Meeting Title: Default | Brainforge Weekly Sync Date: 2025-10-16 Meeting participants: Uttam Kumaran, Caitlyn Vaughn
WEBVTT
1 00:01:09.590 ⇒ 00:01:11.080 Uttam Kumaran: Hello!
2 00:01:11.080 ⇒ 00:01:12.630 Caitlyn Vaughn: Lo!
3 00:01:13.260 ⇒ 00:01:14.940 Uttam Kumaran: I liked your LinkedIn post.
4 00:01:15.090 ⇒ 00:01:16.090 Caitlyn Vaughn: Which one?
5 00:01:16.560 ⇒ 00:01:18.859 Uttam Kumaran: About New York versus Austin.
6 00:01:18.860 ⇒ 00:01:19.730 Caitlyn Vaughn: Oh.
7 00:01:20.480 ⇒ 00:01:23.180 Caitlyn Vaughn: Thanks. I think that one out today, right?
8 00:01:23.760 ⇒ 00:01:24.670 Uttam Kumaran: Yes.
9 00:01:24.670 ⇒ 00:01:26.300 Caitlyn Vaughn: Yay!
10 00:01:27.100 ⇒ 00:01:28.160 Caitlyn Vaughn: I’m.
11 00:01:28.900 ⇒ 00:01:32.010 Uttam Kumaran: tired today.
12 00:01:32.010 ⇒ 00:01:44.020 Caitlyn Vaughn: And I just showered, like, this morning, and then I had to run a positioning meeting with our team, and I was like, and then, everyone kinda…
13 00:01:45.070 ⇒ 00:01:50.519 Uttam Kumaran: Yeah, I feel like 4 out of… one day out of the week, I’m, like, completely brain dead.
14 00:01:50.520 ⇒ 00:01:50.970 Caitlyn Vaughn: Yeah.
15 00:01:50.970 ⇒ 00:01:53.519 Uttam Kumaran: It will be tomorrow. It’s starting to come on.
16 00:01:53.520 ⇒ 00:01:54.390 Caitlyn Vaughn: Yeah.
17 00:01:54.390 ⇒ 00:01:59.769 Uttam Kumaran: And… yeah, but today is our big, like, we do a lot of client meetings today, and like…
18 00:02:00.220 ⇒ 00:02:02.250 Uttam Kumaran: Try to get a bunch of stuff out, so…
19 00:02:04.640 ⇒ 00:02:06.789 Caitlyn Vaughn: for you, and I had Monday off, too.
20 00:02:07.280 ⇒ 00:02:12.230 Uttam Kumaran: I know, that’s why I did not have Monday off. Monday was fucking brutal.
21 00:02:12.230 ⇒ 00:02:15.309 Caitlyn Vaughn: Like, half our team ended up working.
22 00:02:15.310 ⇒ 00:02:18.640 Uttam Kumaran: weird, I didn’t know… I don’t know, like, if it’s officially…
23 00:02:19.520 ⇒ 00:02:21.840 Uttam Kumaran: Is it officially, official, a day off?
24 00:02:21.840 ⇒ 00:02:30.999 Caitlyn Vaughn: It’s a federal holiday, but your company gets to… they have to choose, like, a certain number of holidays to give you off.
25 00:02:31.000 ⇒ 00:02:31.700 Uttam Kumaran: Oh, okay.
26 00:02:31.700 ⇒ 00:02:33.059 Caitlyn Vaughn: I got to do all of them.
27 00:02:33.480 ⇒ 00:02:34.570 Uttam Kumaran: Oh, okay.
28 00:02:34.720 ⇒ 00:02:40.890 Caitlyn Vaughn: So I think most companies don’t do that. Okay. I literally showed up to work, and then Florida was like.
29 00:02:41.300 ⇒ 00:02:45.070 Caitlyn Vaughn: are you daft? Like, don’t be working today. And I was like.
30 00:02:45.070 ⇒ 00:02:51.389 Uttam Kumaran: Oh, I know. That’s why… yeah, I couldn’t take… I can’t take it off, but I did… I told everybody, I was like, if you want to…
31 00:02:51.620 ⇒ 00:02:55.479 Uttam Kumaran: You can, I mean… but some of our clients are still working, so I, like…
32 00:02:56.330 ⇒ 00:02:57.490 Uttam Kumaran: I’m gonna be working, man.
33 00:02:57.490 ⇒ 00:02:59.579 Caitlyn Vaughn: If you want to, you can.
34 00:03:00.180 ⇒ 00:03:05.759 Uttam Kumaran: That’s what I told our team, because… but we have people that aren’t in the States, and some people want to make money, they’re like…
35 00:03:06.020 ⇒ 00:03:10.389 Uttam Kumaran: Dude, I’m like, I’m not gonna get paid, so let’s… I wanna keep working. I said, okay.
36 00:03:10.490 ⇒ 00:03:12.299 Uttam Kumaran: I don’t mind, we have work to do.
37 00:03:12.300 ⇒ 00:03:19.369 Caitlyn Vaughn: Oh my god, that’s like Nico. Nico was like, don’t cancel team meetings. I was like, dude, I’m not putting fucking team meetings on, on, like, a holiday.
38 00:03:19.370 ⇒ 00:03:24.669 Uttam Kumaran: I… yeah, I don’t know, I’m pretty okay… I’m pretty okay if people want to take the day off, like.
39 00:03:25.560 ⇒ 00:03:27.610 Uttam Kumaran: go ahead, because I’d rather them not burn out.
40 00:03:27.740 ⇒ 00:03:28.970 Caitlyn Vaughn: Yeah, yeah, totally.
41 00:03:28.970 ⇒ 00:03:31.769 Uttam Kumaran: I’m gonna be on, so there’s no… yeah.
42 00:03:31.770 ⇒ 00:03:35.639 Caitlyn Vaughn: I’ve had two 4-day work weeks in a row. Feels good.
43 00:03:35.640 ⇒ 00:03:36.960 Uttam Kumaran: That’s nice.
44 00:03:36.960 ⇒ 00:03:43.210 Caitlyn Vaughn: I have been, like, equally productive, if not more productive, than a 5-day work week, which is kind of sad.
45 00:03:43.560 ⇒ 00:03:45.979 Uttam Kumaran: Yeah, no, I think just, like, getting more sleep.
46 00:03:46.910 ⇒ 00:03:56.509 Uttam Kumaran: And you get to think through all the stuff, too, for another, like, 12 hours, like… Yeah. I feel like a lot of times in startup world, you just go week, week, you go day, day, day, and you never get, like.
47 00:03:57.250 ⇒ 00:03:57.910 Caitlyn Vaughn: Perspective.
48 00:03:57.910 ⇒ 00:04:00.850 Uttam Kumaran: To think. Yeah. Or, like, to process, like…
49 00:04:01.330 ⇒ 00:04:03.790 Uttam Kumaran: Anything, so that’s what makes it really tough.
50 00:04:03.790 ⇒ 00:04:04.900 Caitlyn Vaughn: Yeah, totally.
51 00:04:06.040 ⇒ 00:04:06.550 Uttam Kumaran: Oh, you didn’t
52 00:04:07.770 ⇒ 00:04:15.409 Uttam Kumaran: We did, but we didn’t do, we didn’t… we need to add in a couple things, so we didn’t fit… we didn’t get to do the people yet.
53 00:04:17.230 ⇒ 00:04:23.740 Uttam Kumaran: But I do have, like, we didn’t get to add the people, and we also didn’t do…
54 00:04:25.290 ⇒ 00:04:33.579 Uttam Kumaran: I don’t think we… I don’t know if we did revenue… or we didn’t do… ARR, we’re funding.
55 00:04:33.610 ⇒ 00:04:35.609 Caitlyn Vaughn: But we have the rest.
56 00:04:35.870 ⇒ 00:04:37.980 Uttam Kumaran: So, I can share this with you.
57 00:04:38.620 ⇒ 00:04:39.859 Uttam Kumaran: And you can take a look.
58 00:04:47.470 ⇒ 00:04:50.670 Caitlyn Vaughn: Also, my computer just fucking force restarted.
59 00:04:51.300 ⇒ 00:04:52.949 Uttam Kumaran: It’s… that’s good for it, too.
60 00:05:03.240 ⇒ 00:05:06.719 Uttam Kumaran: So, we need to add… so, roughly, like,
61 00:05:07.090 ⇒ 00:05:12.300 Uttam Kumaran: PDL didn’t do a good job at employee count, but did a good job at HQ.
62 00:05:12.720 ⇒ 00:05:13.740 Uttam Kumaran: And…
63 00:05:13.740 ⇒ 00:05:15.119 Caitlyn Vaughn: Wait, wait, okay.
64 00:05:15.400 ⇒ 00:05:17.020 Uttam Kumaran: Oh, I just sent you the,
65 00:05:18.140 ⇒ 00:05:20.569 Uttam Kumaran: I sent it to you in Slack.
66 00:05:21.800 ⇒ 00:05:24.099 Caitlyn Vaughn: Oh, in the BrainPorge channel? Oh, no, in ours.
67 00:05:24.100 ⇒ 00:05:25.000 Uttam Kumaran: you’re… yeah.
68 00:05:25.810 ⇒ 00:05:26.960 Caitlyn Vaughn: Sick.
69 00:05:33.250 ⇒ 00:05:37.990 Uttam Kumaran: So, it did really good on industry and HQ location,
70 00:05:40.230 ⇒ 00:05:45.320 Uttam Kumaran: It did pretty good. It did okay at customer segment.
71 00:05:45.590 ⇒ 00:05:56.710 Uttam Kumaran: And then I don’t have… I… we need to do, Revenue funding, and people.
72 00:06:00.190 ⇒ 00:06:06.070 Uttam Kumaran: But also, like, again, we don’t… we didn’t do, like, people data labs, I like them a lot because of their other signals.
73 00:06:06.400 ⇒ 00:06:07.330 Caitlyn Vaughn: Yeah.
74 00:06:07.500 ⇒ 00:06:10.219 Uttam Kumaran: So, I can also add a section which is, like.
75 00:06:11.110 ⇒ 00:06:18.099 Uttam Kumaran: Because we’re not testing apples to apples, there is some stuff unique about each vendor, so one thing I can do is maybe put that in, like, what is unique about this vendor?
76 00:06:18.300 ⇒ 00:06:21.209 Caitlyn Vaughn: Yeah, I think we had talked about that, that would be really helpful.
77 00:06:21.430 ⇒ 00:06:25.729 Caitlyn Vaughn: They have, like, way more signals and data available.
78 00:06:30.030 ⇒ 00:06:30.710 Uttam Kumaran: Yeah.
79 00:06:31.420 ⇒ 00:06:36.640 Caitlyn Vaughn: reading through this. Industry… Coverage? 95%? It’s a lot.
80 00:06:38.160 ⇒ 00:06:39.509 Caitlyn Vaughn: I have to sneeze.
81 00:06:44.420 ⇒ 00:06:45.190 Uttam Kumaran: Bless you.
82 00:06:46.250 ⇒ 00:06:49.630 Caitlyn Vaughn: I’m back. I’m unwell this morning, Jesus.
83 00:06:52.780 ⇒ 00:06:57.820 Caitlyn Vaughn: Okay, yeah, these reports are really long, it always takes me a little while to, like, look through them.
84 00:06:58.230 ⇒ 00:07:03.370 Caitlyn Vaughn: Customer fit, 30% weight… That’s pretty low, though.
85 00:07:03.660 ⇒ 00:07:04.030 Uttam Kumaran: Yeah.
86 00:07:04.030 ⇒ 00:07:06.740 Caitlyn Vaughn: I think they’ve done worse than Owler, right?
87 00:07:06.740 ⇒ 00:07:07.380 Uttam Kumaran: Yeah.
88 00:07:09.360 ⇒ 00:07:11.230 Caitlyn Vaughn: Dang…
89 00:07:11.730 ⇒ 00:07:17.039 Uttam Kumaran: But I do think that they’re… having those signals is gonna… what’s pushing them over the edge for me, unless I…
90 00:07:17.150 ⇒ 00:07:19.830 Uttam Kumaran: So that’s gonna be… so something I wanna add here is…
91 00:07:22.330 ⇒ 00:07:28.240 Uttam Kumaran: What’s unique, like, something new that they have, because we used them for your stuff, and it was really, really helpful.
92 00:07:32.700 ⇒ 00:07:34.590 Caitlyn Vaughn: Honestly, though, like…
93 00:07:35.610 ⇒ 00:07:36.720 Uttam Kumaran: And they were cheaper.
94 00:07:37.030 ⇒ 00:07:45.659 Caitlyn Vaughn: Yeah, that’s… that’s what I’m thinking. For their, like, final weighted score is, like, 85%. I think Owler was, what, like, 87?
95 00:07:45.660 ⇒ 00:07:46.310 Uttam Kumaran: Yeah.
96 00:07:46.570 ⇒ 00:07:53.600 Caitlyn Vaughn: So, for that, I don’t know if 2% is worth, like… 500% increase in price.
97 00:07:53.600 ⇒ 00:07:54.210 Uttam Kumaran: Yeah.
98 00:07:55.160 ⇒ 00:07:56.070 Uttam Kumaran: I agree.
99 00:07:56.740 ⇒ 00:08:03.980 Caitlyn Vaughn: Okay, cool. Yes, if you could add in the people data to this, that would be really helpful, and then…
100 00:08:05.060 ⇒ 00:08:09.939 Caitlyn Vaughn: If we could add a section that’s, like, what is the…
101 00:08:10.700 ⇒ 00:08:20.230 Caitlyn Vaughn: Oh, actually, the other thing that I would like to see is what are all of the, like, possible fields that we can pull from this company.
102 00:08:20.640 ⇒ 00:08:21.670 Uttam Kumaran: Hmm.
103 00:08:21.670 ⇒ 00:08:28.570 Caitlyn Vaughn: Like, I would love a list of every company, like, if we could just get an Excel sheet stood up with, like, every possible field.
104 00:08:28.990 ⇒ 00:08:30.120 Caitlyn Vaughn: Boom.
105 00:08:30.720 ⇒ 00:08:39.450 Caitlyn Vaughn: and, like, who the company is that does that field, then we could start figuring out, like, who has duplicative fields, what are the different fields. Okay.
106 00:08:40.070 ⇒ 00:08:42.679 Caitlyn Vaughn: And then, if we want to, like, figure out…
107 00:08:43.169 ⇒ 00:08:45.369 Caitlyn Vaughn: If we’ll have this piece of data.
108 00:08:45.840 ⇒ 00:08:49.809 Caitlyn Vaughn: We can, like, search that data and, like, see what providers will provide.
109 00:08:51.250 ⇒ 00:08:58.209 Uttam Kumaran: Yeah, we already are… we already have all the documentation on the AMAP, so what we’ll do is we’ll put together all the endpoints.
110 00:08:58.370 ⇒ 00:09:00.519 Uttam Kumaran: And then all the fields that we’re getting.
111 00:09:01.400 ⇒ 00:09:05.800 Uttam Kumaran: And then I’ll just probably create one spreadsheet.
112 00:09:06.380 ⇒ 00:09:08.310 Uttam Kumaran: Tab per vendor.
113 00:09:08.310 ⇒ 00:09:09.380 Caitlyn Vaughn: per vendor.
114 00:09:09.380 ⇒ 00:09:10.040 Uttam Kumaran: Yeah.
115 00:09:10.280 ⇒ 00:09:14.270 Caitlyn Vaughn: Okay, cool. And can we have, like, a master sheet as well, with, like, every sheet, every…
116 00:09:14.270 ⇒ 00:09:15.660 Uttam Kumaran: with every field.
117 00:09:15.660 ⇒ 00:09:16.479 Caitlyn Vaughn: And every vendor.
118 00:09:17.570 ⇒ 00:09:18.420 Uttam Kumaran: Yeah.
119 00:09:18.420 ⇒ 00:09:19.470 Caitlyn Vaughn: Okay, cool.
120 00:09:21.520 ⇒ 00:09:23.390 Uttam Kumaran: And then what’s next after PDL?
121 00:09:23.630 ⇒ 00:09:24.420 Caitlyn Vaughn: Okay.
122 00:09:24.650 ⇒ 00:09:27.850 Caitlyn Vaughn: So… Let’s see…
123 00:09:40.520 ⇒ 00:09:44.510 Caitlyn Vaughn: Data enrichment testing… Okay, so we have…
124 00:09:46.310 ⇒ 00:09:54.569 Caitlyn Vaughn: We could do Clearbit and Apollo, and see how they… how they end up. Since we’re already using them, that would actually be, like, a very helpful…
125 00:09:55.320 ⇒ 00:09:58.789 Caitlyn Vaughn: Kind of baseline for us to understand.
126 00:09:59.270 ⇒ 00:10:04.099 Caitlyn Vaughn: How good is everyone else’s data based on the data that we’re already paying for and using?
127 00:10:04.390 ⇒ 00:10:05.000 Uttam Kumaran: Okay.
128 00:10:10.710 ⇒ 00:10:13.429 Caitlyn Vaughn: And I think I added the swarm in there, but…
129 00:10:14.280 ⇒ 00:10:16.999 Caitlyn Vaughn: I don’t remember if they have, like, a full…
130 00:10:17.280 ⇒ 00:10:20.559 Caitlyn Vaughn: like, person or company API, or if it’s, like.
131 00:10:20.850 ⇒ 00:10:24.079 Caitlyn Vaughn: Via LinkedIn, which is actually also interesting, maybe.
132 00:10:24.380 ⇒ 00:10:27.770 Uttam Kumaran: With a swarm, and then what was the, the startup one?
133 00:10:28.820 ⇒ 00:10:29.860 Caitlyn Vaughn: Harmonic.
134 00:10:29.860 ⇒ 00:10:30.930 Uttam Kumaran: Yeah, harmonic.
135 00:10:31.270 ⇒ 00:10:31.820 Caitlyn Vaughn: Yeah, true.
136 00:10:31.820 ⇒ 00:10:35.879 Uttam Kumaran: Their stuff is good, I wonder, like, if they’re paying people to get it, or I don’t know what their deal is.
137 00:10:36.260 ⇒ 00:10:37.400 Caitlyn Vaughn: Yeah.
138 00:10:37.400 ⇒ 00:10:38.760 Uttam Kumaran: Follow them on Twitter.
139 00:10:38.760 ⇒ 00:10:39.630 Caitlyn Vaughn: Yeah?
140 00:10:39.630 ⇒ 00:10:44.840 Uttam Kumaran: And they tend to announce startup funding rounds, like, much earlier, so I don’t know, like, how they’re…
141 00:10:45.190 ⇒ 00:10:49.010 Uttam Kumaran: Because I don’t know, how does that work? Like, are they just getting it leaked or something? Like, I don’t know.
142 00:10:49.530 ⇒ 00:10:55.669 Caitlyn Vaughn: I asked them… when I met with them, the guy was like, if I told you that, then…
143 00:10:55.670 ⇒ 00:10:56.770 Uttam Kumaran: Yeah, yeah, yeah.
144 00:10:56.770 ⇒ 00:11:03.280 Caitlyn Vaughn: build it. And I was like, dude, everyone just… I’m not gonna fucking build it. Like, I’m just asking. Yeah.
145 00:11:03.700 ⇒ 00:11:08.510 Caitlyn Vaughn: Some people were really open about it, and some people were like, it’s a big secret. I was like, okay.
146 00:11:10.050 ⇒ 00:11:11.669 Uttam Kumaran: Okay, so let me…
147 00:11:13.570 ⇒ 00:11:16.379 Caitlyn Vaughn: I don’t know that we have APIs for all of these yet.
148 00:11:18.270 ⇒ 00:11:18.860 Uttam Kumaran: Okay.
149 00:11:19.680 ⇒ 00:11:22.749 Caitlyn Vaughn: We definitely… but we can get them. So, like.
150 00:11:23.130 ⇒ 00:11:25.969 Caitlyn Vaughn: I have all the APIs that I sent over to you.
151 00:11:25.970 ⇒ 00:11:26.400 Uttam Kumaran: Yeah.
152 00:11:26.400 ⇒ 00:11:37.480 Caitlyn Vaughn: Then, if you get to one where you’re like, we don’t have harmonic, I’m pretty sure we don’t have one… yet, but I can ping them and get one. Same with Captain Data, same with Chris Data.
153 00:11:38.790 ⇒ 00:11:39.390 Uttam Kumaran: Okay.
154 00:11:40.120 ⇒ 00:11:48.719 Caitlyn Vaughn: WZA would be interesting, too. I mean, yeah, all of these things happen. Maybe next, clear about Apollo, and then we can do WZA, and then just keep… keep going down the list.
155 00:11:49.050 ⇒ 00:11:52.410 Uttam Kumaran: Okay, cool, so I will… so a couple things is we’re gonna add a section on, like.
156 00:11:52.900 ⇒ 00:12:03.450 Uttam Kumaran: it’s gonna be more, like, kinda like, what is unique about this vendor compared to others. That’ll be more like commentary. I’m gonna add… we’re gonna create the spreadsheet on all possible fields and get pulled.
157 00:12:04.050 ⇒ 00:12:10.309 Uttam Kumaran: From each endpoint, and then one spreadsheet tab that sort of brings that together, hopefully, like, some categorization.
158 00:12:10.650 ⇒ 00:12:19.310 Uttam Kumaran: And then as we… as I start to learn… as we, like, start to learn about the costs together, too, I’ll make sure that information gets into the assessment.
159 00:12:19.570 ⇒ 00:12:22.060 Caitlyn Vaughn: Okay. Did you see that sheet that I sent you?
160 00:12:23.880 ⇒ 00:12:30.460 Caitlyn Vaughn: It’s, it’s in… it’s in the data enrichment testing sheet.
161 00:12:32.720 ⇒ 00:12:39.765 Caitlyn Vaughn: I’ll send it over one more time, just in case you need it again. Let’s see… right here…
162 00:12:40.770 ⇒ 00:12:42.580 Caitlyn Vaughn: So if you click on that…
163 00:12:43.310 ⇒ 00:12:45.940 Caitlyn Vaughn: And you scroll to the bottom.
164 00:12:45.940 ⇒ 00:12:46.570 Uttam Kumaran: Yeah.
165 00:12:47.610 ⇒ 00:12:50.069 Caitlyn Vaughn: You see where it says providers we need to test?
166 00:12:50.300 ⇒ 00:12:50.880 Uttam Kumaran: Yeah.
167 00:12:52.080 ⇒ 00:12:54.949 Caitlyn Vaughn: If you click on that, that’s, like, all of the companies that I’ve…
168 00:12:54.950 ⇒ 00:12:56.730 Uttam Kumaran: Oh, yeah. That you talked to originally.
169 00:12:56.730 ⇒ 00:13:00.409 Caitlyn Vaughn: With notes, and then if you scroll to the right, there’s the pricing there.
170 00:13:00.550 ⇒ 00:13:01.319 Uttam Kumaran: Oh, great, okay.
171 00:13:01.320 ⇒ 00:13:01.790 Caitlyn Vaughn: I can’t even.
172 00:13:01.790 ⇒ 00:13:06.350 Uttam Kumaran: So, should I… should we just move stuff here, or would you, like, cause…
173 00:13:07.790 ⇒ 00:13:11.820 Uttam Kumaran: what do you… because I saw you have notes here, we can move our notes here.
174 00:13:12.760 ⇒ 00:13:16.439 Caitlyn Vaughn: What do you mean, notes? Look, you took notes on the performance.
175 00:13:16.440 ⇒ 00:13:18.530 Uttam Kumaran: No, no, like, these, assessments.
176 00:13:18.530 ⇒ 00:13:20.310 Caitlyn Vaughn: -Oh. No, keep them separate.
177 00:13:20.310 ⇒ 00:13:24.400 Uttam Kumaran: Okay. Okay. Okay, great. So, I… I’ll start to pull,
178 00:13:26.230 ⇒ 00:13:30.020 Uttam Kumaran: I’ll pull whatever pricing notes you have from these into ours, too.
179 00:13:30.020 ⇒ 00:13:36.190 Caitlyn Vaughn: Yeah, yeah, that’s kind of, like, what we’ve negotiated with them, although some of these we’ve gone down, like, I think Vector we can do for 8 sets now.
180 00:13:36.930 ⇒ 00:13:37.830 Caitlyn Vaughn: But yeah.
181 00:13:38.130 ⇒ 00:13:38.710 Uttam Kumaran: Okay.
182 00:13:43.130 ⇒ 00:13:43.780 Caitlyn Vaughn: Here you go.
183 00:13:44.820 ⇒ 00:13:50.280 Caitlyn Vaughn: Cool. And then you’re talking to Omni folks this week? Yeah, actually right after this.
184 00:13:50.480 ⇒ 00:13:52.419 Uttam Kumaran: Oh, nice, okay. Yeah, let me know what they say.
185 00:13:52.420 ⇒ 00:13:55.499 Caitlyn Vaughn: Okay, well, do you know anybody at AXA?
186 00:13:57.410 ⇒ 00:14:04.480 Uttam Kumaran: We use EXA, I don’t know anyone. I would like to know somebody, so if I can get a chance to meet somebody through this, I would like to.
187 00:14:04.730 ⇒ 00:14:05.979 Caitlyn Vaughn: Oh my god.
188 00:14:05.980 ⇒ 00:14:06.700 Uttam Kumaran: Bye.
189 00:14:06.700 ⇒ 00:14:08.640 Caitlyn Vaughn: Do you want to hear a story?
190 00:14:08.640 ⇒ 00:14:09.460 Uttam Kumaran: Guess?
191 00:14:09.760 ⇒ 00:14:14.009 Caitlyn Vaughn: Okay, sometimes I feel like I’m just, like, a badass, like…
192 00:14:14.330 ⇒ 00:14:23.109 Caitlyn Vaughn: COO of this company, and I’m, like, so smart and clever, and then sometimes I just question how I’ve ever been hired,
193 00:14:23.220 ⇒ 00:14:25.149 Caitlyn Vaughn: So yesterday?
194 00:14:25.300 ⇒ 00:14:31.009 Caitlyn Vaughn: I realized we’re, like, pushing out our new product soon, right? And I was like, oh, fuck, we actually need…
195 00:14:31.300 ⇒ 00:14:48.679 Caitlyn Vaughn: an agent provider, like AI agent, and web scraping. We don’t have that yet, we just have all these data vendors, but no agents. And so, I was talking to Nico, said about it, and they’re like, oh, yeah, you need to look at, like, EXA and Perplexity, and I was like, okay, what about this other one that we already kind of
196 00:14:48.680 ⇒ 00:14:53.349 Caitlyn Vaughn: started with, and they were like, no, we need to exit. I was like, okay, I’ll book some time with them.
197 00:14:53.350 ⇒ 00:14:58.880 Caitlyn Vaughn: I’ll be, like, non-opinionated until I meet with them, right? So I look up the site.
198 00:14:59.430 ⇒ 00:15:06.350 Caitlyn Vaughn: I book a call, and I’m, like, looking through their website, and I’m like, this doesn’t really seem like agents to me.
199 00:15:06.350 ⇒ 00:15:06.990 Uttam Kumaran: No.
200 00:15:06.990 ⇒ 00:15:18.010 Caitlyn Vaughn: I… I chat GPT’d it, right? Yeah. Like, do, like, do some research between these companies, and it compared and contrasted them, and there is a ton of agent stuff with EXA.
201 00:15:18.010 ⇒ 00:15:20.390 Uttam Kumaran: Yeah. A massive part of what they do.
202 00:15:20.390 ⇒ 00:15:29.739 Caitlyn Vaughn: And so I was like, okay, maybe I’m just, like, missing it, maybe I’m too stupid to understand their website, right? And so I get on with this guy yesterday, and he was like.
203 00:15:30.160 ⇒ 00:15:41.799 Caitlyn Vaughn: what brought you here? And I was like, oh yeah, we’re, like, looking for an agent provider, da-da-da, all the stuff. And he goes, well, are you looking for, like, a, locally hosted or, like, cloud-based? And I was like.
204 00:15:42.040 ⇒ 00:15:45.720 Caitlyn Vaughn: cloud-based. And he’s like, well, where do you host your data?
205 00:15:45.890 ⇒ 00:15:49.450 Caitlyn Vaughn: I was like, Click House, and he was like, no, we’re not a good fit for you.
206 00:15:50.240 ⇒ 00:16:03.230 Caitlyn Vaughn: like, within 2 minutes of the call, and I was like, how… I was like, how would you be able to pull, like, website data and stuff without being connected to the web? And he was like, that’s so much easier than what we do.
207 00:16:03.740 ⇒ 00:16:04.899 Caitlyn Vaughn: And I was like…
208 00:16:05.500 ⇒ 00:16:10.359 Uttam Kumaran: No, I don’t know, what the fuck is this guy talking about? All they are is web search APIs, so, like…
209 00:16:10.360 ⇒ 00:16:22.659 Caitlyn Vaughn: Yes. Yeah. Okay. So, then, after, like, I get off this call in, like, 5 minutes. Like, I was just like, you’re… you’re not a good fit for us. Like, I don’t know what… who told you that we would be. And I was like.
210 00:16:22.790 ⇒ 00:16:31.979 Caitlyn Vaughn: I was like, I’m really trying to understand, because a lot of people recommended this, you know? And he was like, no, I’m telling you, like, we really just specialize in, like, on-prem.
211 00:16:32.340 ⇒ 00:16:33.420 Caitlyn Vaughn: data, and I was like.
212 00:16:33.420 ⇒ 00:16:34.669 Uttam Kumaran: the wrong person.
213 00:16:34.670 ⇒ 00:16:35.939 Caitlyn Vaughn: I was like, okay.
214 00:16:35.940 ⇒ 00:16:37.860 Uttam Kumaran: the wrong company? Wait, what?
215 00:16:37.860 ⇒ 00:16:50.570 Caitlyn Vaughn: So then I ping Victor, I get off, and I’m like, dude, this… this company fucking sucks. Like, everyone has been, like, raving about it, and they’re just… they just told me that we’re a bad fit, because we don’t have… we don’t want, like, on…
216 00:16:50.570 ⇒ 00:17:08.490 Caitlyn Vaughn: on-prem stuff. And he goes, what? He goes, what the fuck? He goes, yeah, they’ve been having some issues lately. I’ve been seeing it in, like, the Twittersphere kind of a thing. And I was like, oh, and he’s like, let me see what nutjob you talk to. He goes on my calendar, and he comes back and he calls me. I’m like, what’s going on? He goes.
217 00:17:08.569 ⇒ 00:17:12.710 Caitlyn Vaughn: You talked to NEXA, not EXA.
218 00:17:16.099 ⇒ 00:17:18.179 Uttam Kumaran: Oh, interesting.
219 00:17:18.180 ⇒ 00:17:23.190 Caitlyn Vaughn: And he prints it out and puts it in the office. Yeah.
220 00:17:23.190 ⇒ 00:17:23.650 Uttam Kumaran: Yeah, I was like.
221 00:17:23.650 ⇒ 00:17:24.140 Caitlyn Vaughn: Like.
222 00:17:24.140 ⇒ 00:17:25.860 Uttam Kumaran: Wait, that’s all they do, what are you talking about?
223 00:17:25.869 ⇒ 00:17:32.949 Caitlyn Vaughn: Yeah, I was also so confused. I was like, Victor, am I… am I missing something major here? And he was just like, what?
224 00:17:33.760 ⇒ 00:17:36.499 Uttam Kumaran: Okay, so did… but you haven’t talked to them yet since then.
225 00:17:36.500 ⇒ 00:17:42.059 Caitlyn Vaughn: Yeah, so then I tried to book a call with EXA, and they didn’t accept my… my…
226 00:17:42.060 ⇒ 00:17:45.099 Uttam Kumaran: I don’t think you need to book… yeah, I guess, basically.
227 00:17:45.310 ⇒ 00:17:51.379 Uttam Kumaran: They’re… them, Perplexity Search, or Google Web Search Agent.
228 00:17:51.380 ⇒ 00:17:52.630 Caitlyn Vaughn: But you should just…
229 00:17:52.630 ⇒ 00:17:57.439 Uttam Kumaran: The Google one is just, like, these guys aren’t that much better, dude. They’re just, like, hot in the startup world.
230 00:17:57.600 ⇒ 00:17:58.970 Caitlyn Vaughn: Yeah, but we kind of want that.
231 00:17:58.970 ⇒ 00:18:00.590 Uttam Kumaran: Okay, okay, okay, fine, fair enough.
232 00:18:00.590 ⇒ 00:18:02.820 Caitlyn Vaughn: We want, like, we want a brand name with it, you know?
233 00:18:02.820 ⇒ 00:18:06.510 Uttam Kumaran: Then, yeah, these are the guys, yeah. But, like… I mean…
234 00:18:06.830 ⇒ 00:18:09.430 Uttam Kumaran: Yeah, they should pick up your phone, I don’t know why they didn’t…
235 00:18:09.760 ⇒ 00:18:19.830 Caitlyn Vaughn: Yeah, I booked a fucking call with the guy, and I was like, we have to wait to accept this meeting. And then I waited for, like, an hour, and I was supposed to go somewhere, and I waited, and they didn’t show up to it.
236 00:18:20.980 ⇒ 00:18:26.350 Uttam Kumaran: Well, they’re really good. They’re, like, the web… best web search… they’re, like, the oddest web search API.
237 00:18:26.800 ⇒ 00:18:30.889 Uttam Kumaran: But, like, low-key, They’re not, like, much… they’re not much better than…
238 00:18:30.890 ⇒ 00:18:32.749 Caitlyn Vaughn: They’re the same. Yeah.
239 00:18:32.750 ⇒ 00:18:38.690 Uttam Kumaran: They have… they just… they just created this, like, these, like, BS things, like websites and some other bullshit, like…
240 00:18:38.690 ⇒ 00:18:40.160 Caitlyn Vaughn: It’s just like Google search.
241 00:18:40.160 ⇒ 00:18:41.160 Uttam Kumaran: API.
242 00:18:41.850 ⇒ 00:18:45.379 Uttam Kumaran: It’s just crazy how they just make all this fucking money, like…
243 00:18:45.470 ⇒ 00:18:46.590 Caitlyn Vaughn: And, and…
244 00:18:46.590 ⇒ 00:18:56.320 Uttam Kumaran: they don’t do anything different, really, like… and also, some of their stuff doesn’t work really well, like, I’ve… I tried it on them, and I’m like, this is not right, and I push off perplexity, and it nailed it, so…
245 00:18:56.320 ⇒ 00:18:57.889 Caitlyn Vaughn: Oh, Perplexity was better.
246 00:18:58.470 ⇒ 00:19:01.060 Uttam Kumaran: For some… for, like, a lot… yeah, for a lot of stuff.
247 00:19:01.170 ⇒ 00:19:05.039 Uttam Kumaran: But these guys are better APIs and, like, better branding.
248 00:19:05.040 ⇒ 00:19:05.720 Caitlyn Vaughn: Fuck.
249 00:19:06.070 ⇒ 00:19:08.320 Caitlyn Vaughn: Yeah. Okay. Alright, fine.
250 00:19:09.820 ⇒ 00:19:17.209 Caitlyn Vaughn: I’m just gonna… I’m just gonna… I probably… I don’t think I’m gonna white-label anybody. I’m just gonna let everybody know whose data it is, you know?
251 00:19:17.210 ⇒ 00:19:18.710 Uttam Kumaran: Yeah, I agree.
252 00:19:19.210 ⇒ 00:19:20.109 Caitlyn Vaughn: Not us.
253 00:19:21.080 ⇒ 00:19:23.160 Caitlyn Vaughn: Not us, not our problem, we didn’t do it.
254 00:19:23.720 ⇒ 00:19:28.230 Uttam Kumaran: Well, yeah, I guess I’m interested to hear what they say, because we’ve tried to use EXA for some stuff.
255 00:19:28.230 ⇒ 00:19:30.480 Caitlyn Vaughn: And it was, like, medium.
256 00:19:30.480 ⇒ 00:19:31.770 Uttam Kumaran: Yeah, medium.
257 00:19:32.070 ⇒ 00:19:37.849 Caitlyn Vaughn: Okay. Aw, your dog. Cute. Okay, well, that all sounds good,
258 00:19:38.040 ⇒ 00:19:40.279 Caitlyn Vaughn: I will let you know with Omni.
259 00:19:40.580 ⇒ 00:19:43.020 Uttam Kumaran: Yeah, let me know what they say.
260 00:19:43.440 ⇒ 00:19:46.649 Uttam Kumaran: I feel like you guys are gonna get a pretty good deal, and then…
261 00:19:46.780 ⇒ 00:19:52.289 Uttam Kumaran: Yeah, we set up Mother Duck, and you should have gotten an invite. We set up, like, a default specific instance.
262 00:19:52.740 ⇒ 00:19:58.149 Uttam Kumaran: And then I… I did not send this yesterday, but I have a thing for Deanna to review.
263 00:19:58.300 ⇒ 00:19:59.100 Caitlyn Vaughn: Hmm.
264 00:19:59.100 ⇒ 00:20:02.270 Uttam Kumaran: Customer Health Dashboard. So, as soon as we get,
265 00:20:03.410 ⇒ 00:20:09.530 Uttam Kumaran: the data connected, like, I will… well, actually, we could probably start building a version of it sooner, so we’ll start doing that.
266 00:20:09.840 ⇒ 00:20:11.110 Uttam Kumaran: So she approves.
267 00:20:12.010 ⇒ 00:20:17.960 Caitlyn Vaughn: Yeah, the invite you sent me for Mother Duck was a week ago. Is that the right one?
268 00:20:18.520 ⇒ 00:20:22.890 Uttam Kumaran: There should be another one?
269 00:20:24.720 ⇒ 00:20:26.179 Caitlyn Vaughn: We don’t want another one.
270 00:20:27.220 ⇒ 00:20:32.120 Uttam Kumaran: Okay, let me actually just do this right now.
271 00:21:02.820 ⇒ 00:21:04.160 Uttam Kumaran: Oh, you’re already in here.
272 00:21:04.300 ⇒ 00:21:09.419 Uttam Kumaran: Okay. Yeah, nevermind, you’re already in here. You should see…
273 00:21:10.300 ⇒ 00:21:16.109 Uttam Kumaran: Yeah, you should see one called… well, we had two. This one is,
274 00:21:18.770 ⇒ 00:21:21.820 Uttam Kumaran: This one should say defaults organization at the top.
275 00:21:26.740 ⇒ 00:21:27.520 Caitlyn Vaughn: Okay.
276 00:21:30.080 ⇒ 00:21:32.499 Caitlyn Vaughn: Defaults organization, I’m in there!
277 00:21:32.500 ⇒ 00:21:36.010 Uttam Kumaran: Okay, great. So I feel like the only thing…
278 00:21:38.680 ⇒ 00:21:41.540 Uttam Kumaran: I need to remove my credit card from this.
279 00:21:41.540 ⇒ 00:21:42.330 Caitlyn Vaughn: Oh, yeah, yeah, yeah.
280 00:21:42.330 ⇒ 00:21:49.229 Uttam Kumaran: Let me do that. Or, can you, can you go in and see update? Can you go in and see… gonna update this?
281 00:21:50.550 ⇒ 00:21:51.419 Caitlyn Vaughn: Let me see…
282 00:21:51.420 ⇒ 00:21:54.880 Uttam Kumaran: And we’ll just stay on the whatever plan right now.
283 00:21:55.040 ⇒ 00:21:59.650 Caitlyn Vaughn: Okay, where are my settings?
284 00:22:01.430 ⇒ 00:22:02.380 Caitlyn Vaughn: Okay.
285 00:22:03.340 ⇒ 00:22:04.840 Caitlyn Vaughn: No, that’s not wrong.
286 00:22:06.050 ⇒ 00:22:12.620 Caitlyn Vaughn: Mmm… Winds… What are we on right now, 25?
287 00:22:12.620 ⇒ 00:22:13.340 Uttam Kumaran: Yeah.
288 00:22:13.910 ⇒ 00:22:18.970 Caitlyn Vaughn: Okay, cool. How do you… Update billing…
289 00:22:21.790 ⇒ 00:22:24.949 Caitlyn Vaughn: Am I an admin on this? Question mark?
290 00:22:25.580 ⇒ 00:22:29.210 Uttam Kumaran: Yes. Maybe try refreshing? I don’t know.
291 00:22:34.030 ⇒ 00:22:36.470 Caitlyn Vaughn: So cute, I love their branding. Oh, there it is. Okay.
292 00:22:36.470 ⇒ 00:22:44.520 Uttam Kumaran: Yeah, these guys are a good, pro- eventually, when you guys are thinking about, supporting, like, exports into data warehouses for, like, default data.
293 00:22:45.450 ⇒ 00:22:46.670 Uttam Kumaran: You should consider them.
294 00:22:46.830 ⇒ 00:22:47.680 Uttam Kumaran: They’re really, really good.
295 00:22:47.680 ⇒ 00:22:49.539 Caitlyn Vaughn: Putting data into what?
296 00:22:49.540 ⇒ 00:22:58.329 Uttam Kumaran: Like, for example, some of your customers may want to say, like, hey, can I get our meeting booking and our workflow run data so that I can move it into our system?
297 00:22:58.330 ⇒ 00:22:59.040 Caitlyn Vaughn: Yep.
298 00:22:59.780 ⇒ 00:23:04.000 Uttam Kumaran: Like, a lot of companies will be like, yeah, we have a native mother duck connector.
299 00:23:04.170 ⇒ 00:23:10.729 Uttam Kumaran: But these guys are really, really great. They… in every sector in data, there’s, like, the new hotness.
300 00:23:10.730 ⇒ 00:23:11.450 Caitlyn Vaughn: Yeah.
301 00:23:11.450 ⇒ 00:23:17.450 Uttam Kumaran: But, like, that’s who these guys are. And their product is really cost-effective and, like, For what they do.
302 00:23:17.660 ⇒ 00:23:20.240 Caitlyn Vaughn: Fuck yeah, I’m super into that.
303 00:23:20.830 ⇒ 00:23:24.329 Caitlyn Vaughn: I think we’re gonna try to white-label Omni, too.
304 00:23:24.800 ⇒ 00:23:25.370 Uttam Kumaran: Nice.
305 00:23:25.370 ⇒ 00:23:30.550 Caitlyn Vaughn: pretty cool. So, I think that’s another, like, lever for me to pull in this conversation.
306 00:23:31.380 ⇒ 00:23:37.040 Uttam Kumaran: Yeah, talk about the startup… talk about the startup discount. They’re gonna charge you for the other… for the white label.
307 00:23:37.910 ⇒ 00:23:40.249 Uttam Kumaran: but see what Brett can do.
308 00:23:40.370 ⇒ 00:23:43.699 Uttam Kumaran: Greg is new there, but he’s, like, long career in data.
309 00:23:44.300 ⇒ 00:23:49.860 Uttam Kumaran: So, probably can pull some strings. He’s leading, like, I think their commercial sales for…
310 00:23:50.220 ⇒ 00:23:51.990 Uttam Kumaran: North America or something, so…
311 00:23:51.990 ⇒ 00:23:53.590 Caitlyn Vaughn: But I was telling him, I’m like.
312 00:23:53.680 ⇒ 00:24:01.700 Uttam Kumaran: I was telling him where we were working with you guys, like, dude, I need a win for, like, it’s my first week here. I’m like, alright, so you can see how it goes.
313 00:24:01.700 ⇒ 00:24:03.509 Caitlyn Vaughn: You’re like, fingers crossed.
314 00:24:03.510 ⇒ 00:24:07.369 Uttam Kumaran: I was like, it’s not up to me. You could schmooze Caitlyn, I don’t know.
315 00:24:07.370 ⇒ 00:24:16.600 Caitlyn Vaughn: That’s so funny. Okay, cool. Yeah, that sounds good. I’ll let you know how that goes. I’m gonna update this card, and then,
316 00:24:16.850 ⇒ 00:24:18.359 Caitlyn Vaughn: Let me know if you…
317 00:24:18.360 ⇒ 00:24:21.519 Uttam Kumaran: Are you guys doing any events, like, the rest of the year?
318 00:24:21.800 ⇒ 00:24:24.159 Caitlyn Vaughn: Oh, actually, I just hired a new partnerships girl.
319 00:24:24.270 ⇒ 00:24:25.589 Uttam Kumaran: I did see that.
320 00:24:25.590 ⇒ 00:24:34.400 Caitlyn Vaughn: Yeah, that’s what I was, like… my computer was, like, restarting, and I’m, like, on my phone trying to send this message out before… so underwater. But I think.
321 00:24:34.400 ⇒ 00:24:35.559 Uttam Kumaran: What’s her background?
322 00:24:35.910 ⇒ 00:24:39.850 Caitlyn Vaughn: She is fucking badass. She’s so cool.
323 00:24:39.850 ⇒ 00:24:40.420 Uttam Kumaran: Wow.
324 00:24:40.420 ⇒ 00:24:47.260 Caitlyn Vaughn: Her background is… she was at Datadog, she built partnerships there, LaunchDarkly, Rattle.
325 00:24:47.260 ⇒ 00:24:47.840 Uttam Kumaran: Right.
326 00:24:47.840 ⇒ 00:25:04.260 Caitlyn Vaughn: like, RevOps Co-op. She’s been at a bunch of companies and just, like, built out their partnerships. I think I’m trying to offload partnerships completely off my plate. It’s just… it’s time. Yeah. Like, putting one hour a week into it and, like, doing a bad job at it. Not… not bad, I just don’t have enough time for it.
327 00:25:04.260 ⇒ 00:25:15.309 Uttam Kumaran: Yeah, well, let me know how I can help. Like, we… I’m still recommending stuff to all of our clients, if we should do actually more of that, but yeah, if you guys are doing an event or something, like, we’d love to help, so…
328 00:25:15.310 ⇒ 00:25:17.690 Caitlyn Vaughn: Cool. Yeah, we want referrals, Utom, that’s what.
329 00:25:17.690 ⇒ 00:25:32.000 Uttam Kumaran: I know, I know, I actually… I should actually… we don’t… we have some B2B folks, I don’t know why I did not… I should go… I should go back and ask them who they’re using. Yeah. But now that’s, like, very top of mind for me. But also, pitch, pitch, Omni on using…
330 00:25:32.580 ⇒ 00:25:33.859 Uttam Kumaran: Default.
331 00:25:34.030 ⇒ 00:25:35.580 Uttam Kumaran: We’re using Revenue Hero.
332 00:25:35.580 ⇒ 00:25:36.430 Caitlyn Vaughn: Oh, really?
333 00:25:36.430 ⇒ 00:25:37.000 Uttam Kumaran: Yeah.
334 00:25:37.000 ⇒ 00:25:43.830 Caitlyn Vaughn: Yeah, when I went through his booking, oh my god, I almost included that in the email. I almost said, looks like we need each other, can’t wait to talk.
335 00:25:43.830 ⇒ 00:25:51.510 Uttam Kumaran: I’ve told them, too. I said… I said… I’ve told them to sell you on… well, I basically said, like, you may need to implement default as part of the deal, you know.
336 00:25:51.510 ⇒ 00:25:58.240 Caitlyn Vaughn: Yeah, yeah, that’s a good idea. I’m gonna use that as a… as a token. What was I gonna say?
337 00:25:59.380 ⇒ 00:26:02.379 Caitlyn Vaughn: I forgot, it’s out of my brain yet, now, but .
338 00:26:02.380 ⇒ 00:26:05.720 Uttam Kumaran: And our team loves default, by the way, like, we’re using it for… we’re starting to use.
339 00:26:05.720 ⇒ 00:26:06.340 Caitlyn Vaughn: Holy crap.
340 00:26:06.340 ⇒ 00:26:08.299 Uttam Kumaran: Because we’re finally starting to get inbound, so…
341 00:26:08.300 ⇒ 00:26:13.319 Caitlyn Vaughn: I remember what I was gonna tell you. I have referred you so much!
342 00:26:13.610 ⇒ 00:26:15.430 Caitlyn Vaughn: Oh, really?
343 00:26:15.650 ⇒ 00:26:17.320 Caitlyn Vaughn: Literally to default.
344 00:26:17.320 ⇒ 00:26:21.380 Uttam Kumaran: No, I know, I know, you definitely have, so… No, we owe you.
345 00:26:21.380 ⇒ 00:26:21.930 Caitlyn Vaughn: Crap.
346 00:26:22.150 ⇒ 00:26:23.550 Uttam Kumaran: We’re, we’re, we’re…
347 00:26:23.690 ⇒ 00:26:39.609 Uttam Kumaran: now I have, like, a whole ecosystem now of, like, go-to-market tools, like, when I talk… I talk about you guys, Clay, NADN, like, we sort of talk about go-to-market engineering, like, the stack, and we have some one-pagers with you guys, and all those tools in it. It’s, like, what we recommend for
348 00:26:39.730 ⇒ 00:26:45.269 Uttam Kumaran: And the pitch is really clean, like, hey, if you’re doing a lot of inbound volume, you need these guys, and they’re gonna compete.
349 00:26:45.390 ⇒ 00:26:47.409 Uttam Kumaran: On any price lever, so… yeah.
350 00:26:47.410 ⇒ 00:26:49.650 Caitlyn Vaughn: Guess who our newest customer is?
351 00:26:50.490 ⇒ 00:26:53.380 Uttam Kumaran: Oh, you gotta… well, dude, that’s… you gotta give me, like, a hint. Or, like, give me a…
352 00:26:53.380 ⇒ 00:26:54.460 Caitlyn Vaughn: Another name.
353 00:26:54.710 ⇒ 00:26:55.600 Uttam Kumaran: play?
354 00:26:55.600 ⇒ 00:26:56.489 Caitlyn Vaughn: No, no, no.
355 00:26:56.490 ⇒ 00:26:57.420 Uttam Kumaran: NHN?
356 00:26:58.200 ⇒ 00:27:01.839 Uttam Kumaran: No way. How did that happen?
357 00:27:02.020 ⇒ 00:27:04.909 Caitlyn Vaughn: They… they need help with inbound. Their tool does not…
358 00:27:04.910 ⇒ 00:27:05.800 Uttam Kumaran: Whoa.
359 00:27:05.800 ⇒ 00:27:06.990 Caitlyn Vaughn: I’m telling you.
360 00:27:07.710 ⇒ 00:27:09.929 Uttam Kumaran: You guys, you know HayReach?
361 00:27:10.840 ⇒ 00:27:12.310 Caitlyn Vaughn: Yeah, a customer.
362 00:27:12.310 ⇒ 00:27:19.780 Uttam Kumaran: Okay, great, cool. Well, oh, okay, well, we pitched them on, data work, because… oh, because they had a post, I’ll show you this.
363 00:27:19.780 ⇒ 00:27:20.750 Caitlyn Vaughn: And it was like…
364 00:27:21.020 ⇒ 00:27:23.830 Uttam Kumaran: I literally was like, dude, we need to help you guys.
365 00:27:23.830 ⇒ 00:27:26.859 Caitlyn Vaughn: Wait, make sure they are. Hey, Reach, that sounds so familiar.
366 00:27:26.860 ⇒ 00:27:29.140 Uttam Kumaran: They’re like a LinkedIn automation tool.
367 00:27:29.140 ⇒ 00:27:29.780 Caitlyn Vaughn: Hold on.
368 00:27:29.780 ⇒ 00:27:32.309 Uttam Kumaran: So we use them for all of our LinkedIn outbound.
369 00:27:34.250 ⇒ 00:27:36.880 Caitlyn Vaughn: Okay, wait, no they’re not. I was thinking of Hey Jen.
370 00:27:37.650 ⇒ 00:27:39.910 Uttam Kumaran: Oh, okay. Yeah, so let me,
371 00:27:40.140 ⇒ 00:27:43.989 Uttam Kumaran: we… they… their CEO of HeyReach put out, like, a,
372 00:27:44.280 ⇒ 00:27:47.579 Uttam Kumaran: A pitch, like, hey, all of our data is shit, and we need help.
373 00:27:47.830 ⇒ 00:27:52.549 Caitlyn Vaughn: can anyone, like, help us with this? We don’t want tools, we want an agency, and I was like.
374 00:27:53.240 ⇒ 00:28:04.000 Uttam Kumaran: I am that person, like, we can help you with this. Smiley face. I was like, please, and then, hold on, let me show you, because it was very funny. Where’s this guy? Yeah, Nick.
375 00:28:04.550 ⇒ 00:28:12.810 Uttam Kumaran: And then I was like, we are the exact people that you need for this. But, of course, when you post anything like this on LinkedIn, you’re just gonna get a ton of…
376 00:28:13.190 ⇒ 00:28:19.040 Uttam Kumaran: People posting, but basically, he posted this thing, like,
377 00:28:20.610 ⇒ 00:28:25.710 Uttam Kumaran: it was like the… it’s, like, honestly kind of, like, similar to where we find a lot of companies, where it’s like, hey, we are PLG-led.
378 00:28:25.860 ⇒ 00:28:27.830 Uttam Kumaran: 8.2 ARR company.
379 00:28:28.030 ⇒ 00:28:33.449 Uttam Kumaran: We don’t know what percentage comes from users with 3 seats or 50 seats, we have no centralized place.
380 00:28:33.660 ⇒ 00:28:37.059 Uttam Kumaran: Need a data warehouse. Here’s our tech stack.
381 00:28:37.550 ⇒ 00:28:41.539 Uttam Kumaran: I don’t want… I want an agency that has already done this.
382 00:28:41.970 ⇒ 00:28:48.530 Uttam Kumaran: I don’t want a powered by AI BI tool, or, like, a random consultant, or a freelancer.
383 00:28:48.730 ⇒ 00:28:51.899 Uttam Kumaran: I was like… Dude, take it!
384 00:28:52.010 ⇒ 00:29:07.440 Uttam Kumaran: I literally… that’s what I sent. I said, this is so, so, so up our wheelhouse. I just emailed. We are not a crappy Python wrapper tool built by SoloDev, we are an agency. And then I sent it to my company, I said, everybody, please like my message.
385 00:29:07.440 ⇒ 00:29:10.860 Caitlyn Vaughn: Hell yeah. Oh my gosh, 460 impressions?
386 00:29:11.460 ⇒ 00:29:12.619 Uttam Kumaran: Hey, not bad.
387 00:29:12.620 ⇒ 00:29:13.650 Caitlyn Vaughn: That’s awesome.
388 00:29:14.140 ⇒ 00:29:16.459 Uttam Kumaran: And we love Hey Reichu, they’re great, though.
389 00:29:16.460 ⇒ 00:29:19.410 Caitlyn Vaughn: Wait, I feel like Harach still sounds familiar, I’m looking…
390 00:29:19.410 ⇒ 00:29:24.979 Uttam Kumaran: I think, it’s… you may have heard it from, like, when you were doing stuff, like, it’s, like, instantly for LinkedIn DMs.
391 00:29:24.980 ⇒ 00:29:30.549 Caitlyn Vaughn: Oh wait, we did have a deal going with HeyReach in May. We closed-lost them.
392 00:29:31.410 ⇒ 00:29:32.990 Uttam Kumaran: They definitely need you.
393 00:29:33.480 ⇒ 00:29:38.009 Caitlyn Vaughn: Yeah, they do. Bring it back. If you get them as a client, bring it back.
394 00:29:38.010 ⇒ 00:29:41.720 Uttam Kumaran: Okay, I’ll make… okay, if I get him back as a client, I’ll get you in there.
395 00:29:41.720 ⇒ 00:29:48.459 Caitlyn Vaughn: Okay, okay, because here’s the other thing, is… so I brought in this woman, Eliza, right? Yeah. And Nico is like…
396 00:29:48.670 ⇒ 00:29:56.580 Caitlyn Vaughn: medium sold on it. I think he’s more sold in getting partnerships off my plate so I can go fully on product versus, like, actually hiring for this role.
397 00:29:56.580 ⇒ 00:29:57.280 Uttam Kumaran: Oh.
398 00:29:57.280 ⇒ 00:30:14.599 Caitlyn Vaughn: I made a deal with him. I was like, hey, we’re gonna hire her part-time for 3 months. If we can close 100k in new revenue, then we get to hire her full-time. And he was like, deal. I’m like, okay, so… we did, like, $300K in revenue from partnerships.
399 00:30:14.850 ⇒ 00:30:18.020 Caitlyn Vaughn: And then… I just kind of, like, dropped everything.
400 00:30:18.020 ⇒ 00:30:18.620 Uttam Kumaran: Yeah, yeah, yeah.
401 00:30:18.620 ⇒ 00:30:24.250 Caitlyn Vaughn: died, right? So I’m like, I need to pick this back up. We need to, like, we need to get this woman hired so that I can.
402 00:30:24.250 ⇒ 00:30:36.439 Uttam Kumaran: Yeah, I mean, dude, you should tell her that we’re a great, like, case study of a partner, where we’re sitting on probably a bunch of places we can sell you into, but like… and I already… we already work with you guys, but I was clearly, like.
403 00:30:36.730 ⇒ 00:30:41.690 Uttam Kumaran: our sales team is not thinking about… or thinking enough about you guys, right? So, in case we can help.
404 00:30:42.160 ⇒ 00:30:46.490 Uttam Kumaran: Yeah, but you guys have a lot of people on that channel, and people are excited about your tool, so…
405 00:30:46.670 ⇒ 00:30:53.349 Uttam Kumaran: I feel like she gave her some pretty clear OKRs to hit on, like, Either partner meetings.
406 00:30:53.710 ⇒ 00:31:00.380 Uttam Kumaran: We’re just establishing our entire partnership motion, too, like, because we have affiliate partners, referral, we have vendor partners.
407 00:31:00.550 ⇒ 00:31:01.000 Caitlyn Vaughn: Yeah.
408 00:31:01.000 ⇒ 00:31:03.190 Uttam Kumaran: Like, how do we co-market, co-sell with them?
409 00:31:03.190 ⇒ 00:31:06.670 Caitlyn Vaughn: Maybe she should meet with your sales team, then.
410 00:31:06.930 ⇒ 00:31:09.270 Uttam Kumaran: I mean, it’s me and, like, two other people, two or three other.
411 00:31:09.270 ⇒ 00:31:19.309 Caitlyn Vaughn: Yeah, no, that’s great. That’s super perfect, and we can, like, talk about strategies for selling, because it’s so hard. If somebody doesn’t know how to sell a tool, you’re, like, not going to sell it, right?
412 00:31:19.310 ⇒ 00:31:37.770 Uttam Kumaran: Well, that’s, yeah, that’s the thing. So we’re even finding out, like, for our partners, like, how do we go to them and share exactly what Brainforge does, how to speak about it, and then start talking about, are there any deals we can co-sell? Other stuff is, like, marketing activities, like, can we do a COPE? Can we post something, a blog together?
413 00:31:37.770 ⇒ 00:31:39.049 Caitlyn Vaughn: Yeah, we’ve done a bunch of stuff.
414 00:31:39.050 ⇒ 00:31:51.460 Uttam Kumaran: yeah, can we post, like, an interview? Can we do… we’ve done a webinar, but can we do a party in New York or in Austin? Like, that’s the stuff that we… like, on the agency side, I think we’re one of the rare tech agencies that can, like.
415 00:31:51.700 ⇒ 00:31:53.839 Uttam Kumaran: Have, like, has some marketing sense.
416 00:31:53.840 ⇒ 00:31:54.220 Caitlyn Vaughn: Yeah.
417 00:31:54.220 ⇒ 00:31:59.940 Uttam Kumaran: to just being, like, random engineers, you know? So for her job is to go find those folks like us.
418 00:32:00.090 ⇒ 00:32:03.590 Uttam Kumaran: And then you still have these partners who will, like, occasionally refer business, right?
419 00:32:03.590 ⇒ 00:32:04.520 Caitlyn Vaughn: Yeah.
420 00:32:04.520 ⇒ 00:32:07.980 Uttam Kumaran: But… Yeah.
421 00:32:07.980 ⇒ 00:32:12.070 Caitlyn Vaughn: That’s a good idea. We have a few partners that are, like, really good marketing partners, and then…
422 00:32:12.070 ⇒ 00:32:12.610 Uttam Kumaran: Great.
423 00:32:12.610 ⇒ 00:32:18.920 Caitlyn Vaughn: A few that are good. We probably have a dozen that are reoccurring, referring, and then…
424 00:32:19.090 ⇒ 00:32:21.710 Caitlyn Vaughn: The rest are… half are, like.
425 00:32:22.070 ⇒ 00:32:26.299 Caitlyn Vaughn: Chatty, but, like, not having any, and the other half are just, like, dead, you know?
426 00:32:26.300 ⇒ 00:32:42.160 Uttam Kumaran: Yeah, but for example, like, we would always talk about default alongside, like, a HubSpot, alongside a data warehouse, so when we talk about tools, like, just like Omni, I say, you need Omni, and you need Mother Duck, and then we also need a bunch of people and process. But I talk about a solution.
427 00:32:42.160 ⇒ 00:32:48.440 Uttam Kumaran: Whereas the vendor may just talk about… you may only be equipped or confident to talk about default.
428 00:32:48.440 ⇒ 00:32:48.820 Caitlyn Vaughn: Hmm.
429 00:32:48.820 ⇒ 00:32:55.709 Uttam Kumaran: And when I come in, I’m like, hey, inbound, you have inbound strategy, you have amplitude for product analytics, you have all these different things.
430 00:32:55.710 ⇒ 00:32:56.170 Caitlyn Vaughn: Hmm.
431 00:32:56.170 ⇒ 00:33:00.800 Uttam Kumaran: And, like, we just… we just, like, make those procurement decisions for a lot of vendors.
432 00:33:00.800 ⇒ 00:33:03.140 Caitlyn Vaughn: Wait, did I tell you we’re building clay?
433 00:33:03.470 ⇒ 00:33:04.380 Uttam Kumaran: Oh, really?
434 00:33:04.590 ⇒ 00:33:06.300 Caitlyn Vaughn: Yeah, it’s, like, almost done.
435 00:33:06.300 ⇒ 00:33:08.070 Uttam Kumaran: Like, the same thing, basically.
436 00:33:08.070 ⇒ 00:33:11.789 Caitlyn Vaughn: It’s just, like, one small part of our platform, but we, like, rebuilt Clay.
437 00:33:12.030 ⇒ 00:33:14.430 Uttam Kumaran: Like, a cell-based, like, workflow.
438 00:33:14.900 ⇒ 00:33:20.010 Caitlyn Vaughn: Yeah, so it’s, like, in a table format. Yeah. Let me show you.
439 00:33:20.570 ⇒ 00:33:25.080 Uttam Kumaran: Nice. I mean, you guys, that’s what you… I feel like if you at least support with Clay.
440 00:33:25.360 ⇒ 00:33:31.769 Uttam Kumaran: support with, like, most of the basic clay features, like, that’s all people need, and they could just get in your platform. There’s nothing, like…
441 00:33:31.960 ⇒ 00:33:37.099 Uttam Kumaran: unique about clay. In fact, I think they just have huge brand value.
442 00:33:37.800 ⇒ 00:33:41.089 Uttam Kumaran: But a lot of this stuff you can do in other platforms, so…
443 00:33:41.090 ⇒ 00:33:43.050 Caitlyn Vaughn: That’s dope.
444 00:33:43.050 ⇒ 00:33:45.110 Uttam Kumaran: You can just copy their UX because you know it’s working.
445 00:33:45.110 ⇒ 00:34:03.079 Caitlyn Vaughn: Yeah, exactly, and we kind of did to a degree, but it’s like, all of these solutions are really good point solutions, but then the problem is that you still have to connect it back to all your other tools, and it’s such a pain. Like, I built it, and Clay was the best tool for this, because of what you can do in Clay, but not for, like.
446 00:34:03.290 ⇒ 00:34:09.940 Caitlyn Vaughn: actually connecting it to everything else. So we, like, built the data layer, we’ve built Clay, we’re just gonna start building all of our competitors.
447 00:34:09.949 ⇒ 00:34:10.839 Uttam Kumaran: Yeah, great.
448 00:34:10.840 ⇒ 00:34:13.710 Caitlyn Vaughn: Yeah, and be, like, a super horizontal tool that already has.
449 00:34:13.719 ⇒ 00:34:14.119 Uttam Kumaran: Great.
450 00:34:14.120 ⇒ 00:34:15.170 Caitlyn Vaughn: are included.
451 00:34:15.370 ⇒ 00:34:20.829 Uttam Kumaran: Yeah, and dude, you own the forms, like, that’s the biggest thing I tell people, is like, you guys own the first touchpoint with the customer, so…
452 00:34:20.830 ⇒ 00:34:21.560 Caitlyn Vaughn: God.
453 00:34:21.560 ⇒ 00:34:25.320 Uttam Kumaran: It’s great. Like, you’re… you should almost… you’re… you’re, like, almost competing with, like, HubSpot.
454 00:34:25.810 ⇒ 00:34:36.880 Uttam Kumaran: forms in a lot of ways, because they’re trying to push, hey, run all of your inbound through HubSpot, right? But their forms are crappy, and then, yeah, the HubSpot platform is really hard to work with.
455 00:34:36.880 ⇒ 00:34:37.670 Caitlyn Vaughn: That is.
456 00:34:37.670 ⇒ 00:34:38.290 Uttam Kumaran: Yeah.
457 00:34:38.760 ⇒ 00:34:41.519 Caitlyn Vaughn: Yeah, we’re like HubSpot built in the century.
458 00:34:41.520 ⇒ 00:34:50.620 Uttam Kumaran: Yes, yes. Yeah, we’re… HubSpot is so annoying, but I don’t have another… I didn’t want to use Atio. I heard some, like, mixed reviews.
459 00:34:50.620 ⇒ 00:34:51.400 Caitlyn Vaughn: I’m gonna.
460 00:34:51.409 ⇒ 00:34:54.379 Uttam Kumaran: So I was like, fuck it, we’ll just use HubSpot for everything.
461 00:34:54.380 ⇒ 00:34:56.499 Caitlyn Vaughn: Yeah, HubSpot is the best out of the three.
462 00:34:56.500 ⇒ 00:34:59.090 Uttam Kumaran: We’re gonna do all of our partnerships in there as well.
463 00:34:59.090 ⇒ 00:35:00.750 Caitlyn Vaughn: Hmm. In where?
464 00:35:00.750 ⇒ 00:35:05.470 Uttam Kumaran: in HubSpot. But we’re gonna create, like, custom objects for different partnerships.
465 00:35:05.470 ⇒ 00:35:09.410 Caitlyn Vaughn: Track partner-led revenue, and just try to have everything in there.
466 00:35:09.580 ⇒ 00:35:14.970 Uttam Kumaran: Versus, like, doing it in a spreadsheet, like, or, like, getting a partner
467 00:35:15.940 ⇒ 00:35:24.470 Uttam Kumaran: I mean, for you guys, I think partner most. For us, we only have, like, maybe 5. We’ll only have 5, 10, 15 partners that are worth talk… that are, like, we’re tracking.
468 00:35:24.470 ⇒ 00:35:26.480 Caitlyn Vaughn: Versus, like, hundreds and hundreds.
469 00:35:26.630 ⇒ 00:35:29.829 Uttam Kumaran: Right, so… Yeah. For us, I’m like, let’s just put everything there.
470 00:35:30.020 ⇒ 00:35:35.060 Caitlyn Vaughn: Yeah, that’s good. Honestly, I think having less partners and higher quality is better.
471 00:35:35.060 ⇒ 00:35:38.619 Uttam Kumaran: Yeah, so we’re, like, kind of… because everybody likes to talk about
472 00:35:39.250 ⇒ 00:35:41.580 Uttam Kumaran: Selling business or doing whatever, but…
473 00:35:41.580 ⇒ 00:35:42.240 Caitlyn Vaughn: Hmm?
474 00:35:42.330 ⇒ 00:35:46.499 Uttam Kumaran: But you also have to find out, like, did we mess up? Did we not equip people?
475 00:35:46.690 ⇒ 00:35:50.059 Uttam Kumaran: With what to talk about, or is it actually that they’re just, like.
476 00:35:50.200 ⇒ 00:35:53.000 Uttam Kumaran: Nobody, you know, they just signed up for the partner network.
477 00:35:53.120 ⇒ 00:35:54.320 Caitlyn Vaughn: Yeah, totally.
478 00:35:54.320 ⇒ 00:35:55.050 Uttam Kumaran: Yeah.
479 00:35:55.050 ⇒ 00:35:57.729 Caitlyn Vaughn: Oh my god, the spacing on this message is so bad.
480 00:35:57.910 ⇒ 00:35:59.130 Caitlyn Vaughn: Goddammit.
481 00:36:03.990 ⇒ 00:36:07.139 Uttam Kumaran: Alright, cool, so I’ll follow up on these things, and then…
482 00:36:07.140 ⇒ 00:36:07.780 Caitlyn Vaughn: Oh, yeah.
483 00:36:07.780 ⇒ 00:36:08.860 Uttam Kumaran: Gotta get something.
484 00:36:09.310 ⇒ 00:36:11.579 Uttam Kumaran: I’ll try to get something to you tomorrow to take a look at.
485 00:36:11.760 ⇒ 00:36:13.309 Caitlyn Vaughn: Oh, that sounds great.
486 00:36:13.490 ⇒ 00:36:14.160 Uttam Kumaran: Okay.
487 00:36:14.930 ⇒ 00:36:15.530 Caitlyn Vaughn: Okay!
488 00:36:15.650 ⇒ 00:36:17.120 Uttam Kumaran: Alright, enjoy.
489 00:36:17.120 ⇒ 00:36:17.580 Caitlyn Vaughn: Bye.
490 00:36:17.580 ⇒ 00:36:18.360 Uttam Kumaran: Bye.