Meeting Title: Uttam Kumaran’s Personal Meeting Room Date: 2024-12-20 Meeting participants: Uttam Kumaran, Nicolas Sucari, Sahana Asokan
WEBVTT
1 00:01:40.290 ⇒ 00:01:40.740 Sahana Asokan: Hello!
2 00:01:40.740 ⇒ 00:01:41.679 Uttam Kumaran: Hey! How are you?
3 00:01:41.680 ⇒ 00:01:43.060 Sahana Asokan: Good. How are you?
4 00:01:43.060 ⇒ 00:01:45.660 Sahana Asokan: Good! Nice to meet you? How’s the week going
5 00:01:46.450 ⇒ 00:01:55.209 Sahana Asokan: just like holidays next week? So wrapping up work, really, till like I think, Jan, so I’m excited, for like small break. How about you.
6 00:01:55.440 ⇒ 00:02:14.510 Uttam Kumaran: Good. Yeah, I don’t think we’ll be wrapping up. I think we’re gonna keep. Probably keep pushing, but a lot of the client stuff slows down for sure. Which gives us a lot of time to like plan for next year. Which we have a lot of lot of that to do so, I’m actually very excited for that. And then, yeah, take a few days off for holidays, so we’ll be good.
7 00:02:14.740 ⇒ 00:02:15.470 Sahana Asokan: Nice.
8 00:02:15.850 ⇒ 00:02:21.279 Uttam Kumaran: Yeah, thank you for taking the time. I know Nico is just joining now. Hey, Nico.
9 00:02:21.930 ⇒ 00:02:23.240 Nicolas Sucari: Hey, Sahana, how you doing.
10 00:02:23.460 ⇒ 00:02:24.560 Sahana Asokan: Hello! How are you?
11 00:02:24.560 ⇒ 00:02:25.210 Uttam Kumaran: Hey!
12 00:02:25.210 ⇒ 00:02:26.870 Nicolas Sucari: I’m doing good. How about you?
13 00:02:27.400 ⇒ 00:02:42.129 Sahana Asokan: I’m good. It’s nice to meet with both of you. I think I met with Robert earlier this week, and I I’m sorry to push up, push on like a timeline against you guys. I was just. I was also planning kind of my contracting work for 2025. So I just wanted to.
14 00:02:42.130 ⇒ 00:02:42.780 Uttam Kumaran: No.
15 00:02:42.780 ⇒ 00:02:43.490 Sahana Asokan: This that’s.
16 00:02:43.490 ⇒ 00:02:55.110 Uttam Kumaran: This perfect? Yeah, I mean, yeah, I guess I think both of us have a lot of context. So really, just wanted to. Just say Hi, and kind of give you a little bit more background on sort of brain forge and
17 00:02:55.394 ⇒ 00:03:17.025 Uttam Kumaran: you know who we are and sort of how we work. So Brainforge is a company that I started about a year and a half ago. You know. Robert has been a close partner of mine. We’ve been doing a lot of client work together and sort of now he’s he’s sort of folding in and is becoming a partner in Brainforge but really a lot of where we started. The company is
18 00:03:17.320 ⇒ 00:03:40.680 Uttam Kumaran: in data services. So we basically implement like Dbt, snowflake, for a lot of people. And in addition, our have leaned on Robert. And now kind of in one house, we’re offering basically full stack data. So also analysis and bi so that’s a lot of the work that we’ve done for clients so far over the past year and a half we’ve worked for a variety of folks. Across Ecom. Cpg manufacturing.
19 00:03:40.680 ⇒ 00:03:56.609 Uttam Kumaran: you know, kind of the regular data stuff like helping clients go from 0 to one. And then we’re also starting over the last like 3, 4 months to implement AI internally. And then also, we’re we’re starting to offer generative AI related services like building bots and knowledge bases and things like that.
20 00:03:56.931 ⇒ 00:04:01.538 Uttam Kumaran: So, yeah, really, just wanted to kind of hear a bit about your background and sort of
21 00:04:01.870 ⇒ 00:04:17.509 Uttam Kumaran: kind of hear like what interested you? You know, working, you know, with us. If I’m talking to Robert, and then, you know, happy to answer any questions, and also kind of just share a bit about how we sort of have Nico maybe share a little bit about how we run client engagements. And stuff like that. So.
22 00:04:18.110 ⇒ 00:04:31.109 Sahana Asokan: Yeah, for sure. So I’m Sahana. I’m based out of Brooklyn, New York. I’ve been in New York for around 4 years I was born and raised in the bay my parents are still in California, so split my time between the west coast and the east coast.
23 00:04:31.676 ⇒ 00:04:39.269 Sahana Asokan: But yeah, I would say, from a career perspective, I’ve been within the product data, analytics, data, analytics, space for the past 6 years.
24 00:04:39.440 ⇒ 00:04:48.739 Sahana Asokan: I started off my career at Schwab, which was financial services. Then my made my way to Bloomberg, which was, is obviously more Fintech
25 00:04:49.276 ⇒ 00:04:54.469 Sahana Asokan: I was at Chainalysis, which is not sure, if you’re familiar, it’s essentially a blockchain.
26 00:04:55.165 ⇒ 00:05:00.820 Sahana Asokan: Like fraud analytics tool. Sorry. Give me one sec.
27 00:05:01.130 ⇒ 00:05:01.790 Uttam Kumaran: Yeah.
28 00:05:13.347 ⇒ 00:05:14.630 Sahana Asokan: Sorry, my- my.
29 00:05:14.630 ⇒ 00:05:15.419 Uttam Kumaran: You’re totally fine.
30 00:05:15.420 ⇒ 00:05:37.510 Sahana Asokan: I think she was on a call. Yeah. So I was at Bloomberg. I was doing more Fintech still supporting Esg and Company financials products. I think a lot of times when people think Bloomberg, they think of the terminal. But I was actually on the product side. So we’re essentially packaging up the data and selling it to different hedge funds.
31 00:05:37.896 ⇒ 00:05:57.989 Sahana Asokan: and basically teaching them how to use that data for their modeling perspective. So customer facing that was kind of where I kind of started getting interest in more customer facing opportunities. It wasn’t like that at chainalysis, but I decided to start contracting last year. So I started just on upwork.
32 00:05:58.040 ⇒ 00:06:02.719 Sahana Asokan: And that’s kind of where I started, almost like an analytics consulting as kind of like a.
33 00:06:02.720 ⇒ 00:06:03.120 Uttam Kumaran: Nice.
34 00:06:03.453 ⇒ 00:06:12.789 Sahana Asokan: And yeah, I’ve been, you know. Now, I’m at calendly, which is, you know, more like just traditional tech. I’m on doing the same thing. Product, analytics.
35 00:06:12.790 ⇒ 00:06:13.190 Uttam Kumaran: Yes.
36 00:06:13.190 ⇒ 00:06:19.000 Sahana Asokan: I support trust and safety. Workflows, integrations, and meeting intelligence. So.
37 00:06:19.000 ⇒ 00:06:19.520 Uttam Kumaran: Okay.
38 00:06:19.520 ⇒ 00:06:24.259 Sahana Asokan: I would say in the span of my career, I’ve really had the opportunity to kind of
39 00:06:24.510 ⇒ 00:06:29.760 Sahana Asokan: scale from different types of businesses which has given me a lot of knowledge in the sense of
40 00:06:30.130 ⇒ 00:06:50.790 Sahana Asokan: adapt according to different business problems. And even within my contracting space. You know, I contract a lot for like really small startups, some of them don’t even really have funding, but given me the opportunity to like get really niche with it, like I was supporting like a music matchmaking app where it was like.
41 00:06:50.790 ⇒ 00:06:51.170 Uttam Kumaran: Nice.
42 00:06:51.170 ⇒ 00:07:06.110 Sahana Asokan: How to like match make, you know musicians to producers. Or and I was hoping, the product manager with her algorithm development in respect to like, how can we fine tune the algorithm to get us better match results right? Like, that’s just one example.
43 00:07:06.250 ⇒ 00:07:20.619 Sahana Asokan: So that’s something I started last year. I’ve loved it. I have around 4 to 5 contracts right now. I think my biggest problem with upwork. And this is kind of a pain point that I had discussed with Robert is just.
44 00:07:20.890 ⇒ 00:07:39.685 Sahana Asokan: I think, the commitment right. I think it’s very variable throughout the year, like right now, my contracts are paused. Because it’s the holidays. Obviously, upwork takes like a fee from me as, and it’s just. It’s not like the best. I also think, just like the transparency and trust between.
45 00:07:40.190 ⇒ 00:07:55.870 Sahana Asokan: you know your client and a contractor is kind of hard and upwork a lot of the times. I see that like if I have 10 h, and if I’m working with like a client in India, for example, they really want to understand what those 10 h are dedicated to. And they want results really fast.
46 00:07:56.240 ⇒ 00:07:58.910 Sahana Asokan: Unfortunately, that’s just not how it works with data, right? Like a lot of.
47 00:07:58.910 ⇒ 00:08:17.140 Uttam Kumaran: Yes, not at all. Yeah. You have no idea how long. I mean, we me and you could talk about this because a lot of people will ask, like, Okay, how long is this gonna take? I’m like, until we get in there. I don’t know, like I have no idea how bad it is, and you don’t really know how how bad it is, either. So one of us has to like, look under the hood, and I totally feel your pain. Yeah.
48 00:08:17.420 ⇒ 00:08:41.129 Sahana Asokan: Yeah. So it’s kind of like, I’m just like, I kind of want something where there’s more trust. I want to be treated like as a peer, almost like a coworker instead of like, okay, I’m billing 10 h like I’m getting value from each hour that I’m billing, and I get it. A lot of these startups don’t have a lot of funding, so they really want to see what value the investment and talent is going to return to them, so I totally empathize with them. But I think that’s something I’m trying to
49 00:08:41.350 ⇒ 00:08:46.745 Sahana Asokan: not move away from. But I kind of want something a little bit more consistent where there’s more trust.
50 00:08:47.170 ⇒ 00:08:51.388 Sahana Asokan: I think it put takes less pressure off of me.
51 00:08:52.210 ⇒ 00:09:11.089 Uttam Kumaran: All those issues, all those issues make a lot of sense. It’s really why I like, when I started the company I’ve done contracting before on the side. And then, basically, I had a choice like, do I stay in like balancing contracts, making a good amount of money? But then, kind of like, it’s still chaos. And then, my, I my, was, I was like.
52 00:09:11.280 ⇒ 00:09:36.229 Uttam Kumaran: what I’m gonna do is we’ll just make this way bigger. I have a lot of friends that are very interested in doing that in the data side. But the management of the clients, the management of billing sort of like clients, churning buyers like all that stuff it’s hard you could get, you can, but the money is really great, but like it still becomes a lot of stress. So then for me, I was like, Okay, cool. I think there’s definitely a lot of demand for still great data people. A lot of companies
53 00:09:36.230 ⇒ 00:09:52.519 Uttam Kumaran: are still going 0 to one but I think I was like, Okay, one. I want to create a place where people that are contracting like can come facilitate that through Brainforge. And the nice thing is we’re established in the space we’re small. But we’re we’re growing. And a lot of other stuff we do is
54 00:09:52.520 ⇒ 00:10:07.469 Uttam Kumaran: we’re starting to standardize a lot. So standardizing a lot of the services around analysis, but also around Dbt and data engineering. And the nice thing about having sort of like that full stack is that we come in and people will hire us. They’ll say I have an analysis problem, but they end up having a, it’s actually a data modeling issue
55 00:10:08.200 ⇒ 00:10:29.749 Uttam Kumaran: like we need to do de work. And instead of saying, like, we don’t do that, it’s more of like we do do that, and we are your partner to kind of make that happen. And so it’s been really, really rewarding. And then to your point about getting to work with a lot of businesses like that’s ultimately like my curiosity. And what I love about this is work with so many different types of people and businesses models.
56 00:10:29.750 ⇒ 00:10:43.940 Uttam Kumaran: And it’s been super fun to do that. And totally see your point, and, like some companies, are just can’t afford. But the problem with that is is, I. I take that partly as like, maybe they’re not ready, because if they can’t afford someone like for 10 h.
57 00:10:43.940 ⇒ 00:11:12.529 Uttam Kumaran: we’re pretty cheap like, what? How are you gonna maintain this? The second thing is, we even deal with some big companies that are wanna like, kinda say, like, Okay, we have a limited budget. I’m like, you’re not. This is an investment like you’re not gonna be able to do it. And then for us also, it’s getting more confident in what we have to sell. Look, we’ve implemented Snowflake, Dbt, 5. Train bi every at like so many companies. Now that I’m confident we’re the fastest people to do it. We’ll save you a lot of future headache. And the way we architect governance all that stuff.
58 00:11:12.700 ⇒ 00:11:31.429 Uttam Kumaran: and like we’re nice people doing it like you don’t have to hire 5 people, and like one of those doesn’t work out. And also, like we have relations, all the vendors. So I help you make the best decision. And I’m like, Hey, we’re worth what we charge. So I kind of like, try to build that up and build. Be more confident. And also we what I tell
59 00:11:31.660 ⇒ 00:11:37.419 Uttam Kumaran: you know our staff is that we’re only as good as like our worst person on our team. So actually, brain forge
60 00:11:37.420 ⇒ 00:11:50.379 Uttam Kumaran: is just the people that work for the company in a long tail. We’re mainly just facilitating people to work with clients, right? And so really for me, our product quality and the quality of our services, the quality of the people we have.
61 00:11:50.380 ⇒ 00:12:13.919 Uttam Kumaran: So this isn’t like what a lot of agencies do is they compete on price? That’s like, not what we’re gonna do. That’s a fast track to just like really sacrificing like the quality of our work. In fact, we want to take on tougher and tougher problems, right? And I want to work with people who really want to take on the toughest analysis problem, not just like, Hey, how many like, how much do we sell yesterday? But like, hey? How should we cohort our customers most effectively
62 00:12:13.920 ⇒ 00:12:31.529 Uttam Kumaran: like the really like sort of like pivotal questions that these companies have. That’s the sort of stuff I want to do. And you know, that’s the stuff that we have a track record of doing. And we’re sort of building an analysis culture around so totally agree with kind of like the challenges that that you mentioned.
63 00:12:32.160 ⇒ 00:12:52.049 Sahana Asokan: Yeah, I think it actually really stood out to me that it’s not just, you know, analytics, it comes with, like, you know, infrastructure. And like the data engineering aspect, too, because I think a really big pain point that I come across a lot is like, like, for example, I was doing some mixed panel work. And I realized a lot of the events were tracked wrong. And I was like, Okay, we need to fix this.
64 00:12:52.110 ⇒ 00:13:10.579 Sahana Asokan: But they don’t have the engineering resources to fix those tracked events and to implement the right properties right? And I think that is kind of where the foundation lacks. If you want good analysis. And if you want good insights, you know the data that you’re tracking needs to be really strong as well. And then they’re like, okay, like, we need to put up another posting on upwork
65 00:13:10.630 ⇒ 00:13:31.169 Sahana Asokan: and hire someone that could fix this for us. Until then, like your contract is on pause. And that’s the kind of stuff I’m trying to avoid for 2025, because it’s like I can use that time and invest it in like a more like long term secure company where you know the work is consistent, but also like, I don’t have to come across these like
66 00:13:31.170 ⇒ 00:13:48.309 Sahana Asokan: very like beginner level issues. That’s kind of where I was like, okay, this makes sense to me because it’s like like the package, right? It’s like, it’s like, not just analytics. It’s not just engineering. It’s like everything you need for, like a strong, for strong insights, for strong strategy, development, etc. So.
67 00:13:48.310 ⇒ 00:13:57.099 Uttam Kumaran: Yeah. And and even for you know, what I tell clients is that analysis is like a last mile problem, because data engineering and data modeling. A lot of our clients don’t care.
68 00:13:57.100 ⇒ 00:13:57.420 Sahana Asokan: Yeah.
69 00:13:57.420 ⇒ 00:14:11.009 Uttam Kumaran: They don’t even know what we’re talking about. And it’s tough, because I worked in an internal org. And so that was like all I did. But you’d our our work on the data. Engineering modeling side goes to a dashboard. And so that dashboard product or the analysis
70 00:14:11.010 ⇒ 00:14:39.570 Uttam Kumaran: is where we really shine. But it’s again, it’s a full stack issue where they may not care about like 80% of the work. But the 20% really matters, so that we need great analysis to pair with everything, and then in terms of like our team. And I’ll I’ll kind of let Nico, after this talk a little bit about how we run some of these projects. But like, we have an engineering team now, maybe like 6 or 7 people across the full stack. So like I cover a lot of de work still. But we have. And like analytics, engineers, we have
71 00:14:39.840 ⇒ 00:14:59.230 Uttam Kumaran: and also we have analysts. And then we also have people on the AI side. So we do like one a weekly sort of engineering meeting with everybody where I kind of just understand, like how people were getting engineering work done broadly. And then also, we’re starting to build more like internal platform tooling for everyone on the data stack. So how do we do like when we bring on a client to snowflake scripts, to set everything up
72 00:14:59.270 ⇒ 00:15:18.630 Uttam Kumaran: playbooks on? How to like do certain analysis? Naming conventions, all that sort of stuff we’re we’re we’re implementing and making available for the team. And then, just like, How do we add more better alerting for clients like, how do we know when things go wrong? Sort of making some of those decisions kind of like you would make them internally in the company. But in fact, we’re making them for like
73 00:15:18.680 ⇒ 00:15:41.900 Uttam Kumaran: several clients simultaneously, and having, like a point of view on like, how how do we effectively run these data engagements, but not only like, how do we run it? Where the clients happy? How do we run it? Where, like the engine, like, we run an engineering team. There needs to be alerting. There needs to be code review process. Stuff like that is is what we’re thinking about so definitely like, if you have opinions on that, too, and there’s a little bit more of like a squad like. Of course.
74 00:15:41.980 ⇒ 00:15:52.119 Uttam Kumaran: everybody’s working for clients, but at least we have some sort of shared learning sort of function as well, which I’m which I love out of everything. So
75 00:15:52.471 ⇒ 00:15:58.250 Uttam Kumaran: and yeah, maybe, Nico, do you want to talk a little bit about like how we run like one of these data engagements.
76 00:15:58.590 ⇒ 00:16:15.590 Nicolas Sucari: Of course, I mean with every client we have meetings during the week where we gather requirements, we try to share what we’ve been doing during the week to we demo dashboards, or anything that we have to share with the clients we are now trying to change a little bit or process in order to plan ahead of the week
77 00:16:15.590 ⇒ 00:16:38.929 Nicolas Sucari: what will be the tasks that we will be working for the clients, and then we have some meetings with the engineers or the analysts, so that we can assign those tasks and start tracking better all of it when we are starting the task when it’s ending, setting due dates, setting estimations, and trying to try to answer all of the questions before we start one of those kind of tickets
78 00:16:38.930 ⇒ 00:16:55.420 Nicolas Sucari: we’re working with notion. We’re trying to have every every piece of information that we need, and that and any documentation that we are creating is in notion. All of the task boards are in notion we are. We have now a person that is helping us on all of that organization. So we have, like
79 00:16:55.420 ⇒ 00:17:17.059 Nicolas Sucari: all of the tasks in one database. That database has these different views for each engineer, for each analyst and also per client, so that we can have everything in one place, and the idea is to have great communication. We use slack in order to maintain the communication between us, and and then we jump into meetings when we need to solve
80 00:17:17.060 ⇒ 00:17:20.882 Nicolas Sucari: like like special special things. Right?
81 00:17:21.520 ⇒ 00:17:47.179 Nicolas Sucari: the idea is, each day we kind of follow on us each other to understand what we’ve been working on and and give like a little update. And we share weekly updates with the client in the meeting. And after the meeting, too. So it’s kind of a scrum process we’re we’re missing some of those ceremonies like the retrospective yet. But we should start doing them so
82 00:17:47.180 ⇒ 00:18:08.510 Nicolas Sucari: any other. I don’t know idea or request that analyst can have. That’s gonna be great. So if you, Sahana, start working and see that we are lacking something. And you see that something we can do, it’s gonna be worth it. Just mention it. And we can obviously add it to the process. We are very flexible in that. We kind of try to improve every week.
83 00:18:08.510 ⇒ 00:18:34.900 Nicolas Sucari: So yeah, we have like team meetings with the entire team in Brainforge, and that if you start working, we’ll be glad to have you there also. And yeah, that’s how we we work with clients. At the end of the day we are a team. We know that we have the analysts that prepare the dashboards, share the analysis with the client, and try to demo with them in the meetings. But before that we have the analytics engineering we have. That’s doing all of the work.
84 00:18:34.900 ⇒ 00:18:39.400 Sahana Asokan: And if we don’t communicate between each other like it’s really difficult to get.
85 00:18:39.400 ⇒ 00:18:49.089 Nicolas Sucari: Things done. So yeah, we kind of try to to keep all of us in touch and and aim for the best deliverables that we can do right.
86 00:18:49.850 ⇒ 00:18:54.030 Sahana Asokan: Yeah, okay, yeah, that sounds good. It makes sense to me. So thank you for that.
87 00:18:55.000 ⇒ 00:19:02.090 Uttam Kumaran: Cool. Yeah. Any other questions that we can answer anything about the company or clients, or.
88 00:19:02.180 ⇒ 00:19:08.750 Sahana Asokan: Yeah, I think for me, next question, which is like on lead. Gen, like, how are you guys like, how did you guys start? You know.
89 00:19:09.260 ⇒ 00:19:14.370 Sahana Asokan: you know, finding clients. I think that I think that’s kind of like my main question, like, How are.
90 00:19:14.370 ⇒ 00:19:15.190 Uttam Kumaran: Yeah.
91 00:19:15.550 ⇒ 00:19:15.900 Sahana Asokan: Market.
92 00:19:15.900 ⇒ 00:19:24.050 Uttam Kumaran: Yeah, so where we started, I quit my job. And then I basically called like everybody I knew in data, for like 3 months.
93 00:19:24.366 ⇒ 00:19:50.543 Uttam Kumaran: I like sat at a coffee shop that’s like near my house, and basically was like called, every single person said, If you don’t need data help, do you have anyone that needs it? So a lot of word of mouth, probably for the 1st year? Which is nice, because I I just made a lot of friends working in data in New York. I worked at, we work. I worked in in New York and I lived in Manhattan. I worked for a bunch of startups there. So I just made a lot of friends and data there, and
94 00:19:50.800 ⇒ 00:20:03.736 Uttam Kumaran: sort of got a couple of clients like through just like having friends. And then, basically, in the last 6 months, we’re we’re kind of focusing on, how do we diversify the pipeline? So we still have a lot of word of mouth referral.
95 00:20:04.030 ⇒ 00:20:24.372 Uttam Kumaran: you know, which is great. Those are that’s free, but it’s very unpredictable. I know Robert kind of scaled a lot of stuff on upwork, I will say, on upwork and a fiverr just like prices. It’s tough, and there’s a lot of competition. Like a lot of competition. That’s very easy ways to compete. And for us we’re really going
96 00:20:24.690 ⇒ 00:20:54.629 Uttam Kumaran: we sell to the top like where we go after Cmo, CEO Cos and and get conversations, get buy in, and then kind of interact with the engineering. Because I actually have. No, I’m so confident that if we go into engineering, we can nail it. But typically they’re not the people that own the budget. So we try to find the people that own the budget and sell into them. So then, second, we do. We have some cold outbound. We do cold Linkedin cold email, for some stuff works well for other stuff, not so much. And then we’re doing content. So we have a lot of content that goes on Linkedin. We have a newsletter.
97 00:20:54.660 ⇒ 00:21:18.850 Uttam Kumaran: We’re pushing out like blog and stuff like that. Getting better will kind of serve us better long term. We do a little SEO but hopefully it becomes big SEO after about a year of doing it usually is the way it works, and then we have partnerships. So we I don’t know if Robert mentioned. But like we’re an amplitude and mixed panel partner. So we get some leads directly through them. I have.
98 00:21:18.850 ⇒ 00:21:48.229 Uttam Kumaran: We’ve done a lot of work with snowflake a lot of work with some other bi tools. So I kind of just get pulled in in case people like think about us in case clients need help, we’ll probably end up longer term. We will still have word of mouth. But hopefully, a lot of our stuff comes through referral not only existing client referral but then also through partnerships. Most likely I don’t know how big the cold sort of motion will work longer term but it’s something that we kind of again. We’re going from just like
99 00:21:48.380 ⇒ 00:21:51.879 Uttam Kumaran: people I know, to like, we actually have, like, sort of 5 different
100 00:21:52.100 ⇒ 00:22:00.199 Uttam Kumaran: ways. We’re getting leads in. So, yeah, I mean, we have a, we have again, we have a full time designer. We have full time content. Person. We have a
101 00:22:00.800 ⇒ 00:22:12.360 Uttam Kumaran: a full time. No, we have a part time. Notion person just does like organizing like sort of the OS for the company. And then, yeah, we have a couple of partners on the outbound side, as well.
102 00:22:13.340 ⇒ 00:22:26.519 Nicolas Sucari: Yeah, we’ve we’ve improved the the website, too. We have one person that works on on that. Yeah, this this year is gonna it’s just crazy a lot of changes. And yeah, I think if everything is paying off. So yeah.
103 00:22:26.860 ⇒ 00:22:33.820 Sahana Asokan: Yeah, I was. Gonna say, I think I see a lot of demand for just like mixed panel support amplitude support on.
104 00:22:34.510 ⇒ 00:22:37.710 Sahana Asokan: So I do that a lot, too, because it’s like I think it’s the easy.
105 00:22:37.710 ⇒ 00:22:38.200 Uttam Kumaran: Nice.
106 00:22:38.200 ⇒ 00:22:40.460 Sahana Asokan: Compared to like Pendo and stuff so.
107 00:22:40.460 ⇒ 00:22:41.110 Uttam Kumaran: Yeah.
108 00:22:41.660 ⇒ 00:22:54.960 Uttam Kumaran: yeah, we use post hog. But I know a lot of people use amplitude. I think the thing with amplitude is apparently it’s they stopped doing professional services, so they rely a lot on partners. And now but that’s so to kind of the way we package is, we go in, and we’ll say
109 00:22:54.960 ⇒ 00:23:17.230 Uttam Kumaran: one or 2. Sometimes we get people that are like, Hey, can you just help us with our amplitude? But of course they they have problems all over the org. So we go in. And we have like a pretty packaged data audit process that we do that we charge for. It takes usually, probably like in a in a few weeks, we can get a sense of the whole lay of the land. And then we basically prescribe like, hey, we you may need our help in Xyz areas.
110 00:23:17.480 ⇒ 00:23:42.790 Uttam Kumaran: And then some people come and they directly come to me. And they’re like, Hey, I need a DVD person they know, and they’re like they know exactly what they want, and those are the best, because I just need to find great people for them, which is a different challenge. But thankfully, we have a bunch of people that are. I would love to send some money to if I can. So that’s kind of like. But we we kind of do some staff augmentation. But most of our work is like sort of this, like holistic
111 00:23:43.128 ⇒ 00:23:47.340 Uttam Kumaran: sort of like data team as a service sort of process.
112 00:23:47.820 ⇒ 00:23:49.160 Sahana Asokan: Nice, very cool.
113 00:23:51.610 ⇒ 00:23:55.160 Uttam Kumaran: Cool. Anything else? I can answer.
114 00:23:57.700 ⇒ 00:24:05.960 Sahana Asokan: I’m good for now it it makes a lot of sense to me. And what you guys are doing. I think it’s really cool. But yeah, any questions you guys have for me.
115 00:24:07.594 ⇒ 00:24:08.850 Nicolas Sucari: Yeah. I think we’re.
116 00:24:09.010 ⇒ 00:24:10.319 Uttam Kumaran: Yeah, go ahead with them.
117 00:24:10.830 ⇒ 00:24:11.739 Uttam Kumaran: There you go.
118 00:24:12.170 ⇒ 00:24:13.520 Nicolas Sucari: And where are you based.
119 00:24:13.790 ⇒ 00:24:16.960 Sahana Asokan: I’m based in Williamsburg. So Brooklyn in New York.
120 00:24:16.960 ⇒ 00:24:17.570 Nicolas Sucari: Okay.
121 00:24:17.740 ⇒ 00:24:18.670 Sahana Asokan: Yeah.
122 00:24:19.590 ⇒ 00:24:25.536 Uttam Kumaran: Cool. So, Robert, yeah, Robert’s there. So that’s really great. And then, yeah, if you ever visit Austin, let me know
123 00:24:25.820 ⇒ 00:24:26.570 Nicolas Sucari: Slightest.
124 00:24:26.570 ⇒ 00:24:29.950 Uttam Kumaran: Or if you’ve been in Argentina, let Nico know.
125 00:24:29.950 ⇒ 00:24:30.650 Sahana Asokan: Okay.
126 00:24:30.650 ⇒ 00:24:31.100 Uttam Kumaran: Yeah.
127 00:24:31.100 ⇒ 00:24:35.659 Sahana Asokan: Yeah, I’m I’ve been in New York for 4 years, but I’m from the Bay Area. So.
128 00:24:35.660 ⇒ 00:24:37.689 Uttam Kumaran: Okay, me, too. I grew up in San Ramon.
129 00:24:37.690 ⇒ 00:24:39.839 Sahana Asokan: Yeah, I’m in San. I’m in San Jose. So.
130 00:24:39.840 ⇒ 00:24:41.650 Uttam Kumaran: Oh, nice. Okay, yeah. Okay.
131 00:24:41.650 ⇒ 00:24:42.250 Uttam Kumaran: Okay.
132 00:24:42.811 ⇒ 00:24:53.000 Uttam Kumaran: okay, perfect. Well, I appreciate the time on Friday. Thanks so much. And then, yeah, I’m sure I’ll coordinate with Robert, and we’ll kind of reach out for for our setup and stuff like that. So.
133 00:24:53.000 ⇒ 00:24:57.879 Sahana Asokan: Okay, thanks, guys. I’m excited about this. And yeah, happy holidays.
134 00:24:58.110 ⇒ 00:24:58.580 Uttam Kumaran: Thanks. Yeah.
135 00:24:58.580 ⇒ 00:25:00.819 Nicolas Sucari: Happy holidays. Too nice to meet you.
136 00:25:00.820 ⇒ 00:25:01.590 Sahana Asokan: Nice to meet you.
137 00:25:02.240 ⇒ 00:25:06.730 Uttam Kumaran: Bye, yeah. Pretty good.
138 00:25:07.700 ⇒ 00:25:11.130 Nicolas Sucari: Pretty good. Yeah, I think she’s kind of senior right?
139 00:25:11.680 ⇒ 00:25:12.530 Uttam Kumaran: She seemed pretty, similar.
140 00:25:13.600 ⇒ 00:25:14.340 Nicolas Sucari: Yeah.
141 00:25:15.030 ⇒ 00:25:16.070 Nicolas Sucari: Like her.
142 00:25:16.980 ⇒ 00:25:21.389 Uttam Kumaran: Yeah, hopefully, she can take on like some of the senior stuff.
143 00:25:23.780 ⇒ 00:25:24.340 Nicolas Sucari: Yep.
144 00:25:24.980 ⇒ 00:25:26.440 Uttam Kumaran: How’s the day going.
145 00:25:28.170 ⇒ 00:25:31.969 Nicolas Sucari: Everything is great. I’m preparing the update for cool parts. I’m gonna send that.
146 00:25:32.720 ⇒ 00:25:39.600 Nicolas Sucari: But yeah, I think everything’s great, that podcast your voice from.
147 00:25:39.600 ⇒ 00:25:40.290 Uttam Kumaran: No, it’s.
148 00:25:40.290 ⇒ 00:25:40.650 Nicolas Sucari: And that’s.
149 00:25:40.650 ⇒ 00:25:41.600 Uttam Kumaran: Crazy.
150 00:25:43.310 ⇒ 00:25:43.799 Uttam Kumaran: It’s crazy.
151 00:25:43.800 ⇒ 00:25:44.470 Nicolas Sucari: That’s it.
152 00:25:45.480 ⇒ 00:25:46.679 Nicolas Sucari: It was.
153 00:25:46.680 ⇒ 00:25:48.559 Uttam Kumaran: I love it, but it’s insane.
154 00:25:48.980 ⇒ 00:25:51.009 Nicolas Sucari: Yeah, I mean, it’s dangerous.
155 00:25:51.820 ⇒ 00:25:55.270 Uttam Kumaran: You know what you know. Why, cause I I told Ryan to also.
156 00:25:57.286 ⇒ 00:26:00.203 Uttam Kumaran: I told Ryan to use this one
157 00:26:01.310 ⇒ 00:26:11.289 Uttam Kumaran: Zoom Meeting where I did a lot of talking. I think one of the engineering meetings I was like, take it because it’s like a lot of me talking, I think, to make it a little bit better, though I’m I probably need to
158 00:26:11.500 ⇒ 00:26:14.770 Uttam Kumaran: like, sit and record off of like a professional mic.
159 00:26:14.900 ⇒ 00:26:18.940 Uttam Kumaran: and then record like a reading like a book where there’s like a lot of complicated.
160 00:26:18.940 ⇒ 00:26:19.485 Nicolas Sucari: Yeah.
161 00:26:20.030 ⇒ 00:26:23.259 Uttam Kumaran: And then give it that. But for a 1st pass, it’s like, really, really good.
162 00:26:23.600 ⇒ 00:26:25.545 Uttam Kumaran: We’ll see. I basically I basically
163 00:26:26.360 ⇒ 00:26:28.530 Uttam Kumaran: Oh, he’s asking if we can use your voice.
164 00:26:29.025 ⇒ 00:26:30.249 Uttam Kumaran: I don’t know. You can.
165 00:26:30.250 ⇒ 00:26:30.870 Nicolas Sucari: Yeah, I mean.
166 00:26:30.870 ⇒ 00:26:32.840 Uttam Kumaran: I won’t, whatever.
167 00:26:32.840 ⇒ 00:26:38.800 Nicolas Sucari: We can use it. I don’t know if it’s gonna be so natural, because my English but
168 00:26:38.990 ⇒ 00:26:40.800 Nicolas Sucari: yeah, if not, I think.
169 00:26:40.800 ⇒ 00:26:42.940 Uttam Kumaran: Or we should do in span, or we should do it in Spanish.
170 00:26:42.940 ⇒ 00:26:44.679 Nicolas Sucari: Yeah, dude, we should do it in time.
171 00:26:44.680 ⇒ 00:26:46.718 Uttam Kumaran: Oh, yeah, actually, we should do that.
172 00:26:47.320 ⇒ 00:26:50.010 Uttam Kumaran: yo, you should record. Yeah, let’s do that.
173 00:26:50.662 ⇒ 00:26:51.227 Uttam Kumaran: Let me
174 00:26:51.510 ⇒ 00:26:52.140 Nicolas Sucari: Yeah.
175 00:26:52.920 ⇒ 00:26:54.350 Uttam Kumaran: Let me let me respond to him.
176 00:26:56.810 ⇒ 00:27:00.020 Nicolas Sucari: Does 11 have the Spanish option.
177 00:27:00.580 ⇒ 00:27:00.940 Uttam Kumaran: So.
178 00:27:00.940 ⇒ 00:27:01.560 Nicolas Sucari: Right.
179 00:27:02.210 ⇒ 00:27:07.279 Uttam Kumaran: Yeah, cause. What we’re gonna do is we’re gonna start releasing the newsletter as like a blog as like a podcast.
180 00:27:07.280 ⇒ 00:27:07.810 Nicolas Sucari: Podcast.
181 00:27:07.810 ⇒ 00:27:08.230 Uttam Kumaran: Every week.
182 00:27:08.230 ⇒ 00:27:08.840 Nicolas Sucari: Okay.
183 00:27:09.510 ⇒ 00:27:10.430 Uttam Kumaran: And I think if we can get.
184 00:27:10.430 ⇒ 00:27:10.880 Nicolas Sucari: Sorry.
185 00:27:10.880 ⇒ 00:27:15.520 Uttam Kumaran: I’m happy to narrate it. But and the spare trying to use these tools.
186 00:27:17.190 ⇒ 00:27:20.240 Uttam Kumaran: you know, for us to to save me a little bit of time.
187 00:27:21.490 ⇒ 00:27:27.570 Nicolas Sucari: Yeah, if not, it doesn’t matter. I mean, it’s gonna be 5 min of reading stuff. So we can do it.
188 00:27:27.570 ⇒ 00:27:32.869 Uttam Kumaran: But see, I know, Ryan, if I if I’m involved, if things are gonna slow down. So I want him to be like Ryan. You have my voice. Now
189 00:27:33.200 ⇒ 00:27:36.508 Uttam Kumaran: run the company! Run the company.
190 00:27:37.060 ⇒ 00:27:41.000 Nicolas Sucari: Start calling people. Yeah. Call my mom. Tell him I’m gonna be.
191 00:27:41.000 ⇒ 00:27:42.699 Uttam Kumaran: Yeah, yeah, please, yeah, exactly.
192 00:27:42.700 ⇒ 00:27:45.050 Uttam Kumaran: Exactly. Like, here’s all these things I need you to like.
193 00:27:45.690 ⇒ 00:27:48.730 Uttam Kumaran: Honestly, yeah, I should just beg a personal assistant.
194 00:27:49.940 ⇒ 00:27:52.690 Uttam Kumaran: I mean, dude at some point with enough of these meetings.
195 00:27:53.010 ⇒ 00:27:55.790 Uttam Kumaran: It’s gonna know how to run a sales call.
196 00:27:56.110 ⇒ 00:27:59.209 Uttam Kumaran: And then what’s gonna happen is, I’m gonna I’m gonna have
197 00:27:59.460 ⇒ 00:28:06.120 Uttam Kumaran: a fake version of me, join a sales call and have my voice and have my appearance. I’m telling you
198 00:28:06.250 ⇒ 00:28:06.980 Uttam Kumaran: for someone.
199 00:28:06.980 ⇒ 00:28:07.610 Nicolas Sucari: Should try that.
200 00:28:07.610 ⇒ 00:28:09.759 Uttam Kumaran: I can be in 5 places at once.
201 00:28:10.810 ⇒ 00:28:11.600 Uttam Kumaran: Yeah.
202 00:28:11.890 ⇒ 00:28:18.279 Nicolas Sucari: That’s gonna be crazy like you’re you’re gonna be at the engineering meeting and the sales meeting at the same time. That’s gonna be crazy.
203 00:28:18.280 ⇒ 00:28:18.770 Uttam Kumaran: Same time.
204 00:28:18.830 ⇒ 00:28:19.080 Nicolas Sucari: Cool.
205 00:28:19.330 ⇒ 00:28:26.460 Uttam Kumaran: Yeah, it’s gonna be insane. That’s the feature cause. Then none of us have to work. We all have our AI agents go to the meetings. That’s it.
206 00:28:27.690 ⇒ 00:28:29.020 Nicolas Sucari: That’s crazy. Yeah.
207 00:28:30.690 ⇒ 00:28:31.430 Nicolas Sucari: Okay.
208 00:28:31.810 ⇒ 00:28:32.630 Nicolas Sucari: Cool.
209 00:28:34.460 ⇒ 00:28:38.629 Uttam Kumaran: Cool. Yeah, I’m gonna stay on for a little bit longer and finish
210 00:28:40.580 ⇒ 00:28:44.210 Uttam Kumaran: Finish a couple of things finishing newsletter and.
211 00:28:44.518 ⇒ 00:28:54.681 Nicolas Sucari: I don’t know who’s gonna be next week. Who’s gonna be online next week. I’m gonna be the entire week. So if you need something, obviously, just let me know with them.
212 00:28:54.990 ⇒ 00:28:57.630 Uttam Kumaran: Probably gonna take off Tuesday.
213 00:28:58.020 ⇒ 00:28:59.500 Nicolas Sucari: No, when it is.
214 00:28:59.500 ⇒ 00:29:00.030 Uttam Kumaran: Say.
215 00:29:00.030 ⇒ 00:29:01.250 Nicolas Sucari: Wednesday or Thursday.
216 00:29:01.770 ⇒ 00:29:03.700 Uttam Kumaran: Yeah, I’ll be honest.
217 00:29:03.700 ⇒ 00:29:08.310 Nicolas Sucari: Don’t worry, I’ll I’ll be. I’ll be online. So yeah.
218 00:29:08.600 ⇒ 00:29:10.049 Nicolas Sucari: let me know if you need anything.
219 00:29:10.530 ⇒ 00:29:12.470 Uttam Kumaran: Yeah. Dan didn’t get back to me.
220 00:29:13.430 ⇒ 00:29:14.469 Uttam Kumaran: I see it nice to meet you
221 00:29:14.470 ⇒ 00:29:18.480 Uttam Kumaran: out of the blue, and I was like, but just keep pushing.
222 00:29:19.370 ⇒ 00:29:19.970 Nicolas Sucari: Yeah, I’m gonna.
223 00:29:20.230 ⇒ 00:29:22.830 Uttam Kumaran: It, send it, send it his email to the update.
224 00:29:23.050 ⇒ 00:29:31.369 Nicolas Sucari: I I’m doing. I’m doing both so sending the email and sending through slack. I’m gonna emphasize a little bit more on the skew stuff
225 00:29:31.470 ⇒ 00:29:34.809 Nicolas Sucari: so they can read it. But
226 00:29:34.920 ⇒ 00:29:41.490 Nicolas Sucari: yeah, I mean, we did everything they they’ve been asking. We need to work on that alerting.
227 00:29:41.800 ⇒ 00:29:43.499 Nicolas Sucari: Yeah, yeah, I know, Ryan. Maybe.
228 00:29:43.500 ⇒ 00:29:44.060 Uttam Kumaran: Yeah.
229 00:29:44.200 ⇒ 00:29:44.750 Nicolas Sucari: Yeah.
230 00:29:45.240 ⇒ 00:29:49.370 Uttam Kumaran: Have to make some decisions for them. Yeah? And then so and then also, we had a good meeting with Jacob.
231 00:29:50.060 ⇒ 00:29:50.890 Nicolas Sucari: Okay.
232 00:29:50.890 ⇒ 00:29:58.020 Uttam Kumaran: So Jacob’s probably gonna come back on, I think I think basically anywhere where Robert’s working. I wanna backfill him.
233 00:29:58.980 ⇒ 00:30:02.720 Nicolas Sucari: Maybe. Eden. No. Yeah. Maybe. Eden, yeah.
234 00:30:03.000 ⇒ 00:30:10.530 Uttam Kumaran: We have Eden, and we have the art company. And then we are we. The TV company wants to work with us, maybe next month.
235 00:30:10.640 ⇒ 00:30:17.520 Uttam Kumaran: and then I I’m pretty sure the ABC Company is gonna close in January. They sent us a bunch of stuff today and
236 00:30:18.490 ⇒ 00:30:19.120 Nicolas Sucari: Nice.
237 00:30:19.690 ⇒ 00:30:22.919 Uttam Kumaran: So we made a really, really like a shitload of progress this month.
238 00:30:23.410 ⇒ 00:30:27.460 Nicolas Sucari: We will need another analytics engineering. Maybe.
239 00:30:27.460 ⇒ 00:30:29.420 Uttam Kumaran: Yeah, yeah, I told
240 00:30:30.700 ⇒ 00:30:34.580 Uttam Kumaran: I wanna see if I could get Brian to do it.
241 00:30:35.190 ⇒ 00:30:37.599 Uttam Kumaran: if not, Brian, then I’ll ask Nick
242 00:30:38.750 ⇒ 00:30:39.659 Nicolas Sucari: Oh, okay.
243 00:30:39.660 ⇒ 00:30:41.730 Uttam Kumaran: If not, I have. I have a few people.
244 00:30:43.770 ⇒ 00:30:47.970 Uttam Kumaran: Yeah, I have a I like, I have at least 3 other people that I know can basically.
245 00:30:47.970 ⇒ 00:30:48.710 Nicolas Sucari: What about?
246 00:30:49.170 ⇒ 00:30:49.630 Uttam Kumaran: Stuff.
247 00:30:50.130 ⇒ 00:30:52.710 Nicolas Sucari: What about Patrick to help with Dde stuff.
248 00:30:53.770 ⇒ 00:30:58.270 Uttam Kumaran: The d stuff I feel like isn’t so bad right now.
249 00:31:00.110 ⇒ 00:31:03.170 Nicolas Sucari: No, just in case, if we have, like pretty common.
250 00:31:03.170 ⇒ 00:31:12.620 Uttam Kumaran: I’m hoping that like when, if we have 3 once, we have 3 or 4 clients, I think I’m gonna consider bringing in someone with snowflake background to contract.
251 00:31:14.770 ⇒ 00:31:18.400 Uttam Kumaran: Until then it’s hard, because there’s maybe only like 5.
252 00:31:18.520 ⇒ 00:31:20.999 Uttam Kumaran: Initially, this work. But at the end there’s like.
253 00:31:21.000 ⇒ 00:31:21.360 Nicolas Sucari: Yeah.
254 00:31:21.360 ⇒ 00:31:22.250 Uttam Kumaran: Not that much work.
255 00:31:22.250 ⇒ 00:31:23.269 Nicolas Sucari: It’s nothing to do. Yeah.
256 00:31:23.270 ⇒ 00:31:27.920 Uttam Kumaran: So I’d rather bring on someone to kind of like help me with like the platform.
257 00:31:28.590 ⇒ 00:31:29.335 Nicolas Sucari: Okay.
258 00:31:30.630 ⇒ 00:31:36.459 Uttam Kumaran: Maybe. Like, yeah, I have a 1 friend in mind that could be interested
259 00:31:36.720 ⇒ 00:31:39.020 Uttam Kumaran: to kind of help me think about like, how do we
260 00:31:39.260 ⇒ 00:31:43.239 Uttam Kumaran: build more like platform stuff like onboarding, alerting?
261 00:31:45.710 ⇒ 00:31:48.490 Uttam Kumaran: So I may ask him to to help us.
262 00:31:49.214 ⇒ 00:31:52.115 Uttam Kumaran: But like he’s not good, he’s in
263 00:31:53.220 ⇒ 00:32:03.750 Uttam Kumaran: He. He can also take on client work. But it’s he’s in Asia, like he’s traveling in Asia. So the timing is kind of rough to be on meetings.
264 00:32:04.110 ⇒ 00:32:04.770 Nicolas Sucari: Yeah.
265 00:32:05.160 ⇒ 00:32:09.910 Uttam Kumaran: But if he work, if he works with me on just platform stuff, then it could work better. So
266 00:32:10.540 ⇒ 00:32:24.230 Uttam Kumaran: let me see. I mean the 1st thing it starts with, like, I need to just create a huge backlog of everything we want to do. And then that way, I can sort of piece it off and say, Hey, go, go! Take this on. Work on it whenever you want to. So that’s the thing we’re we’re kind of working on
267 00:32:24.693 ⇒ 00:32:32.589 Uttam Kumaran: and I think also, next month, I want to think about what other stuff we want to do from a Pm automation side.
268 00:32:33.010 ⇒ 00:32:46.829 Uttam Kumaran: I think definitely, we need something that’s like creating creating tickets from take tickets from slack.
269 00:32:47.481 ⇒ 00:32:51.920 Nicolas Sucari: Or like creating tickets for meetings, or like at least putting it somewhere.
270 00:32:52.520 ⇒ 00:32:54.950 Uttam Kumaran: So I and that’s complete work on.
271 00:32:55.400 ⇒ 00:33:04.840 Nicolas Sucari: If you are able to create this like knowledge base that we can feed every day with what’s been happening in slack or
272 00:33:05.820 ⇒ 00:33:19.130 Nicolas Sucari: in Github like, I think that’s gonna be like great, because you can ask the status of everything. And if you need to create a ticket like you can ask, Hey, what? What was happening on slack today? Do we need to create some to create a ticket? And
273 00:33:19.270 ⇒ 00:33:20.990 Nicolas Sucari: maybe it could work right.
274 00:33:22.060 ⇒ 00:33:22.985 Uttam Kumaran: Exactly
275 00:33:24.410 ⇒ 00:33:27.619 Uttam Kumaran: So I think on that, for sure.
276 00:33:29.080 ⇒ 00:33:33.670 Nicolas Sucari: I don’t know if there is a way of exporting slack slacks messages every day or.
277 00:33:33.670 ⇒ 00:33:35.899 Uttam Kumaran: We have, we do it. Yeah, we’re we’re doing it.
278 00:33:36.690 ⇒ 00:33:39.530 Nicolas Sucari: But there is like a web hook, so that we can keep.
279 00:33:39.660 ⇒ 00:33:41.599 Nicolas Sucari: or an Api that we can call.
280 00:33:41.940 ⇒ 00:33:44.780 Uttam Kumaran: I don’t know how it’s getting done, but Casey did it once.
281 00:33:45.270 ⇒ 00:33:48.649 Uttam Kumaran: cause I told him I wanted to run AI on one of the channels
282 00:33:48.940 ⇒ 00:33:52.600 Uttam Kumaran: just to see if it’s possible it worked. But yeah, we need to
283 00:33:52.730 ⇒ 00:33:57.930 Uttam Kumaran: work on that. Basically, I want to export all of that to
284 00:33:58.600 ⇒ 00:34:01.839 Uttam Kumaran: somewhere where we can run AI on on each of the channels.
285 00:34:05.930 ⇒ 00:34:06.250 Nicolas Sucari: Okay.
286 00:34:06.250 ⇒ 00:34:12.339 Uttam Kumaran: Yeah, I think. Yeah, we’ll think about some stuff I don’t know. It seems a little bit more too much work to automate
287 00:34:13.207 ⇒ 00:34:20.219 Uttam Kumaran: definitely like, if we can get every, if we can get clients on our meetings, then
288 00:34:20.469 ⇒ 00:34:23.219 Uttam Kumaran: summarizing and sending it at least to you.
289 00:34:23.580 ⇒ 00:34:27.080 Uttam Kumaran: is really helpful, and then also keeping all of that in one area. Like.
290 00:34:27.199 ⇒ 00:34:35.799 Uttam Kumaran: for example, I want automatically meetings with pool parts to go into the Google drive for pool parts and it automatically goes into the pool parts. AI bot
291 00:34:36.050 ⇒ 00:34:47.171 Uttam Kumaran: right as knowledge. So that’s sort of things I want to work with Casey on is like, can we look at who? What the domain is on the email invite or the title automatically route that to the right area?
292 00:34:48.260 ⇒ 00:34:51.019 Uttam Kumaran: but that this one’s gonna take a little bit of time.
293 00:34:52.500 ⇒ 00:34:57.243 Nicolas Sucari: Yeah. Oh, but I think it’s something we can do, and maybe we can use
294 00:34:57.750 ⇒ 00:35:03.849 Nicolas Sucari: because, granola the like it that’s really good summaries and notes.
295 00:35:03.850 ⇒ 00:35:10.469 Uttam Kumaran: Yeah, yeah, yeah, so so basically, we, I’m gonna I’m first, st gonna we’re gonna update because we have the meeting note.
296 00:35:10.860 ⇒ 00:35:14.679 Uttam Kumaran: But I’m gonna update that to use like a granola format.
297 00:35:15.020 ⇒ 00:35:22.139 Uttam Kumaran: Okay? And then also, we’re gonna we are gonna have multiple meet. So now, the reason why I wanted to go, categorize all the meetings and put the meeting.
298 00:35:22.455 ⇒ 00:35:22.770 Nicolas Sucari: Yeah.
299 00:35:22.770 ⇒ 00:35:34.757 Uttam Kumaran: Yeah. So the transcript will fit. AI will know what type of meeting this is. Understand the goals and then be able to output that. That’s the reason we wanted to do that mainly
300 00:35:35.290 ⇒ 00:35:54.690 Uttam Kumaran: cause having a goal for a meeting. And some of that, it’s like, yeah, okay, it’s helpful for us. But I want the AI to understand why we had the meeting, what the outcomes are, and then sub build a summary based on that like, if it’s a project management meeting, then it’s different than if it’s a client meeting, right? So I already built some granola templates for me that I’m using that I’ll just repurpose
301 00:35:56.090 ⇒ 00:36:01.100 Nicolas Sucari: Maybe maybe one way of doing it is like naming the meetings with some code. Yeah.
302 00:36:01.100 ⇒ 00:36:02.179 Uttam Kumaran: Like if it is a client.
303 00:36:02.180 ⇒ 00:36:05.339 Nicolas Sucari: Meeting. We just like put in brackets or
304 00:36:05.768 ⇒ 00:36:11.059 Nicolas Sucari: like pull parts. And we know that’s a client meeting. And if it is operations like something like that.
305 00:36:12.770 ⇒ 00:36:21.130 Nicolas Sucari: Maybe it’s easy doing that. And we can have, like our naming convention in one sheet. And when you need to create a meeting, we just make sure that
306 00:36:21.350 ⇒ 00:36:24.890 Nicolas Sucari: we use one of those codes.
307 00:36:25.540 ⇒ 00:36:26.792 Uttam Kumaran: Yeah. I wonder?
308 00:36:31.680 ⇒ 00:36:36.379 Uttam Kumaran: yeah. I wonder if it’s the title, or maybe we can even put in the notes.
309 00:36:36.800 ⇒ 00:36:40.390 Nicolas Sucari: Or maybe we can also do you know what we can create
310 00:36:41.070 ⇒ 00:36:51.719 Nicolas Sucari: like a user like, invite someone to the meeting that that email is kind of the code. If you have that person in the meeting goes to somewhere. But you need to create accounts. I think.
311 00:36:51.720 ⇒ 00:36:59.040 Uttam Kumaran: I think there’s probably 2 ways. One is like we have some id in the title. The second thing is, the AI should be able to look at the transcript and basically
312 00:36:59.410 ⇒ 00:37:00.020 Uttam Kumaran: it out.
313 00:37:00.730 ⇒ 00:37:01.110 Nicolas Sucari: That one.
314 00:37:01.110 ⇒ 00:37:05.029 Uttam Kumaran: So that’ll be the backup. I think we’ll have it. Auto categorized.
315 00:37:07.410 ⇒ 00:37:09.010 Uttam Kumaran: But yeah, summarize.
316 00:37:09.010 ⇒ 00:37:13.359 Nicolas Sucari: The Ids. Yeah, the Ids may be easy to start with.
317 00:37:13.560 ⇒ 00:37:14.390 Nicolas Sucari: I think.
318 00:37:14.870 ⇒ 00:37:18.179 Uttam Kumaran: Yeah, like, I think of some id system.
319 00:37:21.060 ⇒ 00:37:24.719 Uttam Kumaran: Or, yeah, like, at least look for the client name and the title.
320 00:37:25.350 ⇒ 00:37:25.920 Nicolas Sucari: Yeah.
321 00:37:26.110 ⇒ 00:37:33.060 Uttam Kumaran: Like for internal meetings, for internal meetings. I don’t mind having the weird titles and stuff like that, but external. Maybe it’s a little bit weird.
322 00:37:33.690 ⇒ 00:37:37.163 Nicolas Sucari: For external meetings. I’m also, I’m always using like
323 00:37:37.970 ⇒ 00:37:49.130 Nicolas Sucari: If you see how we have the or, for example, divide a cocoa meeting I always use like the client’s name first, st and then like to. I don’t know. How do you say these icons?
324 00:37:49.660 ⇒ 00:37:50.869 Nicolas Sucari: They do like.
325 00:37:51.380 ⇒ 00:37:52.570 Uttam Kumaran: Oh, yeah.
326 00:37:54.160 ⇒ 00:37:54.950 Uttam Kumaran: The Emoji.
327 00:37:54.950 ⇒ 00:37:58.820 Nicolas Sucari: Yeah, I, yeah, they are not. I don’t know how you say, like the
328 00:37:59.690 ⇒ 00:38:02.370 Nicolas Sucari: yeah minor. And I don’t know how to say it.
329 00:38:02.370 ⇒ 00:38:04.209 Uttam Kumaran: Oh, the the headaches.
330 00:38:04.210 ⇒ 00:38:06.560 Nicolas Sucari: How do you call them these ones?
331 00:38:07.160 ⇒ 00:38:13.395 Nicolas Sucari: Oh, I don’t know what those are I don’t know. I don’t even know. Well, I know. I know I know what those are, but I don’t know what they’re called like.
332 00:38:14.330 ⇒ 00:38:16.799 Uttam Kumaran: Does anyone know what that’s called? I don’t know.
333 00:38:17.540 ⇒ 00:38:18.800 Nicolas Sucari: I know it’s like.
334 00:38:18.800 ⇒ 00:38:23.009 Uttam Kumaran: I don’t know. I don’t know what is. It’s called brack. People say brackets sometimes.
335 00:38:23.570 ⇒ 00:38:26.450 Nicolas Sucari: But brackets are like these ones, right?
336 00:38:28.330 ⇒ 00:38:34.870 Nicolas Sucari: So I I kind of do all parts. Sometimes I do like these like I
337 00:38:35.060 ⇒ 00:38:42.810 Nicolas Sucari: I I do like this, or sometimes I do like all parts like that.
338 00:38:43.830 ⇒ 00:38:45.199 Uttam Kumaran: Yeah, I like that one.
339 00:38:45.780 ⇒ 00:38:50.550 Nicolas Sucari: Okay, yeah, that’s the one I’m using for vitaco bad. Yeah.
340 00:38:51.150 ⇒ 00:38:55.989 Nicolas Sucari: I guess. Like, when it’s a client meeting we can use like this format.
341 00:38:56.500 ⇒ 00:38:57.200 Uttam Kumaran: Okay.
342 00:38:59.810 ⇒ 00:39:01.310 Nicolas Sucari: Okay. Cool.
343 00:39:01.740 ⇒ 00:39:02.520 Uttam Kumaran: Okay.
344 00:39:02.840 ⇒ 00:39:12.810 Uttam Kumaran: cool. Alright. I guess if we don’t talk today, then have a good weekend, and then yeah, I’ll be. I’ll be doing a couple of things tomorrow afternoon, just like some notion work.
345 00:39:13.391 ⇒ 00:39:15.830 Uttam Kumaran: And then I’ll be yeah. Be back on Monday.
346 00:39:16.670 ⇒ 00:39:19.500 Nicolas Sucari: Cool. Let me know if you need anything, I’ll I’ll be in line, too.
347 00:39:19.670 ⇒ 00:39:20.559 Uttam Kumaran: Okay. Okay.
348 00:39:21.480 ⇒ 00:39:23.479 Nicolas Sucari: Bye, you, Tom, have a great weekend. Bye, bye.
349 00:39:23.480 ⇒ 00:39:24.160 Uttam Kumaran: You too.