Meeting Title: Brainforge Sales and Case Studies Overview Date: 2025-08-12 Meeting participants: Hannah Wang, Giselle Agot
WEBVTT
1 00:00:12.290 ⇒ 00:00:13.719 Giselle Agot: Hi, Hannah!
2 00:00:15.010 ⇒ 00:00:16.560 Hannah Wang: Hey, how’s it going?
3 00:00:17.050 ⇒ 00:00:18.599 Giselle Agot: All good, how about you?
4 00:00:19.190 ⇒ 00:00:21.289 Hannah Wang: Well, I’m doing well.
5 00:00:21.670 ⇒ 00:00:22.859 Hannah Wang: Nice meeting you.
6 00:00:23.070 ⇒ 00:00:28.579 Giselle Agot: Nice meeting you. Sorry, this is just going to be quick. It’s just a hi hello for me, actually.
7 00:00:29.420 ⇒ 00:00:53.030 Giselle Agot: last week, and I have to move it, like, this week, because, I know you’re super busy, and of course, our schedule doesn’t meet. Like, in the afternoon, I’m already out, so that’s why I just plotted it to here, but just, to make sure that I have all the tasks checked in my checklist, so that’s why I’m meeting you. So, Amber told me to just meet you, and probably just tell me about the sales side, like, how is it that you
8 00:00:53.130 ⇒ 00:01:00.420 Giselle Agot: I’m actually… I actually have sales questions with Amber, and she told me that maybe I could, like, ask you in this call, so….
9 00:01:00.420 ⇒ 00:01:01.459 Hannah Wang: Yeah, sure.
10 00:01:01.600 ⇒ 00:01:15.040 Giselle Agot: One question was, that I asked her was, do you have, like, a, sales document template that you usually ask with a client, especially, like, a potential lead that’s, you know, something like that?
11 00:01:15.180 ⇒ 00:01:33.210 Hannah Wang: Let me think… so, to give you more context about who does what, so Robert and Utam, obviously they’re, like, the CEOs, but they spend 50% of their time doing sales, so if you… usually I try not to bother them with questions, but if I can’t answer it.
12 00:01:33.210 ⇒ 00:01:45.669 Hannah Wang: Then you can go to Sid. So, I don’t know if you met Sid, but Sid is the sales coordinator on our side, so she should be able to answer more of the sales questions, and then if she doesn’t know, then…
13 00:01:46.090 ⇒ 00:01:59.489 Hannah Wang: you can also try to ask me. I might not know, because I’m… I’m more of, like, on the marketing, design side, and then I’m also helping out a little bit with partnerships, with other companies.
14 00:01:59.490 ⇒ 00:01:59.820 Giselle Agot: Okay.
15 00:01:59.820 ⇒ 00:02:06.169 Hannah Wang: For a little bit before we had Sid, I did help out with sales, but it was very…
16 00:02:06.820 ⇒ 00:02:11.540 Hannah Wang: Light touch, it was more if they needed follow-up emails to be written.
17 00:02:11.770 ⇒ 00:02:13.780 Giselle Agot: And I just helped them draft it.
18 00:02:13.780 ⇒ 00:02:14.310 Hannah Wang: ….
19 00:02:14.310 ⇒ 00:02:14.770 Giselle Agot: Okay.
20 00:02:14.770 ⇒ 00:02:18.879 Hannah Wang: But let me send you some, maybe, Notion…
21 00:02:19.420 ⇒ 00:02:23.070 Hannah Wang: documents that might be helpful, …
22 00:02:24.990 ⇒ 00:02:28.959 Hannah Wang: So, this one… this notion is…
23 00:02:29.150 ⇒ 00:02:38.020 Hannah Wang: the sales notion page, it has a lot of stuff. I even don’t know everything that’s on it, but maybe…
24 00:02:38.210 ⇒ 00:02:41.400 Hannah Wang: Let me try to also share my screen.
25 00:02:52.740 ⇒ 00:02:55.790 Hannah Wang: You asked about if there’s any questions that we ask.
26 00:02:56.090 ⇒ 00:02:58.409 Hannah Wang: clients, right? If we’re, like, …
27 00:02:58.950 ⇒ 00:03:02.149 Hannah Wang: I guess it’s like the discovery, like a discovery.
28 00:03:02.150 ⇒ 00:03:02.550 Giselle Agot: No.
29 00:03:02.550 ⇒ 00:03:03.589 Hannah Wang: call? Okay.
30 00:03:03.880 ⇒ 00:03:04.710 Giselle Agot: Correct.
31 00:03:04.930 ⇒ 00:03:06.240 Hannah Wang: …
32 00:03:10.670 ⇒ 00:03:18.360 Hannah Wang: I see… I don’t… No… if we… Do…
33 00:03:18.610 ⇒ 00:03:29.680 Hannah Wang: It probably is here somewhere, and if not, it’s all in Utam and Robert’s brain, so that’s, like, the worst case scenario. That’s okay.
34 00:03:30.470 ⇒ 00:03:32.900 Hannah Wang: You can try to ask Sid as well.
35 00:03:32.900 ⇒ 00:03:33.530 Giselle Agot: No problem.
36 00:03:33.530 ⇒ 00:03:39.469 Hannah Wang: And then dig through this Notion page, because I think it’s just, like, the hub for all,
37 00:03:39.590 ⇒ 00:03:41.320 Hannah Wang: Sales-related things.
38 00:03:41.920 ⇒ 00:03:42.310 Hannah Wang: Yeah.
39 00:03:42.310 ⇒ 00:04:01.350 Giselle Agot: Okay. And then, also, Amber mentioned, like, asking you about what we do, like, the Brainforge website and case studies. I already have an idea, like, what we do, because I’m also… I’m attending to client calls already starting last week, so, probably there’s some few things that I don’t know yet, so maybe you can share some.
40 00:04:01.610 ⇒ 00:04:03.810 Hannah Wang: What is it? Well, I also…
41 00:04:04.430 ⇒ 00:04:16.329 Hannah Wang: I’m also still trying to develop the language to explain what we do, but I guess high-level overview, we are a data and AI consultancy, so basically, instead of
42 00:04:16.329 ⇒ 00:04:26.269 Hannah Wang: companies hiring a super expensive data or AI engineer, like, usually those cost, like, they’re, like, six figures, like 120,000 US dollars.
43 00:04:26.270 ⇒ 00:04:37.340 Hannah Wang: Per year, and they’re very… they’re quite expensive. Maybe even more than that, like $200K. So instead of having companies hire, like, a dedicated data engineer.
44 00:04:37.570 ⇒ 00:04:45.909 Hannah Wang: we can come in at, like, a way… like, as a fractional data team, and basically help them implement, or I guess diagnose
45 00:04:45.950 ⇒ 00:04:59.679 Hannah Wang: their data and AI needs, and then just, like, help them implement it, and then if, after our contract ends and they don’t want to renew with us, then we basically give, like, follow-up,
46 00:04:59.850 ⇒ 00:05:10.299 Hannah Wang: just, like, a follow-up kind of, like, here’s what you could do, next steps after we leave, like, support, I guess. And for the past, like.
47 00:05:10.730 ⇒ 00:05:13.789 Hannah Wang: Fourish… three-ish months?
48 00:05:13.790 ⇒ 00:05:21.680 Giselle Agot: We’re on, like, the marketing and branding side, we’re trying to figure out the language that we wanted to use to describe.
49 00:05:22.120 ⇒ 00:05:25.940 Hannah Wang: how to marry data and AI together,
50 00:05:25.940 ⇒ 00:05:26.305 Giselle Agot: Hmm.
51 00:05:26.670 ⇒ 00:05:37.350 Hannah Wang: Because I think before, like, when the company was started, it was pretty separate, like, data… we offer data services, and then AI services are kind of separate, but I think now…
52 00:05:37.530 ⇒ 00:05:42.929 Hannah Wang: how we try to explain it is that we basically use AI
53 00:05:43.540 ⇒ 00:05:55.489 Hannah Wang: you… we leverage AI in our workflows to enable us to better help you with your data steps. So, we’re trying to more incorporate the language of, like, oh.
54 00:05:55.490 ⇒ 00:06:05.400 Hannah Wang: data and AI are not separate, they’re very much together, and that’s one of our strengths, is that we use both to help you, whether it is
55 00:06:05.400 ⇒ 00:06:13.569 Hannah Wang: that you need, like, a data service or an AI service, whatever it is, like, we’ll marry the two fields together and, like, help you do that. So…
56 00:06:14.170 ⇒ 00:06:22.490 Hannah Wang: I guess more specific things that we do, from what I know, it’s, like, from the data side, usually clients…
57 00:06:22.830 ⇒ 00:06:24.990 Hannah Wang: They’re…
58 00:06:25.530 ⇒ 00:06:33.559 Hannah Wang: number one ask, I think, is, they have, like, data sources that are scattered throughout all different platforms, and
59 00:06:33.560 ⇒ 00:06:50.410 Hannah Wang: their marketing team has to manually go into each of those, like, websites and just, like, pull data from it, and that’s obviously, like, a waste of time and not as efficient. So, what we do is we come in, we gather all those sources, and we bring them into one, like, data source.
60 00:06:51.460 ⇒ 00:07:00.540 Hannah Wang: thing, I don’t know all the terminology, like, a data warehouse, and then from there, based on that data, we, like, build dashboards, so that
61 00:07:00.630 ⇒ 00:07:20.119 Hannah Wang: our clients and their marketing and business teams have, like, one comprehensive view of, like, where all the data’s coming from, so that… so that they can make strategic decisions. I think that’s, like, the important part. We’re not just pulling in data for the sake of pulling in data and having it all in one place. We’re doing that to enable
62 00:07:20.120 ⇒ 00:07:34.130 Hannah Wang: like, decision makers within the companies to be like, okay, maybe we should stop making this product, or maybe we should make more of this product so that we can drive more revenue, stuff like that. So that’s, like, the data services, kind of, like, what
63 00:07:34.130 ⇒ 00:07:38.930 Hannah Wang: We do, like, on a very, very high level. Obviously, we do, like, other stuff, too.
64 00:07:39.130 ⇒ 00:07:54.290 Hannah Wang: And then for AI side, it’s, like, automating internal workflows. So, like, even here at BrainForge, we have, like, an internal AI team, and I don’t know if you saw, you’ve seen, like, the data platform, let me…
65 00:07:54.900 ⇒ 00:07:58.190 Hannah Wang: Yeah, so that’s kind of the stuff that we built, so it’s like.
66 00:07:58.910 ⇒ 00:08:14.870 Hannah Wang: like, yeah, Zoom has their own, like, meeting recording and stuff, but they don’t have, like, a summary, and they might have a transcript, but you can’t create tickets from it. So I think it’s… we do… the things that we do internally, we also help clients do. …
67 00:08:15.380 ⇒ 00:08:23.220 Hannah Wang: So yeah, that’s, like, a high-level overview. I can also share with you… I’ll share this.
68 00:08:23.330 ⇒ 00:08:26.409 Hannah Wang: Link later, but, …
69 00:08:26.640 ⇒ 00:08:41.320 Hannah Wang: So these are all the sales assets that we have. I know it’s… there’s, like, a lot going on here, but, this is kind of like a one-pager that we send to clients who are interested. Let me…
70 00:08:42.340 ⇒ 00:08:44.599 Hannah Wang: Yeah, let me send that over to you after.
71 00:08:44.910 ⇒ 00:08:46.449 Hannah Wang: This meeting, but…
72 00:08:46.860 ⇒ 00:08:53.469 Hannah Wang: It’s kind of like, oh, this is… yeah, we turn chaos into clarity for decisions… decision making.
73 00:08:54.250 ⇒ 00:09:07.939 Hannah Wang: We fix your systems, we structure your data, and we deliver AI. These are the metrics, whatever. But these are, like, the high-level three services that we kind of offer. So, data services.
74 00:09:07.940 ⇒ 00:09:20.359 Hannah Wang: And then strategy, so we also help with, like, roadmapping and making sure that everything’s, like, documented correctly, and I think that’s where the PMs obviously help with the clients, and then we have, like, AI, so…
75 00:09:20.760 ⇒ 00:09:21.940 Hannah Wang: basically.
76 00:09:22.420 ⇒ 00:09:33.160 Hannah Wang: cutting costs where we need to cut costs, because you can automate it with AI, you can speed up execution, because AI is really fast at doing stuff, etc. And then, I can also send you…
77 00:09:33.850 ⇒ 00:09:50.809 Hannah Wang: this, too. This is, like, a more specific version of the document I showed you. It’s basically the same thing, except that, it’s more technical, so we send these more to, like, the technical folks who will understand the language, but…
78 00:09:51.680 ⇒ 00:09:53.660 Hannah Wang: Yeah, it’s like, oh, these are…
79 00:09:53.800 ⇒ 00:10:04.169 Hannah Wang: this is, like, the data engine… data stuff that we do, this is the AI stuff that we do, this is the strategy stuff that we do, so we do, like, A-B testing, we do…
80 00:10:04.430 ⇒ 00:10:11.190 Hannah Wang: all these other terminologies that I don’t really know. Data engineering, we implement data warehouses, we…
81 00:10:11.360 ⇒ 00:10:23.369 Hannah Wang: we’re, like, HIPAA and SOC 2 compliant, we do cost optimization, AI, we build, like, chatbots, we do… we do agentic workflows, stuff like that, so….
82 00:10:23.680 ⇒ 00:10:24.290 Giselle Agot: Beautiful.
83 00:10:24.490 ⇒ 00:10:31.530 Hannah Wang: Yeah, I know that was, like, a lot of information. I’ve been here since late January, and I still feel like I’m…
84 00:10:31.690 ⇒ 00:10:41.480 Hannah Wang: trying to understand what we do, so I… it’s okay if it’s confusing. It’s like, what the heck do we even do? It’s, like, hard to explain. So hopefully that….
85 00:10:41.480 ⇒ 00:10:44.440 Giselle Agot: What are these case studies? We also have case studies.
86 00:10:45.000 ⇒ 00:10:46.130 Giselle Agot: Yeah.
87 00:10:47.010 ⇒ 00:10:47.560 Hannah Wang: So….
88 00:10:47.560 ⇒ 00:10:49.620 Giselle Agot: Is this people?
89 00:10:50.110 ⇒ 00:10:50.840 Hannah Wang: Sorry?
90 00:10:50.970 ⇒ 00:10:52.569 Giselle Agot: Are you using Figma?
91 00:10:52.570 ⇒ 00:10:53.540 Hannah Wang: Yes, yeah.
92 00:10:53.540 ⇒ 00:10:54.150 Giselle Agot: Okay.
93 00:10:54.150 ⇒ 00:10:58.579 Hannah Wang: Well, let me share my whole screen so I can share with you, …
94 00:10:59.820 ⇒ 00:11:05.530 Hannah Wang: So these are the case studies that we have. I think a better view would probably be…
95 00:11:06.370 ⇒ 00:11:15.980 Hannah Wang: Right here. So if you go to the platform, under other actions, you can go to Marketing Assets, and these are where all the assets that you saw in Figma live.
96 00:11:16.340 ⇒ 00:11:18.900 Hannah Wang: So you can go to the case studies folder.
97 00:11:19.680 ⇒ 00:11:24.479 Hannah Wang: And basically, we just, like, exported it, so you’ll be able to see it in PDF form.
98 00:11:24.670 ⇒ 00:11:30.459 Hannah Wang: So yeah, these are basically the case studies that we have. …
99 00:11:30.830 ⇒ 00:11:34.680 Hannah Wang: it’s just easier for me to navigate here. So, …
100 00:11:35.010 ⇒ 00:11:41.230 Hannah Wang: some of these are anonymized, some of them are not, but ABC Home, this is the client that Amber
101 00:11:41.520 ⇒ 00:11:46.919 Hannah Wang: PMs, and they’re, like, a home services company for pest control and other stuff.
102 00:11:47.120 ⇒ 00:11:52.330 Hannah Wang: So, this is… a case study that we made for them. Basically, we made, like, a…
103 00:11:52.700 ⇒ 00:12:00.600 Hannah Wang: AI agent, that helps their team get answers to questions quickly, like their customer service …
104 00:12:00.810 ⇒ 00:12:05.569 Hannah Wang: I forgot what CSR stands for, Customer Service Rep… something, like….
105 00:12:05.570 ⇒ 00:12:08.769 Giselle Agot: Yeah, representative? Yes, exactly. Yeah. ….
106 00:12:09.160 ⇒ 00:12:09.670 Hannah Wang: Yes.
107 00:12:09.670 ⇒ 00:12:15.739 Giselle Agot: I actually attended to one call yesterday, and they were talking about some agents, so yeah.
108 00:12:15.740 ⇒ 00:12:23.530 Hannah Wang: Yeah, this is what this is. Yeah, Andy is the agent. What other client call have you been on so far? Do you remember?
109 00:12:23.840 ⇒ 00:12:25.150 Giselle Agot: default.
110 00:12:25.520 ⇒ 00:12:36.809 Hannah Wang: Okay, default, we don’t have a case study with them yet, so I don’t have anything to show you, but, Vitacoco was a past client as well, and some of these are anonymized, so, like.
111 00:12:37.150 ⇒ 00:12:49.329 Hannah Wang: we didn’t work for Amazon, we just implemented an Amazon dashboard. That’s why it says Amazon. But yeah, you can see some of these have, like, vague non-client names, so those are more, …
112 00:12:49.840 ⇒ 00:13:05.630 Hannah Wang: anonymized, and honestly, some of them, like this case study, was an internal project that we did, for running marketing campaigns, but we just, like, made it into a case study and pretended that there was a client.
113 00:13:05.630 ⇒ 00:13:06.250 Giselle Agot: ….
114 00:13:06.590 ⇒ 00:13:11.620 Hannah Wang: A recent one that I made was for Eden. This is… one of…
115 00:13:11.800 ⇒ 00:13:29.239 Hannah Wang: the clients that I think also Amber is trying to start PM… starts at PM. They are a health company, they offer GLP-1, like, weight loss pills and stuff like that. So I recently made this case study, like, basically finished it up this morning,
116 00:13:29.850 ⇒ 00:13:39.899 Hannah Wang: So yeah, all the case studies… I didn’t upload this yet to the platform, but … but basically all the ones that you see in that Figma file, you should be able to
117 00:13:40.010 ⇒ 00:13:42.630 Hannah Wang: Grab here, as well as…
118 00:13:42.880 ⇒ 00:13:48.929 Hannah Wang: all of our assets, so, like, that one asset that I showed you.
119 00:13:49.140 ⇒ 00:13:58.859 Hannah Wang: earlier, that’s right here, uploaded, and you can grab the link to it, and just, like, send it to whoever you want, …
120 00:14:00.180 ⇒ 00:14:05.910 Hannah Wang: Yeah, so, I don’t know if that answered your question about case studies, but … okay, cool.
121 00:14:06.060 ⇒ 00:14:11.820 Giselle Agot: It did. I haven’t seen this, I mean, with my training with Amber, so she asked me.
122 00:14:11.820 ⇒ 00:14:12.140 Hannah Wang: Okay.
123 00:14:12.140 ⇒ 00:14:27.459 Giselle Agot: asking what these case studies are, and how it looks like, how, so yeah, I now have an understanding what it is. And I can also find that in the marketing assets, which I also have access to. So I think I’m all good. Okay.
124 00:14:27.990 ⇒ 00:14:31.860 Giselle Agot: that’s just what I have here in my agenda list, those…
125 00:14:32.390 ⇒ 00:14:39.699 Giselle Agot: items… I don’t have any questions at the moment, probably I will in the future, but I will just Slack you if I do.
126 00:14:40.020 ⇒ 00:14:48.449 Hannah Wang: Okay, and you are a project coordinator, right? So… what does that mean? Like, I don’t really… I know there’s, like, project manager, but what’s a different.
127 00:14:48.450 ⇒ 00:14:48.879 Giselle Agot: Thank you.
128 00:14:48.880 ⇒ 00:14:50.340 Hannah Wang: Diana Coordinator.
129 00:14:50.960 ⇒ 00:15:04.739 Giselle Agot: I’m thinking the difference is the project manager gets to, like, have the conversation with the clients. Coordinator is the one that’s coordinating the tickets. In the project that I’m assigned to, like, default.
130 00:15:04.770 ⇒ 00:15:16.910 Giselle Agot: It’s Autumn who’s communicating with the client, and yeah, that was my first worry when I was, listening to the call, because I was like, what are they talking about? I don’t have any idea, so…
131 00:15:17.040 ⇒ 00:15:41.929 Giselle Agot: In the years of working as a project manager, I have to really understand, what the business, or what the client’s business is, so that I can fully deliver and explain to them, what we are presenting or anything. So I was like, I’m not really sure if I understand what they’re talking about, it’s too technical, but it made me understand that what Autumn needs is someone who can manage the tickets, who can manage the tasks.
132 00:15:41.930 ⇒ 00:16:00.329 Giselle Agot: give him updates, daily updates, in the channel, so that he will know, and be prepared as well in calls, same as this one. But eventually, Amber did mention that I might be handling, but I’m not sure, but for now, it’s, coordinating, like, internal coordination with the tickets and the projects, so…
133 00:16:00.330 ⇒ 00:16:04.630 Giselle Agot: Just understanding, what the business is.
134 00:16:04.630 ⇒ 00:16:12.280 Hannah Wang: what we do. Okay, I will share one more thing that might be helpful, so… if you go to Notion…
135 00:16:12.510 ⇒ 00:16:17.639 Hannah Wang: So I sent you the sales one already. Let me send you…
136 00:16:19.380 ⇒ 00:16:35.039 Hannah Wang: I think… no, not this one. I think this one. So… so, maybe, like, 2 months ago, when we were trying to marry data and AI, like, the concepts together, we read a book called, Building a Story Brand, and
137 00:16:35.050 ⇒ 00:16:42.459 Hannah Wang: Basically that book helped us with our branding and just our language and tone that we have.
138 00:16:43.090 ⇒ 00:17:00.280 Hannah Wang: And we, like, jotted down notes from our brainstorming sessions. We did, like, a book club, the marketing team in Utam, and we read through the book, and we brainstormed. So maybe this section right here will help you. Brandscript V0, 0.2, so let me send that in the chat.
139 00:17:00.770 ⇒ 00:17:03.349 Hannah Wang: This basically, in plain English.
140 00:17:03.500 ⇒ 00:17:15.710 Hannah Wang: to me, in plain English, describes, like, kind of what we do. So, our main ICP, they’re senior leaders, so, like, head of product, head of marketing, CEO, CPO,
141 00:17:16.050 ⇒ 00:17:30.130 Hannah Wang: CTO… I don’t know about, like, CFO, but yeah, just, like, head C-suite people, those are our ICPs, senior leaders at mid-market, so that means, like, maybe 500.
142 00:17:30.690 ⇒ 00:17:40.259 Hannah Wang: like, 200 to 500 employees at tech-enabled U.S. companies, and 5 to 110 million 5 to 100 million
143 00:17:40.570 ⇒ 00:17:48.399 Hannah Wang: In revenue, so those are the companies that we go for, who are under pressure to grow with fewer resources.
144 00:17:48.820 ⇒ 00:17:49.610 Giselle Agot: Hmm.
145 00:17:49.610 ⇒ 00:17:59.139 Hannah Wang: This is all kind of, like, ChatGPT-fied, so don’t mind all the language that might be, like, too fancy or whatever, but, …
146 00:17:59.360 ⇒ 00:18:06.950 Hannah Wang: basically, we go for C-suite leaders at these types of companies, and the problem that they have is,
147 00:18:07.090 ⇒ 00:18:15.119 Hannah Wang: They feel like they can’t make this… like, the right… they’re not confident in the decisions that they’re making, because
148 00:18:15.540 ⇒ 00:18:21.449 Hannah Wang: their data, they just don’t have enough, like, data-driven decisions,
149 00:18:22.830 ⇒ 00:18:36.920 Hannah Wang: Because, like I said, maybe their data is all over the place, they don’t have, like, a central dashboard, one source of truth. They want to implement AI, but they just don’t know how to, and obviously, in this day and age, everyone wants to implement AI.
150 00:18:36.920 ⇒ 00:18:44.009 Hannah Wang: So, they probably feel the pressure to be like, oh, I need to utilize AI, but I don’t know how to do that. So those are the people that we go for.
151 00:18:44.010 ⇒ 00:18:56.939 Hannah Wang: So the problems that they feel, like, externally, it’s like, oh, I don’t know how to make the right decisions. And then the book also said, like, oh, you need a hit on internal and philosophical problems that your clients might be facing.
152 00:18:57.030 ⇒ 00:19:06.480 Hannah Wang: So, internal problems might be like, oh, because I don’t know how to make these decisions, I feel, like, inefficient, I don’t feel good at my job, I feel behind.
153 00:19:06.490 ⇒ 00:19:21.169 Hannah Wang: Stuff like that. And so, where we come in is… we’re like, oh, we’ve been there too, like, we know the problems that you’re facing, we know what it’s like to run a company… try to run a company without data and AI, we know what it’s like to…
154 00:19:21.170 ⇒ 00:19:27.980 Hannah Wang: dig through all these weird dashboards to get metrics that don’t really help in the long run.
155 00:19:28.880 ⇒ 00:19:44.149 Hannah Wang: So, we, like, empathize with you, and we know how to fix your problem. So we’re… we’re… we’re your guide, and we’ll give you a plan. The plan is to take you from chaos, the chaos that you feel internally, externally, into clarity.
156 00:19:44.580 ⇒ 00:19:44.940 Giselle Agot: Hmm.
157 00:19:44.940 ⇒ 00:19:50.549 Hannah Wang: And these are, like, the steps that we’ll do. So first, we’ll, like, hop on a call with you to diagnose the problem.
158 00:19:50.700 ⇒ 00:20:08.039 Hannah Wang: And then next, we’ll, like, design the fix, so we’ll come up with, like, a technical design document, a TDD, that’s kind of maybe something you’ll hear often. We’ll come up with, like, a roadmap for you. We’ll send you a plan, timelines, architecture diagrams.
159 00:20:08.040 ⇒ 00:20:16.730 Hannah Wang: And then lastly, we’ll deploy it for you. So we’ll actually build it for you, and walk you through that. And these are kind of, like.
160 00:20:17.400 ⇒ 00:20:24.239 Hannah Wang: the comp… like, we guarantee that you’ll be confident when you work with us, you’ll, like, see results, and…
161 00:20:24.370 ⇒ 00:20:31.630 Hannah Wang: weeks, not months, we’re a part of your team, stuff like that. And then…
162 00:20:31.840 ⇒ 00:20:42.490 Hannah Wang: I think on all of our… a lot of our sales collateral, like, we need to direct them to a call to action. So it’s like, oh, if you… if this sounds good, like, book a call with us, book a strategy call with us.
163 00:20:42.680 ⇒ 00:20:43.760 Hannah Wang: …
164 00:20:44.040 ⇒ 00:20:58.040 Hannah Wang: pop on a call to do, like, an AI workshop with us. That’s, like, one of the, lead generating, like, lead gens that we’re doing, like, that we’re offering, like, a free one-hour workshop, basically. ….
165 00:20:59.240 ⇒ 00:21:07.610 Hannah Wang: And, if you hop on a call with us, like, we’ll help you avoid failure, and you’ll end in a success. So…
166 00:21:07.650 ⇒ 00:21:27.009 Hannah Wang: Hopefully that gives you more of, like, a… I know it’s less technical, but I think it’s more of, like, a story that we’re trying to tell to leads, that this is what we do for our clients, and we’re… yeah. Like, you have a problem, we’re your guide, and we’ll guide you through it, and we’ll help you. So, you can read through this,
167 00:21:27.270 ⇒ 00:21:29.969 Hannah Wang: To hopefully give you a better idea of what
168 00:21:30.600 ⇒ 00:21:33.389 Hannah Wang: We do in terms of, like.
169 00:21:34.690 ⇒ 00:21:41.560 Hannah Wang: yeah, data and AI. Oh, this part was the most helpful to me, especially…
170 00:21:41.710 ⇒ 00:21:56.419 Hannah Wang: this long, long pitch right here. So, everyone’s under pressure to do AI, but most organizations aren’t ready. At Brainforge, we’ll help you do it. So yeah, we clean up broken systems, so this is, like, the data stuff that we’re talking about.
171 00:21:56.420 ⇒ 00:22:14.549 Hannah Wang: We structure the right data, and then we ship, like, we integrate AI, basically, into the systems that we use to clean up your broken systems and structure the data, using co-pilots, automations and tools, and then all of that will help you
172 00:22:14.620 ⇒ 00:22:19.820 Hannah Wang: Go from… chaos to clarity, basically. …
173 00:22:20.390 ⇒ 00:22:23.680 Hannah Wang: So these are, like, examples, like, oh, if…
174 00:22:24.170 ⇒ 00:22:37.520 Hannah Wang: Yeah, you might need us if you’re still manually updating spreadsheets, like, you try to do AI, but it’s not working, you feel like you’re not… you’re flying blind, like, you don’t know what you’re doing, stuff like that.
175 00:22:37.680 ⇒ 00:22:38.790 Hannah Wang: …
176 00:22:43.090 ⇒ 00:22:58.690 Hannah Wang: Yeah, and I think even these notes, too, like, these are notes from Robert that he wrote on July 1st. Reading through this might be helpful, too, because it’s, like, how Utam and Robert kind of think and process, like, that’s right here, listed here.
177 00:22:59.320 ⇒ 00:23:02.280 Hannah Wang: So…
178 00:23:02.380 ⇒ 00:23:08.700 Hannah Wang: Yeah, and then all these other parts, like, you don’t… it’s a lot, you don’t need to read through it. Maybe, yeah, just…
179 00:23:08.930 ⇒ 00:23:13.600 Hannah Wang: this here… And then the brand script V0.2.
180 00:23:13.780 ⇒ 00:23:17.699 Hannah Wang: will be helpful. And then… I’m trying to think…
181 00:23:17.910 ⇒ 00:23:20.870 Hannah Wang: If there’s anything else. I know there’s, like, a…
182 00:23:24.150 ⇒ 00:23:40.050 Hannah Wang: Oh, my Zoom is in the way. So, there’s this chat GPT prompt that I think Robert started. I will also send this to you. I don’t know how helpful this will be, but…
183 00:23:44.140 ⇒ 00:23:47.050 Hannah Wang: In an ideal world, like, instead of
184 00:23:47.340 ⇒ 00:23:58.630 Hannah Wang: Ryan asking… Ryan’s our content person, so he, like, posts content on LinkedIn and stuff for Utam and Robert and the company. Instead of Ryan asking Utam and Robert, like, hey.
185 00:23:58.820 ⇒ 00:24:13.780 Hannah Wang: what do you think about this? Like, ideally, he’d use this, exec… executive brain GPT to answer the questions for him, because this GPT is supposed to think like Utom and Robert. So maybe reading through this might be helpful, too.
186 00:24:14.390 ⇒ 00:24:21.140 Hannah Wang: yeah, it’s, like, kind of what we do. And then, there was one more thing that I was going to send you.
187 00:24:21.550 ⇒ 00:24:34.369 Hannah Wang: … … I can’t remember what that was. If I remember it, I’ll send it to you on Slack.
188 00:24:34.400 ⇒ 00:24:46.160 Hannah Wang: But yeah, hopefully that’s, like, a good start. There’s, like, a lot of stuff on Notion, I know, so hopefully me sending you direct links is a little bit more helpful than you trying to dig through it yourself.
189 00:24:46.640 ⇒ 00:24:49.849 Giselle Agot: Yeah, thank you so much, Hannah, and I know…
190 00:24:49.850 ⇒ 00:25:08.639 Giselle Agot: Yeah, it’s taking your time as well. I know you’re super busy, but these are very helpful to me, so I’ll take some time to read these, and yeah, it gives me an idea now, like, what we do, how can we help the clients that we are, working with, and what’s the reason why they want our services, so yeah.
191 00:25:08.950 ⇒ 00:25:20.559 Hannah Wang: Yeah, and hopefully being on the calls, too, will help you, because I’ve been being looped into more, like, partnership calls, and it’s been helpful, even though I just kind of sit there, and Utam does all the talking, like, it’s…
192 00:25:20.940 ⇒ 00:25:23.760 Hannah Wang: It’s helpful just to, like, hear it over and over again.
193 00:25:23.760 ⇒ 00:25:24.570 Giselle Agot: what….
194 00:25:24.570 ⇒ 00:25:29.969 Hannah Wang: They do, … But yeah, like, no problem at all, I’m…
195 00:25:30.890 ⇒ 00:25:46.199 Hannah Wang: not as busy as I was before. I think my roles have been shifting a lot, but yeah, don’t worry about bothering me, it’s not a bother at all. So, you can feel free to ping me if you have any more questions, and then I’ll try to think of more things that might be
196 00:25:46.380 ⇒ 00:25:49.690 Hannah Wang: Helpful to you? … But yeah.
197 00:25:50.270 ⇒ 00:25:52.409 Giselle Agot: Alright, thank you, thank you so much, Hannah.
198 00:25:52.410 ⇒ 00:26:02.749 Hannah Wang: Yeah, it was nice meeting you, and hopefully working here is fun. I know it’s fast-paced, and it’s, like, a lot at once, but the people are really nice, so hopefully…
199 00:26:03.310 ⇒ 00:26:04.959 Hannah Wang: Yeah, you’ll see that too.
200 00:26:05.370 ⇒ 00:26:08.220 Giselle Agot: Thank you, thank you, Hannah. Bye. Alright, bye.