Meeting Title: Brainforge x Clint Consulting Opportunity Date: 2026-04-28 Meeting participants: Brian Sloane, Uttam Kumaran
WEBVTT
1 00:00:56.610 ⇒ 00:00:58.119 Uttam Kumaran: Hey, how’s it going?
2 00:00:58.540 ⇒ 00:01:00.980 Brian Sloane: Hello. Good. How about yourself?
3 00:01:00.980 ⇒ 00:01:01.640 Uttam Kumaran: A.
4 00:01:02.020 ⇒ 00:01:04.209 Uttam Kumaran: Good. How’s the week going so far?
5 00:01:05.379 ⇒ 00:01:14.869 Brian Sloane: Pretty good. Actually, I was in Boston over the weekend with my wife. She had a conference, and I hopped along for the ride to…
6 00:01:15.240 ⇒ 00:01:20.749 Brian Sloane: So just, you know, go hang out and see some friends, so… Settling back and into…
7 00:01:20.750 ⇒ 00:01:21.500 Uttam Kumaran: Nice.
8 00:01:21.820 ⇒ 00:01:23.420 Brian Sloane: But, yeah, that was nice.
9 00:01:25.090 ⇒ 00:01:32.709 Brian Sloane: Eva, thanks for, for hopping on a… a call. I appreciate it.
10 00:01:32.710 ⇒ 00:01:45.900 Uttam Kumaran: Of course. How do you, oh yeah, I’ll go. I’ll, drinks. I know Clint from almost, like, maybe 5 years ago now. Yeah, probably, like, yeah, probably 5, 4 or 5 years ago.
11 00:01:46.480 ⇒ 00:02:05.449 Uttam Kumaran: ago, we connected when I was, I was leading product at this company called Prequel. They’re, like, a data transformation startup based out of New York, and just connected through the founders of that company, and then sort of became fast friends, both kind of, like, data nerds. And yeah, I, you know, I sort of…
12 00:02:05.490 ⇒ 00:02:18.659 Uttam Kumaran: I started my business, you know, about 3 years ago, and you know, has been working on his business as well, sort of a similar time frame, so we’ve just been, like, supportive in however we can, and
13 00:02:18.740 ⇒ 00:02:25.780 Uttam Kumaran: Yeah, just, like, try to, you know, where we can make connections to each other, try to do so. So, just a good friend of mine.
14 00:02:25.780 ⇒ 00:02:27.199 Brian Sloane: Very good. Oh, yeah.
15 00:02:27.370 ⇒ 00:02:29.340 Brian Sloane: Awesome. Yeah, I,
16 00:02:30.100 ⇒ 00:02:39.510 Brian Sloane: admittedly, I haven’t known Clint too long myself, but somebody I worked with, while I was at RJ Metrics a while back,
17 00:02:39.790 ⇒ 00:02:46.540 Brian Sloane: you know, knew Clint, and so I was kind of talking to my friend Sarah about
18 00:02:46.540 ⇒ 00:03:02.330 Brian Sloane: what I’m up to these days, and she was like, oh, you should talk to Clint. He’s, like, in this space and really knowledgeable, so I had a great conversation with Clint as a result, and, you know, and I was, you know, really happy that he’d, you know, introduced me to some other folks, yourself included, so…
19 00:03:03.210 ⇒ 00:03:10.660 Brian Sloane: that’s kind of what brought me here. I can go more into my background and so forth as well, if it’s helpful, and the types of.
20 00:03:10.660 ⇒ 00:03:26.969 Uttam Kumaran: Yeah, I think even hearing… even… I think what would be lovely is, like, yeah, like, what part of the conversation led him down to think about me, and, like, I’m, yeah, more than happy to share, maybe fill in the gaps at that point with, like, sort of what we’re up to, and, yeah, that’d be great.
21 00:03:27.990 ⇒ 00:03:32.550 Brian Sloane: Yeah, so, you know, I, I…
22 00:03:32.700 ⇒ 00:03:40.639 Brian Sloane: got in touch with him because… and I was telling my friend Sarah this, but, you know, I’ve been working,
23 00:03:40.870 ⇒ 00:03:48.310 Brian Sloane: on this journey… I was at this journey that started at RTM Metrics, which was a company in the Philly area. I’m not sure if you’re familiar with.
24 00:03:48.310 ⇒ 00:03:49.450 Uttam Kumaran: Yes, I am.
25 00:03:49.450 ⇒ 00:03:51.079 Brian Sloane: Okay,
26 00:03:51.360 ⇒ 00:04:03.249 Brian Sloane: I started there in, like, 2013 with our geometric, which was, like, full-stack BI tool. You know, it was really exciting when Redshift was, like, the data warehouse that people…
27 00:04:03.250 ⇒ 00:04:03.660 Uttam Kumaran: Yes.
28 00:04:03.660 ⇒ 00:04:14.090 Brian Sloane: cared about, right? And then people started… there was more data warehouses, and we realized we shouldn’t be so coupled with it, and ultimately, Stitch spun out of RJ Metrics, and I went down to…
29 00:04:14.520 ⇒ 00:04:23.390 Brian Sloane: the Stitch journey, which was really exciting, starting with the days that Stitch launched, and then ultimately Stitch grew, and was acquired by Talent, which was acquired.
30 00:04:23.390 ⇒ 00:04:23.740 Uttam Kumaran: Yes.
31 00:04:23.740 ⇒ 00:04:24.720 Brian Sloane: click, so this was.
32 00:04:24.720 ⇒ 00:04:25.170 Uttam Kumaran: Yes.
33 00:04:25.170 ⇒ 00:04:26.569 Brian Sloane: You know.
34 00:04:26.570 ⇒ 00:04:29.549 Uttam Kumaran: I’m very… so I’m familiar with Stitch.
35 00:04:29.620 ⇒ 00:04:46.750 Uttam Kumaran: probably since, like, 2018 onto Talon. I mean, we still have some customers that are on… that are on Stitch, but then I learned about Talon through that, and then I learned about Qlik kind of also through that. You know, I just know all the… like, there’s not a ton of big ETL providers, and Stitch is
36 00:04:47.170 ⇒ 00:04:49.450 Uttam Kumaran: Still, you know, pretty big one, so…
37 00:04:49.450 ⇒ 00:04:50.100 Brian Sloane: Yeah.
38 00:04:50.610 ⇒ 00:04:53.060 Brian Sloane: Yeah, so I went through that journey, but
39 00:04:53.340 ⇒ 00:05:16.719 Brian Sloane: But now I’m looking to see what’s, what’s next, I mean, and, in the data space, and, you know, do I want to find an exciting opportunity at a new data company as, you know, as, like, driving, driving product? But conversely, I’m also just excited about helping companies solve problems, in the data space.
40 00:05:16.770 ⇒ 00:05:39.380 Brian Sloane: you know, perhaps, how does it map with AI? I mean, I guess everybody needs… everyone needs to be thinking about AI these days, so, you know, do I want to do some sort of fractional consulting, myself? You know, helping companies with… with the expertise I’ve kind of built up over the years? Because I think it is fun to help solve problems with companies,
41 00:05:39.380 ⇒ 00:05:50.009 Brian Sloane: And whether it’s, you know, whether that’s a full-time thing or not, I don’t think that’s the most important detail to me. So, in talking through that with Clint, he was like, oh, I know, you know.
42 00:05:50.010 ⇒ 00:05:57.850 Brian Sloane: I know someone that might be great to talk to, because I guess you probably do some of the latter, right? You’re… you’re jumping in, working with companies, helping them solve.
43 00:05:57.850 ⇒ 00:05:58.380 Uttam Kumaran: Yeah.
44 00:05:58.380 ⇒ 00:06:17.729 Brian Sloane: problems, you know, from what I read in data and AI, you know, I see product strategy, product analytics, different things like that. So, that’s kind of what led me towards you, and I’d love to learn more about what you do, what your thoughts are on the space, and I’ll stop there, but .
45 00:06:17.730 ⇒ 00:06:33.809 Uttam Kumaran: Sure, sure, sure. No, that’s amazing as a form of background. Yeah, it’s a great handoff. So, my background is in computer engineering and then, you know, sort of data engineering. I worked, you know, at a number of firms, sort of increasingly smaller in New York.
46 00:06:33.810 ⇒ 00:06:46.389 Uttam Kumaran: As, like, a BI engineer, then I kind of data engineering, and then I built internal reporting teams, then I kind of transitioned. I worked on, customer-facing analytics for a startup, sort of built out their
47 00:06:46.390 ⇒ 00:06:55.019 Uttam Kumaran: free, freemium, enterprise, sort of customer analytics suite. And then, like, the last company prequel, sort of…
48 00:06:55.020 ⇒ 00:07:10.660 Uttam Kumaran: went from, like, paper to first product for… for their initial, like, sort of a no-code transformation, like, semantic layer building. This was, like, 2022. So… so I’ve done sort of a bunch of different roles in data. I’m very… you know, I was personally really opinionated on data products.
49 00:07:10.660 ⇒ 00:07:27.369 Uttam Kumaran: And use a lot of data products, and sort of the person that, like, reads all the, you know, update blogs on everything, and sort of goes to all the meetups, and so getting a chance to build my own was really, really fun. And then, yeah, sort of left… left that company, and then kind of, like, unexpectedly, and was
50 00:07:27.600 ⇒ 00:07:34.520 Uttam Kumaran: just didn’t see eye-to-eye with, you know, the direction they were going. I mean, startups is really hard, and,
51 00:07:34.520 ⇒ 00:07:50.630 Uttam Kumaran: you know, as an employee, it’s like, you want to go all in, but if you don’t see that, like, hey, there’s gonna be something after 5 years, sort of tough. And that was, like, my kind of my third stint. And then, in the middle of each of those, I had done some, like, part-time consulting or contracting.
52 00:07:50.630 ⇒ 00:08:00.769 Uttam Kumaran: And was kind of, like, unimpressed overall with, like, how much business is coming to some of those contractors, and how bad the execution was.
53 00:08:00.920 ⇒ 00:08:08.250 Uttam Kumaran: Like, coming from startup world, like, you’re used to juggling a lot, but also you, you kind of, like, try to do your best work, and
54 00:08:08.250 ⇒ 00:08:25.639 Uttam Kumaran: I just saw… I just wasn’t impressed by, like, sort of the IT service system integrator market in… for data. I mean, you know, I’m familiar with working with a lot of the bigger names and sort of modern data stack consulting, like PH Data, Brooklyn Data, Slalom, but again, outside of that, and even with them, I feel like
55 00:08:25.640 ⇒ 00:08:41.309 Uttam Kumaran: some other implementations, I was like, this was slow and wasn’t, like, really that great. And so, when I left, this was about 3 years ago, like, April, actually, like, 3 years ago, I sort of was like, okay, should I go back to another startup, or should I try to…
56 00:08:41.350 ⇒ 00:08:45.370 Uttam Kumaran: You know, kind of, like, start something like a consulting company.
57 00:08:45.400 ⇒ 00:09:03.000 Uttam Kumaran: I knew I could do, like, freelance consulting, and so actually, like, that wasn’t as interesting to me as just, like, can we start a firm where, you know, I can call a bunch of my friends that I met in data, I can kind of compete at some of these larger contracts. The AI piece wasn’t that clear at that point, it was, like, just 3.5 was out, and…
58 00:09:03.000 ⇒ 00:09:10.560 Uttam Kumaran: wasn’t super clear as it is now on, like, how that affects the service business, but, you know, I was super forward on that, and so…
59 00:09:10.680 ⇒ 00:09:24.019 Uttam Kumaran: Yeah, that’s sort of how we started. So, basically just, like, 3 months into that, got our first sort of, like, contract. I was just working that, and then, you know, 4 or 5 months later, got another, and was able to bring on someone, like, part-time, and then…
60 00:09:24.120 ⇒ 00:09:39.870 Uttam Kumaran: slowly, like, climbed our way. It’s a completely bootstrapped business. We have about 23 people now. Sort of, yeah, sort of a bunch of… now, actually, maybe, like, 60%, 70% here in the States, and kind of some people scattered.
61 00:09:39.870 ⇒ 00:09:51.329 Uttam Kumaran: wherever. I mean, again, we recruit a lot from, like, dbt Slack, like, The Measure Slack, just, like, wherever I know great data people are, and I feel like we’ve done a good job at giving those folks a great home.
62 00:09:51.330 ⇒ 00:10:02.599 Uttam Kumaran: And really what’s been, I feel like, a joy is, like, it’s similar to a startup in where you’re running, like, multiple data teams, embedded into multiple different companies, and so there is a sort of a complexity
63 00:10:02.600 ⇒ 00:10:11.789 Uttam Kumaran: And, like, a context switching to that, but ultimately, like, the work isn’t as hard as anything that I’m sure me and you have done before. It’s actually more about, like.
64 00:10:11.850 ⇒ 00:10:14.250 Uttam Kumaran: We’re typically called when there’s a fire.
65 00:10:14.400 ⇒ 00:10:26.900 Uttam Kumaran: And so you’re not often walking into a situation that’s, like, hunky-dory and, like, everything’s going well. So part of that is, like, people, part of that is, like, like, actually just, like, the engineering work, and so we’re sort of having to…
66 00:10:26.900 ⇒ 00:10:34.530 Uttam Kumaran: deal with each of those constraints. And then there’s also team building, right? Like, being an internal engineer is much different than being a consultant.
67 00:10:34.530 ⇒ 00:10:49.869 Uttam Kumaran: But there’s also a lot of ways people think about consultants that we are not. Like, we don’t do any, like, staff augmentation or, like, dev shop style work. It’s all owned relationships with the companies, whether it’s, like, C-suite or, you know, VP level and up.
68 00:10:49.890 ⇒ 00:11:02.799 Uttam Kumaran: And so we’ve sort of climbed to build that reputation, build relationships. And so, on one side, you know, that’s sort of like our data story as to starting a traditional data consultancy. Throughout the whole process, though.
69 00:11:02.800 ⇒ 00:11:12.160 Uttam Kumaran: we’ve used AI to build the whole business. So, like, whether it started just, like, for emails or for contracts, and then now it’s sort of at a completely different level, where we have, like.
70 00:11:12.160 ⇒ 00:11:25.190 Uttam Kumaran: internal agents, everybody in the company, including, like, the business side, is using cursor, Cloud Code, or some format of executing their knowledge work. We have skills that we’re developing, we have harnesses that we’re developing.
71 00:11:25.240 ⇒ 00:11:38.130 Uttam Kumaran: And so our speed is really, really amazing. And then really about, like, a year and a half ago, I felt like we were far enough around AI that actually, like, hey, we should go deploy AI as a service.
72 00:11:38.130 ⇒ 00:11:49.859 Uttam Kumaran: And so we’ve also sort of now do several different AI engagements, whether that’s strategy work, whether that’s actually building agents, harnesses, skills. There’s also, like, a huge, like, learning and development component to that.
73 00:11:49.860 ⇒ 00:12:06.330 Uttam Kumaran: So that’s, like, sort of the state of the… of the business now, is, like, we have, like, 3 core service areas. Data, which is, like, data engineering, modeling, so that’s dbt, Snowflake, work. We have, like, strategy and analytics, so that’s, like, Amplitude, Mixed panel, product analytics.
74 00:12:06.330 ⇒ 00:12:12.399 Uttam Kumaran: traditional, like, McKinsey-Bain-style, like, decision intelligence, and then we have AI, which is sort of, like.
75 00:12:12.430 ⇒ 00:12:22.929 Uttam Kumaran: kind of, like, encompasses quite a lot. It actually has some overlap. You know, for example, we do, like, Cortex AI work on the Snowflake platform. Okay, that’s a mix of, sort of, both modes.
76 00:12:24.190 ⇒ 00:12:31.480 Uttam Kumaran: And yeah, and I think in the last, sort of, like, six… yeah, in the last 6 or 7 months, we’ve seen a lot of growth. And so, I feel like…
77 00:12:31.620 ⇒ 00:12:37.320 Uttam Kumaran: What’s been our advantage in the market is that AI engineering is, like.
78 00:12:37.400 ⇒ 00:12:54.179 Uttam Kumaran: I’ve always seen this, and I just feel like the market really just caught up, is, like, it’s mostly data engineering. Like, it’s, like, 90% data engineering, on two sides. It’s like, you have to land the data into structured context, whether that’s database, whether that’s, like, in-memory, whether that’s, like, on-the-fly context.
79 00:12:54.200 ⇒ 00:13:04.329 Uttam Kumaran: Whether that’s RAG or whatever, and then on the other side, you have integrations, like, is that through a Slack assistant? Is that through Teams? Is that through an email or a background workflow?
80 00:13:04.720 ⇒ 00:13:14.410 Uttam Kumaran: picking the LLM is kind of the easiest part, and that’s actually getting cheaper and better every day, but I think what’s not getting easier is the fact that people are, like, just trying to one-shot really difficult problems.
81 00:13:14.430 ⇒ 00:13:29.959 Uttam Kumaran: And these are actually sophisticated sort of solutions to deliver, an end-to-end solution that’s, like, not, like, completely deterministic, but is, like, predictable, and actually, like, achieves an outcome versus, like, just throw a bunch of data into ChatGPT.
82 00:13:30.070 ⇒ 00:13:44.339 Uttam Kumaran: Which is, frankly, like, where still most people are. And so we’re in an interesting boat where our company is pretty far, we’re figuring out how to commercialize a lot of that, but our customers are still really far behind, many of which are just doing the normal data stuff.
83 00:13:44.450 ⇒ 00:13:59.680 Uttam Kumaran: let alone, like, anything in AI. However, we’re trying to shift our business to be, like, we’re the AI partner. We also do… we are good as an AI partner because of all the data, you know, background that we have. And in addition, we’re really forward on the AI side, so…
84 00:14:00.000 ⇒ 00:14:02.810 Uttam Kumaran: That’s, like, the spiel.
85 00:14:03.170 ⇒ 00:14:12.269 Brian Sloane: Makes a lot of sense, and I think, you know, I think that the progression makes sense as well from the underlying, you know, data stuff to AI, and…
86 00:14:12.640 ⇒ 00:14:20.119 Uttam Kumaran: Not as linear, I will say, as, like, I was able to capture, like, we… I didn’t be like, hey, tomorrow we’re doing this. It’s sort of, like, congealed into this, but…
87 00:14:20.230 ⇒ 00:14:27.669 Uttam Kumaran: we rolled with the punches really well, which I think is more of, like, what our strength is. You know, whatever the… wherever the market sort of weaves us.
88 00:14:27.900 ⇒ 00:14:31.819 Uttam Kumaran: you know, I think that’s where we’re going, and in data, you’re seeing it’s… everything’s going towards, like.
89 00:14:31.980 ⇒ 00:14:45.740 Uttam Kumaran: natural language style interfaces for querying, so a lot of text-to-SQL, a lot of, like, rendering image… rendering decisions on the fly, but it’s like, you still need data warehouses, you still need various modes of capturing information, you know?
90 00:14:46.010 ⇒ 00:14:52.980 Brian Sloane: Yeah, makes a lot of sense, and I think, what you described as your state of
91 00:14:53.110 ⇒ 00:15:02.490 Brian Sloane: of life, you know, 3 years ago, or whenever that was, is, like, in some ways, where I am at the moment, where I’m like, should I be joining another
92 00:15:02.780 ⇒ 00:15:15.579 Brian Sloane: startup or something, or… but my mind was like, oh, maybe this is an opportunity to… to do some of this consulting. Admittedly, I haven’t done… in transparency, I haven’t done a lot of that consulting. Yeah. I’ve.
93 00:15:15.580 ⇒ 00:15:25.080 Uttam Kumaran: And you’ll be surprised, most of the people at that company are internal product people that I… because, like, I also didn’t really do it very seriously, and frankly, I… like, most of those folks…
94 00:15:25.080 ⇒ 00:15:35.829 Uttam Kumaran: in, like, high-level consulting, they’re not, like, really good at engineering. The thing that is, like, we’ve always kind of struggled with this, and we’re getting a lot better, is, like, it’s a heavy… it’s a much heavier communication, and, like.
95 00:15:35.960 ⇒ 00:15:46.160 Uttam Kumaran: managing up sort of situation, and then if you’re an internal engineer. Because it’s all hinged on… it’s oftentimes the bigger company we work for.
96 00:15:46.320 ⇒ 00:15:52.719 Uttam Kumaran: they’re actually just happy, like, even if we do a decent job. And so we’ve always had engineering as our strength, but…
97 00:15:52.830 ⇒ 00:15:59.509 Uttam Kumaran: the communication is really, like, interesting. It’s a lot of, like, okay, decks and progress updates and things like that, and…
98 00:15:59.750 ⇒ 00:16:09.430 Uttam Kumaran: But most of the people start in this business either from, like, an MBA, where they don’t really know the delivery aspect of the service, but they, like, can sell it, or you have, like, folks like us that are, like.
99 00:16:09.700 ⇒ 00:16:13.230 Uttam Kumaran: I could build whatever you need, but, like, we’re figuring out the packaging.
100 00:16:13.410 ⇒ 00:16:22.059 Uttam Kumaran: I… I don’t know, I prefer to be able to do everything, and we’ll figure out the packaging, and so luckily, I think in the last, like, 2 years, year and a half, we’ve gotten really good at, like.
101 00:16:22.210 ⇒ 00:16:24.739 Uttam Kumaran: The sales, the packaging, the delivery…
102 00:16:24.870 ⇒ 00:16:33.310 Uttam Kumaran: and the engineering we’ve always been pretty, pretty, pretty good at, and so I don’t think that’s that big of a deal. I think more of the deals, actually, are you opinionated about, like.
103 00:16:33.430 ⇒ 00:16:46.650 Uttam Kumaran: how to deploy a service, or, like, how to engineer something, and also, are you, like… you have a sense of urgency? Because in consulting, most of the time, like, most of our peers and competitors, like, don’t have any sense of urgency, and so…
104 00:16:46.800 ⇒ 00:16:50.799 Uttam Kumaran: I don’t know, they tend to just, like, get the contract, and they’re like, cool, we’re in, like.
105 00:16:50.980 ⇒ 00:16:54.580 Uttam Kumaran: you tell us what to do. We’re not like them, like, we’re like a partner.
106 00:16:54.700 ⇒ 00:17:04.669 Uttam Kumaran: And I’m like, you’re not holding your end of the bargain by, like, giving us great direction. Like, we talk to the clients that way, you know? Which I think has been fun, and I think that’s why we’ve been able to grow
107 00:17:05.140 ⇒ 00:17:06.669 Uttam Kumaran: You know, so fast.
108 00:17:07.569 ⇒ 00:17:23.209 Brian Sloane: Yeah, it sounds exciting. I actually… I’m curious, you were talking through all, like, a lot of the high level there. Do you… are you building, like, your own solutions, that you help companies with, or are you helping them implement other
109 00:17:23.449 ⇒ 00:17:42.119 Brian Sloane: like, you know, you’re bringing in, you know, a Sitch or a Fivetran for a data thing, and then you hand it off to them, or maybe it’s a combination of both, but are you putting your own layer, like, are you delivering a product that you kind of built, if you will, to them, or is it pretty much all just implementation of other products?
110 00:17:42.380 ⇒ 00:17:51.300 Uttam Kumaran: Yeah, so… I think this is where, like, there’s a big evolution happening in, like, services businesses. So, traditionally, we go and we implement all their infrastructure.
111 00:17:51.300 ⇒ 00:18:02.749 Uttam Kumaran: So they… the client has a direct relationship with Five Trainer Stitch, Snowflake, dbt, the BI tool, Amplitude, whatever. We implement. We also have, like, great partnerships with them, so, like.
112 00:18:02.760 ⇒ 00:18:15.239 Uttam Kumaran: we sort of implement the best in class, and then sort of, like, help them do that, so really more aligned to System Integrator. Now, though, because of our capabilities, we’re actually able to, like, take
113 00:18:15.390 ⇒ 00:18:21.679 Uttam Kumaran: Off-the-shelf, open-source software, and sort of, like, do a little bit of, like, last mile work on top of that.
114 00:18:21.680 ⇒ 00:18:22.170 Brian Sloane: Hmm.
115 00:18:22.170 ⇒ 00:18:33.480 Uttam Kumaran: in addition to just, like, pretty serious integration work, or, like, development work, on the client’s behalf. So we’re not necessarily… we don’t do any managed service. We also don’t have any products.
116 00:18:33.750 ⇒ 00:18:53.090 Uttam Kumaran: But we have a lot of know-how, and we have, like, internal products, meaning, like, we build a lot of stuff for ourselves, which shows that, like, we can go basically do that for the customer. Really, the thing, and this is sort of, like, what we’re talking about, is, like, you just… we could do a lot more customization than previously we were allowed to do as a services firm.
117 00:18:53.090 ⇒ 00:18:59.340 Uttam Kumaran: Like, typically you have, like, you have sort of the stack, which is, like, all the tools, and then you have, like, the firm, which is, like.
118 00:18:59.340 ⇒ 00:19:09.159 Uttam Kumaran: us who come in and, like, help implement it. Now we can almost be like, actually, you know, like, for 20% of the cost of stuff, like, and for 100% more control and security.
119 00:19:09.160 ⇒ 00:19:26.279 Uttam Kumaran: you can implement, like, this feature, right? Snowflake’s not a great example, but, like, you kind of know what I mean. And that’s, like, what we’re starting to do. And that’s been really fun, because, again, we… we’re trying as much as possible to align towards, like, a business outcome, not necessarily, like.
120 00:19:26.400 ⇒ 00:19:35.799 Uttam Kumaran: how much it’s gonna cost to develop it. And as a services firm, you weren’t typically allowed to price that way, or do things that way. It was, like, all, like, time and materials.
121 00:19:36.050 ⇒ 00:19:47.719 Uttam Kumaran: now we’re actually able to price, sort of, like, hey, we’re gonna try to deliver an outcome, or, like, we’re gonna almost… for me, I try to think about us competing with, like, internal teams. Like, we’re given a budget to deliver, like, on a set of objectives.
122 00:19:47.840 ⇒ 00:20:04.759 Uttam Kumaran: Because ultimately, like, our hour is actually getting more and more efficient, so billing, like, a billable hour is not a business model that we’re interested in anymore. But we can only say that if we’re actually able to deliver tons and tons of value, and so we’re able to come in and actually do a lot of, like.
123 00:20:05.470 ⇒ 00:20:15.150 Uttam Kumaran: software customization work, light software development, like, actually app development work. And again, it’s all internal, so nothing’s, like, customer-facing, typically.
124 00:20:15.150 ⇒ 00:20:15.660 Brian Sloane: Nope.
125 00:20:15.660 ⇒ 00:20:24.279 Uttam Kumaran: But we’re able to go beyond just, like, plugging tools in, and then, you know, again, we were, like, developing dbt models, developing dashboards.
126 00:20:24.500 ⇒ 00:20:32.249 Uttam Kumaran: we’re able to go beyond that now, you know, which has been awesome. And all of our team is totally equipped to do that as well.
127 00:20:33.320 ⇒ 00:20:33.980 Brian Sloane: Got it.
128 00:20:34.560 ⇒ 00:20:36.330 Brian Sloane: Yeah, that makes a lot of sense.
129 00:20:38.700 ⇒ 00:20:44.630 Uttam Kumaran: Yeah, I wonder what’s, like, your… what’s, like, your gut instinct, like, thinking about it? Because it’s also important to be, like, what are you…
130 00:20:45.340 ⇒ 00:20:52.200 Uttam Kumaran: like, what the goal… what your goal is, you know? If you’re like, okay… I mean, because for me, the option was, like, hey, you go to, like, a bigger company.
131 00:20:52.470 ⇒ 00:20:58.329 Uttam Kumaran: I think it’s just gonna be, like, sit back and relax, and, like, whatever. Then you go to startup, it’s…
132 00:20:58.490 ⇒ 00:21:08.630 Uttam Kumaran: Product startup, I don’t know. Like, I’ve worked in product service most of my career. I don’t know how… I mean, I’m talking to you, I wonder how you feel, but I think it’s so hard to make a bet, like…
133 00:21:08.970 ⇒ 00:21:16.959 Uttam Kumaran: yeah, I don’t know where you make a bet. I guess you make a bet at the LLM layer, and then sort of as close to that as possible, because
134 00:21:17.070 ⇒ 00:21:19.910 Uttam Kumaran: the application layer, I feel like.
135 00:21:20.300 ⇒ 00:21:23.740 Uttam Kumaran: Unless you have a really amazing distribution method.
136 00:21:23.900 ⇒ 00:21:29.880 Uttam Kumaran: that can be your moat. Like, I don’t know if there’s much, like, in terms of a technical moat, unless your product is, like, actually super, super…
137 00:21:30.050 ⇒ 00:21:40.809 Uttam Kumaran: superior or unique, so I’m just… yeah. And then the services angle, starting a services company is… it’s tough, like, it’s a people-heavy business.
138 00:21:41.220 ⇒ 00:21:43.890 Uttam Kumaran: It’s a lot slower sales cycles.
139 00:21:44.230 ⇒ 00:21:55.109 Uttam Kumaran: it’s not a recurring revenue situation, unless you can sort of, like… we’re starting to get into that mode. So yeah, I mean, it’s not like there’s an easy route, but…
140 00:21:55.400 ⇒ 00:21:59.480 Uttam Kumaran: I don’t know, product startups seems tough to me, but yeah, I don’t know what you’re thinking.
141 00:22:00.440 ⇒ 00:22:06.850 Brian Sloane: Yeah, I mean, I… I would say… To your first point.
142 00:22:07.530 ⇒ 00:22:15.120 Brian Sloane: Yeah, you could join a big company and relax, although I’m, you know, I’m looking for something that is,
143 00:22:15.440 ⇒ 00:22:18.380 Brian Sloane: mentally.
144 00:22:18.380 ⇒ 00:22:21.180 Uttam Kumaran: Also, medium. Medium company.
145 00:22:21.180 ⇒ 00:22:22.919 Brian Sloane: But sometimes it’s mentally rewarding.
146 00:22:22.920 ⇒ 00:22:23.310 Uttam Kumaran: Yeah.
147 00:22:23.310 ⇒ 00:22:37.570 Brian Sloane: Right? So, admittedly, right, you know, working at Qlik, which was, 3,500 people, which is, like, not that big compared to, you know, like, a Google of the world, but big enough that there’s a lot of bureaucracy.
148 00:22:37.570 ⇒ 00:22:38.090 Uttam Kumaran: Yes.
149 00:22:38.090 ⇒ 00:22:46.390 Brian Sloane: you know, challenges, that you don’t see when I was working at Stitch originally, which was 30 people. And,
150 00:22:46.440 ⇒ 00:23:01.460 Brian Sloane: And, you know, I didn’t get up every morning with the excitement that I did when I was working on Switch back in the day. So for me, it’s like finding a place that brings that excitement, whether it’s a product or not, or a service, or whatnot.
151 00:23:01.630 ⇒ 00:23:12.140 Brian Sloane: And then it’s a strong team. I think those are the things that really, are important, something that you can resonate, to, and that people that you really enjoy working with.
152 00:23:12.800 ⇒ 00:23:16.920 Brian Sloane: And, yeah, as, you know, a product startup, I think,
153 00:23:16.920 ⇒ 00:23:33.280 Brian Sloane: for me, it would… those would be the main things. I think it’s, like, there’s a risk with that, but if you can find something that seems exciting to work on every day, then that’s, like, gonna bring you the most joy… most joy, and maybe it doesn’t pan out, and you don’t become a unicorn or something, but at least you had fun.
154 00:23:33.280 ⇒ 00:23:45.729 Uttam Kumaran: There’s a lot of room in the middle, yeah, so that’s… yeah, that’s sort of more of it, is like, you know, that’s what’s unique, I think, about our business, is that we’re not supposed to be operating sort of like we are, and it’s partly my fault, because
155 00:23:45.730 ⇒ 00:23:54.690 Uttam Kumaran: we… I operate the business like a product startup, in that, like, there’s a lot of collaboration. Like, it’s not a typical consultancy where you’re like, oh, I’m just on this client, I don’t know anybody. It’s like…
156 00:23:54.780 ⇒ 00:24:06.729 Uttam Kumaran: Everybody, it’s like, it’s… on the inside, it’s like a product company. It runs, like, everybody knows everybody, and then almost our service is, like, the product in the way we think about delivering and having, like, a platform approach.
157 00:24:06.750 ⇒ 00:24:16.809 Uttam Kumaran: Which I don’t… in this industry, which again, like, I’m… over the last 3 years, I’ve learned a lot about is not the case. Like, most people don’t start to…
158 00:24:17.090 ⇒ 00:24:19.650 Uttam Kumaran: Do playbooks and start to, like.
159 00:24:20.000 ⇒ 00:24:36.900 Uttam Kumaran: modularized, like, work until, like, 5-10 years in, which, for me, I’m like, what? Like, that’s only… like, I only think about abstractions and, like, baskets of work and clear deliverables and trying to, like, be like, cool, we have this piece, now let’s, like, build
160 00:24:36.940 ⇒ 00:24:44.069 Uttam Kumaran: So, it’s been interesting. The other part is, like, I’ve… we’ve been able to attract a lot of people that I don’t think themselves they would see
161 00:24:44.150 ⇒ 00:24:54.449 Uttam Kumaran: Them working in consulting, but we frame the problem, and the way we attack it is in this way, where we’re trying to create these reproducible systems of delivering services work
162 00:24:54.700 ⇒ 00:25:09.799 Uttam Kumaran: And then we use a whole lot of AI, and that’s also the thing, I think, in the data industry, it’s still a little bit slow, and, in the consulting industry, it’s even worse. Like, it’s so bad. I think most people are, like.
163 00:25:09.930 ⇒ 00:25:14.669 Uttam Kumaran: they may have turned Copilot on in Teams, and sort of, that’s sort of the way they’re running, so…
164 00:25:15.140 ⇒ 00:25:28.150 Uttam Kumaran: I feel like it’s been really fun to run this business, and then we have, like, super amazing engineers, so I’m not, like, a typical MBA-style, like, business guy, like, I still do a lot of, like.
165 00:25:28.390 ⇒ 00:25:36.849 Uttam Kumaran: my… most of my screen are, like, cloud code terminals right now, and so I’m developing a lot of our platform, which is, like, okay, our Slack assistant.
166 00:25:40.720 ⇒ 00:25:44.259 Brian Sloane: Oh, Lost you. Is that me or you?
167 00:25:46.790 ⇒ 00:26:06.439 Uttam Kumaran: work as deals, and trying to get us partnerships with, like, Google or Amazon, and then enabling everybody. Like, how am I enabling people to actually, use skills to develop, like, dbt models, go to market with, like, Snowflake? Like, can we launch Snowflake for a client in, like, 2 weeks versus, like, typically that’s, like, 3 months, 6 months, you know?
168 00:26:06.470 ⇒ 00:26:14.450 Uttam Kumaran: And so I’m thinking more about, like, the Brainforge as a platform for kind of, like, folks like you that are like, okay, there’s an interesting challenge.
169 00:26:14.580 ⇒ 00:26:28.930 Uttam Kumaran: But it’s interesting, because we’re in a market where the innovation’s super, super low. Like, not only innovation on, like, business model, but, like, you’re not gonna meet an innovation partner, typically, that’s a consultancy. That… those… that type of behavior is reserved for
170 00:26:29.000 ⇒ 00:26:47.709 Uttam Kumaran: product startups, and I feel like we’ve done a lot, not only innovating in our own company, in, like, dogfooding basically everything we use on the AI side, but also innovating on behalf of clients, developing solutions faster for them, getting them onboarded onto, like, all the AI tools that come with their different data platform decisions.
171 00:26:49.510 ⇒ 00:26:55.090 Uttam Kumaran: And so, yeah, it’s… it’s been fun. Like, I think we’ve carved out a piece of this, like, market that we’re really just trying to, like.
172 00:26:55.220 ⇒ 00:26:56.770 Uttam Kumaran: Dig into, you know.
173 00:26:58.220 ⇒ 00:27:02.339 Brian Sloane: Good. Yeah, that makes a lot of sense.
174 00:27:02.640 ⇒ 00:27:17.859 Brian Sloane: I guess my question for you is, you know, do you see, you know, do you have any, like, strong advice for me? Also, like, is there an opportunity for us to work together in some capacity in the future? You know, I’m just… I’m exploring all my options, so I’m just curious to understand… Sure.
175 00:27:18.640 ⇒ 00:27:20.549 Uttam Kumaran: Yeah, I mean, this is where, like, I have…
176 00:27:20.550 ⇒ 00:27:21.020 Brian Sloane: head.
177 00:27:21.580 ⇒ 00:27:23.049 Uttam Kumaran: Yeah, I have a lot of…
178 00:27:23.150 ⇒ 00:27:35.490 Uttam Kumaran: close friends that are in your space. I mean, one, like, you come recommended from Clint, like, you totally have, like, your ability to come see the inside of our business and chat with some of our people. I mean, I think…
179 00:27:35.630 ⇒ 00:27:48.639 Uttam Kumaran: hearing your background and hearing what you’re interested in, certainly, I think, at the minimum, especially if you’re interested in fractional, you can totally come in, see what it’s like to work with, like, one client, and sort of see how our operations are, and even just dip your toe.
180 00:27:48.670 ⇒ 00:28:02.200 Uttam Kumaran: I will say I don’t think that’s, like, very common in the consulting business, but, like, I run the company, and we’ve done that with a lot of people, where people start, sort of, like, fractionally, and then whether they’re like, okay, I want to go this direction, or like, okay, I’m actually gonna… I actually…
181 00:28:02.300 ⇒ 00:28:17.799 Uttam Kumaran: I don’t know, working with clients is tough, whatever. So, certainly, I think I would love to introduce you to a couple more people, just for you to learn about our business more, and they’ll tell you more about, like, kind of the stuff we’re working on. And then, yeah, I think broadly, I think you’re in a…
182 00:28:17.800 ⇒ 00:28:27.119 Uttam Kumaran: really amazing moment to make a, like, an awesome decision while AI is hot. I think my one piece of advice is don’t go anywhere where they’re not, like.
183 00:28:27.500 ⇒ 00:28:38.039 Uttam Kumaran: speaking about AI in the first, like, 5 minutes. Second, don’t go anywhere where… if they’re speaking about AI, and then they don’t themselves use it, like.
184 00:28:38.240 ⇒ 00:28:47.000 Uttam Kumaran: in the way that they’re talking about it. People could be early, but if someone is like, we’re super AI-forward, our product’s AI, and then internally they’re,
185 00:28:47.260 ⇒ 00:28:51.750 Uttam Kumaran: they’re, like, all just using, like… they’re just doing, like, prompting and chat GPT, like…
186 00:28:51.870 ⇒ 00:28:55.599 Uttam Kumaran: like, projects, I would be suspect, you know?
187 00:28:55.600 ⇒ 00:28:55.950 Brian Sloane: Yep.
188 00:28:55.950 ⇒ 00:29:13.579 Uttam Kumaran: So, that’s probably a second point, is that we work with a lot of vendors and a lot of partners who appear very, very AI-forward, who are, like, the least bit AI-forward. And so, that’s probably… whatever industry or decision you go into, I think trying to hold that true, because
189 00:29:13.770 ⇒ 00:29:27.370 Uttam Kumaran: I don’t know… I couldn’t sell AI or do AI work without having tried to run an AI… really, really AI-native company. Like, I read a lot about RAMP and a lot of these guys, and we’re sort of doing a lot of the same things.
190 00:29:27.470 ⇒ 00:29:33.840 Uttam Kumaran: But I don’t know how you could learn to talk, and especially learn to sell a solution in AI without…
191 00:29:34.080 ⇒ 00:29:37.770 Uttam Kumaran: Basically doing it yourself, like, and understanding the primitives.
192 00:29:37.870 ⇒ 00:29:54.100 Uttam Kumaran: So that’s probably my one advice, whether you go into product startup, or anywhere in product, or into consulting, like, try to join an environment where they’re very forward, even if they’re early, and maybe they haven’t figured it all out, that’s fine, but, like, where you just see a really low barrier to, like.
193 00:29:54.300 ⇒ 00:30:01.870 Uttam Kumaran: use Claude… use Claude code, develop skills, like, do that? I… I don’t know, I think that’s probably my, like.
194 00:30:02.640 ⇒ 00:30:07.009 Uttam Kumaran: That’s my biased advice. If, like, I was on the market, like, that’s what I would be really thinking about.
195 00:30:07.010 ⇒ 00:30:20.909 Brian Sloane: That makes a lot of sense. I mean, you know, recently I’ve spent a lot of my time just, like, using Cloud Code myself for little personal projects and things like that, and I even, you know, I spun up, OpenCloud for myself to, like, see, like, what would, like.
196 00:30:20.910 ⇒ 00:30:31.609 Brian Sloane: what would life be like with a personal assistant, right? And I’ll admit that, like, doing it for, like, personal stuff, it’s sometimes hard to find the best use cases for it.
197 00:30:31.610 ⇒ 00:30:33.530 Uttam Kumaran: Oh my god, it’s giving me, like… Yes, exactly.
198 00:30:33.530 ⇒ 00:30:43.239 Brian Sloane: morning briefings based off of my calendar, and what I’m going to be doing, and stuff like that, but it’s, you know, it’s not gonna do the laundry for me yet.
199 00:30:43.240 ⇒ 00:30:43.610 Uttam Kumaran: Yes.
200 00:30:43.610 ⇒ 00:30:44.710 Brian Sloane: along those lines.
201 00:30:44.710 ⇒ 00:30:51.009 Uttam Kumaran: You know, in a business, there’s so many problems, yet, like, it’s almost like the integration work is, like.
202 00:30:51.070 ⇒ 00:31:07.039 Uttam Kumaran: really tough, or, like, getting the requirements, or, like… So that’s where we’re at, you know? And that’s why this business is a fun guinea pig, because I’ve had to solve every step of the way from being solo, to, like, a few people, to now we have, like, a bunch of departments, and…
203 00:31:07.080 ⇒ 00:31:13.910 Uttam Kumaran: I’ve been able to, like, test it the whole way, and so we are the first customer of every single thing we do, which is…
204 00:31:13.910 ⇒ 00:31:14.280 Brian Sloane: Right.
205 00:31:14.280 ⇒ 00:31:18.359 Uttam Kumaran: Which is fun, but it’s just as painful because, like, there’s not, like, a playbook.
206 00:31:18.660 ⇒ 00:31:23.129 Uttam Kumaran: But even for our customers, there’s even less of a playbook, so we are that, like, sort of…
207 00:31:23.490 ⇒ 00:31:42.120 Uttam Kumaran: North Star, and that we’ve tried it internally. So our demos often are just, like, our stuff working for our things, and they rhyme a lot. You know, you’re producing for sales, there’s, like, producing meeting notes, or generating, like, hey, I want to prepare for this meeting, or I want to understand, or I want to get feedback on a meeting.
208 00:31:42.120 ⇒ 00:31:47.759 Uttam Kumaran: And, like, we’ve… I’m sort of systematically going through, like, sales, finance, marketing, legal, delivery.
209 00:31:47.760 ⇒ 00:32:02.649 Uttam Kumaran: And, like, pushing, like, what is the latest? How do we use it? Like, not… so not just engineering, like, engineering is, like, table stakes, right? So, like, that’s not a question. It’s actually, like, the rest of the business where your stakeholders are very non-technical.
210 00:32:02.770 ⇒ 00:32:07.939 Uttam Kumaran: I’m like, how do you solve a problem for them, you know? That’s been really, really fun.
211 00:32:09.320 ⇒ 00:32:17.010 Brian Sloane: Yeah, and so to your point, that’s, like, whatever I end up doing, I want to be using those tools to do it.
212 00:32:17.010 ⇒ 00:32:17.450 Uttam Kumaran: Yeah.
213 00:32:17.450 ⇒ 00:32:30.390 Brian Sloane: does seem like the future, so, that’s kind of, that would certainly be table stakes for me, is, like, to be able to do that stuff, as part of whatever I end up doing.
214 00:32:31.080 ⇒ 00:32:32.160 Brian Sloane: So…
215 00:32:32.450 ⇒ 00:32:49.959 Brian Sloane: Yeah, respectful of your time, I know we’re already past the official slot here. I’d, I’d say, yeah, like, if there’s other folks, you know, that I could talk to to hear more about what you’re all doing, and understand if there’s, you know, an opportunity for me to help out, I’d love to…
216 00:32:50.900 ⇒ 00:32:55.880 Brian Sloane: To continue that conversation, and just kind of see where it goes.
217 00:32:56.620 ⇒ 00:33:09.250 Uttam Kumaran: Okay, definitely, yeah, and then even on this conversation thing, any reflection on what I said, or you can grill our folks on whether I’m lying about where we are, too, like, I would… I would… we’re pretty open book and pretty transparent about
218 00:33:09.250 ⇒ 00:33:20.390 Uttam Kumaran: our challenges, but also, like, where the business is heading. So, you know, I’ll definitely… let me talk internally and get you in front of a few people, just so you can ask them about their role, and…
219 00:33:20.390 ⇒ 00:33:33.890 Uttam Kumaran: I mean, I think it’s a fair question. Anybody you talk to at the business to ask them how they’re using AI or have been enabled, I think you’ll be… I think you’ll hopefully be impressed, and yeah, I mean, I… again, I think we’re a friendly place to people that want to start fractionally and sort of, like.
220 00:33:33.930 ⇒ 00:33:40.970 Uttam Kumaran: see what it’s like to… to… to do this. So, yeah, I’m looking forward to seeing if there’s an opportunity, for sure.
221 00:33:41.400 ⇒ 00:33:42.080 Brian Sloane: Awesome.
222 00:33:42.260 ⇒ 00:33:44.919 Brian Sloane: Great. Well, thank you for your time.
223 00:33:44.920 ⇒ 00:33:45.590 Uttam Kumaran: Yeah, thank you.
224 00:33:45.590 ⇒ 00:33:48.309 Brian Sloane: Like, good conversation, and we’ll be in touch.
225 00:33:48.720 ⇒ 00:33:50.399 Uttam Kumaran: Okay, perfect. Thanks, Brian. Appreciate it.
226 00:33:50.400 ⇒ 00:33:50.940 Brian Sloane: Right.
227 00:33:51.410 ⇒ 00:33:51.780 Uttam Kumaran: Bye.