’re… I’ve bought… we’ve bought a… we do a lot of, like, procurement in the data space, and so we’re very opinionated, so I’m happy to…
201 00:30:04.890 ⇒ 00:30:19.819 Uttam Kumaran: So one thing that I want to hammer to her, as she knows she’s mentioned all these tools, and I can tell that that’s, like, what’s overwhelming to her about this problem. And so what we’re trying to convey is, like, we’ve supported the procurement and, like, the organization, the integration work across
202 00:30:19.940 ⇒ 00:30:20.939 Uttam Kumaran: all these tools.
203 00:30:20.940 ⇒ 00:30:36.759 Audio shared by Uttam Kumaran: to send, like, we have sort of diagrams on, like, what we… what our recommendations are, why or why not? So I can send that over, too, but… And do you typically go Snowflake, or do you sometimes do Databricks? Like, I don’t have a preference right now. Yeah, so I would say that our… our guidance is that it sort of depends on how much data we’re talking about and who’s going to be using it. Like, if you guys are thinking about in the future doing
204 00:30:36.760 ⇒ 00:30:42.299 Audio shared by Uttam Kumaran: more serious data science, you have several analysts internally that need to use the data, you can use Snowflake. If you’re budget-constrained, there are also some
205 00:30:42.300 ⇒ 00:30:56.070 Audio shared by Uttam Kumaran: pretty good budget options, like Mother Duck, that’s… those are new that you should try. I’ve just used Snowflake my whole career, and it’s really great. Snowflake and Databricks… I think Databricks leans way more data science, and, like, it’s more… I would say it’s way less intuitive to just run simple SQL queries.
206 00:30:56.070 ⇒ 00:31:02.169 Audio shared by Uttam Kumaran: Snowflake is really great, although both of them are, like, kind of the most expensive options. That makes sense. Yeah, and then we…
207 00:31:02.340 ⇒ 00:31:07.860 Uttam Kumaran: So, also, I can tell she’s… it seems like she’s either slacking someone else while we’re talking or writing something down.
208 00:31:08.010 ⇒ 00:31:25.169 Uttam Kumaran: So I’m assuming it’s the latter, and so what I’m trying to give to her is enough talking points that when she goes and sells this engagement to her boss, or when they go talk to other consultants, she has enough talking points to suss them out.
209 00:31:25.300 ⇒ 00:31:38.910 Uttam Kumaran: So, I’m over-explaining. Like, super over-explaining this versus this versus this versus this. I’m not saying yes or no answers. I’m almost like, well, here’s how you should think about it if I was in your position, right?
210 00:31:38.910 ⇒ 00:31:41.070 Samuel Roberts: I was actually gonna… Talk about that real quick.
211 00:31:41.070 ⇒ 00:31:41.520 Audio shared by Uttam Kumaran: controlled.
212 00:31:41.520 ⇒ 00:31:42.040 Uttam Kumaran: Yeah.
213 00:31:42.040 ⇒ 00:31:56.390 Samuel Roberts: But I was wondering, you’re, like, mentioning all the different vendors and stuff, like, is that because… I mean, I assume it’s because she kind of got into it herself and, like, seemed a little bit like she had already done some research, but I imagine the over-explaining is probably good, but is it too much for some sales calls, where they’re not…
214 00:31:57.710 ⇒ 00:32:07.909 Uttam Kumaran: Yeah, some places don’t care at all about any of these tools. They know that they sell on Shopify, and they know the money comes in via Stripe, and they’re like…
215 00:32:07.910 ⇒ 00:32:08.730 Samuel Roberts: Right, okay.
216 00:32:08.730 ⇒ 00:32:17.530 Uttam Kumaran: So, for her, again, this is one flavor of a call, where it is a little bit more architecture heavy, but she… I could tell that she…
217 00:32:17.530 ⇒ 00:32:18.100 Samuel Roberts: Yeah.
218 00:32:18.100 ⇒ 00:32:24.800 Uttam Kumaran: Kind of brought that up, and that may be one of her key concerns in doing this on her own, is how many
219 00:32:25.000 ⇒ 00:32:38.089 Uttam Kumaran: tools there is and how to string them all together. And so what I’m trying to get to the point of checkbox is that we’re an authority in choosing the right tools within your budget and stringing them together, and we have familiarity with all of them, right? So…
220 00:32:38.350 ⇒ 00:32:47.910 Uttam Kumaran: And I’m also trying to take her through this journey, and get her to remember what the other company was, to get her to remember what these things were.
221 00:32:48.350 ⇒ 00:32:53.770 Uttam Kumaran: And then to… and then, of course, she’s gonna be like, yes, exactly what I want, right? .
222 00:32:54.630 ⇒ 00:33:10.730 Audio shared by Uttam Kumaran: So we write a ton of SQL on dbt. You can run dbt for free, it’s open source, or you can pay, it’s like… dbt is, like, 50 bucks a license, but again, depends on how many people you’re thinking about using it. We kind of create these, like, these marts, basically, which I’m sure you’re… I don’t know what the architecture was before, but we, like, land the data, do some modeling, create these, like, fixed mart tables.
223 00:33:10.940 ⇒ 00:33:20.989 Uttam Kumaran: So this is where, again, I don’t know how technical she is, I don’t know how much she was involved in that data team, so I’m going a little bit deep. I… this is not so often that we go this deep on an intro call.
224 00:33:21.140 ⇒ 00:33:24.949 Uttam Kumaran: But I can tell that she’s, like, she’s not looking for…
225 00:33:25.310 ⇒ 00:33:30.939 Uttam Kumaran: like, the high-level data strategy, which some of our calls are. She’s, like.
226 00:33:31.160 ⇒ 00:33:38.620 Uttam Kumaran: can you get me to exactly, like, where I need? I remember what we had back then, so I’m almost trying to refresh your memory on what those…
227 00:33:38.620 ⇒ 00:33:44.459 Audio shared by Uttam Kumaran: for customers, things like that. And then finally, yeah, we basically take that to a BI tool, or we also…
228 00:33:44.860 ⇒ 00:33:48.720 Uttam Kumaran: The other thing I remember here is that we need to put,
229 00:33:49.940 ⇒ 00:33:54.330 Uttam Kumaran: we need to put a reverse ETL tool here, and we probably need to put, like, a…
230 00:33:55.400 ⇒ 00:33:57.720 Uttam Kumaran: Conversion tool or something here, too, also.
231 00:33:57.720 ⇒ 00:34:08.739 Audio shared by Uttam Kumaran: a tool like Hightouch, Polyatomic also offers reverse ETL. I know 5chan started offering that, so if you want to send that back into Klaviyo or Salesforce or whatever, or, like, you want to send it to your conversion platforms for ad optimization, you can send those out. So this is, like, our typical
232 00:34:08.760 ⇒ 00:34:25.879 Audio shared by Uttam Kumaran: Stack sounds, like, pretty similar to, like, what you were used to before. Yeah, and like, at Brave, we did so much stuff where it was, like, coefficient reports that were, like, High Touch was pumping stuff back into coefficient. I’m saying this the right way, but then it’s, like, then we built off a lot of Google Sheets off of those, like, that got updated regularly, and I don’t know… I don’t know if that’s the direction we’re gonna go here, but I kind of like… I kind of like to…
233 00:34:25.880 ⇒ 00:34:40.090 Audio shared by Uttam Kumaran: be able to be, like, what were my daily metrics, what were my weekly metrics, and, like, be able to, like, have things, like, refreshing regularly, like, that you can just, like, run math off of versus just looking at it. And so, I think that’s, like, a culture thing that I’ll have to understand better about this place. Yeah, so that’s also where, like, again, like, this is an example, and we have… we sort of…
234 00:34:40.090 ⇒ 00:34:55.269 Audio shared by Uttam Kumaran: this is just, like, we’re… my background is in data, and, like, I built data teams, and so I’m very opinionated on, like, what the tools you choose and why, and so we have, like… we built, like, one of these for every part of the stack, and so I’m happy to send you these. Mainly, it’s just, like, choose the right tools. You can’t… at a certain level, you can’t go wrong, but, like, at some point, if you choose Power BI,
235 00:34:55.270 ⇒ 00:35:08.020 Audio shared by Uttam Kumaran: you are going a little bit wrong, like, it will slow down a bunch of stuff. I haven’t heard anybody mention Power BI, I’ve heard people mention Looker just because somebody already uses Looker, but, like, it’s like, oh, like, that team uses Looker, so should we just use Looker everywhere? So, like, I guess, like, tell me, are you… are you gonna come in and sort of be, like, head of data?
236 00:35:08.020 ⇒ 00:35:13.030 Uttam Kumaran: So this is where, again, we’re further discovering, okay, there’s… someone has Looker, someone… somewhere randomly.
237 00:35:13.220 ⇒ 00:35:15.650 Uttam Kumaran: Like, and then I’m like, okay, well then…
238 00:35:15.770 ⇒ 00:35:25.270 Uttam Kumaran: I’m also trying to figure out, like, what her role is, because I just got a LinkedIn DM. This is the first time I’ve talked to her, so I don’t have much background at all, right? So, this is where I basically am asking her that.
239 00:35:25.270 ⇒ 00:35:33.080 Audio shared by Uttam Kumaran: what are you thinking, like, what do you… yeah, like, give me a sense of what your goals are. I wouldn’t be the head of data, because I don’t do any coding, I don’t whatever. No, I don’t think you… I don’t think you necessarily need to in order to sort of, like.
240 00:35:33.440 ⇒ 00:35:42.349 Audio shared by Uttam Kumaran: Because head of data is, like, also, I think data teams commonly you have a head of data, but what is every… as long as every team is using data, like, there’s more, it’s more, like, are you actually using it to drive decisions, right? Yes, so I think that
241 00:35:42.350 ⇒ 00:35:59.320 Audio shared by Uttam Kumaran: that the head of data would roll up to me. Cool, okay. Yeah, so, like, and the thing is, we run pretty scrappy, so I think, like, here’s the thing. I’m like, I could make a case that’s, like, we should just hire a head of data now, and they should start building out our stack, right? I think the reason to maybe work with a consultant prior is that we can have the stack be built out a little faster, potentially, right? And then… and then, like.
242 00:35:59.340 ⇒ 00:36:19.959 Audio shared by Uttam Kumaran: get, like, the best recommendations, like… I don’t know, my head of data I loved at Brave, and I’m like, if I could just bring him in, he could build the stack out, that’s awesome. But, like, I think having a consultancy to, like, build it out, pipe everything together up front, build the recommendations, and then theoretically hire somebody who can both be a bit of data engineer and analytic support, which is kind of what he did, like, that profile person could be nice to then, like, hire after this. How do you feel in terms of that sequencing?
243 00:36:20.810 ⇒ 00:36:39.280 Uttam Kumaran: Great. This is a great… we’re thinking about hiring a consultant. Hey, consultant, what do you think about hiring a consultant? Lay up, right? I’m, like, this is great, because we have opinions, right? And I actually… my opinion is not F that, never hire a head of data. As you’ll see, I’ll give an answer on why I think she’s kind of on the right track.
244 00:36:39.280 ⇒ 00:36:51.220 Audio shared by Uttam Kumaran: You just hired one person, they should be able to do all of this? No, I mean, I will caveat, of course, I’m very biased, but as I was on, like, I was only recently building data teams myself, like, here’s a couple reasons of, like, why, even if you don’t consider us, you should consider someone in this phase.
245 00:36:51.220 ⇒ 00:37:10.050 Uttam Kumaran: So the other thing you do is you say… what I commonly do is I’m like, even if you don’t think about us, you should go… you should… this is what you should think about in general. So you’re doing, like, the non-sale sell. You’re kind of being like, I’m a trusted partner here. Like, I don’t… I’m… you’re almost removing the Brain Forge whole thing.
246 00:37:10.050 ⇒ 00:37:24.879 Uttam Kumaran: And making it very low pressure. When, in fact, most consultancies and most salespeople are going to be like, this needs to close 100%, and they, like, try to get… they try to do these things like, okay, if you had the budget, would this be yes, would this be yes?
247 00:37:25.050 ⇒ 00:37:34.890 Uttam Kumaran: I just don’t sell like that, right? The way we do things is I’m sort of trying to build, like, a trusted partnership to share that we could be the people that could solve your problem.
248 00:37:34.890 ⇒ 00:37:47.389 Audio shared by Uttam Kumaran: One is, you may hire a head of data. One is, like, if you can’t get your guy or your gal, it’s gonna be… it’s really tough to find that great person, so a high odds of not finding that perfect person. Second is, it will take them time to ramp up. Like, when I mentioned we come in in, like, a month.
249 00:37:47.430 ⇒ 00:38:06.870 Audio shared by Uttam Kumaran: we kind of get there. The only reason I say a month is, like, in case we can’t get access to stuff, it takes us a while, but I’m, like, two weeks, we generally have, like, a pretty good sense of, like, what you need. As you can tell, we even made it pretty far, even on just this call, like, figuring things out. So, speed is certainly one thing. Second is, like, some of these decisions you make on infrastructure, that person, when you hire them, will be very thankful, and you can kind of set them up for success. The last piece is very expensive. Like, head of data.
250 00:38:06.930 ⇒ 00:38:12.660 Audio shared by Uttam Kumaran: Who is worth, like, their weight, very expensive, and that person commonly doesn’t also want to do the work.
251 00:38:12.660 ⇒ 00:38:16.769 Audio shared by Uttam Kumaran: Like, the person you’re used to, and, like, me, or, like, it’s just, like.
252 00:38:16.770 ⇒ 00:38:34.310 Audio shared by Uttam Kumaran: those people are also not on the ground often. They’re like, oh, I want to be, like, head of data, that’s where I need 5 analysts and 3 data engineers. That’s not, like, the situation, especially at a company like… I can’t hire my guy just yet, but I’m like, let’s use a consultant when I put on my knowledge… No, I think you should scheme for him, and I think we should help you make the case to him that, like, hey, you’re coming into a great environment, you won’t have to do the dirty work. For us, we’re like a… I come in and, like, throw us into the…
253 00:38:34.310 ⇒ 00:38:48.409 Audio shared by Uttam Kumaran: biggest fire possible, where we can make the biggest impact. Because also, like, something about data is you now have a bunch of people in the company who are doing their own thing, nobody trusts, like, a single source of truth, right? So they’re all, like, doing their own thing. It will take these slow wins to start to build, okay, like, I trust the work that Shivani’s doing, we nailed it something here.
254 00:38:48.660 ⇒ 00:38:54.180 Uttam Kumaran: So the other thing, when we come into companies, our job is to make There are stakeholder…
255 00:38:54.320 ⇒ 00:39:08.930 Uttam Kumaran: win, and our stakeholder famous, right? So, one thing I’m mentioning to her is, like, I’m trying to understand, like, what her goals are, like, professionally within Element, and how what we’re doing is lining up to her, right? So she’s talking about how there’s these disparate environments.
256 00:39:08.930 ⇒ 00:39:19.959 Uttam Kumaran: So I’m like, okay, there’s probably some people that are complaining that data is in one place, probably some people complaining that they don’t have the right data, or that, like, it’s not accurate, right? So I’m trying to figure out, like, what the problems are, and then
257 00:39:19.960 ⇒ 00:39:23.759 Uttam Kumaran: Think of the case studies that that sort of match… match to there.
258 00:39:25.750 ⇒ 00:39:34.230 Uttam Kumaran: Yeah, so I mean, I… I guess I kind of wanted to pause here, like, any sort of comments or thoughts from anybody that’s, like, listening on, like.
259 00:39:34.390 ⇒ 00:39:38.850 Uttam Kumaran: on what you’re hearing, I guess, what’s been helpful to hear, what’s been interesting?
260 00:39:45.370 ⇒ 00:39:59.799 Samuel Roberts: I mean, it might be this call specifically, but I think it’s definitely… I’ve seen you on a few others now, personally, and I see the, like, establishing, like, the authority and knowledge and, like, being the people to go to. Whether or not it’s even, like, who to, like…
261 00:39:59.880 ⇒ 00:40:09.080 Samuel Roberts: the way you were saying… I think you just were getting at it, like, not all consultants are going to sell the same way like this, but showing that you know what’s… like, that you have the…
262 00:40:09.890 ⇒ 00:40:25.890 Samuel Roberts: expertise is almost more important than being like, and get us right now, because yeah, if they’re going to bring someone in, they might still want to bring us in earlier, or, you know, work with some… like, there’s… there’s different ways that that can play out, and I think you’ve… I see you establishing that more here than I have in even other calls, I think maybe it’s because it’s a little more…
263 00:40:27.020 ⇒ 00:40:32.179 Samuel Roberts: details-oriented, and I get that now more than I did before.
264 00:40:33.480 ⇒ 00:40:34.030 Gabriel Lam: I…
265 00:40:34.450 ⇒ 00:40:48.149 Gabriel Lam: I am a fan of, like, the relationship building. I think often it’s like, even if you don’t work with this person, they might know, like, hey, we had a great call with Brainforge, you can reach out to them, and that would end up being something else. And I think seeing it that way really, sort of.
266 00:40:48.150 ⇒ 00:40:56.069 Gabriel Lam: breaks the whole, like, hey, buy our thing kind of mentality, and be like, hey, we’re offering value, whether you take it or not, someone will take it. And that’s really the goal.
267 00:40:56.070 ⇒ 00:40:56.730 Uttam Kumaran: Yes.
268 00:40:58.580 ⇒ 00:40:59.110 Gabriel Lam: Yes.
269 00:40:59.110 ⇒ 00:41:04.440 Uttam Kumaran: That’s a great point, yeah. I mean, you… you’ve identified that’s exactly our strategy most of the time.
270 00:41:06.230 ⇒ 00:41:19.329 Hannah Wang: I think it’s just helpful hearing your thought processes of, like, why you say certain things, and, like, why you bring it up, because when I… I watched this call before, like, a couple weeks ago, and…
271 00:41:19.400 ⇒ 00:41:27.350 Hannah Wang: I, like, obviously, I didn’t know, like, what you were thinking or processing when you said certain things after Giovanni said something, so…
272 00:41:27.460 ⇒ 00:41:29.689 Hannah Wang: I’m just amazed at…
273 00:41:29.860 ⇒ 00:41:39.379 Hannah Wang: all the… all the brain work that goes in, like, just your internal processing and how you’re, like, playing… you’re… basically, it’s like a dance, right? So you’re just…
274 00:41:39.380 ⇒ 00:41:50.860 Hannah Wang: I don’t know, it’s… it’s cool to see, like, how you pitch, and obviously you make it tailored to each client, so, just seeing your thought processes behind it is…
275 00:41:51.030 ⇒ 00:41:52.820 Hannah Wang: It’s cool, and…
276 00:41:53.020 ⇒ 00:42:02.059 Hannah Wang: I noted on the marketing assets, I will help make a change and make it easier. Yeah.
277 00:42:02.060 ⇒ 00:42:08.440 Uttam Kumaran: Yeah, and… and I agree, like, it’s, I’m… I’m… I’m speaking, but also…
278 00:42:09.210 ⇒ 00:42:25.679 Uttam Kumaran: thinking about, like, what, where we are in the conversation. I will have, at some point, looked at the clock a couple times and been like, okay, where does this conversation need to go? I’m always thinking about, is there helpful… because the lovely thing about us is we have beautiful diagrams, decks.
279 00:42:25.680 ⇒ 00:42:36.360 Uttam Kumaran: So I know if there’s a right moment to bring one up, I should bring one up, but I think also there is a challenge to having that many on the salesperson to know what’s the right thing to bring up at the right time.
280 00:42:36.390 ⇒ 00:42:44.619 Uttam Kumaran: The second thing I’m sort of trying to… trying to get to the point where, okay, we’ve built authority here, right? And then what is… what is next? Like…
281 00:42:44.800 ⇒ 00:42:54.059 Uttam Kumaran: you know, and I think what one thing I could just fast-forward, kind of, probably towards the end of is just hearing a little bit about, okay, how did we end up closing this conversation? .
282 00:42:54.060 ⇒ 00:43:00.529 Audio shared by Uttam Kumaran: like, oh, that’s so interesting, I wouldn’t have thought of, like, asking. Yeah, like, people, sometimes people are, like, for data security or something, they’re like, hey, try to produce
283 00:43:00.690 ⇒ 00:43:10.859 Audio shared by Uttam Kumaran: Just waiting for that, so I need to create a little bit of a sense of urgency. Yeah. So that’s kind of how we… there’ll be 5 people on this call. These are… like, I would say we’re pretty inexpensive for the damage that we come in and do. Yeah.
284 00:43:11.320 ⇒ 00:43:12.659 Uttam Kumaran: So, we’re kind of getting to the.
285 00:43:12.660 ⇒ 00:43:21.659 Audio shared by Uttam Kumaran: I can bring in 100 people if you need it. You’ll talk to, like, bigger companies who are, like, there’ll be five people on this call, and it’ll be, like, a big sales call. We’re somewhere in the middle, like, I’m not… I’m a last week.
286 00:43:21.660 ⇒ 00:43:22.020 Uttam Kumaran: Yeah, let’s.
287 00:43:22.020 ⇒ 00:43:28.370 Audio shared by Uttam Kumaran: Versus, I’ve hired a lot of data consultants, and again, like, people… The data team needs to be doing REST and SS, like, that’s… So, like, what did the data team do?
288 00:43:28.480 ⇒ 00:43:29.810 Audio shared by Uttam Kumaran: so it’s cheaper, and then I can, like.
289 00:43:29.920 ⇒ 00:43:32.350 Audio shared by Uttam Kumaran: But it is… that is a… that is a feature of that, but I would say.
290 00:43:32.350 ⇒ 00:43:33.520 Uttam Kumaran: Honestly, there’s a point…
291 00:43:33.520 ⇒ 00:43:38.999 Audio shared by Uttam Kumaran: Like, the people everywhere are the same level. Like, one, of course, like, daily. We’re like, how did that sprint go? What am I trying to achieve in the next…
292 00:43:39.160 ⇒ 00:43:44.270 Audio shared by Uttam Kumaran: And then the, like, once I’ve picked probably, like, a couple, I’m gonna bring somebody in from the tech team, and this guy who does, like.
293 00:43:44.270 ⇒ 00:43:57.020 Uttam Kumaran: Okay, so… I would say we… Here, she’s gonna outline, sort of, like, okay, what is the process she’s going through to, like, find this… this… this consultancy that she wants to work with? It’s clear that she’s… she wants to work with somebody. Even at this point, I’m like.
294 00:43:57.800 ⇒ 00:44:02.389 Uttam Kumaran: I feel pretty good about how this whole pitch… I skipped a bunch, but the rest of the call went pretty well.
295 00:44:02.390 ⇒ 00:44:04.900 Audio shared by Uttam Kumaran: I think you’ll find is very, very fair. Like, I know a lot of…
296 00:44:04.900 ⇒ 00:44:20.999 Uttam Kumaran: I’m sharing with her that, okay, like, a little bit of a hint on, like, what are our pricing? How do we typically work? I mentioned hourly versus project. They said they run month-long sprints at Element. I said, whatever you need, we can sort of mimic that, which is great that they have some organization themselves.
297 00:44:21.000 ⇒ 00:44:21.570 Audio shared by Uttam Kumaran: are…
298 00:44:21.660 ⇒ 00:44:30.770 Audio shared by Uttam Kumaran: like, I would say we’re pretty inexpensive for the damage that we come in and do. Yeah. And, like, I don’t know, I think we’ve found that with our clients, like, they tend to see the ROI pretty clearly, so…
299 00:44:30.770 ⇒ 00:44:45.790 Audio shared by Uttam Kumaran: That’s great. Okay, cool. So, on my side, I’m gonna have a few… basically, the way that I’m structuring this process is I’m talking to a few companies, like, just one-to-one, and then the, like, once I’ve picked probably, like, a couple, I’m gonna bring somebody in from the tech team, and this guy who does, like, our… a lot of, like, our finance analysis, supply-demand forecasting, and things, like, right now.
300 00:44:46.080 ⇒ 00:44:50.709 Audio shared by Uttam Kumaran: Just for the next conversation, so they can meet some of the stakeholders. And then… Totally, great, yeah. I’m hoping to, like.
301 00:44:51.150 ⇒ 00:45:01.029 Audio shared by Uttam Kumaran: I don’t know timeline-wise, I’m like, I was hoping to kick this off in January, but, like, if there’s a world that I pick somebody in November and we’re kicking off in December, like, great, right? So I think… I think that’s kind of the timeline right now. If I can get ahead of it, then that’s even better.
302 00:45:01.030 ⇒ 00:45:21.020 Audio shared by Uttam Kumaran: Okay, and then, yeah, on our side, I’ll send you, sort of, the materials that we covered today. That’s awesome. And then even if, like, you don’t end up going with us, you have any questions about data stuff that I can be helpful with… Yeah. I’m more than happy to. This is all we do. Yeah. So, no, it’s, like, fun to, like, I just, even as I’m having these conversations, I’m like, oh, 5DRAN and whatever, and people are like, oh, but, like, have you thought about… what did you say today? Mother Duck for Snowflake? I’m like, I would not have heard of Mother Duck, so… Yeah, but again, these are, like, these can be pretty pricey decisions, not only in just, like.
303 00:45:21.020 ⇒ 00:45:25.379 Audio shared by Uttam Kumaran: The cost of the tool, but the impact it’s gonna have on every data person, or anyone who ever accesses, like.
304 00:45:25.380 ⇒ 00:45:50.349 Audio shared by Uttam Kumaran: it’s a… it’s a heavy decision to make, so you just want to go with the right… the right… And I like when people are, like, tool agnostic, and trying to think about what does this business look like? Yeah, we work also with nothing. Like, I come to places where they’re like, you can’t buy anything. I’m like, alright, well, we’ll do it all for free, and you’re gonna see why that kind of sucks. It’s not like we’re not going to do it, though. Like, I’m not… we don’t live and die by the tools, it’s just the shovels. We just… it’s the shovels we use, so if we get bad shovels, then we dig slowly, and we dig small holes, and that’s it, right? Like, that’s it. Okay, super nice to meet you.
305 00:45:50.350 ⇒ 00:45:57.799 Audio shared by Uttam Kumaran: want to do another conversation with you, like, for sure, so I’m actually leaving on vacation tomorrow, going away for a week, and then… Great. I just started this job, but I was like, okay.
306 00:45:58.050 ⇒ 00:46:07.479 Uttam Kumaran: So, we kind of… we kind of end up there, where she’s like, okay, we want to have a conversation, so I then follow up with an email where we kind of outline exactly what we talked about.
307 00:46:07.480 ⇒ 00:46:26.359 Uttam Kumaran: talk a little bit about… here’s… I basically sent her all the diagrams that we presented, and I said, hey, can we hop on another call? But this was an example of a call that went very, very well, where someone walks in, they kind of know what they want, they’re open to using consultants. Both of those are typically not the case.
308 00:46:26.830 ⇒ 00:46:41.120 Uttam Kumaran: usually they’re, like, internal versus external, and they are, thinking about… they don’t even know, like, what they need. And so, that’s sort of, like, what we’re trying to arrive at is… is those two decisions. And it’s clear, she just said the timeline, right?
309 00:46:41.160 ⇒ 00:46:57.739 Uttam Kumaran: she wants to do something by January, she’s opening next month, which means, okay, like, the clock starts now to keep momentum. So she says she’s going off on vacation, okay, the moment she gets back, I’ll probably send a note. She emailed me yesterday asking to hop on the phone on Wednesday, so I’ll be talking to her again on Wednesday.
310 00:46:57.850 ⇒ 00:47:04.700 Uttam Kumaran: And so this is it. And so, at any moment, Robert and I have 10 to 15 of these
311 00:47:05.360 ⇒ 00:47:12.489 Uttam Kumaran: going on in parallel at any different stage, either kicking off, Or, like, towards the end.
312 00:47:12.680 ⇒ 00:47:20.889 Uttam Kumaran: And it’s actually not the fact that, like, this one call was hard, it’s the fact that we have to go to every call, like,
313 00:47:21.720 ⇒ 00:47:30.920 Uttam Kumaran: we have to go to every call like it’s the most important call. You know, like, we don’t… every… every call we take is like the Super Bowl, basically. And so…
314 00:47:31.060 ⇒ 00:47:38.999 Uttam Kumaran: Where we can use a lot of help is making sure that we have those documents, that we have the talking points clearly laid out.
315 00:47:39.120 ⇒ 00:47:45.470 Uttam Kumaran: But otherwise, then we just have to come in and dance, and I think that’s the tough… that’s the toughest part, is that at any moment.
316 00:47:45.760 ⇒ 00:48:03.449 Uttam Kumaran: we don’t know whether this… like, I don’t know whether Element is… for example, I may hop on the call on Wednesday, there may be someone else that comes in and just doesn’t like consultants, nixes the whole thing, and I have to be okay with that, right? And so, you sort of don’t know until the end whether this is ghost. You have to treat every meeting
317 00:48:03.710 ⇒ 00:48:09.180 Uttam Kumaran: Like, it’s, like it’s a couple hundred thousand dollar meeting, you know?
318 00:48:09.280 ⇒ 00:48:17.550 Uttam Kumaran: And but you can’t be too serious. You know, you have to kind of have fun, and you kind of have to meet people, and…
319 00:48:17.700 ⇒ 00:48:25.990 Uttam Kumaran: and understand where people are coming from, and give advice, and you kind of hope that they decide to go with us, you know? So, this is, like, a little bit of an insight. I think,
320 00:48:26.190 ⇒ 00:48:38.730 Uttam Kumaran: I don’t know, this has been extremely painful to watch me talk for, like, half an hour, but I feel like it was, it was hopefully a little bit enlightening into, like, how this goes, and yeah, I feel like we can probably do,
321 00:48:39.420 ⇒ 00:48:42.330 Uttam Kumaran: more game tape reviews via Loom.
322 00:48:42.460 ⇒ 00:48:48.639 Uttam Kumaran: I’m gonna need to not listen to me talk for another week or two after this, but…
323 00:48:49.060 ⇒ 00:48:50.860 Uttam Kumaran: Yeah, we’ll do one of mine.
324 00:48:50.860 ⇒ 00:48:52.100 Robert Tseng: Next time, don’t worry.
325 00:48:52.450 ⇒ 00:49:00.149 Uttam Kumaran: Yeah, please. This is also a good one, like, we should review one that is not so good. That’ll be even worse.
326 00:49:00.420 ⇒ 00:49:03.330 Uttam Kumaran: But cool.
327 00:49:03.760 ⇒ 00:49:19.450 Uttam Kumaran: So yeah, that’s kind of all I had planned for today. I know, maybe I wanted to spend maybe a little bit at the end of the call talking about stuff for insomnia, but, probably anyone else have any last closing points before I kind of let people who aren’t on that client drop?
328 00:49:24.680 ⇒ 00:49:30.340 Uttam Kumaran: Okay, great. Well, yeah, I guess, maybe Demolade, if you want to stay on, and then…
329 00:49:30.650 ⇒ 00:49:36.310 Uttam Kumaran: Maybe Zoran, if you just want to stay at home, we could just brief Robert on Eden stuff, and then,
330 00:49:36.620 ⇒ 00:49:39.140 Uttam Kumaran: Yeah, I’ll probably talk to everybody else later.
331 00:49:41.910 ⇒ 00:49:42.479 Uttam Kumaran: Thank you.
332 00:49:44.090 ⇒ 00:49:45.399 Samuel Roberts: This is you. Bye.
333 00:49:47.650 ⇒ 00:49:48.110 Robert Tseng: Okay.
334 00:49:48.240 ⇒ 00:49:50.720 Uttam Kumaran: Cool, so on…
335 00:49:50.720 ⇒ 00:49:51.140 Robert Tseng: minutes.
336 00:49:51.140 ⇒ 00:49:59.150 Uttam Kumaran: Yeah. FYI. Okay, okay. Okay. Yeah. On Eden, really quick, like, Zoran is sort of continuing to push things forward on…
337 00:49:59.440 ⇒ 00:50:06.269 Uttam Kumaran: like, trying this conversion thing with a thank you page, and then we’re talking to Northbeam on Thursday.
338 00:50:06.490 ⇒ 00:50:07.339 Uttam Kumaran: And I…
339 00:50:07.340 ⇒ 00:50:11.350 Robert Tseng: Can I ask about that last Thursday.
340 00:50:11.700 ⇒ 00:50:14.989 Uttam Kumaran: Yeah, yeah, yeah. I emailed them asking them if I can…
341 00:50:15.700 ⇒ 00:50:21.850 Uttam Kumaran: Me earlier, but he hasn’t gotten back to me, so…
342 00:50:23.070 ⇒ 00:50:26.530 Uttam Kumaran: I’ll be talking about, like, a number of clients during that time, so…
343 00:50:27.150 ⇒ 00:50:34.599 Robert Tseng: Okay, and then Zoran, I booked a call for the two of us. I just wanted to make sure that you got that, and we were…
344 00:50:34.600 ⇒ 00:50:36.469 Zoran Selinger: Indeed, I did get that.
345 00:50:37.200 ⇒ 00:50:37.900 Robert Tseng: Okay.
346 00:50:38.310 ⇒ 00:50:40.500 Zoran Selinger: That’s for tomorrow.
347 00:50:40.610 ⇒ 00:50:42.639 Zoran Selinger: 4PM my time, yeah.
348 00:50:43.740 ⇒ 00:50:44.410 Robert Tseng: Okay.
349 00:50:45.050 ⇒ 00:50:49.029 Robert Tseng: That’s weird. It’s not showing up in my calendar. Maybe I put my wrong email, and I put.
350 00:50:49.030 ⇒ 00:50:54.909 Zoran Selinger: Are we talking about the meeting with Cameron? I was just… someone was at the door, so I wasn’t here for the last minute.
351 00:50:54.910 ⇒ 00:50:59.820 Robert Tseng: Yeah, yeah, I was talking about with, with the…
352 00:50:59.820 ⇒ 00:51:00.939 Zoran Selinger: That’s in my calendar.
353 00:51:01.080 ⇒ 00:51:03.140 Zoran Selinger: Yeah, it is in my calendar, yeah?
354 00:51:04.250 ⇒ 00:51:04.670 Robert Tseng: Okay.
355 00:51:04.670 ⇒ 00:51:05.160 Zoran Selinger: tomorrow.
356 00:51:05.160 ⇒ 00:51:13.349 Robert Tseng: Oh, I’m… I’m saying I don’t think it made it onto mine. Oh, oh, no, no, okay, it did, sorry. I was looking on the wrong thing. Okay, cool. Yeah, yeah, I see it. Okay, cool. Yeah.
357 00:51:15.200 ⇒ 00:51:22.399 Robert Tseng: Yeah, don’t worry about Stuart, I think he’s wrong, he’s just, like, making noise, whatever. Like, we’ll do our evaluation, like, I don’t really need to involve him.
358 00:51:23.290 ⇒ 00:51:34.930 Zoran Selinger: He’s so intense, so today he sent me a video, and he wanted me to look at the video, and wanted to even pay
359 00:51:35.450 ⇒ 00:51:37.869 Zoran Selinger: For the time to watch the video.
360 00:51:38.680 ⇒ 00:51:41.369 Zoran Selinger: Send me your PayPal or Venmo.
361 00:51:41.490 ⇒ 00:51:46.109 Zoran Selinger: Yeah, that’s careful not. Yeah.
362 00:51:47.310 ⇒ 00:51:49.940 Robert Tseng: Okay, you don’t have to do any of that, that’s fine.
363 00:51:49.940 ⇒ 00:52:01.989 Zoran Selinger: I looked at the video very quickly, it was, it was fine, I keep, I keep reiterating that, okay, like, there’s a reason behind.
364 00:52:02.700 ⇒ 00:52:10.020 Zoran Selinger: our decision, and we’re looking into everything. Just wanna make sure that that point is… gets across, basically.
365 00:52:10.560 ⇒ 00:52:14.780 Robert Tseng: Okay. Yeah, I know, sorry, you can be a handful, like, I’m just saying, you don’t have to do everything he tells.
366 00:52:14.780 ⇒ 00:52:17.229 Zoran Selinger: Oh, it is fine, it is fine, it’s fine. Okay.
367 00:52:19.420 ⇒ 00:52:20.010 Robert Tseng: Okay.
368 00:52:20.430 ⇒ 00:52:21.490 Zoran Selinger: Okay, cool.
369 00:52:22.560 ⇒ 00:52:41.070 Uttam Kumaran: Okay, and then for Insomnia, yeah, I… I’m… so, on Facebook, what did we try last time, Robert? Because I have them on the line, and I can get Facebook closed out. I know they said your personal email was in there, I was like, can you just do the… can you do their insomnia email? They said, make sure you have a Facebook account with your Insomnia email.
370 00:52:41.150 ⇒ 00:52:42.739 Uttam Kumaran: I was gonna do that.
371 00:52:42.740 ⇒ 00:52:51.120 Robert Tseng: That was the… that was the issue… oh yeah, that’s where we left off last time. We didn’t end up making one. So… yeah. Wait, you, you, you, okay, yeah, I, I…
372 00:52:51.550 ⇒ 00:53:02.790 Robert Tseng: Because we’re still pulling from that random Facebook dashboard that the agency gives us. Yeah. Yeah, I never… I never really got a Facebook account to work with their thing, so…
373 00:53:03.500 ⇒ 00:53:08.090 Robert Tseng: Like, my permanent Facebook account doesn’t work because I’m banned on ads on Facebook.
374 00:53:08.090 ⇒ 00:53:08.485 Uttam Kumaran: Yeah.
375 00:53:08.880 ⇒ 00:53:11.109 Robert Tseng: For life. Well, I’m gonna try with the Insomnia email.
376 00:53:11.420 ⇒ 00:53:13.620 Uttam Kumaran: Okay. I’m gonna try with your insomnia email.
377 00:53:13.750 ⇒ 00:53:15.670 Uttam Kumaran: And let’s kind of see what happens.
378 00:53:15.840 ⇒ 00:53:17.090 Uttam Kumaran: Okay.
379 00:53:19.920 ⇒ 00:53:29.980 Uttam Kumaran: Okay, and then there’s kind of a… there’s… Amber’s gonna send, like, an update on analysis.
380 00:53:31.160 ⇒ 00:53:33.840 Uttam Kumaran: That you can get out to con… are you meeting with them today?
381 00:53:35.210 ⇒ 00:53:37.179 Robert Tseng: I didn’t get…
382 00:53:38.790 ⇒ 00:53:44.949 Robert Tseng: the invite, so… I don’t know. I just assumed that we didn’t, because I wasn’t on the call.
383 00:53:46.450 ⇒ 00:53:51.820 Robert Tseng: Maybe they, like, took it off and forgot to add it back in. But no one said anything, so… kinda just…
384 00:53:52.700 ⇒ 00:53:53.960 Robert Tseng: Trying not to…
385 00:53:54.790 ⇒ 00:53:59.980 Uttam Kumaran: Okay. I just… I think we should just get something on the analysis front to them today. Is there anything we can send?
386 00:54:00.430 ⇒ 00:54:03.889 Robert Tseng: Yeah, I mean, Amber’s deck from Friday.
387 00:54:03.890 ⇒ 00:54:05.270 Uttam Kumaran: Yeah, I agree.
388 00:54:05.330 ⇒ 00:54:10.409 Robert Tseng: I need… I’ve started reviewing it, it just… reviews take me a while, so I didn’t end up finishing it.
389 00:54:10.410 ⇒ 00:54:10.770 Uttam Kumaran: Yeah.
390 00:54:10.850 ⇒ 00:54:17.369 Robert Tseng: But yeah, she can share. She basically finished out an analysis last week, and then…
391 00:54:17.370 ⇒ 00:54:33.619 Robert Tseng: was kind of on a different side quest. I don’t think we need to share the side quest, we can just share, like, what… the direction she’s heading in. Give, like, a preliminary brief, kind of like what we did with README. It’s like, hey, we started on this, these are the questions that are coming out, like, what would you rather us, like, kind of look into?
392 00:54:33.640 ⇒ 00:54:39.129 Robert Tseng: Because I feel like what she puts out is, like, some of it is not ready, some of it is…
393 00:54:39.510 ⇒ 00:54:48.820 Robert Tseng: I get… yeah, anyway, so it’s just kind of… there’s, like, they’re in different stages, which I… yeah, which is how it should be. Like, I don’t think everything is gonna be buttoned up every week.
394 00:54:50.110 ⇒ 00:54:53.189 Uttam Kumaran: So, do you think that today I should just fire one of those off?
395 00:54:53.720 ⇒ 00:54:58.380 Uttam Kumaran: Or do you wanna… Do you want us to draft you a message to fire off?
396 00:54:59.110 ⇒ 00:55:02.719 Robert Tseng: I can… I can draft the message, I just… I might…
397 00:55:03.100 ⇒ 00:55:08.059 Robert Tseng: After my next call, I might just, like, spend 15 minutes to just send the message.
398 00:55:08.740 ⇒ 00:55:10.359 Uttam Kumaran: Okay. Because I feel good about…
399 00:55:10.360 ⇒ 00:55:18.230 Robert Tseng: Give them something to be discussing this week, and then I want to make sure we grab time with them. Yeah. And then, in parallel, you’re handling the situation.
400 00:55:18.230 ⇒ 00:55:19.490 Uttam Kumaran: Yeah, yeah, yeah.
401 00:55:19.490 ⇒ 00:55:25.129 Robert Tseng: And the… and the brays, which were just blocked by the current thing, so that’s still the biggest blocker for us.
402 00:55:25.130 ⇒ 00:55:29.150 Uttam Kumaran: So that I’ll push, like, that’ll… that’ll… we’re good on, I’ll keep pushing that, so…
403 00:55:30.520 ⇒ 00:55:30.950 Robert Tseng: Yeah.
404 00:55:30.950 ⇒ 00:55:32.550 Uttam Kumaran: Okay,
405 00:55:32.780 ⇒ 00:55:37.449 Uttam Kumaran: Yeah, that’s… those are kind of the two biggest things, so as long as we’re good there, then, yeah, I’m fine.
406 00:55:40.100 ⇒ 00:55:50.819 Robert Tseng: Okay. I know I gave the opinion that we shouldn’t move forward with the AI Decisioning Studio. This is, like, a one and a half hour demo that, like, Braves, like, kinda made me sit in on last week… last week.
407 00:55:50.900 ⇒ 00:56:01.419 Robert Tseng: I kind of gave my perspective. I think, you know, I’m open to doing it for, like, a limited pilot, but not paying the, whatever, $150,000 a year that they want to charge on top of what they’re paying.
408 00:56:01.750 ⇒ 00:56:14.889 Robert Tseng: Amber’s analysis somewhat informs that decision. I think she contradicts what I’m saying a little bit, so I think I have more reservations with my opinion, but I also, like, don’t feel like I understand her analysis enough to really change my mind on it.
409 00:56:15.620 ⇒ 00:56:16.260 Uttam Kumaran: Okay.
410 00:56:16.590 ⇒ 00:56:17.140 Robert Tseng: Yeah.
411 00:56:19.070 ⇒ 00:56:25.670 Uttam Kumaran: Yeah, I mean, I feel like what might be best is, like, for you to send something, and then just to ask them, like, hey, can we get 30 minutes to do a meeting this week?
412 00:56:26.080 ⇒ 00:56:27.899 Uttam Kumaran: To get some FaceTime this week.
413 00:56:28.380 ⇒ 00:56:32.409 Robert Tseng: Yeah, that’s pretty much what I’m gonna do at… after this call, yeah.
414 00:56:32.630 ⇒ 00:56:33.090 Uttam Kumaran: Okay.
415 00:56:33.090 ⇒ 00:56:40.950 Robert Tseng: And then, demilade, since you’re on this call, I asked you, I gave you the draft, that’s the message I’m sending to the offer, so I just need that data file in a way.
416 00:56:40.950 ⇒ 00:56:41.570 Demilade Agboola: Yeah.
417 00:56:41.720 ⇒ 00:56:45.790 Robert Tseng: I mean, as much as you can strip out stuff that’s not like…
418 00:56:46.690 ⇒ 00:56:55.260 Robert Tseng: identifying of our customers. It’s fine if you send out more stuff, I can go strip it out myself, but just… that’s… that’s… that’s the last piece.
419 00:56:55.800 ⇒ 00:57:02.110 Demilade Agboola: Yeah, so the only thing is our internal customer ID, but, like, obviously that doesn’t identify the customer.
420 00:57:02.450 ⇒ 00:57:03.790 Demilade Agboola: That’s the only identity.
421 00:57:03.790 ⇒ 00:57:12.219 Robert Tseng: Any, like, hashed ID, like, it’s fine, doesn’t really matter. I think it probably should be good to leave in there, because we need to prove that it is, like.
422 00:57:12.740 ⇒ 00:57:16.149 Robert Tseng: You know, we have this link between transactions and customers.
423 00:57:16.360 ⇒ 00:57:33.550 Robert Tseng: But yeah, I think the… it’s… it’s not 600K, it’s $188K, and the solution is to withhold the next invoice, with one of their outstanding invoices. So, and already… everyone on Eden’s clear on that. The ELT is signed off, so we just need to send that. I just need to.
424 00:57:33.550 ⇒ 00:57:33.990 Demilade Agboola: send that fly.
425 00:57:33.990 ⇒ 00:57:34.920 Robert Tseng: So, yeah.
426 00:57:34.920 ⇒ 00:57:42.620 Demilade Agboola: I have sent it to you, and I’ve marked the column that has the cause of disparity as column O.
427 00:57:42.850 ⇒ 00:57:46.660 Demilade Agboola: So if you filter by that, you can see the individual classifications of
428 00:57:47.130 ⇒ 00:57:50.590 Demilade Agboola: What’s causing the dispute slash disparity.
429 00:57:50.760 ⇒ 00:57:53.379 Demilade Agboola: And you can look at it individually.
430 00:57:54.200 ⇒ 00:57:54.740 Robert Tseng: Yeah.
431 00:57:54.920 ⇒ 00:57:55.750 Robert Tseng: Okay.
432 00:57:58.980 ⇒ 00:58:00.380 Robert Tseng: Cool. Anything else?
433 00:58:01.360 ⇒ 00:58:02.849 Demilade Agboola: Nothing from my end.
434 00:58:05.200 ⇒ 00:58:06.019 Uttam Kumaran: That’s it.
435 00:58:06.520 ⇒ 00:58:08.410 Robert Tseng: Alright, sounds good.
436 00:58:08.870 ⇒ 00:58:09.380 Demilade Agboola: Alright, Ben.
437 00:58:09.380 ⇒ 00:58:10.060 Uttam Kumaran: Okay.
438 00:58:10.540 ⇒ 00:58:11.189 Uttam Kumaran: Thanks, Ashley.
439 00:58:12.710 ⇒ 00:58:13.460 Uttam Kumaran: Goodbye.