Meeting Title: Third Bridge x Brainforge AI Collaboration Date: 2026-02-19 Meeting participants: Luke Scorziell, Melanie Vladimirschi
WEBVTT
1 00:01:47.360 ⇒ 00:01:48.300 Luke Scorziell: Over the…
2 00:02:08.229 ⇒ 00:02:09.239 Melanie Vladimirschi: Hey, Luke!
3 00:02:09.429 ⇒ 00:02:12.160 Melanie Vladimirschi: Can you hear me? Hey, Melody. How are you?
4 00:02:12.410 ⇒ 00:02:13.940 Luke Scorziell: Good! How are you doing?
5 00:02:14.290 ⇒ 00:02:17.720 Melanie Vladimirschi: Good, nice to speak with you again.
6 00:02:17.720 ⇒ 00:02:24.260 Luke Scorziell: I know, yeah, it’s been a while. I will say from the beginning, my Wi-Fi has been terrible today, so if it, like.
7 00:02:24.260 ⇒ 00:02:25.250 Melanie Vladimirschi: You’re fine.
8 00:02:25.370 ⇒ 00:02:29.710 Melanie Vladimirschi: All, all good, I can hear you and see you perfectly.
9 00:02:29.710 ⇒ 00:02:32.619 Luke Scorziell: Okay, well, feel free to, yeah.
10 00:02:32.960 ⇒ 00:02:42.400 Luke Scorziell: interrupt me if it’s, like… But, yeah, how have you been? What have you, how have things at Third Bridge been?
11 00:02:42.400 ⇒ 00:02:59.270 Melanie Vladimirschi: Good! Things at Thurbridge have been great. We have now… I can’t remember when we spoke, like, the size of the survey team, but now it’s, like, 18 people. I think it was probably, like, around 10 when we spoke, so still growing, still hiring. Wow.
12 00:02:59.840 ⇒ 00:03:06.520 Melanie Vladimirschi: we have the team in LA now as two people, so… but…
13 00:03:06.750 ⇒ 00:03:18.039 Melanie Vladimirschi: They are actually really good, so it’s all going well, and then… I don’t… I think, like, the pee side of things, like, Sahir… did… were you there when Sahir was there?
14 00:03:18.640 ⇒ 00:03:21.260 Luke Scorziell: I, like, briefly overlap with it here, and .
15 00:03:21.260 ⇒ 00:03:22.810 Melanie Vladimirschi: Just came back to London.
16 00:03:23.050 ⇒ 00:03:23.959 Luke Scorziell: Oh, really?
17 00:03:23.960 ⇒ 00:03:25.850 Melanie Vladimirschi: Yeah, so…
18 00:03:26.330 ⇒ 00:03:32.330 Melanie Vladimirschi: he wanted to come back to London, and he… because obviously he went from LA to London back.
19 00:03:32.330 ⇒ 00:03:34.419 Luke Scorziell: Yeah, I remember that.
20 00:03:34.420 ⇒ 00:03:36.310 Melanie Vladimirschi: Which is really funny, so…
21 00:03:36.390 ⇒ 00:03:49.059 Melanie Vladimirschi: I think there’s, like, some changes in the team there, but… yeah, no, things at Thurbridge are good. We’re hopefully gearing up, this year for, like.
22 00:03:49.060 ⇒ 00:04:00.179 Melanie Vladimirschi: strong focus on our content business, rather than our services business, because obviously with AI, I’m sure you’re feeling it everywhere as well, like, just the…
23 00:04:00.850 ⇒ 00:04:06.940 Melanie Vladimirschi: I think more and more the expert network industry as a whole will be less reliant on, like.
24 00:04:08.640 ⇒ 00:04:15.710 Melanie Vladimirschi: you know, the service that we offer, which was always our, like, our selling point, is, like, how great our PMs are, and how much.
25 00:04:15.710 ⇒ 00:04:16.450 Luke Scorziell: Yeah.
26 00:04:16.450 ⇒ 00:04:24.110 Melanie Vladimirschi: like, can tailor exactly the expert that you… the client requests to the client, and it’s like, AI can do that now? 4.
27 00:04:24.670 ⇒ 00:04:30.550 Melanie Vladimirschi: Great. So how do we double down on the content side of the business, which is, like.
28 00:04:31.060 ⇒ 00:04:39.869 Melanie Vladimirschi: more… gonna be, I think, more valuable for clients if they can already, like, use their existing,
29 00:04:40.030 ⇒ 00:04:53.300 Melanie Vladimirschi: whatever they use, whether it’s, like, ChatGPT or whatever LLM, like, Gemini, Claude, to then feed our, like, content library into their…
30 00:04:54.150 ⇒ 00:05:03.690 Melanie Vladimirschi: existing LLMs. So that’s what, like, Thurbridge, I would say at a macro level, where we’re going.
31 00:05:04.070 ⇒ 00:05:11.869 Melanie Vladimirschi: less on the services side. So, quite interesting, but, like, with AI, it’s gonna change things quite a lot.
32 00:05:12.140 ⇒ 00:05:16.079 Luke Scorziell: Yeah, no, where are you guys in that process? That’s really interesting.
33 00:05:16.240 ⇒ 00:05:22.780 Melanie Vladimirschi: We’ve already kicked it off with… I mean, I don’t know if you’ve… if you follow Thurbridge on LinkedIn, but, like, every other…
34 00:05:22.910 ⇒ 00:05:34.540 Melanie Vladimirschi: week, there’s, like, a partnership announcement, so the recent partnership with Anthropic, so that any Clawed user has access to our…
35 00:05:34.830 ⇒ 00:05:40.109 Melanie Vladimirschi: content now, but, like, we’re gonna probably do one with… I think the OpenAI one is…
36 00:05:40.910 ⇒ 00:05:44.419 Melanie Vladimirschi: Like, about to be signed, so…
37 00:05:44.530 ⇒ 00:05:49.710 Melanie Vladimirschi: So yeah, lots of cool things. But when you messaged, I wasn’t sure if you were…
38 00:05:49.970 ⇒ 00:06:04.779 Melanie Vladimirschi: referencing, because I want to hear more about what you’re doing and your company as well, but I thought that maybe, because it sounds like it’s in that space as well, it could be an interesting conversation to have with, like, our partnerships guide to.
39 00:06:05.250 ⇒ 00:06:17.379 Luke Scorziell: Yeah, yeah, I mean, it’s interesting that you’re describing that, because that’s, like, literally what we’ve been doing for ourselves, and then for clients, is we build, like, a knowledge base, that, like, like, I’ll just give you the example for…
40 00:06:18.230 ⇒ 00:06:19.550 Luke Scorziell: We do,
41 00:06:20.040 ⇒ 00:06:27.670 Luke Scorziell: We have an internal knowledge base, we are an agency, so we consult with a lot of clients, implementing, like, AI and data infrastructure for them.
42 00:06:27.850 ⇒ 00:06:40.589 Luke Scorziell: And all of our call transcripts, typically get recorded, and then uploaded into that platform. So then, like, today, if, you know, when I’m prepping, it’s like.
43 00:06:40.650 ⇒ 00:06:59.720 Luke Scorziell: I can say, like, oh, I’m meeting with, Melanie, and this is her, like, the background that I have on her, like, can you give me, like, relevant information from recent calls that we’ve had on, like, what would… what would be interesting to implement for Third Bridge. So that’s, like, yeah, been one use case that’s been really cool, but yeah, I was totally thinking with, like.
44 00:06:59.950 ⇒ 00:07:10.789 Luke Scorziell: content, it’s like, you just have a library, and then the LLM can index it, and then you just ask it, like, straight questions, so…
45 00:07:12.250 ⇒ 00:07:16.409 Melanie Vladimirschi: It’s very… it’s very… it’s exactly where we’re going, which is really funny, so…
46 00:07:16.410 ⇒ 00:07:26.139 Luke Scorziell: Yeah, and I mean, we work with, like, Claude, and we’re using Cursor a lot, and then… so it’s like…
47 00:07:26.690 ⇒ 00:07:31.449 Luke Scorziell: like, I’ve been writing on LinkedIn a little bit, too, about, like, it’s, like, the next step
48 00:07:31.610 ⇒ 00:07:35.530 Luke Scorziell: for, like, a non… most non-technical users, I think, is, like.
49 00:07:35.650 ⇒ 00:07:38.989 Luke Scorziell: to stop using LLMs as, like, just…
50 00:07:39.210 ⇒ 00:07:56.280 Luke Scorziell: a chatbot and… and start using something that has, like, a clean index knowledge base. Like, I’m using, like, GitHub and all these coding tools, but I have, like, no clue. Like, you know, I’m doing marketing, so it’s… Yeah. I’m like, what am I doing on this? Yeah.
51 00:07:57.070 ⇒ 00:07:57.540 Luke Scorziell: But it is…
52 00:07:57.540 ⇒ 00:08:01.559 Melanie Vladimirschi: I mean, it is great, it is, like, such a game changer, right? So… that’s…
53 00:08:01.560 ⇒ 00:08:02.390 Luke Scorziell: Yeah.
54 00:08:02.390 ⇒ 00:08:03.310 Melanie Vladimirschi: Awesome.
55 00:08:03.440 ⇒ 00:08:09.950 Luke Scorziell: But I can give… I mean, I can give you more context on, like, specifically what I’m… I’m doing, too. I don’t know how much… I’m sure.
56 00:08:09.950 ⇒ 00:08:15.620 Melanie Vladimirschi: No, I would love to hear more, and also, like, the… when you reached out,
57 00:08:16.000 ⇒ 00:08:21.549 Melanie Vladimirschi: like, how you envision Thurbridge collaborating as well, which would be…
58 00:08:21.980 ⇒ 00:08:25.209 Luke Scorziell: Yeah, I mean, so, we do…
59 00:08:25.560 ⇒ 00:08:39.490 Luke Scorziell: We’re a consultancy, and kind of like a service implementation partner of a lot of different, like, data infrastructure, so that’s kind of where we started, is more on the data side, and I think I was just thinking back to, like, the…
60 00:08:39.590 ⇒ 00:08:46.440 Luke Scorziell: intranet at Third Bridge, and, like, how clunky and, like, hard to move around it is.
61 00:08:46.770 ⇒ 00:08:50.830 Luke Scorziell: But… and so part of what we do on the data side is, like, bring…
62 00:08:51.160 ⇒ 00:09:02.780 Luke Scorziell: AI into, like, whatever data and information our clients have to kind of help it work with that, as opposed to when you’re, like, bringing your data into, like.
63 00:09:03.300 ⇒ 00:09:08.439 Luke Scorziell: OpenAI, or you’re like, I have no clue where all this information is going, and like, do I really.
64 00:09:08.440 ⇒ 00:09:15.789 Melanie Vladimirschi: agents run, like, trying to streamline the data that is already existing.
65 00:09:15.790 ⇒ 00:09:23.050 Luke Scorziell: Yeah, yeah, exactly. And so… that, like, we’ve found…
66 00:09:23.680 ⇒ 00:09:32.849 Luke Scorziell: People appreciate, because it’s, like, if your, like, data is kind of, like, gold right now, and so the information that you have is really important, and then when it’s, like.
67 00:09:32.940 ⇒ 00:09:41.560 Luke Scorziell: I don’t know, personally, I don’t really trust OpenAI, all that much. I trust, like, Anthropic maybe a little more, but with, like, just,
68 00:09:41.650 ⇒ 00:09:59.709 Luke Scorziell: seeing the history of, like, a lot of these bigger, like, LLM providers, it’s like, oh, they, like, really don’t care about, like, it’s kind of… yeah, just what they want. So… so anyway, so we do a lot of, like, data infrastructure, but then we also have built, like, co-pilots, and, like, these knowledge-based systems, and…
69 00:10:00.010 ⇒ 00:10:09.190 Luke Scorziell: a lot of the AI stuff kind of on top of the data, and I think that’s what has… what was really interesting to me about coming into Brainforge is, like.
70 00:10:09.840 ⇒ 00:10:24.299 Luke Scorziell: I’m… I don’t really have a data background. I’ve liked experimenting with AI, but learning that, like, AI becomes, like, magnitudes more effective when the information that it’s working with is structured well.
71 00:10:25.010 ⇒ 00:10:25.630 Melanie Vladimirschi: Totally.
72 00:10:26.000 ⇒ 00:10:38.350 Luke Scorziell: So, yeah, I mean, that’s kind of, like, what we’re doing, and I’m leading our, like, go-to-market and marketing, and it’s been, like, super fun to just, like, it’s like drinking out of a fire hose, learning,
73 00:10:38.470 ⇒ 00:10:57.849 Luke Scorziell: But, yeah, and I guess what I… like, I was thinking about the intranet, and just… I mean, I had, like, a few kind of specific ideas, but then was more just, like… I feel like I know Third Bridge’s business pretty well. I know that AI… I’ve always thought, like, at some point, AI is going to revolutionize how expert networks work.
74 00:10:57.920 ⇒ 00:11:00.489 Luke Scorziell: And it seems like there’s… yeah, just, like.
75 00:11:00.870 ⇒ 00:11:06.340 Luke Scorziell: I don’t know, like, I already have a lot of relationships at Third Bridge, so it’s like, how can I help, and…
76 00:11:06.490 ⇒ 00:11:11.540 Luke Scorziell: Yeah, be of, of, of service in, like, this…
77 00:11:11.540 ⇒ 00:11:12.120 Melanie Vladimirschi: Totally.
78 00:11:12.120 ⇒ 00:11:16.840 Luke Scorziell: weird stage that we’re in, because people… yeah, it’s like… Everything’s moving super quick.
79 00:11:17.030 ⇒ 00:11:20.389 Melanie Vladimirschi: We’re trying to ship stuff for clients, like, in, like, under…
80 00:11:20.470 ⇒ 00:11:29.920 Luke Scorziell: 3 to 4 weeks to get, like, a minimum viable thing, and so it’s… it’s just like… yeah, it feels like things are changing really quickly.
81 00:11:30.220 ⇒ 00:11:38.960 Melanie Vladimirschi: Totally. On the intranet side, we have, like… so we’ve hired in the last, like, I want to say…
82 00:11:39.500 ⇒ 00:11:45.619 Melanie Vladimirschi: 6 months, a whole team that does exactly what you described internally.
83 00:11:46.520 ⇒ 00:11:49.089 Melanie Vladimirschi: So, that’s where, like, the expert…
84 00:11:49.330 ⇒ 00:11:58.769 Melanie Vladimirschi: Like, the… if you look at the data that we currently have on, like, expert pages or client pages, for example, there’s a team that’s, like.
85 00:11:58.990 ⇒ 00:12:11.879 Melanie Vladimirschi: looking at, and again, like, building a bunch of different, like, this takes, like, thousands of agents to figure out, like, each one is something different, but, like, taking expert information and client information, and then…
86 00:12:12.270 ⇒ 00:12:26.160 Melanie Vladimirschi: like, helping PM. For now, we still have PMs, right? Like, I think maybe in two years, it might be a different story, we might not have that many people, on the team, but for now, the PMs are basically
87 00:12:26.270 ⇒ 00:12:39.330 Melanie Vladimirschi: like, their lives are just so much easier than when you were around, because you already have the recommendation directly from the, like, agent.
88 00:12:39.610 ⇒ 00:12:48.180 Melanie Vladimirschi: So, if a client comes to you and says, hey, Luke, I need to speak with formers at X, in 2 seconds, there’s, like, a list.
89 00:12:48.960 ⇒ 00:12:49.760 Luke Scorziell: huh.
90 00:12:50.090 ⇒ 00:12:59.950 Melanie Vladimirschi: So that’s really… I mean, it’s, again, as you said, like, revolutionizing, like, the intranet and Compass and whatever, like, how everything worked.
91 00:13:00.360 ⇒ 00:13:14.279 Melanie Vladimirschi: So that’s being built right now, and we’ve… we’re doing some, like, trials with the teams, but I don’t know… I… to be honest, it’s a totally different, like, separate team, it’s R&D, it sits with…
92 00:13:14.280 ⇒ 00:13:14.680 Luke Scorziell: Yeah.
93 00:13:14.680 ⇒ 00:13:20.849 Melanie Vladimirschi: the AI guy, so I’m not sure, but I can try to find out if they’re using anyone
94 00:13:21.060 ⇒ 00:13:23.250 Melanie Vladimirschi: External, or if they’re.
95 00:13:23.250 ⇒ 00:13:23.590 Luke Scorziell: Yeah.
96 00:13:23.590 ⇒ 00:13:25.020 Melanie Vladimirschi: everything in-house.
97 00:13:25.720 ⇒ 00:13:30.029 Luke Scorziell: Yeah, well, I’m curious, on your end, too, like, what is…
98 00:13:30.200 ⇒ 00:13:33.120 Luke Scorziell: AI implementation on the surveys team look like?
99 00:13:34.530 ⇒ 00:13:41.269 Melanie Vladimirschi: For us, we’re gonna ben- because surveys live on the intranet, we’re gonna benefit from whatever is built out for…
100 00:13:41.270 ⇒ 00:13:42.040 Luke Scorziell: Hmm.
101 00:13:42.040 ⇒ 00:13:46.070 Melanie Vladimirschi: for expert pages and client pages, so essentially, it’s like…
102 00:13:46.690 ⇒ 00:13:53.520 Melanie Vladimirschi: Client comes in and says, I want to survey 200 customers of X software.
103 00:13:54.030 ⇒ 00:14:04.540 Melanie Vladimirschi: I would expect that in the next few months, we have, like, an agent delivering what are the 200 customers that they’re gonna survey, or whatever it is.
104 00:14:04.560 ⇒ 00:14:05.320 Luke Scorziell: And…
105 00:14:05.800 ⇒ 00:14:12.329 Melanie Vladimirschi: automatically, like, a lot of the process of sending a survey out will also be automated.
106 00:14:13.500 ⇒ 00:14:23.060 Melanie Vladimirschi: Which, again, as you said, like, this is all going very quickly, so TBD on timelines and things like that, but that is how I think
107 00:14:25.180 ⇒ 00:14:30.159 Melanie Vladimirschi: Changing the workflow today will be the most effective.
108 00:14:31.300 ⇒ 00:14:35.400 Melanie Vladimirschi: do I think surveys in the next…
109 00:14:35.520 ⇒ 00:14:43.530 Melanie Vladimirschi: I think, like, surveys are… like, clients are always gonna want surveys to validate information, right? They’re always gonna wanna hear from real experts.
110 00:14:44.030 ⇒ 00:14:49.479 Melanie Vladimirschi: on topics that they know nothing about.
111 00:14:52.280 ⇒ 00:15:03.999 Melanie Vladimirschi: But I think the process on our side is just gonna be so much quicker than, like, going through and encompassing thousands of people who could be relevant, we don’t know if they’re relevant, like…
112 00:15:04.370 ⇒ 00:15:11.099 Melanie Vladimirschi: I would expect an AI or, like, an agentic system to tell me who’s relevant, who’s not.
113 00:15:11.260 ⇒ 00:15:14.150 Melanie Vladimirschi: So… Does that make sense?
114 00:15:14.330 ⇒ 00:15:15.230 Luke Scorziell: Yeah.
115 00:15:15.450 ⇒ 00:15:15.830 Melanie Vladimirschi: where…
116 00:15:15.830 ⇒ 00:15:20.250 Luke Scorziell: I mean, it sounds like the subtext is that maybe, like, there’s gonna be a slimming…
117 00:15:20.450 ⇒ 00:15:22.239 Luke Scorziell: A lot of us slimming down.
118 00:15:22.410 ⇒ 00:15:23.000 Luke Scorziell: Megan?
119 00:15:23.120 ⇒ 00:15:27.830 Melanie Vladimirschi: I think so, probably. Like, I don’t think the… I don’t think the…
120 00:15:28.540 ⇒ 00:15:37.279 Melanie Vladimirschi: manpower, and this is probably true for a lot of, like, services businesses, right? Like, with AI, do you actually need.
121 00:15:39.070 ⇒ 00:15:55.100 Melanie Vladimirschi: people on the ground, if a… what you probably do need still is, like, someone validating what the AI is doing in the immediate future. I don’t think that’s going away, but in, like… and I don’t think anyone… anything’s changing, by the way, in the next, like, year, for sure.
122 00:15:55.100 ⇒ 00:15:55.440 Luke Scorziell: Yeah.
123 00:15:55.560 ⇒ 00:16:06.499 Melanie Vladimirschi: like, headcount, whatever. But maybe next year? Will there be different expectations for headcount? Like, potentially, in 2 years? This is just my…
124 00:16:06.970 ⇒ 00:16:07.550 Melanie Vladimirschi: Personally.
125 00:16:07.550 ⇒ 00:16:08.129 Luke Scorziell: You know…
126 00:16:08.130 ⇒ 00:16:10.499 Melanie Vladimirschi: you, like, I… I haven’t, like…
127 00:16:10.730 ⇒ 00:16:18.740 Melanie Vladimirschi: you know, asked the founders specifically, but I do think… The smarter these systems are.
128 00:16:19.870 ⇒ 00:16:20.440 Luke Scorziell: Huh.
129 00:16:20.440 ⇒ 00:16:24.729 Melanie Vladimirschi: The more we can help our clients without even relying on
130 00:16:25.060 ⇒ 00:16:30.590 Melanie Vladimirschi: people, which was our moat for so long, right? Like, our… the quality.
131 00:16:30.590 ⇒ 00:16:31.000 Luke Scorziell: Yeah.
132 00:16:31.000 ⇒ 00:16:33.119 Melanie Vladimirschi: the PMs we had.
133 00:16:33.120 ⇒ 00:16:38.020 Luke Scorziell: the… Do you have other competitors put out, like, AI…
134 00:16:38.450 ⇒ 00:16:42.760 Luke Scorziell: forward stuff yet, or is Third Bridge, like, Catching up.
135 00:16:42.760 ⇒ 00:16:52.390 Melanie Vladimirschi: ThirdBridge is definitely, like, I would say, I think everyone’s on the same page. I mean, you… also with these kinds of things, it’s really hard because…
136 00:16:53.030 ⇒ 00:16:56.490 Melanie Vladimirschi: you only see what goes out on LinkedIn, or, like.
137 00:16:56.490 ⇒ 00:16:56.950 Luke Scorziell: Yeah.
138 00:16:57.200 ⇒ 00:17:02.230 Melanie Vladimirschi: You’ve heard, maybe, from a cli- or, like, heard from a friend of a friend, or a client.
139 00:17:02.230 ⇒ 00:17:02.930 Luke Scorziell: And…
140 00:17:02.930 ⇒ 00:17:07.589 Melanie Vladimirschi: mentioned to an expert, you know, so there’s not a… I don’t have a lot of,
141 00:17:08.480 ⇒ 00:17:21.200 Melanie Vladimirschi: what’s the word? Like, trust is not the word, but, like, I don’t really know what our competitors are necessarily doing better or worse.
142 00:17:22.540 ⇒ 00:17:26.339 Melanie Vladimirschi: But yeah, some of the, like, one that comes to mind, like, Pro Sapient.
143 00:17:26.460 ⇒ 00:17:33.579 Melanie Vladimirschi: they’re super… they’ve always been, like, the AI expert network, so everything they put out, I think, is very…
144 00:17:35.370 ⇒ 00:17:47.220 Melanie Vladimirschi: interesting, whether clients are using these or not is another question. Like, one of the things that they… I know it’s, like, on their LinkedIn, but it’s a product that they’re offering, which is AI-moderated calls.
145 00:17:49.650 ⇒ 00:18:00.860 Melanie Vladimirschi: that’s something that clients are asking about more and more, but it’s different to the internal productivity AI use case that I mentioned, which is more of, like, I think what you were going for.
146 00:18:00.860 ⇒ 00:18:01.740 Luke Scorziell: Yeah.
147 00:18:02.340 ⇒ 00:18:03.270 Luke Scorziell: Well, it’s…
148 00:18:03.580 ⇒ 00:18:05.020 Melanie Vladimirschi: Internally, like…
149 00:18:05.020 ⇒ 00:18:19.349 Luke Scorziell: Yeah, it’s interesting, too, because we built ourselves, like, a case study agent, and it… you can just interview… so, like, if an engineer does a project, then we send this to them, and then…
150 00:18:19.990 ⇒ 00:18:26.650 Luke Scorziell: they just talk to the agent, and then it will write up a case study. So I was kind of also thinking that’d be interesting for.
151 00:18:26.860 ⇒ 00:18:30.139 Melanie Vladimirschi: For forum calls, right?
152 00:18:30.140 ⇒ 00:18:31.630 Luke Scorziell: Or you’re, like…
153 00:18:31.910 ⇒ 00:18:40.890 Luke Scorziell: I mean, right now, you’re kind of bottlenecked probably by the time that the experts have to prep and do forum calls, versus if you could kind of
154 00:18:42.120 ⇒ 00:18:53.220 Luke Scorziell: have it, like, guided by them, I guess, to a degree. It’s, like, the output, I would imagine, would be… could be significant. And then it’s, like, just the customization, too, where you can have, like, a whole…
155 00:18:53.340 ⇒ 00:18:59.699 Luke Scorziell: Or if a client has a specific question, and then they just want to submit that to the AI, and then the AI can kind of…
156 00:18:59.940 ⇒ 00:19:01.450 Luke Scorziell: do that,
157 00:19:02.170 ⇒ 00:19:17.740 Luke Scorziell: Yeah, so it’s… it’s… we find it… I mean, I’m like, this is kind of an interesting, scary time, like, I don’t fully know what’s gonna happen. It’s also exciting, because there are so many problems, I guess, that we get to solve.
158 00:19:17.740 ⇒ 00:19:21.399 Melanie Vladimirschi: different layers. Have you heard of, ListenLabs?
159 00:19:21.910 ⇒ 00:19:23.979 Luke Scorziell: No, I don’t think so. Libs and Labs?
160 00:19:23.980 ⇒ 00:19:37.929 Melanie Vladimirschi: Listen Labs, so it’s… they’re… I think they just raised their Series B, and they’re doing a lot in the, like, moderated conversation space. Like, 11 Labs is the one that’s, like, voice agents.
161 00:19:40.530 ⇒ 00:19:49.409 Melanie Vladimirschi: I think with Forum, and some of the calls that we’re doing, and specifically, like, our consulting clients are really interested in this, because
162 00:19:49.680 ⇒ 00:19:55.970 Melanie Vladimirschi: They get to… Offload their, like.
163 00:19:56.530 ⇒ 00:20:06.660 Melanie Vladimirschi: whatever. For a call, for example, they have their question set, they train an agent on their question set, and then the agent runs the call with
164 00:20:06.660 ⇒ 00:20:20.930 Melanie Vladimirschi: an expert, so that’s, like, the… what ProSapien is doing as well with the AI-moderated calls, right? So it’s, like, a similar product, we’re just not developing it in-house, we’re relying on our clients to come to us with their preferred vendors of interest, and
165 00:20:21.310 ⇒ 00:20:25.090 Melanie Vladimirschi: doing some, like, potential partnerships with them, so…
166 00:20:25.750 ⇒ 00:20:30.860 Melanie Vladimirschi: So yeah, I’m not, like, to be clear, I’m aware of everything that’s happening.
167 00:20:30.860 ⇒ 00:20:35.530 Luke Scorziell: But I’m not at, like, the forefront of any of this. I think, like…
168 00:20:35.870 ⇒ 00:20:50.319 Melanie Vladimirschi: for surveys, I’m just gonna, like, benefit from… from everything that gets… like, all of the changes that are made to the connections, like, platform, whether it’s intranet, whether it’s Specialist Expert Hub, whether it’s, like, client portal.
169 00:20:50.320 ⇒ 00:20:58.330 Melanie Vladimirschi: But they are, like, the team is building all of that now. And if you’d like, I can ask them, like.
170 00:20:58.390 ⇒ 00:21:00.909 Melanie Vladimirschi: who they’re working with.
171 00:21:00.910 ⇒ 00:21:01.490 Luke Scorziell: Yay.
172 00:21:02.610 ⇒ 00:21:03.519 Luke Scorziell: I mean, I would just be.
173 00:21:03.520 ⇒ 00:21:04.429 Melanie Vladimirschi: Get out.
174 00:21:04.940 ⇒ 00:21:08.290 Luke Scorziell: I’d just be curious even to, like…
175 00:21:09.280 ⇒ 00:21:16.970 Luke Scorziell: Yeah, like, I… I was also just kind of wanting to catch up, wasn’t just… just to, like, let me see how we can, budget.
176 00:21:17.670 ⇒ 00:21:22.190 Luke Scorziell: Yeah, like, because I’ve just been curious, like, how our companies, like Third Bridge.
177 00:21:22.330 ⇒ 00:21:25.449 Luke Scorziell: And other service companies responding to…
178 00:21:25.790 ⇒ 00:21:28.230 Luke Scorziell: to AI, and then I think just,
179 00:21:28.920 ⇒ 00:21:34.810 Luke Scorziell: Yeah, like… so, it would be interesting, I don’t know if there are, like, other people that would be open to talking.
180 00:21:35.240 ⇒ 00:21:38.759 Luke Scorziell: Cause that, yeah, I think we’re kind of…
181 00:21:41.420 ⇒ 00:21:53.259 Luke Scorziell: just saying, like, a pretty cool opportunity as, like, an up-and-coming firm to work with. Like, we work faster than a lot of the consulting firms, we are cheaper, like, we’re more native to…
182 00:21:53.400 ⇒ 00:21:56.910 Luke Scorziell: Like, the, the,
183 00:21:58.130 ⇒ 00:22:11.339 Luke Scorziell: like, we have developers, but then it’s also, like, we’re very AI-native, so it’s not just, like, we’re kind of shifting focus, but we’ve really grown up in the last couple years during this time. And so, yeah, it’s been cool to see, like, just…
184 00:22:11.480 ⇒ 00:22:12.570 Luke Scorziell: Comparing it.
185 00:22:12.780 ⇒ 00:22:18.910 Luke Scorziell: Even, like, against some of the bigger consulting firms, who do implementation, it’s like.
186 00:22:19.440 ⇒ 00:22:27.559 Luke Scorziell: Yeah, we just don’t have the headcount and the, like, slow-moving… Nature of them.
187 00:22:27.920 ⇒ 00:22:32.680 Luke Scorziell: Yeah, and we’re also not tied down to, like, the hourly…
188 00:22:33.720 ⇒ 00:22:40.830 Luke Scorziell: Like, rates that consulting firms have typically always gone with, and so now it’s… which is interesting now, because they’re finding that it’s, like.
189 00:22:41.410 ⇒ 00:22:45.570 Luke Scorziell: If you can do everything significantly faster, then…
190 00:22:45.670 ⇒ 00:22:50.240 Luke Scorziell: How do you actually charge? And, then it’s, it’s like…
191 00:22:50.600 ⇒ 00:22:56.129 Luke Scorziell: They’re doing projects that… yeah, it’s just interesting to see how we’ve kind of come up.
192 00:22:56.640 ⇒ 00:22:57.640 Luke Scorziell: been, like…
193 00:22:57.930 ⇒ 00:23:04.680 Luke Scorziell: a very, unique vertical, I guess, and kind of are able to compete with some of the
194 00:23:05.110 ⇒ 00:23:09.640 Luke Scorziell: Like, larger players, so, yeah, yeah.
195 00:23:10.630 ⇒ 00:23:11.300 Melanie Vladimirschi: Right.
196 00:23:11.900 ⇒ 00:23:21.590 Melanie Vladimirschi: Well, I can… I’m sure people would be open to having a conversation. I’ll try to figure out who the best person is, but if you have any, like.
197 00:23:22.040 ⇒ 00:23:27.990 Melanie Vladimirschi: I don’t know, like, one-pagers, decks, materials that you can send me, that would be helpful.
198 00:23:28.270 ⇒ 00:23:33.979 Luke Scorziell: Yeah, I can send you… we have, like, our AI… And I just…
199 00:23:34.160 ⇒ 00:23:41.790 Luke Scorziell: I wrote a white paper more for, like, ad agencies, but, kind of showing, like, how we’ve worked with them, but I can send you a…
200 00:23:41.790 ⇒ 00:23:48.349 Melanie Vladimirschi: What’s your, like, target, like, target audience in terms of, like, who’s your ideal client?
201 00:23:49.010 ⇒ 00:23:51.280 Luke Scorziell: Yeah, I think it’s…
202 00:23:52.120 ⇒ 00:24:01.049 Luke Scorziell: we’re kind of thinking through all this stuff right now, but we’ve done a lot with, like, e-commerce, brands and, and, CPG.
203 00:24:01.270 ⇒ 00:24:11.519 Luke Scorziell: We’ve done, like, some SaaS products, we are working with, like, an ad agency right now. We’ve worked with a home services client. I think, like.
204 00:24:13.070 ⇒ 00:24:13.760 Melanie Vladimirschi: the thing.
205 00:24:13.760 ⇒ 00:24:15.559 Luke Scorziell: So it’s… it’s a little bit…
206 00:24:16.780 ⇒ 00:24:23.200 Luke Scorziell: agnostic right now. I think we’re working with some partners, Who…
207 00:24:23.860 ⇒ 00:24:28.860 Luke Scorziell: are growing a lot that I think we’ll kind of want to… like…
208 00:24:29.180 ⇒ 00:24:36.000 Luke Scorziell: tag on to a little bit, and I think the vertical there that we’re looking at is, like, retail and e-commerce.
209 00:24:36.200 ⇒ 00:24:42.890 Luke Scorziell: So right now, we don’t have, like, we’re not super segmented, but just…
210 00:24:44.020 ⇒ 00:24:50.009 Luke Scorziell: So, yeah, we’ve done a lot of work with different people. But yeah, one of our biggest clients so far has been, like, a…
211 00:24:50.330 ⇒ 00:25:00.110 Luke Scorziell: they’re, like, a pest control, brand down in Texas, and they have… they had, like, all these customer service reps that needed,
212 00:25:01.150 ⇒ 00:25:07.409 Luke Scorziell: that it was just confusing for them to be able to, like, talk through the different services that this company offered.
213 00:25:07.670 ⇒ 00:25:10.839 Luke Scorziell: It’s, like, upwards of, like, 20 or 30 services that they do.
214 00:25:11.000 ⇒ 00:25:15.569 Luke Scorziell: And each of them has, like, a separate order of operations,
215 00:25:15.900 ⇒ 00:25:23.099 Luke Scorziell: And so we built them, like, an internal knowledge base, to where now, like, a user can ask, like.
216 00:25:23.290 ⇒ 00:25:29.320 Luke Scorziell: oh, this cl… this person is asking for this, like, who do I need to call and set up to do… to do this?
217 00:25:29.480 ⇒ 00:25:34.190 Luke Scorziell: Similar thing with, like, sales agents and reps, where they can, like.
218 00:25:34.480 ⇒ 00:25:38.519 Melanie Vladimirschi: Use the knowledge base and the call to sell.
219 00:25:38.840 ⇒ 00:25:39.800 Luke Scorziell: And…
220 00:25:40.200 ⇒ 00:25:51.429 Luke Scorziell: So, yeah, it’s… it’s been, like, I think our primary things are, like, we’re really good at data, and we’re really good at solving problems, and… and… and we’re finding that AI is a great way to do that, so…
221 00:25:51.950 ⇒ 00:25:52.790 Melanie Vladimirschi: Totally.
222 00:25:53.030 ⇒ 00:25:54.190 Melanie Vladimirschi: That’s great.
223 00:25:54.530 ⇒ 00:26:00.399 Melanie Vladimirschi: I… yeah, if you have anything that you can send over, that would be helpful, and I can,
224 00:26:01.130 ⇒ 00:26:14.480 Melanie Vladimirschi: yeah, I would need to do some digging on our end to be… because, like, obviously ThirdBridge is huge, and it’s so… there are so many different, like, products, and teams, and so…
225 00:26:14.710 ⇒ 00:26:15.110 Luke Scorziell: Dude.
226 00:26:15.710 ⇒ 00:26:17.010 Melanie Vladimirschi: right person.
227 00:26:17.280 ⇒ 00:26:24.540 Luke Scorziell: If there are ways, too, that I can be helpful to you, I mean, obviously, I’ll try to get that over, but if, yeah, if you ever have questions, or just, like.
228 00:26:25.610 ⇒ 00:26:33.490 Luke Scorziell: trying to figure out AI on the surveys team, and just want, like, a… because we’re… we do, like, we’re doing, like, trainings and stuff, too.
229 00:26:33.830 ⇒ 00:26:38.800 Luke Scorziell: just interesting to… I don’t know, that’s, again, like we said, like, moving pretty fast, so…
230 00:26:40.620 ⇒ 00:26:43.539 Luke Scorziell: Yeah, that’s exciting to hear it’s grown a lot, too.
231 00:26:44.870 ⇒ 00:26:45.330 Melanie Vladimirschi: Yay!
232 00:26:45.330 ⇒ 00:26:48.040 Luke Scorziell: The LA team has doubled, or maybe.
233 00:26:48.960 ⇒ 00:26:57.880 Melanie Vladimirschi: Yeah, I mean, we’re at zero, so… But… yeah, it’s… it’s good.
234 00:26:58.610 ⇒ 00:27:05.959 Melanie Vladimirschi: Great. Anyway, it was great to hear more, and I’m glad, yeah, glad to hear that that’s…
235 00:27:06.520 ⇒ 00:27:08.480 Melanie Vladimirschi: Like, that’s also the…
236 00:27:08.710 ⇒ 00:27:17.029 Melanie Vladimirschi: I would say the role that you’re doing as well, because it is, like, a really interesting space right now, and I’m sure, like, even if
237 00:27:17.230 ⇒ 00:27:37.060 Melanie Vladimirschi: at Thurbridge, I think right now there may be, like, internal teams doing kind of a similar thing already, so even if it doesn’t work out for this time, like, I think many, many organizations will need help with all these different use cases, so… But in any case, I will try to find out who the right people
238 00:27:37.060 ⇒ 00:27:37.550 Melanie Vladimirschi: to speak to.
239 00:27:37.550 ⇒ 00:27:44.890 Luke Scorziell: Yeah, no, that’d be great, I appreciate that. Yeah, so… yeah, it was fun to catch up, and I don’t know, I’m always…
240 00:27:45.020 ⇒ 00:27:54.040 Luke Scorziell: But we’re just finding a special place, I guess, in my heart. The more time goes on, the less I am, like, oh man, it was so hard. It’s like, oh, I learned a lot and got to…
241 00:27:54.390 ⇒ 00:28:06.739 Melanie Vladimirschi: Right? Everyone says this, it’s like, oh, you know, grass is always greener, and then you’re like, oh, it’s actually good. Yeah, yeah, and I think that… But I think people think they’re gonna change a lot now. Let’s see.
242 00:28:07.160 ⇒ 00:28:14.629 Luke Scorziell: Yeah, no, I mean, I’ve always thought, like, that that role would become somewhat redundant in AI. That’s really…
243 00:28:14.970 ⇒ 00:28:19.829 Luke Scorziell: Light took off, so, it’ll be interesting. We’re gonna be in, like, a whole new economy.
244 00:28:22.820 ⇒ 00:28:25.189 Luke Scorziell: But yeah, well, I don’t know.
245 00:28:25.480 ⇒ 00:28:27.730 Luke Scorziell: I guess Tulsa here, hello, if you see him.
246 00:28:27.730 ⇒ 00:28:30.240 Melanie Vladimirschi: I will. I will. I’ll let him know.
247 00:28:30.240 ⇒ 00:28:36.500 Luke Scorziell: Cool. Well, I’ll follow up with some case studies and… Perfect. Yeah, send you some of our stuff, so…
248 00:28:36.500 ⇒ 00:28:41.129 Melanie Vladimirschi: Amazing. Thank you so much, Luke, and it’s great to chat with you. I’m sure we’ll be in touch.
249 00:28:41.130 ⇒ 00:28:43.280 Luke Scorziell: Yeah, that sounds good. Alright, thanks, Dylan.
250 00:28:43.930 ⇒ 00:28:44.570 Luke Scorziell: Bye.