Meeting Title: Uttam-Kumaran <> Anna-Malfanova Date: 2024-08-12 Meeting participants: Uttam, Anna Malfanova
WEBVTT
1 00:04:40.740 ⇒ 00:04:42.230 Anna Malfanova: Yeah, she’s gone on board.
2 00:04:55.570 ⇒ 00:04:56.500 Anna Malfanova: No.
3 00:04:57.370 ⇒ 00:04:58.430 Anna Malfanova: the
4 00:05:04.150 ⇒ 00:05:06.819 Anna Malfanova: is here about.
5 00:05:15.520 ⇒ 00:05:16.510 Anna Malfanova: Oh, wow!
6 00:05:20.840 ⇒ 00:05:23.149 Anna Malfanova: Notice! How do you come?
7 00:05:27.680 ⇒ 00:05:29.900 Anna Malfanova: Your academic?
8 00:05:31.030 ⇒ 00:05:33.369 Anna Malfanova: But it’s not that, you know.
9 00:05:42.270 ⇒ 00:05:43.050 Anna Malfanova: Loom.
10 00:05:48.270 ⇒ 00:05:49.429 Anna Malfanova: Let’s see another
11 00:05:54.840 ⇒ 00:05:56.040 Anna Malfanova: in a budget.
12 00:05:56.730 ⇒ 00:05:57.939 Anna Malfanova: English support team
13 00:05:58.730 ⇒ 00:06:00.210 Anna Malfanova: or somewhere else.
14 00:06:11.390 ⇒ 00:06:12.469 Anna Malfanova: No, I think she’s
15 00:06:14.400 ⇒ 00:06:15.929 Anna Malfanova: the time of action
16 00:06:17.290 ⇒ 00:06:18.850 Anna Malfanova: very unpresidential.
17 00:06:19.440 ⇒ 00:06:20.200 Anna Malfanova: No shame.
18 00:06:26.670 ⇒ 00:06:27.650 Anna Malfanova: Publication.
19 00:06:32.150 ⇒ 00:06:33.169 Anna Malfanova: Oh, he’s
20 00:06:39.910 ⇒ 00:06:41.240 Anna Malfanova: recall them.
21 00:07:03.850 ⇒ 00:07:04.495 Anna Malfanova: And
22 00:07:21.690 ⇒ 00:07:22.600 Anna Malfanova: he’s occurring alone
23 00:07:23.640 ⇒ 00:07:25.770 Anna Malfanova: the most there is a controller.
24 00:07:30.170 ⇒ 00:07:32.109 Anna Malfanova: I’ll just click, cheat down
25 00:07:51.750 ⇒ 00:07:53.890 Anna Malfanova: usual stallum.
26 00:11:57.440 ⇒ 00:11:58.200 Anna Malfanova: Hmm.
27 00:13:12.880 ⇒ 00:13:14.959 Anna Malfanova: but you took a lot of them
28 00:14:09.810 ⇒ 00:14:11.850 Anna Malfanova: split between juvenile.
29 00:14:53.190 ⇒ 00:14:55.110 Anna Malfanova: neutral, neutral.
30 00:15:56.190 ⇒ 00:15:56.830 Uttam: Hello!
31 00:15:57.750 ⇒ 00:15:58.900 Anna Malfanova: Hello!
32 00:15:59.980 ⇒ 00:16:02.369 Uttam: And I said
33 00:16:02.660 ⇒ 00:16:04.319 Uttam: so, sorry for the delay.
34 00:16:04.840 ⇒ 00:16:16.889 Anna Malfanova: That’s fine. It’s okay. It’s okay. Nice to meet you, too. Let me make sure I pronounce your name correctly. It’s you, Tom, or please correct me.
35 00:16:16.890 ⇒ 00:16:17.630 Uttam: Utahm.
36 00:16:18.080 ⇒ 00:16:18.700 Anna Malfanova: Town.
37 00:16:19.200 ⇒ 00:16:19.960 Uttam: Yes.
38 00:16:20.160 ⇒ 00:16:22.069 Uttam: yeah, thank you. Sorry. I’m just coming.
39 00:16:22.680 ⇒ 00:16:25.070 Uttam: Quite a close friend of mine’s wedding today.
40 00:16:25.380 ⇒ 00:16:29.490 Anna Malfanova: Oh, this is an important occasion, of course, of course.
41 00:16:29.490 ⇒ 00:16:38.063 Uttam: Yeah, so so just just traveling back home. But I I wanted to make sure. Adam, really, you know, highly recommended you guys. So I I didn’t.
42 00:16:38.440 ⇒ 00:16:41.919 Uttam: you know. Was it really excited for this conversation? So thank you for taking the time.
43 00:16:42.320 ⇒ 00:17:03.970 Anna Malfanova: Yeah, thank you, too. Thank you. And yeah, I’m really interested, you know, to learn more about your company. I had time, and I’ve studied your website also visit your Linkedin page. So I see that you extensively do data analytics. And so it will be interesting to learn more. And of course I’ll be more than happy to tell more about us.
44 00:17:04.290 ⇒ 00:17:05.230 Anna Malfanova: and.
45 00:17:05.230 ⇒ 00:17:06.000 Uttam: Perfect.
46 00:17:07.349 ⇒ 00:17:08.610 Uttam: Yeah, maybe I.
47 00:17:08.750 ⇒ 00:17:12.569 Anna Malfanova: You’d love to proceed without web camera, right?
48 00:17:12.780 ⇒ 00:17:14.149 Anna Malfanova: Or you just didn’t.
49 00:17:14.150 ⇒ 00:17:20.010 Uttam: Yes, yeah, that’s perfect. Yeah. Sorry. I’m I’m just just in transit. But yeah, that’s totally fine.
50 00:17:20.010 ⇒ 00:17:21.829 Anna Malfanova: No problem, no problem.
51 00:17:22.106 ⇒ 00:17:25.309 Uttam: Yeah, I guess I’d love to tell you a little bit about
52 00:17:25.952 ⇒ 00:17:34.519 Uttam: you know the company. So Brain Forge is a company that we started. You know, about a year ago, and we
53 00:17:35.159 ⇒ 00:17:37.039 Uttam: with Snowflake and
54 00:17:37.059 ⇒ 00:17:53.319 Uttam: Dbt related data analytics. And so we work with a bunch of clients here in the Us. You know, primarily focused on data engineering data, modeling analytics, engineering. And then we do some like business intelligence related tasks as well. But you know.
55 00:17:53.419 ⇒ 00:17:55.629 Uttam: I’m sure you can understand.
56 00:17:56.129 ⇒ 00:18:02.459 Uttam: you know, good work for a client. They they try to ask you, for, you know other. Can you do other things for us?
57 00:18:02.879 ⇒ 00:18:10.829 Uttam: Lot of what I’m interested in is finding partners that we can involve in projects, you know, that are a little bit outside of our scope.
58 00:18:11.164 ⇒ 00:18:17.339 Uttam: And you know, of course, just would love to meet people that have access to, you know, great engineers. So.
59 00:18:22.152 ⇒ 00:18:25.109 Anna Malfanova: But I I lost you.
60 00:18:25.650 ⇒ 00:18:27.079 Uttam: Oh, you mentioned I mentioned that.
61 00:18:27.600 ⇒ 00:18:36.339 Uttam: Yeah, that we work. You know, with a bunch of different clients, and you know he really recommended that I speak to you just to see if there’s any opportunities for us to collaborate
62 00:18:36.380 ⇒ 00:18:37.650 Uttam: in the futures.
63 00:18:39.120 ⇒ 00:18:41.100 Anna Malfanova: Yeah, sure. Sure. Thank you so much.
64 00:18:41.100 ⇒ 00:18:42.520 Uttam: Your business, and you know.
65 00:18:44.470 ⇒ 00:18:52.250 Anna Malfanova: You know I have some breaks. I don’t know, probably. Do you hear me? Well, because I hear you with some breaks in connection.
66 00:18:52.250 ⇒ 00:18:56.870 Uttam: Oh, okay, give me one second. Let me just maybe I should just switch my air pods. Hold on
67 00:18:57.210 ⇒ 00:18:58.239 Uttam: one second.
68 00:19:52.300 ⇒ 00:19:53.369 Uttam: Okay, how is this.
69 00:19:54.838 ⇒ 00:19:56.719 Anna Malfanova: Let’s try it. Yeah, let’s try it.
70 00:19:56.720 ⇒ 00:19:57.480 Uttam: Okay.
71 00:19:57.480 ⇒ 00:20:13.620 Anna Malfanova: Good morning, girl. So let’s test it. Yeah, I got your idea that you cover data analytics solution mainly. And you’re interested to find a partner who can probably cover some expertise which is not within your scope.
72 00:20:13.620 ⇒ 00:20:15.490 Uttam: Yes, 100%. Yes.
73 00:20:15.490 ⇒ 00:20:36.740 Anna Malfanova: Okay, okay, gotcha, gotcha. Okay. So let me tell a few words about our company. And of course you’re welcome to interrupt me. And also, I’m basically also interested to discuss a data analytic direction, specifically data engineering. But I’ll get back to it a little bit later. Okay?
74 00:20:37.185 ⇒ 00:20:58.120 Anna Malfanova: So yeah, our company’s name is 7 pro we are software development and tech consultant company established in the United States and in Estonia. So yeah, we work with Adam already for a few years. And yeah, he already recommended quite a lot of customers to.
75 00:20:58.120 ⇒ 00:20:58.830 Uttam: Great.
76 00:20:59.020 ⇒ 00:21:13.110 Anna Malfanova: So my sincerest gratitude to him, you know, and we have indeed a very good and trustful cooperation. So I’m really happy that now we are speaking with you. Yeah, amazing.
77 00:21:13.540 ⇒ 00:21:34.679 Anna Malfanova: So yeah, regarding our tech expertise. We work basically in terms of the technologies, we work both with web technologies for Javascript Javascript to work with all frameworks like popular frameworks, I mean, react, note view, angular. Js.
78 00:21:34.680 ⇒ 00:21:59.480 Anna Malfanova: so all that popular stuff apart from Gs, we also work a lot with.net, with Java, with python. Oh, also, we provide quality assurance services, devops, services for customers if needed. Also ui design depending on the customers, requirements and needs of his
79 00:21:59.540 ⇒ 00:22:24.059 Anna Malfanova: project. We built our target solution for our clients. It is worth mentioning. We have 2 main corporation models for customers the 1st one is called out staffing Model. I’m sure you’ve heard about it. When we provide to you as a customer, a specialist it could be developers. I don’t know data scientists, data engineers.
80 00:22:24.060 ⇒ 00:22:30.240 Anna Malfanova: whoever so technical staff who work for you as a client
81 00:22:30.270 ⇒ 00:22:36.159 Anna Malfanova: full time and long term. Basically, it’s like your employee.
82 00:22:36.210 ⇒ 00:22:55.860 Anna Malfanova: but reside in in our premises. And it’s registered. This person registered on our side, and from our end also help you to manage this person. But of course you still have access and to direct communication with this developer, any other specialist?
83 00:22:56.040 ⇒ 00:22:57.650 Anna Malfanova: Okay? Oh.
84 00:22:57.770 ⇒ 00:23:22.739 Anna Malfanova: a second model that is project based model. Here we build turnkey solutions for clients. So in this case, customer is less interested in the communication process. He will not be managing this person directly. The customer has an idea, I don’t know to implement some Crm system, let’s say, and he just interested to get the final result.
85 00:23:23.000 ⇒ 00:23:38.489 Anna Malfanova: So in this sense, we built this solution for him with our own means, with our developers, so customer is less involved into the development and communication process, so he may have a project manager from our end
86 00:23:38.520 ⇒ 00:23:43.490 Anna Malfanova: who will like update him? How the progress
87 00:23:43.830 ⇒ 00:24:01.120 Anna Malfanova: goes. And so yeah, eventually, customer is interested in the final solution. Also, we can help our customers, let’s say like, say you, for instance, I don’t know what kind of services you may need. But let’s.
88 00:24:01.120 ⇒ 00:24:01.830 Uttam: Sake.
89 00:24:01.830 ⇒ 00:24:22.130 Anna Malfanova: You are not experienced in like no quality assurance. You don’t have testers, and you need to some testing services. I don’t know for 4 months or for 2 months. So for some hours, then also help you with this and provide you this target expertise on this hourly basis.
90 00:24:22.130 ⇒ 00:24:51.440 Anna Malfanova: Just as long as you need this expertise. So this option is also possible, and we also work like this with some of our even existing customers, I mean, who already have full time teams with us, I mean out staffing teams like 10 people, and they may have some part time. Service, like devops normally devops, is not needed for full time work. And we can provide this help on an hourly basis.
91 00:24:51.440 ⇒ 00:24:52.620 Anna Malfanova: Okay, okay.
92 00:24:52.790 ⇒ 00:24:58.420 Anna Malfanova: so this is regarding our services and approaches. As for our clients.
93 00:24:58.720 ⇒ 00:25:15.210 Anna Malfanova: We work a lot with startup companies. By the way, we work also with enterprise companies like stable big companies, mainly, I would say, mainly most of our customers are from the startup world, so we know what it is, you know.
94 00:25:15.210 ⇒ 00:25:15.900 Uttam: Yeah, it’s crazy.
95 00:25:15.900 ⇒ 00:25:23.449 Anna Malfanova: Development speed, you know, and frequently changing requirements. So we know how to deal with this.
96 00:25:23.959 ⇒ 00:25:46.899 Anna Malfanova: Regarding the geography of our customers. This is the United States. Obviously, this is Europe, specifically Germany, Denmark. And also we hope to develop the Netherlands direction a lot business 3. And Israel. We work also extensively with Israel as a country of startups.
97 00:25:46.900 ⇒ 00:25:47.640 Anna Malfanova: Okay.
98 00:25:48.348 ⇒ 00:26:00.571 Anna Malfanova: what else to mention? Yeah, quality is our priority to provide our customers with quality. So without this, I guess Adam will not recommend us.
99 00:26:01.525 ⇒ 00:26:02.920 Uttam: Yeah, that’s true.
100 00:26:02.920 ⇒ 00:26:15.789 Anna Malfanova: Alright. And one more important thing to mention is the stability of our company. I mean the attrition rate, the turnover rate of our employees
101 00:26:16.198 ⇒ 00:26:40.320 Anna Malfanova: on average our employees stays with us for 3, 4 years in high tech industry. It’s not typical in high tech industry. It’s about one or 2 years. The attrition rate is very high in our company. It’s very low. We indeed take care of our employees, pay attention to many things, so we try to resolve a
102 00:26:40.320 ⇒ 00:26:52.279 Anna Malfanova: problem problem before it becomes a disaster. Yes, this is the one of our mottos. It’s very important for us, because.
103 00:26:52.280 ⇒ 00:27:03.108 Anna Malfanova: respectively, would it would give stability and predictability for our clients, and to those who are interested in long term cooperation, it’s very important.
104 00:27:03.560 ⇒ 00:27:28.490 Anna Malfanova: one more thing probably, is the last thing that I should mention the seniority level of our team. We are not a big company. So right now we have 60 people, 60 0 out of these people around 45 people are technical people, and most of them 90% of this tech staff are senior level specialists. We are rarely hire medium
105 00:27:28.490 ⇒ 00:27:48.470 Anna Malfanova: or a junior specialist. Again, because we work a lot with startups. And in startup world the price for mistake, or some long estimations, are very high. So we prefer to work mainly with senior guys.
106 00:27:48.790 ⇒ 00:27:52.489 Anna Malfanova: So yeah, this is in a nutshell. Very, very briefly.
107 00:27:52.490 ⇒ 00:28:17.659 Uttam: No, I appreciate it. No, it’s I know it’s hard to, you know, summarize everything. So yeah, I just had a maybe a couple of questions. So when you’re doing you know, contracts for on like a project basis, are you typically providing the client with a flat rate for the entire delivery. Do you do like a monthly fee? Because, I mean, you know, how do you kind of typically deal with? Hey? We need. We just need a few more weeks or requirements changes. You can talk to that.
108 00:28:18.700 ⇒ 00:28:46.430 Anna Malfanova: Yeah, a good question. So if we speak about project based model, we work on a time and material basis. So when customer pay for the actual hours that each specialist spend. Well when we approach such projects. So we give our customers some estimation. Normally, it’s rough estimation, if needed. We can provide more sorry estimation, but
109 00:28:46.430 ⇒ 00:28:55.349 Anna Malfanova: more salary estimation normally requires more effort, and this stage already can be payable. So rough is a general or
110 00:28:55.420 ⇒ 00:29:09.710 Anna Malfanova: timeline we can give, we give to our customers for free, and if a customer finds this estimation acceptable, then we sign a contract and start cooperating on an hourly basis.
111 00:29:10.236 ⇒ 00:29:33.940 Anna Malfanova: But not on a fixed price. Model. Fixed price model feeds only a very, very short projects where you can estimate each feature and a fixed price project requires definitely a specification, written specification, so that both the customer and us see in detail what
112 00:29:33.940 ⇒ 00:29:57.129 Anna Malfanova: we agree on. What feature will you expect, and we commit to this feature. And in case of change requests, because in fixed price model, it’s very frequent situation with when customer eventually want to change something, and since changes are required, then it will extend
113 00:29:57.130 ⇒ 00:30:22.299 Anna Malfanova: the initial timeline, and respectively, we will not be able to fit into the fixed budget. So this is very rigid model, or which fits on the very small projects. Normally, it’s better. And from our experience it’s more effective to work according to time and material model. If you need a project.
114 00:30:23.330 ⇒ 00:30:25.639 Uttam: Okay? And yeah.
115 00:30:25.810 ⇒ 00:30:33.310 Uttam: to give you. And to give you a sense of you know what that that’s really helpful. Give you a sense of like what? Some of the opportunities that are coming our way.
116 00:30:33.400 ⇒ 00:30:54.199 Uttam: for example. You know, I’ll get a lead or an opportunity, you know, working through one right now where a friend of mine’s like, Hey, I I’m working on a I’m working with a client. They need someone to build the front end for an internal application, can you? Is there something in your wheelhouse, you know, of course.
117 00:30:54.750 ⇒ 00:30:55.740 Uttam: and
118 00:30:58.520 ⇒ 00:30:59.540 Uttam: try to.
119 00:31:05.240 ⇒ 00:31:08.940 Anna Malfanova: Uta, I lose you again. Some connection.
120 00:31:08.940 ⇒ 00:31:16.259 Uttam: Say yes. But again, my expert I wanted to speak with you is and you know, like we can get that. Okay. Can you hear me now?
121 00:31:17.710 ⇒ 00:31:30.809 Anna Malfanova: Now. Yes, now it seems. Yes, and I stopped. I started hearing you with breaks when you said that. For instance, your friend need to build a front end application, and then the connection dropped.
122 00:31:32.170 ⇒ 00:31:46.159 Uttam: Okay? Yeah. I I guess to continue, yeah, I’d like they’re they get an opportunity to build the front end for an internal application. And they ask me, Kate, can your company handle this in that situation? Would love to see.
123 00:31:52.010 ⇒ 00:31:53.967 Anna Malfanova: The same issue.
124 00:31:54.620 ⇒ 00:31:55.699 Uttam: There are.
125 00:31:56.410 ⇒ 00:32:00.364 Uttam: you know. The situation is, we own the relating models.
126 00:32:01.140 ⇒ 00:32:03.099 Uttam: can you? You can hear me now or no.
127 00:32:03.100 ⇒ 00:32:12.776 Anna Malfanova: No, it it is just the same, you know. I hear you well for a few seconds, and then it starts dropping. You know it just some noise.
128 00:32:14.364 ⇒ 00:32:24.930 Anna Malfanova: I’m really sorry. I don’t know. It seems on my side. The connection is, I don’t know. It seems to be fine you need you need.
129 00:32:24.930 ⇒ 00:32:25.520 Uttam: Give me!
130 00:32:26.380 ⇒ 00:32:27.230 Anna Malfanova: Yeah.