Meeting Title: Uttam-Kumaran’s-Personal-Meeting-Room Date: 2024-11-08 Meeting participants: Roy, Nicolas Sucari, Ryan Brosas, Casie Aviles, Luke Daque, Uttam Kumaran, Miguel
WEBVTT
1 00:00:26.360 ⇒ 00:00:28.389 Miguel: Oh, I thought, it’s just us again.
2 00:00:29.400 ⇒ 00:00:31.480 Uttam Kumaran: No, I was. I’m the one that’s late.
3 00:00:35.490 ⇒ 00:00:36.290 Miguel: Hey, guys.
4 00:00:36.700 ⇒ 00:00:37.570 Uttam Kumaran: Hey, everyone.
5 00:00:38.110 ⇒ 00:00:40.690 Luke Daque: Hello! Hello! Congratulations!
6 00:00:40.690 ⇒ 00:00:41.160 Miguel: Doing, good.
7 00:00:41.160 ⇒ 00:00:41.740 Luke Daque: So
8 00:00:42.330 ⇒ 00:00:43.369 Luke Daque: guys congrats.
9 00:00:43.370 ⇒ 00:00:45.992 Uttam Kumaran: In the car. Everyone’s coming, I guess.
10 00:00:46.980 ⇒ 00:00:47.940 Luke Daque: Yeah.
11 00:00:48.130 ⇒ 00:00:49.640 Miguel: I got the black color.
12 00:00:49.980 ⇒ 00:00:56.257 Uttam Kumaran: I’m the only one that shared my picture, though everybody’s gotta be driving something, even if you’re driving a scooter, I wanna see.
13 00:00:56.570 ⇒ 00:00:57.819 Uttam Kumaran: or a bike.
14 00:00:58.500 ⇒ 00:01:00.379 Luke Daque: I don’t have a picture of my car.
15 00:01:00.620 ⇒ 00:01:05.877 Miguel: I could send the picture, but that was very short. So it’s like my legs are there? I’ll take again.
16 00:01:10.380 ⇒ 00:01:13.169 Miguel: I was supposed to get the Miata, Luke.
17 00:01:13.190 ⇒ 00:01:15.320 Miguel: But then, when I sat there
18 00:01:15.430 ⇒ 00:01:22.010 Miguel: like, Wait, let me show you like my body was basically like this, because I’m 6 foot one, right, and then I had to
19 00:01:22.030 ⇒ 00:01:24.170 Miguel: to go like that like I can’t fit you.
20 00:01:24.670 ⇒ 00:01:26.530 Uttam Kumaran: Are you? 6? 1, Miguel.
21 00:01:26.740 ⇒ 00:01:27.610 Miguel: Yeah, yeah.
22 00:01:28.050 ⇒ 00:01:31.499 Uttam Kumaran: No way dude. You don’t seem that tall sitting down.
23 00:01:31.800 ⇒ 00:01:34.610 Miguel: No, because the cover is like all the way there.
24 00:01:35.310 ⇒ 00:01:36.539 Uttam Kumaran: I’m 6. 1.
25 00:01:36.850 ⇒ 00:01:37.690 Miguel: Oh, really.
26 00:01:38.300 ⇒ 00:01:39.190 Uttam Kumaran: Yeah.
27 00:01:41.440 ⇒ 00:01:42.380 Uttam Kumaran: I don’t know. I mean.
28 00:01:42.380 ⇒ 00:01:42.790 Luke Daque: Just go.
29 00:01:42.790 ⇒ 00:01:45.345 Uttam Kumaran: That sound disrespectful. I thought you were way shorter.
30 00:01:46.745 ⇒ 00:01:46.990 Miguel: No.
31 00:01:47.440 ⇒ 00:01:53.749 Uttam Kumaran: That’s great. Okay, cool. But yeah, you do have the camera like, you’re like.
32 00:01:53.750 ⇒ 00:01:55.469 Miguel: Yeah, yeah, I’m always like here.
33 00:01:57.030 ⇒ 00:02:03.209 Miguel: because my eyes are kind of messed up. You know my, like, I think this eye is like 3, 50. This eye is like 400 or something.
34 00:02:03.640 ⇒ 00:02:04.390 Luke Daque: Wow!
35 00:02:04.690 ⇒ 00:02:05.519 Miguel: That’s kind of messed up.
36 00:02:06.163 ⇒ 00:02:07.449 Uttam Kumaran: Wow. Okay.
37 00:02:12.190 ⇒ 00:02:19.110 Luke Daque: I have to have my eyes checked as well like my right eye. There’s like a spot in the middle that’s like blurry
38 00:02:19.610 ⇒ 00:02:20.720 Luke Daque: dude that’s.
39 00:02:20.720 ⇒ 00:02:22.839 Uttam Kumaran: Maybe glaucoma. You gotta get checked.
40 00:02:22.840 ⇒ 00:02:24.210 Miguel: Yeah. You got it checked.
41 00:02:24.400 ⇒ 00:02:24.935 Luke Daque: Yeah.
42 00:02:26.180 ⇒ 00:02:28.269 Miguel: Like one of my uncles, is blind
43 00:02:28.520 ⇒ 00:02:29.399 Miguel: because of that.
44 00:02:30.936 ⇒ 00:02:31.930 Nicolas Sucari: I mean.
45 00:02:31.930 ⇒ 00:02:33.800 Miguel: Losing his vision, slowly.
46 00:02:33.800 ⇒ 00:02:36.169 Nicolas Sucari: You. You can’t scare Ryan like that.
47 00:02:36.170 ⇒ 00:02:36.710 Miguel: It’s a.
48 00:02:37.730 ⇒ 00:02:40.030 Uttam Kumaran: I don’t know. Look, I
49 00:02:40.260 ⇒ 00:02:45.419 Uttam Kumaran: I think you got it. I think I I also have eye problems and support.
50 00:02:46.056 ⇒ 00:02:46.693 Miguel: Check.
51 00:02:47.330 ⇒ 00:02:48.550 Uttam Kumaran: Important.
52 00:02:51.460 ⇒ 00:02:52.029 Miguel: I think that’s it.
53 00:02:52.030 ⇒ 00:02:52.910 Luke Daque: Yeah.
54 00:02:55.000 ⇒ 00:02:56.066 Uttam Kumaran: Okay, cool.
55 00:02:57.340 ⇒ 00:03:11.230 Uttam Kumaran: I guess I wanted to. Yeah, talk about a couple of things. One, you know. I think we had a really great design meeting. I think everybody here, except for Casey, was was part of that. So that was really great. We had a lot of amazing ideas, I think.
56 00:03:11.564 ⇒ 00:03:25.505 Uttam Kumaran: Most importantly, a couple of things. One, we’re gonna be adding more AI chat, bots and stuff to the site. So that should be really awesome. I think you know, Miguel, you and Casey will probably lead that. I think second thing is
57 00:03:26.630 ⇒ 00:03:28.169 Uttam Kumaran: I actually
58 00:03:28.320 ⇒ 00:03:31.659 Uttam Kumaran: would love to demo the N. 8 n.
59 00:03:32.519 ⇒ 00:03:33.349 Uttam Kumaran: Stella
60 00:03:34.540 ⇒ 00:03:35.100 Miguel: Source.
61 00:03:35.100 ⇒ 00:03:39.920 Uttam Kumaran: Thing, so let me pull that up on my end. I know I I sent the wrong link, but I also don’t know.
62 00:03:41.310 ⇒ 00:03:50.420 Uttam Kumaran: I don’t know where to go to get the right link. I couldn’t find it. But someone will have to show me, because I just sent literally the invite to but this is like
63 00:03:50.550 ⇒ 00:03:59.759 Uttam Kumaran: the sales Hubspot help for Sella source. And actually let me. I want to just pull up and let me get let me walk through it if I can, and then correct me where I’m wrong.
64 00:04:02.150 ⇒ 00:04:04.640 Uttam Kumaran: because I’m not gonna get every single thing right.
65 00:04:08.180 ⇒ 00:04:24.459 Uttam Kumaran: But I wanna share with everybody this because we’re gonna you’re gonna start to see these appear in our slack and it should be really, really in interesting to start to, you know, have AI integrated there, and being able to chat over, you know the work that we’ve done. So this is you know our.
66 00:04:24.510 ⇒ 00:04:36.264 Uttam Kumaran: and then workflow for this chat. Bot and to walk through what the process is. We have this Google drive folder. I think if I go to
67 00:04:39.100 ⇒ 00:04:40.790 Uttam Kumaran: if I go to Stella.
68 00:04:46.400 ⇒ 00:04:48.409 Uttam Kumaran: Is there a folder.
69 00:04:49.921 ⇒ 00:04:51.610 Casie Aviles: I might not have shared it.
70 00:04:52.370 ⇒ 00:04:56.112 Uttam Kumaran: Okay, do you want to share with me? Really quickly? I just show everybody.
71 00:04:57.080 ⇒ 00:04:58.359 Casie Aviles: Yeah, yeah, sure. Sure.
72 00:05:02.420 ⇒ 00:05:04.930 Uttam Kumaran: So basically, we have a folder of documents.
73 00:05:05.356 ⇒ 00:05:22.427 Uttam Kumaran: We basically look for if a file is created or file is updated in that folder. We basically set a file id update super base, which actually holds our like vector, information. And then what we do is
74 00:05:23.440 ⇒ 00:05:30.199 Uttam Kumaran: we download. We take that file, extract it, insert it, and then basically create embeddings out of it.
75 00:05:30.551 ⇒ 00:05:33.628 Uttam Kumaran: I think the thing we’ll probably work on is
76 00:05:34.260 ⇒ 00:05:39.839 Uttam Kumaran: modifying, like the text, splitter and modifying some of the ways depending on what kind of text it is.
77 00:05:41.250 ⇒ 00:05:44.734 Uttam Kumaran: but basically, we’re then able to take those
78 00:05:45.200 ⇒ 00:05:55.200 Uttam Kumaran: all those documents. Use the embeddings and then build a rag agent on top of it, which is what this is. Here. I’ll just show soon as like you share that with me.
79 00:05:55.410 ⇒ 00:05:57.699 Uttam Kumaran: Miguel. I can just show
80 00:05:58.000 ⇒ 00:06:00.034 Uttam Kumaran: I mean, Casey. I can just show you that
81 00:06:04.560 ⇒ 00:06:08.150 Casie Aviles: But yeah, I sent it over to the chat.
82 00:06:09.080 ⇒ 00:06:09.844 Uttam Kumaran: Oh, great. Okay.
83 00:06:16.520 ⇒ 00:06:17.290 Uttam Kumaran: cool.
84 00:06:18.180 ⇒ 00:06:25.281 Uttam Kumaran: So this is a rag folder for Sella and you have a couple of different document types here. Oh, it’s gonna open.
85 00:06:27.063 ⇒ 00:06:30.530 Uttam Kumaran: We have the web script info about Stella
86 00:06:31.017 ⇒ 00:06:36.902 Uttam Kumaran: we also did a we also did a couple of other things. I asked.
87 00:06:37.750 ⇒ 00:07:04.520 Uttam Kumaran: I asked Casey to get our entire repo. So this is. This is all of the files in the repository, and literally all of the different things. Just looking at this. Now. We can probably filter out a couple of different folders like we probably don’t need all of it, but I think this is a really good test. This has all our logic for the work that we’ve done for Stella. All the SQL logic. Basically, the next thing is, we actually have all of our
88 00:07:05.295 ⇒ 00:07:06.990 Uttam Kumaran: is this the?
89 00:07:08.160 ⇒ 00:07:10.373 Uttam Kumaran: Oh, this is like, okay, this is the
90 00:07:12.080 ⇒ 00:07:14.330 Uttam Kumaran: This is the case. Studies that we wrote.
91 00:07:14.743 ⇒ 00:07:20.490 Uttam Kumaran: oh, this is the notion, and then this is the actual slack. So we also
92 00:07:21.430 ⇒ 00:07:30.480 Uttam Kumaran: oh, this isn’t everything yet. But we we exported our entire slack channel with all of the conversations that we’ve had about the client
93 00:07:30.906 ⇒ 00:07:34.603 Uttam Kumaran: into a text file as well. And then I think we’re
94 00:07:35.140 ⇒ 00:07:51.819 Uttam Kumaran: working on. Or this may be the Csv with everything. So then we’re working on basically, how do we get all the data? So basically, the goal is like, can we get all of the Github, the notion, the emails, and the slack. And then eventually we’ll also bring in the zoom transcripts
95 00:07:51.840 ⇒ 00:08:12.519 Uttam Kumaran: so that everything we’ve done for this person or this client is in one place. So then you should be easily be able to go to the chat box and say, like, explain to me what we did in Dbt. For Stella, and I don’t know. I don’t know if this is gonna work or not. It’s probably for Casey to figure it out.
96 00:08:12.520 ⇒ 00:08:13.770 Casie Aviles: Yeah, yeah.
97 00:08:14.409 ⇒ 00:08:15.689 Uttam Kumaran: But ideally.
98 00:08:15.880 ⇒ 00:08:29.229 Uttam Kumaran: when when people people want to ask, what do we do for them? What could we have done even for active clients. I want all the data loaded here. And so this should happen on a live process. So it looks like it got close. It’s like
99 00:08:29.410 ⇒ 00:08:35.520 Uttam Kumaran: we use. This is their key updates to the data build tool set up. So tell me about
100 00:08:38.360 ⇒ 00:08:40.370 Uttam Kumaran: they’re quoting
101 00:08:40.770 ⇒ 00:08:44.049 Uttam Kumaran: data model. Let’s see what it says.
102 00:08:44.070 ⇒ 00:08:46.760 Uttam Kumaran: So it’s not bad. I mean, it’s getting close.
103 00:08:46.820 ⇒ 00:08:55.520 Uttam Kumaran: We will have to chunk Github differently than we chunk other stuff. And yeah, I think it’s, you know. Probably we just need to get better a little bit of metadata. But
104 00:08:55.610 ⇒ 00:08:59.230 Uttam Kumaran: we’re gonna set what we’re gonna set these up basically for every single client.
105 00:09:00.058 ⇒ 00:09:02.350 Uttam Kumaran: And probably honestly, we can.
106 00:09:04.090 ⇒ 00:09:15.059 Uttam Kumaran: I mean I. And I guess this for Miguel and Casey. Do we need to create one of these workflows for every client? Or can we like wrap this in a workflow? And then you just plug in the right Google drive. And then
107 00:09:15.190 ⇒ 00:09:17.470 Uttam Kumaran: you plug in the right, like
108 00:09:17.550 ⇒ 00:09:20.026 Uttam Kumaran: front facing thing right. The chat interface.
109 00:09:20.662 ⇒ 00:09:30.849 Miguel: There’s a way to do it, but it’s I haven’t really explored it. Because if you look at the for example, if you open the anything there. There’s like, yeah, that one try to open that
110 00:09:31.100 ⇒ 00:09:37.969 Miguel: you can instead of like in the folder. There’s like a choice to do expression, instead of like path.
111 00:09:39.320 ⇒ 00:09:41.580 Uttam Kumaran: Oh, yeah, yeah. So then we have it all dynamically. Yeah.
112 00:09:41.580 ⇒ 00:09:43.340 Miguel: Yeah, yeah, we could have that dynamic.
113 00:09:43.340 ⇒ 00:09:47.769 Uttam Kumaran: Yeah, yeah, cause this is all gonna be the same. Basically.
114 00:09:48.030 ⇒ 00:09:48.780 Miguel: Yeah, yeah.
115 00:09:48.780 ⇒ 00:09:54.579 Uttam Kumaran: And it’s like, forget. For example, if we improve the way we do chunking, I don’t wanna have to go do that 5 different times.
116 00:09:54.920 ⇒ 00:10:09.540 Miguel: Yeah, actually, what could be improved here, like from an initial point of view, is, I tried doing it, but you know, I got it got a bit lost, is it’s using the smaller text embedding if you open like the embedding tab under super base.
117 00:10:09.910 ⇒ 00:10:12.250 Miguel: the one above the green one. Yeah, yeah.
118 00:10:12.740 ⇒ 00:10:14.359 Miguel: The embedding one below that.
119 00:10:16.150 ⇒ 00:10:19.509 Miguel: The open? Yeah, that one. It’s using the small one, I believe.
120 00:10:20.700 ⇒ 00:10:31.839 Miguel: Text embedding. Ada, yeah, if we could use large, but if you use large, it kind of fails everything because it’s some data mismatch. So I wanted to explore that. But you know we had too much stuff to worry about.
121 00:10:32.050 ⇒ 00:10:45.120 Uttam Kumaran: Yeah. So I think we have a couple of things. One, I, we wanna, we wanna have probably different flows based on different data types or different source data. Right? Like we should be chunking slack differently than we chunk Github differently than we chunk
122 00:10:45.370 ⇒ 00:10:46.560 Uttam Kumaran: documents.
123 00:10:47.298 ⇒ 00:10:58.279 Uttam Kumaran: I also want to get all of our Zoom Meetings into here. So that’s something else we’ll have to work on. The last thing is, yeah, I want to have like we want to have good evals.
124 00:10:58.400 ⇒ 00:11:03.930 Uttam Kumaran: So we can start building in evaluations so that we know how accurate we are. Basically
125 00:11:05.590 ⇒ 00:11:07.050 Uttam Kumaran: but it’s getting closer.
126 00:11:08.400 ⇒ 00:11:23.489 Uttam Kumaran: so this should be a huge save, and I would say, for the content folks and design folks to learn about the stuff we’ve done when we’re working on active project. If we want to think about ways to upsell things like that, or even just like again, how do we improve what we’re doing? I think this is gonna be really awesome.
127 00:11:23.823 ⇒ 00:11:27.269 Uttam Kumaran: I will tell you that there’s a lot of companies like
128 00:11:27.630 ⇒ 00:11:30.700 Uttam Kumaran: glean that are selling this for like
129 00:11:30.940 ⇒ 00:11:32.860 Uttam Kumaran: tens of thousands of dollars.
130 00:11:32.900 ⇒ 00:11:34.980 Uttam Kumaran: And it’s really this simple.
131 00:11:35.010 ⇒ 00:11:41.550 Uttam Kumaran: And so the lovely thing is, once we even get this to like a decent level, we’re gonna start to advertise this and share that. This is something we could do.
132 00:11:41.910 ⇒ 00:11:44.009 Uttam Kumaran: So super super excited
133 00:11:44.630 ⇒ 00:11:45.780 Uttam Kumaran: about this.
134 00:11:46.767 ⇒ 00:11:54.632 Uttam Kumaran: The other thing I wanted to share is the stuff Miguel has been working on for a client called Hpi. Hpi is a
135 00:11:54.990 ⇒ 00:11:59.239 Uttam Kumaran: is a commercial real estate company based here in Austin.
136 00:11:59.894 ⇒ 00:12:06.039 Uttam Kumaran: Called. Yeah. This is Hpi. Tx. They’re the number one commercial real estate owner in Austin.
137 00:12:07.031 ⇒ 00:12:09.559 Uttam Kumaran: They own pretty massive
138 00:12:10.620 ⇒ 00:12:11.480 Uttam Kumaran: buildings
139 00:12:11.570 ⇒ 00:12:14.110 Uttam Kumaran: like, let’s see, I’ll show you a couple
140 00:12:14.630 ⇒ 00:12:17.029 Uttam Kumaran: yeah, like 3 0, 1 Congress.
141 00:12:18.970 ⇒ 00:12:21.060 Uttam Kumaran: they literally own this whole building.
142 00:12:21.360 ⇒ 00:12:22.370 Uttam Kumaran: It’s
143 00:12:23.280 ⇒ 00:12:26.160 Uttam Kumaran: yeah. It’s it’s like, right here. I live like.
144 00:12:26.710 ⇒ 00:12:28.200 Uttam Kumaran: I live like over here.
145 00:12:29.670 ⇒ 00:12:40.579 Uttam Kumaran: But it’s huge, like they own, like giant Class A, and they’re they’re they’re immediately doing like selling these to tenants. For example, attendant can go in here and say, cool, I want to go look at
146 00:12:40.680 ⇒ 00:12:41.950 Uttam Kumaran: the space
147 00:12:44.130 ⇒ 00:12:56.560 Uttam Kumaran: they’re able to get this thing and say, Okay, cool, like, for example, if I was like, I want Brain Forge to have a space. Tell me what options you have 20,000 square feet, you know. And so you can expect, typically like anywhere from like
148 00:12:56.900 ⇒ 00:13:00.050 Uttam Kumaran: 10 to $30 per square feet
149 00:13:00.717 ⇒ 00:13:05.159 Uttam Kumaran: for monthly rent. And to give you a sense of like what that is.
150 00:13:05.210 ⇒ 00:13:10.432 Uttam Kumaran: let’s say it’s let’s say we, it’s 20. Let’s say it’s a $30 per square feet.
151 00:13:11.970 ⇒ 00:13:14.239 Uttam Kumaran: It’s like 600 KA month.
152 00:13:16.300 ⇒ 00:13:20.330 Uttam Kumaran: you know, to to to like rent this entire floor.
153 00:13:20.350 ⇒ 00:13:46.107 Uttam Kumaran: So it’s very, very expensive properties. What we did for them is basically they. They have like a lease negotiation process. So they have standards that they use to basically measure to that. They want to go with clients. And when tenants come in like a brain forge is leasing space, I would say, we can’t do that. But can you add more parking spots? Can you change the the red pricing things like that? And so they wanted a process to help them basically figure out,
154 00:13:46.610 ⇒ 00:13:49.049 Uttam Kumaran: figure out how they could improve
155 00:13:49.343 ⇒ 00:14:08.079 Uttam Kumaran: their terms and understand whether a proposal from a tenant is valid or not. So that’s kind of what we built and what we’ll be demoing for them on Monday. Is this app? And again, this is all stuff. We just built in a few weeks. That takes in their lease agreements. And we have like that in a Google drive.
156 00:14:08.080 ⇒ 00:14:20.639 Uttam Kumaran: We can then chat with those agreements. And this is what I’ll be demoing to their to their CEO and their coo on Monday. So we’ll be making a little bit of improvements of this, probably over the weekend, but really really excited.
157 00:14:21.055 ⇒ 00:14:23.644 Uttam Kumaran: You know, this is our full end to end. Demo that
158 00:14:23.960 ⇒ 00:14:34.980 Uttam Kumaran: you know, Miguel led. And we’ve done a lot of stuff in react and express for the back end with Mongo. And it’s amazing. I think, regardless of how this project ends up.
159 00:14:35.010 ⇒ 00:14:46.090 Uttam Kumaran: We’re gonna turn this into some. We’re gonna turn this some materials and start advertising this to real estate companies. And this is super super powerful. And going back to our design meeting this week.
160 00:14:46.200 ⇒ 00:14:51.250 Uttam Kumaran: we’re we’re gonna put this up on the site for sure, with some fake data and basically have people.
161 00:14:51.622 ⇒ 00:14:56.130 Uttam Kumaran: be able to test this on their own, which I’m super super excited about.
162 00:14:58.170 ⇒ 00:15:00.514 Uttam Kumaran: So that’s on the
163 00:15:01.630 ⇒ 00:15:05.329 Uttam Kumaran: AI side. Anything on the data side?
164 00:15:06.760 ⇒ 00:15:10.659 Uttam Kumaran: Luke, we want to share about anything we accomplish
165 00:15:10.890 ⇒ 00:15:14.139 Uttam Kumaran: this week. I don’t know. It’s probably mostly client stuff, right?
166 00:15:14.140 ⇒ 00:15:22.869 Luke Daque: Yeah, I guess nothing much for Brainforge. But more on like the Javi coffee stuff or refunds. That was like a
167 00:15:24.090 ⇒ 00:15:26.310 Luke Daque: a tricky one to to get.
168 00:15:26.670 ⇒ 00:15:27.940 Luke Daque: yeah, yeah.
169 00:15:30.500 ⇒ 00:15:30.950 Uttam Kumaran: Possible?
170 00:15:30.950 ⇒ 00:15:31.530 Nicolas Sucari: And maybe.
171 00:15:32.050 ⇒ 00:15:32.710 Uttam Kumaran: Yeah. Go ahead.
172 00:15:32.710 ⇒ 00:15:35.930 Nicolas Sucari: Sorry just just to share uttan we are working with
173 00:15:36.298 ⇒ 00:15:49.570 Nicolas Sucari: like, closely with Fivetran and new connectors that we haven’t worked with that on all parts before with Javi, they want to ingest new data sources. So we’re like fixing issues and adding more connectors every
174 00:15:49.660 ⇒ 00:16:10.680 Nicolas Sucari: like, yeah, every week. So yeah, maybe we’re like looking into getting more and more data in. And that is helping us understand different connectors, different issues, different ways of addressing problems. And how we’re gonna be finding solutions and maybe working on other modeling stuff.
175 00:16:11.105 ⇒ 00:16:17.940 Nicolas Sucari: And finally, we’ll get to better dashboards and better insights for the client. That’s what we are working on right now.
176 00:16:23.470 ⇒ 00:16:33.230 Uttam Kumaran: Yeah, I’m we’ve been. We made a lot of progress. We’re balancing pool parts, them. We’re also started working with Stella again. I think on the pool part side, we’re gonna have to figure out
177 00:16:33.420 ⇒ 00:16:44.189 Uttam Kumaran: some more stuff. I don’t know. Even this week there hasn’t been any work. So we’re gonna have to think about what the you know process for that client is. I’m gonna retry to reach out to Ben again, and we haven’t heard back from there.
178 00:16:44.520 ⇒ 00:16:46.520 Uttam Kumaran: their team, Ian on.
179 00:16:46.610 ⇒ 00:16:47.576 Uttam Kumaran: you know.
180 00:16:48.640 ⇒ 00:17:00.259 Nicolas Sucari: Yeah, it’s been. It’s been. It’s been tough to get work from them. They are not being communicative, they are, don’t. They’re not joining the meetings anymore. So yeah, maybe we need like specific stuff that we can
181 00:17:00.390 ⇒ 00:17:05.140 Nicolas Sucari: start building for them so that we can get them back on track again.
182 00:17:05.849 ⇒ 00:17:06.369 Uttam Kumaran: Yeah.
183 00:17:06.369 ⇒ 00:17:15.019 Luke Daque: Yeah, maybe the last I think, what they were interested in is is the automation piece right? Like, based on the last conversation. So maybe we can like
184 00:17:15.699 ⇒ 00:17:17.749 Luke Daque: back to them on that like.
185 00:17:17.750 ⇒ 00:17:18.190 Uttam Kumaran: Yeah, we can.
186 00:17:18.190 ⇒ 00:17:20.350 Luke Daque: Introduce AI to to them, and stuff.
187 00:17:20.720 ⇒ 00:17:24.170 Uttam Kumaran: Yeah, that’s what I want to start thinking about a little bit more. So we’ll see
188 00:17:26.990 ⇒ 00:17:30.444 Uttam Kumaran: cool. I guess I’ll transition a little bit to the
189 00:17:31.190 ⇒ 00:17:37.650 Uttam Kumaran: to the content and like sales side. So one of the big things this week
190 00:17:38.510 ⇒ 00:17:43.699 Uttam Kumaran: And I don’t know what the best way of like sharing. This is maybe
191 00:17:44.475 ⇒ 00:17:47.940 Uttam Kumaran: maybe it’s even just going through what I sent in slack
192 00:17:48.684 ⇒ 00:17:52.159 Uttam Kumaran: but if I go to our external sales
193 00:17:52.360 ⇒ 00:17:54.320 Uttam Kumaran: and then go to.
194 00:17:55.330 ⇒ 00:18:16.149 Uttam Kumaran: So one of the things that you know, I sent to the team this week was about our email program and I met someone who’s sending like about a hundred 1,000 emails a month. And he gave me he gave us a lot of tips on our email program. One, our content and our clay setup is really really great. To give you guys a sense of like how you know. Sophisticated.
195 00:18:16.270 ⇒ 00:18:25.529 Uttam Kumaran: we are right now, I’m just gonna walk through like one example of, like the clay table we’re using for a specific campaign.
196 00:18:28.530 ⇒ 00:18:30.930 Uttam Kumaran: Like, let’s take. Let’s take
197 00:18:31.990 ⇒ 00:18:34.910 Uttam Kumaran: like, oh, this. Let’s take this like lookalike campaign.
198 00:18:35.090 ⇒ 00:18:49.460 Uttam Kumaran: Basically, what we’re doing is let’s say we we take like flow code, look alike. Flow. Code, of course, is the is this QR Code company that I previously worked for and was leading data at. So basically, one of the things we could do is we could
199 00:18:49.510 ⇒ 00:18:58.039 Uttam Kumaran: target companies that are similar to flow code. And then, you know, basically say, Hey, we have experience in doing this. Do you wanna have a conversation with us.
200 00:18:58.070 ⇒ 00:19:17.120 Uttam Kumaran: What we do is we use this company called ocean. We find all these different QR code companies. We rank them by company size and revenue, and then we actually just create a table where we scrape like, do we? Is there is there? Can we get more information on their revenue size, rank them by score, and then basically find people at the company.
201 00:19:17.429 ⇒ 00:19:33.229 Uttam Kumaran: What we then do is we, then, once we find people at the company, we then enrich them. We find their titles. We then find you know, more information about where they’re located. We then get their email, and then we craft a personalized message to each of them.
202 00:19:33.770 ⇒ 00:19:49.549 Uttam Kumaran: And this is like all stuff that Erickson’s team is doing across 10 different campaigns. So we’re using every single enrichment source. We’re using 3 different AI, we’re using Claude Gemini and Openai to craft messaging. And then we send them a great email.
203 00:19:49.820 ⇒ 00:20:00.639 Uttam Kumaran: And so our content is really great. Our our email quality is really good. The only thing that we’re working on is there’s been a huge shock of like email deliverability. As people are starting to use more AI tools.
204 00:20:00.640 ⇒ 00:20:24.600 Uttam Kumaran: So we have, like, almost like 10 or 15 domains that we use to send emails out. And we send about 50 emails. Per, we’re actually changing a little bit. So we’re gonna lower the amount of emails we’re sending per domain and kind of improve our deliverability. Basically, the way we measure it is like is our emails landing in spam. And one of the key ways we measure, that is, if we’re getting people that are sending out of office
205 00:20:24.910 ⇒ 00:20:53.529 Uttam Kumaran: notifications like, Hey, my, I’m not active. I’m out of office. That’s how we know the email actually landed in their inbox. And so that’s 1 of the key ways we actually look at. If our emails are good and we’ve actually been seeing a little bit of a decrease. And so I sent some notes to Ericsson that he’s making updates on about our quality and so I’m really really excited for that we’re still gonna aim to, you know, hit about 6,000 to 10,000 emails a month. But we always wanna make sure that those are actually landing in people’s inboxes.
206 00:20:53.975 ⇒ 00:21:02.530 Uttam Kumaran: So that’s 1 thing. The next thing. And I know, Roy, I saw that you joined. Do you want to talk about how calling is gone this week.
207 00:21:02.942 ⇒ 00:21:18.059 Uttam Kumaran: And you know, maybe I’ll just give a have a quick look at Pixie, but I kind of do want to share with everybody like kind of the things that we’re working on. And to give everybody a sense again, Roy has come on to kind of lead.
208 00:21:18.375 ⇒ 00:21:42.369 Uttam Kumaran: Our cold phone program about how we’re contacting, you know, clients and booking meetings. And he was actually able to, you know, make about a hundred calls this week is what I is. What I saw in here. And and really, Kixi is amazing. I’ve actually listened to a couple, Roy, and and it’s like it’s all they’re awesome. Where we’re we’re calling people who are part of our Stella manufacturing campaign.
209 00:21:42.450 ⇒ 00:21:48.529 Uttam Kumaran: And yeah, Roy, I guess I’ll let you take it away if you want to chat a bit about your process, and and how it went this week.
210 00:21:49.450 ⇒ 00:21:53.529 Roy: Sure. So along with a cold email rather with
211 00:21:54.450 ⇒ 00:22:00.440 Roy: So we kind of went with that strategy. Since Erickson was actually dealing with the emails of these people
212 00:22:00.460 ⇒ 00:22:02.640 Roy: ideally, I’ll try to help them up
213 00:22:02.720 ⇒ 00:22:05.900 Roy: as a as a mode of Omni Channel.
214 00:22:06.120 ⇒ 00:22:10.119 Roy: and I guess the the biggest challenge I really had was because
215 00:22:10.400 ⇒ 00:22:18.029 Roy: I usually come in or encounter a lot a lot of different people or different roles with a whole list. So
216 00:22:18.674 ⇒ 00:22:29.699 Roy: I guess the part that I might really need help with is, it’s either I look for specific accounts. That would be our ideal. Icp, yeah.
217 00:22:30.226 ⇒ 00:22:39.980 Roy: redundant. So, or or Icp, or I could put them under real personas, you know, Ops man, or you know, people in Ops
218 00:22:40.110 ⇒ 00:22:44.210 Roy: people in it, people in Hr. Business development
219 00:22:44.390 ⇒ 00:22:55.310 Roy: and just kind of have the same script when it comes to approaching them. So it’s kind of, really, that segmenting that
220 00:22:55.760 ⇒ 00:22:58.390 Roy: now given that I’m tackling a list that
221 00:22:58.690 ⇒ 00:23:03.190 Roy: may come into the same company, you know it’d be calling, and
222 00:23:04.430 ⇒ 00:23:08.129 Roy: with how we can help. It’s kind of it’s kind of hard like.
223 00:23:08.380 ⇒ 00:23:18.349 Roy: hey is. So I would. For this campaign. Specifically, I’m I’m I’m targeting people who are in Ops. So still kind of refining the messaging.
224 00:23:18.680 ⇒ 00:23:19.020 Uttam Kumaran: Okay.
225 00:23:19.020 ⇒ 00:23:19.920 Roy: Might work.
226 00:23:20.170 ⇒ 00:23:20.930 Roy: Yeah.
227 00:23:22.100 ⇒ 00:23:39.715 Uttam Kumaran: And I think you know I listen to a couple, and I do. I feel like now. I have a good sense of like what kind of people say. And so I can definitely, I’m gonna I’ll send some notes over on, like, okay, here’s here’s where I think here’s where I think we could have maybe said like, this is what we do and like. Here’s how we can help you.
228 00:23:39.960 ⇒ 00:23:40.530 Roy: Yeah. The pitch.
229 00:23:40.777 ⇒ 00:23:46.480 Uttam Kumaran: Think I needed to hear a couple of these to kind of like. Give you that feedback. I didn’t. It wasn’t really like
230 00:23:46.560 ⇒ 00:24:10.760 Uttam Kumaran: clicking with me how best to provide that. But I do have a good understanding. The second thing is, I think the stuff that Casey’s working on for the agent is gonna help a lot. You know, if like, for example, like, let’s say you’re on a call. And someone asks you a question. You could actually probably have the agent up and ask it really quickly. And so I want to try to be creative there. But I I do have some feedback after listening to some of these calls. And so this has been really great.
231 00:24:13.709 ⇒ 00:24:19.950 Uttam Kumaran: And tell tell us, like, how does Kixi working and like? What do you think about the total like? Are the goals that we set?
232 00:24:20.383 ⇒ 00:24:26.719 Uttam Kumaran: You know. And like, yeah, if you could talk about that because not everybody is familiar with, you know, dialing and things like that.
233 00:24:27.520 ⇒ 00:24:35.013 Roy: Sure. So oftentimes in Kixee. How you upload it is, how it shows up as a list. So you know,
234 00:24:36.190 ⇒ 00:24:39.930 Roy: goes from one to 100. If you’re gonna upload that specific list
235 00:24:40.190 ⇒ 00:24:43.120 Roy: you particularly with Kixi.
236 00:24:43.230 ⇒ 00:24:46.590 Roy: it it has power list. It has this
237 00:24:47.120 ⇒ 00:24:50.329 Roy: segment called power lists, and with the power lists.
238 00:24:50.450 ⇒ 00:24:51.740 Roy: Do you
239 00:24:51.790 ⇒ 00:24:56.509 Roy: have to do this segmenting before you apply it? But then you can re upload.
240 00:24:56.640 ⇒ 00:25:09.059 Roy: and you can just update so it wouldn’t cause any like duplicates. So once that’s once that’s in place, they also have any automations that if you do any call disposition.
241 00:25:09.280 ⇒ 00:25:18.639 Roy: it can send a specific person to a follow up follow up power list. So it basically does that kind of binning or smart
242 00:25:18.870 ⇒ 00:25:21.399 Roy: smart list on its own. So
243 00:25:21.640 ⇒ 00:25:26.420 Roy: it’s it’s pretty powerful. I didn’t really go for
244 00:25:26.650 ⇒ 00:25:31.519 Roy: so it can dial multiple number of people at at the same time, but
245 00:25:31.730 ⇒ 00:25:39.659 Roy: depending on the size. It wouldn’t really make sense at this time, because we just started with with a Stella Stella size. But
246 00:25:39.770 ⇒ 00:25:41.410 Roy: definitely, it can catch
247 00:25:41.900 ⇒ 00:25:44.680 Roy: can catch number of people that would be
248 00:25:45.100 ⇒ 00:25:50.190 Roy: it basically is gonna help us have more conversations per hour.
249 00:25:50.260 ⇒ 00:25:51.280 Roy: So that
250 00:25:51.600 ⇒ 00:25:56.340 Roy: it’s it’s not like you’re gonna hit. A lot of the voice mails.
251 00:25:56.440 ⇒ 00:25:58.339 Roy: but kind of reduces that
252 00:25:58.480 ⇒ 00:26:01.550 Roy: that downtime, how it really helps.
253 00:26:05.200 ⇒ 00:26:13.360 Uttam Kumaran: Yeah, I’m super excited. I think you know, we’re gonna figure out I’m gonna I’m gonna try. And and now that we also have these, and I I assume we can get
254 00:26:13.850 ⇒ 00:26:17.500 Uttam Kumaran: like, can we get the transcript from these, or I can get the audio at least right.
255 00:26:18.377 ⇒ 00:26:21.769 Roy: Yeah, you can get the audio. Transcript there.
256 00:26:21.870 ⇒ 00:26:28.989 Roy: Yeah, there are other bit more expensive dialers. But I believe there are like call
257 00:26:29.450 ⇒ 00:26:31.900 Roy: call taking notes. I believe.
258 00:26:31.900 ⇒ 00:26:38.950 Uttam Kumaran: As long as we can. As long as we can get the audio out I can transcribe, because I also I think it’ll help
259 00:26:39.190 ⇒ 00:26:45.600 Uttam Kumaran: if I can load all of them into something too, it’ll also help to give feedback, and for you to ask questions over it.
260 00:26:46.550 ⇒ 00:26:48.939 Roy: That if you can download them in in bulk.
261 00:26:50.670 ⇒ 00:26:55.060 Uttam Kumaran: Yeah, no, we’ll. We’ll work on that and that probably something I work with the AI team on.
262 00:26:55.730 ⇒ 00:27:01.379 Uttam Kumaran: But this is really great. I mean. Look, I think you know, Roy, we started working, you know, probably like 2 months ago. And
263 00:27:01.540 ⇒ 00:27:04.529 Uttam Kumaran: I I’m really excited. I do think that
264 00:27:04.550 ⇒ 00:27:08.349 Uttam Kumaran: this is gonna be a key channel for us. I
265 00:27:08.400 ⇒ 00:27:11.609 Uttam Kumaran: I do think that. You know, I listen to some of the calls. And one I’m
266 00:27:11.720 ⇒ 00:27:25.599 Uttam Kumaran: I’m impressed, but also like getting someone on the phone and being able to have that moment with them, I think, is super super important. And I know a lot of people were saying like, Oh, I don’t handle that or something else, but you will improve, and we’ll we’ll give you the the points of
267 00:27:25.690 ⇒ 00:27:42.740 Uttam Kumaran: a pain that you can, you can hit them with. And then it’s again finding who the right person isn’t. And again, if that if that referral to that, whoever the leadership is comes from someone internally, it’ll be really, really strong. So we’re gonna keep going. I think again, like the one thing I tell you know, we talk a lot about is just like
268 00:27:42.840 ⇒ 00:27:56.912 Uttam Kumaran: we’re. This isn’t gonna be super pretty to start with. But we’re gonna work on it. And the other thing is, you know, we can get more twilio I can get. Tell me if, like the phone number ends up, not working. I can get a twilio
269 00:27:57.420 ⇒ 00:27:59.070 Uttam Kumaran: number, or whatever.
270 00:27:59.790 ⇒ 00:28:01.199 Uttam Kumaran: that’s something we can.
271 00:28:01.200 ⇒ 00:28:14.220 Roy: We can clean. That’s actually something we can clean. So there’s a bad number disposition there. Then I can probably route that to a power list like bad number power list. Then we can
272 00:28:15.360 ⇒ 00:28:16.770 Roy: that type of
273 00:28:17.190 ⇒ 00:28:18.140 Roy: sending.
274 00:28:19.010 ⇒ 00:28:19.370 Uttam Kumaran: Okay.
275 00:28:19.840 ⇒ 00:28:21.930 Uttam Kumaran: awesome. This was really, really
276 00:28:21.970 ⇒ 00:28:26.330 Uttam Kumaran: cool. The other thing I want to kind of share is
277 00:28:27.120 ⇒ 00:28:28.500 Uttam Kumaran: content stuff?
278 00:28:29.123 ⇒ 00:28:29.666 Uttam Kumaran: So
279 00:28:30.390 ⇒ 00:28:36.609 Uttam Kumaran: if I just go to Brainforge. Ryan did an awesome job on my content. This week
280 00:28:36.620 ⇒ 00:28:53.000 Uttam Kumaran: we had a couple of different pieces. Go out. We, we talked about podcast ad spend. And we talked about stuff like this bigquery. Ryan, I mean, yeah, Ryan, we should put Luke on here because he’s the one that contributed a lot to this. I actually do want to shout.
281 00:28:53.449 ⇒ 00:29:03.639 Uttam Kumaran: Both of you guys out. I you know, I usually review a lot of the content. But I was. I was extremely busy this week. Like, have. Basically.
282 00:29:04.010 ⇒ 00:29:13.479 Uttam Kumaran: I’ve been in meetings for the last 3 days straight until, like 9 or 10 o’clock. So I did message and saying I messaged Ryan on the contents. They say, hey? I asked Luke.
283 00:29:14.154 ⇒ 00:29:26.105 Uttam Kumaran: if he can provide his perspective on this, because although I can, I just didn’t have the kind of the brain at the moment. And you guys had an amazing, you know, back and forth here. About it, I think.
284 00:29:26.720 ⇒ 00:29:33.030 Uttam Kumaran: it was super super awesome to kind of see that and this is really like it made me really happy to kind of see that?
285 00:29:33.439 ⇒ 00:29:52.620 Uttam Kumaran: You guys could work together. And we have a lot of other subject matter experts. On the team that I want to help start help our content folks, and our design folks provide more feedback to what is going to help. I mean, this is a really really great example of something that we worked on that ended up
286 00:29:54.120 ⇒ 00:30:17.547 Uttam Kumaran: online. Let me go. Let me go back. Yeah. That ended up going live. And so, you know, we post a great blog post about Snowflake versus bigquery. I’m really great to link both of them and this will end up being in our glossary, too. So yeah, I would love to get, because also a lot of these blogs are coming from me, and so I would love to have some other people contribute and and have that
287 00:30:18.470 ⇒ 00:30:34.879 Uttam Kumaran: although I I have, I don’t really like I don’t. I’ve contrary to popular belief, I really don’t enjoy seeing my face like everywhere. But the other thing I’ll share is on Linkedin. It’s been really positive this week, too. So if I go to the Brainforge account.
288 00:30:36.080 ⇒ 00:30:39.760 Uttam Kumaran: we have a couple of posts that
289 00:30:40.330 ⇒ 00:31:01.425 Uttam Kumaran: that Ryan did that that, and we made a couple of key. Changes. One is, we started using bold you know, kind of helps draw people’s attention. I think we’re gonna try another one. Ryan, where we do almost the arrows. I think that could be helpful, too, but I do like how we do have some breakup of content.
290 00:31:02.050 ⇒ 00:31:09.899 Uttam Kumaran: you know, we’re getting. We’re getting likes and comments. I know some of these folks are just, you know, friends of mine. But we’re gonna start increasing.
291 00:31:10.432 ⇒ 00:31:16.227 Uttam Kumaran: But you know, we’re gonna start having Miguel and Nico also start to post, and we’re gonna start to get. I’m pretty sure some really great
292 00:31:16.874 ⇒ 00:31:21.086 Uttam Kumaran: you know, movement here. And so we post. We posted 2 2 things.
293 00:31:21.430 ⇒ 00:31:25.209 Uttam Kumaran: the search versus actually, what I think? 3 things.
294 00:31:26.052 ⇒ 00:31:39.317 Uttam Kumaran: Right? Yeah, the 5, th the 7, th and the 5th to 6. And then today, so it’s it’s been great. I mean, I’m glad we have a lot of content. We also have the news that are going out. And it’s great. You know, we’re getting
295 00:31:40.160 ⇒ 00:31:45.840 Uttam Kumaran: We’re getting great content on these. And you know, I think eventually we could probably start boosting these and running some ads against these.
296 00:31:46.191 ⇒ 00:31:56.119 Uttam Kumaran: The other thing that I’ll share is on the analytics side. We’re growing our follower count a little bit. You know, we have about 171 followers. My goal is that we
297 00:31:56.200 ⇒ 00:32:07.395 Uttam Kumaran: I mean, ideally, we try to double each period. But you know, hopefully, we can get this past 200 this month. Again, I’ll remind everyone if you have a chance to invite your network of people?
298 00:32:07.770 ⇒ 00:32:09.800 Uttam Kumaran: they can be friends, family, or
299 00:32:09.970 ⇒ 00:32:16.959 Uttam Kumaran: ask coworkers. That would be really amazing. The more people see our stuff the more people like it and repost it. It’s really gonna make a difference.
300 00:32:17.284 ⇒ 00:32:19.560 Uttam Kumaran: And you can see that, you know, we’re
301 00:32:19.620 ⇒ 00:32:34.710 Uttam Kumaran: compared to the past month. But even if we just go to the last like 15 days, we’re getting good reactions. We’re getting good impressions and comments and repost so very, very happy about that, and our click through rate is super super high. Even Ryan was. You know, we talked about this this week.
302 00:32:34.730 ⇒ 00:32:36.779 Uttam Kumaran: and then followers. You know, this is where
303 00:32:37.190 ⇒ 00:32:48.550 Uttam Kumaran: we’re gonna want to see this start to go up. You know, I had a huge spike because I invited a bunch of people. But you know, I wanna I wanna start to see us get into like closer, you know, definitely past 500 into a thousand.
304 00:32:50.540 ⇒ 00:32:52.660 Uttam Kumaran: I don’t know what is employee advocacy.
305 00:32:53.190 ⇒ 00:32:53.900 Uttam Kumaran: Oh.
306 00:32:55.200 ⇒ 00:32:58.439 Uttam Kumaran: oh, this is like I can. Oh, I don’t know. I guess this is
307 00:32:59.680 ⇒ 00:33:01.229 Uttam Kumaran: yeah. I don’t really know what this is.
308 00:33:01.828 ⇒ 00:33:05.859 Uttam Kumaran: So that’s really great. And then I I posted a couple of times this week.
309 00:33:06.690 ⇒ 00:33:07.330 Uttam Kumaran: Which
310 00:33:07.670 ⇒ 00:33:11.570 Uttam Kumaran: I’m getting better at. But again we’re getting a lot of impressions.
311 00:33:12.105 ⇒ 00:33:15.359 Uttam Kumaran: Like, if I go to post impressions.
312 00:33:15.806 ⇒ 00:33:22.169 Uttam Kumaran: You can see that this is over like, let’s just do the past like 14 days. I didn’t post anything the past like
313 00:33:22.820 ⇒ 00:33:25.599 Uttam Kumaran: I didn’t in this period I didn’t post anything. So this is like
314 00:33:25.650 ⇒ 00:33:30.089 Uttam Kumaran: 2 weeks, which is my bad. But I posted again yesterday, and you could see that
315 00:33:30.130 ⇒ 00:33:35.879 Uttam Kumaran: we’re starting to get past a thousand we’re getting. And this is past 14 days. And we posted some of these 2 weeks ago.
316 00:33:35.920 ⇒ 00:33:41.519 Uttam Kumaran: So past stuff is collecting impressions and engagement so very, very awesome to see that.
317 00:33:43.000 ⇒ 00:33:53.660 Uttam Kumaran: And so yeah, again, I’ll I’ll encourage if everyone can like and comment or spend, you know, even just 10 min on Linkedin once a week. That would help out, you know, Ryan and the whole team.
318 00:33:54.067 ⇒ 00:33:58.842 Uttam Kumaran: The other thing I wanna just walk through quickly is on the site.
319 00:34:00.150 ⇒ 00:34:15.400 Uttam Kumaran: So we made a couple of changes. Cleaned up with some of the Logos here. You know, we have some really strong call to actions that are consistent, like booking call booking call, which is really good. So this all looks really awesome.
320 00:34:15.715 ⇒ 00:34:31.090 Uttam Kumaran: We, I think we completed. Oh, we completed the services. Yeah. So we have in this new services. Page and then we want to get out a services page on AI and automation. We don’t have one now, so that’s what we’ll try to get done as soon as we can.
321 00:34:31.532 ⇒ 00:34:37.690 Uttam Kumaran: This looks really really awesome. The about us pages here, the blog pages here, the pricing pages here
322 00:34:37.850 ⇒ 00:34:40.750 Uttam Kumaran: so really, really excited. We had our 1st
323 00:34:41.317 ⇒ 00:34:46.205 Uttam Kumaran: direct booking this week as well with a company called Wonder Sign.
324 00:34:47.050 ⇒ 00:34:52.210 Uttam Kumaran: He didn’t tell me exactly how he found us. He was like, yeah, we just did research. And we found you guys. But
325 00:34:52.940 ⇒ 00:34:55.730 Uttam Kumaran: that’s awesome, like someone booked directly
326 00:34:56.010 ⇒ 00:35:02.830 Uttam Kumaran: through our booking link. And I talk to them. And they’re a real person. So that’s like a huge, huge milestone. I know we
327 00:35:03.000 ⇒ 00:35:20.970 Uttam Kumaran: I’ve been working towards that, and somehow they found us. But again, that’s the kind of feedback loop that I’m looking for, and I can go update our goals to say that we have one person. I don’t know where they came from, but I’ll just put it through on something. But this is a real company, and and we have some leads with them. So I’m really really excited. There.
328 00:35:21.717 ⇒ 00:35:32.079 Uttam Kumaran: The other thing I want to talk about is we’ve been working with some subject matter experts on the medical side. I know some people on the company are involved on this initiative. Where
329 00:35:32.370 ⇒ 00:35:38.270 Uttam Kumaran: we’re looking to create a campaign around medical we have 2 people on
330 00:35:38.270 ⇒ 00:36:03.490 Uttam Kumaran: who are friends of mine are connected to me. Who are doctors? And Phd, candidates, who are in the medical sector around AI and Ml, and so they’re helping us basically put together the lead list as well as put together the content and the marketing that we’re gonna go live with next week. I know Erickson, Ryan, and me are are all involved in kind of putting this together. But
331 00:36:03.490 ⇒ 00:36:31.120 Uttam Kumaran: super seamless process. We’re gonna get some content out about you know, using AI in the in the clinical space, optimizing appointment, scheduling, helping with healthcare things like that. So I’m super super pumped and hopefully start to break into to the healthcare sector as well. We will then probably have a couple of we’ll. We’ll then have a nice breadth of campaigns that we’re running so I’m super super excited there any questions, or if anyone wants to be included in this channel, feel free to join, it’s just under sales.
332 00:36:31.190 ⇒ 00:36:32.710 Uttam Kumaran: Industry, medical?
333 00:36:35.800 ⇒ 00:36:37.770 Uttam Kumaran: yeah. Any other
334 00:36:39.280 ⇒ 00:36:43.469 Uttam Kumaran: questions? I feel like I’ve for the most part covered.
335 00:36:45.580 ⇒ 00:36:46.660 Uttam Kumaran: everything
336 00:36:46.680 ⇒ 00:36:47.829 Uttam Kumaran: on my mind.
337 00:36:55.910 ⇒ 00:36:56.710 Uttam Kumaran: Cool.
338 00:36:57.592 ⇒ 00:37:02.220 Uttam Kumaran: So I guess I’ll just talk briefly. So for next week, you know, the biggest thing is.
339 00:37:02.290 ⇒ 00:37:07.599 Uttam Kumaran: it would be great to get a couple of more posts out about AI and medical. I’m really excited for that.
340 00:37:07.965 ⇒ 00:37:24.229 Uttam Kumaran: I think we’re. Gonna I think the other thing and we’re gonna send today is to get me Miguel and Nico’s accounts, posting and reposting. So that’s I think it’s gonna be huge unlock for us. It’s gonna really improve the improve the impressions on our on our Linkedin.
341 00:37:24.490 ⇒ 00:37:46.619 Uttam Kumaran: The other thing is, I want to. There we’re running a couple of campaigns, but I honestly want to start to focus on the ones that are winning. If if manufacturing, if it’s not the right time, I want us to make a call on that. I don’t want us to be spread across like 10 campaigns. Or we’re not focusing. So I’m going to do a little bit of an audit and look at like, is there a couple of areas we want to focus. We have been improving our our
342 00:37:46.920 ⇒ 00:37:50.360 Uttam Kumaran: our messaging and the copy. And so I’m I’m impressed by that
343 00:37:50.835 ⇒ 00:38:01.520 Uttam Kumaran: and we’re gonna look to improve our deliverability. The second thing is me and I’m gonna be spending a lot more time closely with Ryan and the design team. Kind of. I mean.
344 00:38:01.830 ⇒ 00:38:02.570 Uttam Kumaran: I
345 00:38:02.934 ⇒ 00:38:13.629 Uttam Kumaran: think we’re we’re doing well on the client side. We’ve had some good wins, and I wanna get those out. So we’re also gonna try to do some video content as well. So we’ll be really pushing for that stuff next week.
346 00:38:13.660 ⇒ 00:38:23.647 Uttam Kumaran: And then, yeah, we really again continue to look forward to the stuff that’s happening on the phone side and making sure that, Roy, you have all the information that you need
347 00:38:24.780 ⇒ 00:38:26.120 Uttam Kumaran: and then we’ll go from there.
348 00:38:27.740 ⇒ 00:38:31.119 Uttam Kumaran: We have some big demos next week, and some proposals going out as well. So
349 00:38:33.080 ⇒ 00:38:34.115 Uttam Kumaran: any
350 00:38:35.160 ⇒ 00:38:37.050 Uttam Kumaran: thing else that I can answer.
351 00:38:37.980 ⇒ 00:38:39.520 Miguel: I have an update with them.
352 00:38:39.520 ⇒ 00:38:39.960 Uttam Kumaran: Yeah.
353 00:38:40.030 ⇒ 00:38:42.940 Miguel: Regarding via cocoa. Remember, I set it up.
354 00:38:42.940 ⇒ 00:38:43.830 Uttam Kumaran: It’s working
355 00:38:44.060 ⇒ 00:38:45.060 Uttam Kumaran: like.
356 00:38:45.060 ⇒ 00:38:46.909 Miguel: This? Yeah, yeah, there’s outputs.
357 00:38:47.860 ⇒ 00:38:48.230 Uttam Kumaran: Hell, yeah.
358 00:38:48.230 ⇒ 00:38:54.360 Miguel: I just checked it now. So yeah, it’s working. The chrome job is working it script for 7 and 8.
359 00:38:54.500 ⇒ 00:38:59.149 Miguel: Yeah, is it? 9.th Yeah, it’s probably gonna skip, scrape again later for the 9.th
360 00:38:59.580 ⇒ 00:39:01.139 Miguel: So yeah, it’s running.
361 00:39:01.140 ⇒ 00:39:03.489 Uttam Kumaran: Oh, nice. Okay. Great hell, yeah.
362 00:39:03.940 ⇒ 00:39:09.320 Uttam Kumaran: Cool. I was. I was like, worried that it wasn’t gonna work like, meaning like their Vm was gonna shut down. Basically.
363 00:39:10.100 ⇒ 00:39:12.420 Miguel: I mean, that’s not really our control. It just.
364 00:39:12.420 ⇒ 00:39:13.969 Uttam Kumaran: No, no, for sure, for sure.
365 00:39:14.840 ⇒ 00:39:17.059 Miguel: But yeah, it’s working so nice.
366 00:39:22.780 ⇒ 00:39:25.020 Miguel: Yeah, I think that’s pretty much it on my end.
367 00:39:26.480 ⇒ 00:39:27.660 Miguel: Shut the cameras off.
368 00:39:31.070 ⇒ 00:39:31.920 Nicolas Sucari: Fun guys.
369 00:39:32.720 ⇒ 00:39:33.069 Uttam Kumaran: Cool.
370 00:39:33.420 ⇒ 00:39:34.229 Nicolas Sucari: Right, link.
371 00:39:34.530 ⇒ 00:39:36.210 Uttam Kumaran: Yeah, really strong week.
372 00:39:36.760 ⇒ 00:39:40.022 Uttam Kumaran: if anything, chat with everybody in slack. And
373 00:39:40.590 ⇒ 00:39:42.299 Uttam Kumaran: yeah, have a really great weekend.
374 00:39:43.410 ⇒ 00:39:44.149 Miguel: Bye, everyone.
375 00:39:44.710 ⇒ 00:39:45.710 Nicolas Sucari: Bye, guys.
376 00:39:45.710 ⇒ 00:39:46.680 Luke Daque: Think, see you.
377 00:39:48.250 ⇒ 00:39:48.940 Ryan Brosas: Bye.