Meeting Title: Uttam <> Aravind Date: 2024-06-18 Meeting participants: Aravindan Jayachandran, Uttam Kumaran
WEBVTT
1 00:01:47.410 ⇒ 00:01:48.190 Aravindan Jayachandran: Hey! With them!
2 00:01:48.630 ⇒ 00:01:50.140 Uttam Kumaran: Hey, Arvin, how are you?
3 00:01:50.470 ⇒ 00:01:52.140 Aravindan Jayachandran: Morning. I’m good. How are you?
4 00:01:52.520 ⇒ 00:01:53.450 Uttam Kumaran: Hey? Good!
5 00:01:54.400 ⇒ 00:01:55.809 Uttam Kumaran: How long is it going?
6 00:01:56.210 ⇒ 00:01:57.380 Uttam Kumaran: Things are good.
7 00:01:58.570 ⇒ 00:01:59.210 Aravindan Jayachandran: Yeah.
8 00:02:00.656 ⇒ 00:02:01.270 Uttam Kumaran: Yeah. Yeah.
9 00:02:01.520 ⇒ 00:02:03.889 Aravindan Jayachandran: Doing fine. Yes, going. Things are
10 00:02:04.080 ⇒ 00:02:05.638 Aravindan Jayachandran: going kind of a quick.
11 00:02:06.520 ⇒ 00:02:07.930 Uttam Kumaran: Okay, in what way?
12 00:02:07.930 ⇒ 00:02:08.539 Aravindan Jayachandran: Yeah.
13 00:02:08.680 ⇒ 00:02:10.209 Aravindan Jayachandran: yeah, because
14 00:02:10.240 ⇒ 00:02:12.200 Aravindan Jayachandran: we started the product of
15 00:02:12.870 ⇒ 00:02:17.893 Aravindan Jayachandran: alright. And we have also taken a lot of
16 00:02:18.800 ⇒ 00:02:22.072 Aravindan Jayachandran: people, we have kind of taken quite a bit of time.
17 00:02:22.590 ⇒ 00:02:23.160 Uttam Kumaran: Yeah.
18 00:02:23.970 ⇒ 00:02:32.091 Aravindan Jayachandran: And one of the things that we are trying to do is we are trying to see if we can take interns and convert to them to put them all foot them all.
19 00:02:33.385 ⇒ 00:02:35.459 Aravindan Jayachandran: So we have taken around
20 00:02:36.190 ⇒ 00:02:42.449 Aravindan Jayachandran: from what we when we saw you last time. Right? We are 0 employees. Right? I was only one. Now we have around 23 people.
21 00:02:43.440 ⇒ 00:02:44.650 Uttam Kumaran: 25 people.
22 00:02:45.200 ⇒ 00:02:45.770 Aravindan Jayachandran: Yeah.
23 00:02:46.220 ⇒ 00:02:47.920 Uttam Kumaran: Wow! No way.
24 00:02:48.440 ⇒ 00:02:54.890 Aravindan Jayachandran: Yeah, I have to build it, because if you don’t build it, then then it’s not going to scale.
25 00:02:55.520 ⇒ 00:02:56.319 Uttam Kumaran: I think that.
26 00:02:56.871 ⇒ 00:02:58.130 Aravindan Jayachandran: Take the chance right? So.
27 00:02:58.130 ⇒ 00:03:00.600 Uttam Kumaran: Yeah, to take the initial initial like.
28 00:03:00.790 ⇒ 00:03:01.860 Uttam Kumaran: investment.
29 00:03:01.900 ⇒ 00:03:03.060 Uttam Kumaran: Right? Yeah.
30 00:03:03.060 ⇒ 00:03:03.750 Aravindan Jayachandran: Blake.
31 00:03:03.900 ⇒ 00:03:06.109 Aravindan Jayachandran: and we are. We are taking very.
32 00:03:06.840 ⇒ 00:03:09.140 Aravindan Jayachandran: very safe pets as well.
33 00:03:09.500 ⇒ 00:03:12.800 Aravindan Jayachandran: We are not hiring people at. Huge salaries
34 00:03:13.335 ⇒ 00:03:18.659 Aravindan Jayachandran: gather. We are trying to give opportunities to people who are struggling to start their start their career
35 00:03:19.132 ⇒ 00:03:22.410 Aravindan Jayachandran: because we can afford to do that. Being a product we don’t have.
36 00:03:23.230 ⇒ 00:03:26.025 Aravindan Jayachandran: We don’t have too much of a question on time, please.
37 00:03:26.280 ⇒ 00:03:27.195 Uttam Kumaran: Yeah, yeah, yeah.
38 00:03:27.880 ⇒ 00:03:32.580 Aravindan Jayachandran: And we have the we have 1 h we have around 3 or 4 people who are like leads.
39 00:03:32.880 ⇒ 00:03:35.869 Aravindan Jayachandran: and they’re they are able to manage them. That’s what they are paying
40 00:03:36.050 ⇒ 00:03:36.580 Aravindan Jayachandran: the.
41 00:03:36.580 ⇒ 00:03:36.910 Uttam Kumaran: Okay.
42 00:03:38.060 ⇒ 00:03:43.629 Aravindan Jayachandran: Yeah. And just like how I have given 2, 3 interns to you. Right?
43 00:03:43.760 ⇒ 00:03:50.409 Aravindan Jayachandran: We also have a larger pool of interns, and we are giving them projects we are giving them topics to work on.
44 00:03:50.720 ⇒ 00:04:03.839 Aravindan Jayachandran: So today, I wanted to kind of bounce it off with you. That’s that’s that of this meeting. Right? I know you guys are going to work on few things. But we are also trying to work on few so few a few use cases.
45 00:04:04.457 ⇒ 00:04:08.059 Aravindan Jayachandran: And if you feel we want to add to it.
46 00:04:08.830 ⇒ 00:04:12.920 Aravindan Jayachandran: I I wanted to give this give this to you.
47 00:04:12.960 ⇒ 00:04:19.079 Aravindan Jayachandran: So you can add to this as well, and that we can get some people to work on some problems and statement of the idea.
48 00:04:19.760 ⇒ 00:04:23.319 Aravindan Jayachandran: Right? I’ll just present it to you.
49 00:04:25.100 ⇒ 00:04:25.830 Uttam Kumaran: Yeah, please.
50 00:04:34.040 ⇒ 00:04:37.669 Aravindan Jayachandran: So if you see here first, st let me show
51 00:04:38.770 ⇒ 00:04:41.170 Aravindan Jayachandran: one, which is intense.
52 00:04:45.880 ⇒ 00:04:46.760 Aravindan Jayachandran: I’ll be, sir.
53 00:04:55.480 ⇒ 00:04:57.150 Aravindan Jayachandran: How can I help?
54 00:05:00.170 ⇒ 00:05:01.610 Aravindan Jayachandran: Is this to put it.
55 00:05:10.440 ⇒ 00:05:14.989 Aravindan Jayachandran: So this is what we are currently given for a a set of people
56 00:05:15.566 ⇒ 00:05:20.159 Aravindan Jayachandran: who are doing the 3rd year in Siren College, which is in Chennai, right?
57 00:05:20.780 ⇒ 00:05:27.080 Aravindan Jayachandran: So we have given them a topic, and they have kind of creating some Prds and aggregated results.
58 00:05:27.090 ⇒ 00:05:29.489 Aravindan Jayachandran: So they’re going to present to us tomorrow. Alright.
59 00:05:29.490 ⇒ 00:05:30.070 Uttam Kumaran: Okay.
60 00:05:30.360 ⇒ 00:05:32.059 Aravindan Jayachandran: I’ll share this with you as well.
61 00:05:33.110 ⇒ 00:05:36.220 Aravindan Jayachandran: You can add to this, if you want okay.
62 00:05:37.922 ⇒ 00:05:41.545 Aravindan Jayachandran: that way, you can also try to give some
63 00:05:42.660 ⇒ 00:05:47.500 Aravindan Jayachandran: some topics to students. And they can also try to just get so that’s that’s it.
64 00:05:48.080 ⇒ 00:05:48.640 Uttam Kumaran: Okay.
65 00:05:52.150 ⇒ 00:05:52.929 Aravindan Jayachandran: Student school.
66 00:05:54.260 ⇒ 00:06:00.510 Aravindan Jayachandran: So, for example, this is fine tuning January image integration. This is one of the projects that we’re working on. Are you remember, we
67 00:06:00.650 ⇒ 00:06:03.289 Aravindan Jayachandran: we spoke about fashion tech, right?
68 00:06:03.290 ⇒ 00:06:04.469 Uttam Kumaran: Yes, yes, yes.
69 00:06:04.780 ⇒ 00:06:09.509 Aravindan Jayachandran: So this one is a preparation for the fashion tech. There is some discussion going on there
70 00:06:09.750 ⇒ 00:06:14.500 Aravindan Jayachandran: still. Still, they they are supposed to give us some data for training. And all of this stuff. Right?
71 00:06:14.620 ⇒ 00:06:25.330 Aravindan Jayachandran: So we we have this team who is currently working on taking a open, a model training training that open a model, using some images and trying to get some opt out of it right?
72 00:06:25.760 ⇒ 00:06:31.160 Aravindan Jayachandran: So once we get the actual mood boards from the designers. We will also, we’ll get into the
73 00:06:31.250 ⇒ 00:06:32.900 Aravindan Jayachandran: data preparation phase.
74 00:06:33.350 ⇒ 00:06:37.669 Aravindan Jayachandran: and then we’ll get into the training on the fine tuning. That’s that’s the idea. Right.
75 00:06:37.770 ⇒ 00:06:40.999 Aravindan Jayachandran: So there are this. This guy is our employee.
76 00:06:41.590 ⇒ 00:06:45.879 Aravindan Jayachandran: He is. He is a full time, intern who is going to be?
77 00:06:46.324 ⇒ 00:06:50.409 Aravindan Jayachandran: Who is their seniors. So this this guy is senior, is his. Okay?
78 00:06:50.897 ⇒ 00:06:55.490 Aravindan Jayachandran: So. But this guy is completed his course. And he has joined us. Right?
79 00:06:55.590 ⇒ 00:06:58.880 Aravindan Jayachandran: So he is kind of mandering, mentoring this people right?
80 00:06:59.603 ⇒ 00:07:09.319 Aravindan Jayachandran: Similarly, they have one more application for the subscription based thing one of the doctors that we are working with was has been asking this for quite some time.
81 00:07:09.600 ⇒ 00:07:13.699 Aravindan Jayachandran: So we have some code base. We have some documents. So we have shared this.
82 00:07:13.820 ⇒ 00:07:17.850 Aravindan Jayachandran: So Canadian, our rule, are our employees full time employees.
83 00:07:18.030 ⇒ 00:07:26.881 Aravindan Jayachandran: And this team had experience wanted to work on Sunday. So they are working on this project. Right? It’s a flatter print project.
84 00:07:27.910 ⇒ 00:07:31.300 Aravindan Jayachandran: and I’m every project. I’m also trying to see if they can
85 00:07:31.682 ⇒ 00:07:33.447 Aravindan Jayachandran: bring in some kind of
86 00:07:34.521 ⇒ 00:07:38.050 Aravindan Jayachandran: some kind of an Ea. Or Mdm. Code.
87 00:07:38.270 ⇒ 00:07:41.040 Aravindan Jayachandran: So advanced analytics. At least, that’s what we are trying. Let’s see.
88 00:07:43.060 ⇒ 00:07:48.327 Aravindan Jayachandran: So this again, this guy is another employee, and we are speaking about the spend tracker for
89 00:07:48.860 ⇒ 00:07:51.220 Aravindan Jayachandran: creating something like a speed collector of sauce.
90 00:07:51.709 ⇒ 00:07:56.760 Aravindan Jayachandran: This, again, is one of the employees idea. So we are. We are kind of taking it and see where it goes.
91 00:07:56.760 ⇒ 00:08:03.050 Uttam Kumaran: And then employees. Idea, what does that mean? That’s just like just to work on something just to have some like progress on something.
92 00:08:03.600 ⇒ 00:08:08.349 Aravindan Jayachandran: Yeah. So this will help us in testing these 2 ways. Okay.
93 00:08:08.380 ⇒ 00:08:12.890 Aravindan Jayachandran: so while we don’t want to give all of those.
94 00:08:13.540 ⇒ 00:08:17.140 Aravindan Jayachandran: all of the people, whatever we are developing as a product. You don’t want to give it to the students.
95 00:08:17.659 ⇒ 00:08:21.019 Aravindan Jayachandran: But if they are able to make progress in these 2 areas.
96 00:08:21.190 ⇒ 00:08:22.229 Uttam Kumaran: I see, I see.
97 00:08:22.230 ⇒ 00:08:25.969 Aravindan Jayachandran: We can, we can take it and use it in our our application. That’s right.
98 00:08:26.280 ⇒ 00:08:27.010 Uttam Kumaran: Okay. Okay.
99 00:08:27.010 ⇒ 00:08:33.429 Aravindan Jayachandran: Right. So while while the overall idea might be different, but this 2 will be very specific. For example.
100 00:08:33.480 ⇒ 00:08:40.159 Aravindan Jayachandran: we have this Ocr coming in multiple places, right? For when we go to the beneficiary in a field
101 00:08:40.510 ⇒ 00:08:45.180 Aravindan Jayachandran: they want to take a photograph, and they want to extract the texture and put it into a database, right?
102 00:08:45.460 ⇒ 00:08:47.690 Aravindan Jayachandran: So Osia will become very handy there.
103 00:08:48.260 ⇒ 00:08:57.489 Aravindan Jayachandran: Alright, can I? Also, I mean something of this classification of of those data, and something like that. Right? So these 2, if if they are able to make some progress here.
104 00:08:57.620 ⇒ 00:09:00.410 Aravindan Jayachandran: then I can use it in in my app. That’s that’s the idea.
105 00:09:00.920 ⇒ 00:09:02.090 Uttam Kumaran: Okay. Okay. Yeah, yeah.
106 00:09:02.090 ⇒ 00:09:07.309 Aravindan Jayachandran: Yeah, mental health is something which is also some like something like a fashion fashion. Tick
107 00:09:07.801 ⇒ 00:09:13.100 Aravindan Jayachandran: there is a talk with all of slip, Nina, who is working with us for the startup.
108 00:09:13.130 ⇒ 00:09:17.819 Aravindan Jayachandran: So we are trying to create the app and show him some kind of a proof of concept again.
109 00:09:18.630 ⇒ 00:09:22.890 Aravindan Jayachandran: this is just a Poc. We don’t want to show it to him unless he signs the contract. So.
110 00:09:23.070 ⇒ 00:09:23.530 Uttam Kumaran: Yeah, yeah.
111 00:09:23.530 ⇒ 00:09:32.530 Aravindan Jayachandran: Again. This is, anyway, will be part of our PGA manager will be part of our health platform, anyway. So this will help us in learning about it. That’s idea
112 00:09:34.026 ⇒ 00:09:39.009 Aravindan Jayachandran: this is especially for Caesar. Right objected, and taken to begin with pharmacy.
113 00:09:39.778 ⇒ 00:09:43.830 Aravindan Jayachandran: We know there is a bigger problem in pharmacy is identifying
114 00:09:44.618 ⇒ 00:09:51.489 Aravindan Jayachandran: identifying the inventory uploading the inventory, identifying the inventory and editing the inventory right?
115 00:09:51.580 ⇒ 00:09:55.330 Aravindan Jayachandran: An audit of it. So this is. This is for farmers specifically
116 00:09:55.590 ⇒ 00:10:02.279 Aravindan Jayachandran: so they are. They are currently working on it. And then we have. This is another another student who is playing
117 00:10:02.988 ⇒ 00:10:05.779 Aravindan Jayachandran: for context based? Right? For example, there are
118 00:10:06.750 ⇒ 00:10:10.570 Aravindan Jayachandran: 5 people who are doing having a discussion. Okay?
119 00:10:11.372 ⇒ 00:10:23.459 Aravindan Jayachandran: Can we use Ea to identify the context of the discussion and say, Okay, based on the voice and pitch, saying, Oh, this is Ag speaking, this is Hutum speaking. This is cb, speaking, right? Can we classify this.
120 00:10:24.208 ⇒ 00:10:28.149 Aravindan Jayachandran: This will also be very important for us in a clinical setting.
121 00:10:28.240 ⇒ 00:10:31.410 Aravindan Jayachandran: When the doctor is connecting talking to this patient right?
122 00:10:31.760 ⇒ 00:10:35.820 Aravindan Jayachandran: Who is the doctor? Who is the patient? What are they discussing if they can transcribe it?
123 00:10:35.930 ⇒ 00:10:38.600 Aravindan Jayachandran: The whole medical transcription industry. Is that right?
124 00:10:39.010 ⇒ 00:10:39.650 Uttam Kumaran: Yeah.
125 00:10:40.390 ⇒ 00:10:47.879 Aravindan Jayachandran: So that’s something which you want to try. We have given several IoT projects, but nobody had chosen the IoT projects yet. Okay.
126 00:10:48.110 ⇒ 00:10:53.049 Aravindan Jayachandran: so we have. We have listed to some other college priority which is specializing in IoT.
127 00:10:53.708 ⇒ 00:10:57.100 Aravindan Jayachandran: There is a college in Andra which is called Care University.
128 00:10:57.480 ⇒ 00:11:03.690 Aravindan Jayachandran: So those guys specialize in IoT and embedded the design. So we have reached out to them for some
129 00:11:03.800 ⇒ 00:11:08.447 Aravindan Jayachandran: internship as well. So this but if you want to add a few more
130 00:11:08.780 ⇒ 00:11:09.490 Uttam Kumaran: Yeah.
131 00:11:09.970 ⇒ 00:11:11.760 Aravindan Jayachandran: Please do you’ll.
132 00:11:11.760 ⇒ 00:11:16.730 Uttam Kumaran: I have one. I have one in particular, and that’s honestly similar to the
133 00:11:17.100 ⇒ 00:11:31.700 Uttam Kumaran: spend tracker. It’s basically there’s a used case here that I was working on with. A friend of mine who’s in the insurance industry. He’s he works in trucking and like commercial insurance.
134 00:11:31.720 ⇒ 00:11:40.580 Uttam Kumaran: Basically, people here get insurance on their when they’re truck drivers and for their businesses for their farms, things like that. So a lot of this like rural things. And so
135 00:11:40.810 ⇒ 00:12:02.689 Uttam Kumaran: in that process. And we have all this documented actually, because I was gonna kick off this as its own company. But I just ran out of time. So actually, I have like a lot of information on this. But basically there are these Pdfs that all of those people have to fill out in order to get insurance, and so there he’s a broker for insurance. So he goes and interviews the business owners, ask them like hundreds of questions.
136 00:12:02.770 ⇒ 00:12:22.639 Uttam Kumaran: and then has to go fill out like 10 or 20 or 30 different documents that are all unique to different insurance providers. Basically, the idea was, can we record that interview process. Take on the emails that are sent between the clients and try to auto, fill as much of those forms as possible
137 00:12:22.670 ⇒ 00:12:29.250 Uttam Kumaran: so that it could save him. Basically 20% of the time in doing the deal is going to this process. And so.
138 00:12:29.250 ⇒ 00:12:34.579 Aravindan Jayachandran: I think we can. Yeah, that. So that is something very similar to not.
139 00:12:34.580 ⇒ 00:12:47.219 Uttam Kumaran: It’s it’s similar to this. No, I think it’s similar to the spend tracker, because there is cause. These Pdfs are all unique to the broker. So there is some several sort of Ocr, so there’s 2 things. There’s Ocr and text scraping
140 00:12:47.410 ⇒ 00:13:02.089 Uttam Kumaran: that needs to be done to actually gather what fields are in the document which needs to be kind of done on the fly, because not all these documents aren’t standardized. The second thing is, there’s gonna be some sort of either speech transcription, or some sort of rag over email.
141 00:13:02.090 ⇒ 00:13:02.669 Aravindan Jayachandran: I mean so.
142 00:13:02.670 ⇒ 00:13:03.440 Uttam Kumaran: So happen
143 00:13:03.580 ⇒ 00:13:04.859 Uttam Kumaran: there’s an excel mix.
144 00:13:04.860 ⇒ 00:13:07.140 Aravindan Jayachandran: Identification. And this one, yeah.
145 00:13:07.140 ⇒ 00:13:12.380 Uttam Kumaran: So the thing is the speech identification. There are some great Apis that already exist
146 00:13:12.550 ⇒ 00:13:14.580 Uttam Kumaran: that do this really well.
147 00:13:14.810 ⇒ 00:13:29.050 Aravindan Jayachandran: They they do text to text, to voice to text. Right? It’s it’s there. But what it is missing is identifying the difference between context. Right? When a doctor speaks, when a way, when a when a patient speaks right, there’s a 2 different
148 00:13:29.360 ⇒ 00:13:38.000 Uttam Kumaran: Yeah, you need to do what’s called like, you need to do like the dialerization, basically like who’s talking and basically create the diary of like this person, this person, this person? Yeah, I agree.
149 00:13:38.000 ⇒ 00:13:44.590 Aravindan Jayachandran: Yeah, that that is not there. There is one ap currently available and even one more, one of the startup feature to us as well.
150 00:13:45.077 ⇒ 00:13:58.279 Aravindan Jayachandran: Who has done this? Okay, if if somebody has done it in 3 months, even if these guys were able to do it assistance, I’ll take it right? They’re not a problem because he’s he is saying, it’s a unique thing. I I am going to charge like millions of dollars. And okay, I’ll I’ll deliver it myself.
151 00:13:58.420 ⇒ 00:13:59.030 Aravindan Jayachandran: Yeah, yeah, yeah.
152 00:13:59.030 ⇒ 00:13:59.880 Uttam Kumaran: Yeah.
153 00:13:59.880 ⇒ 00:14:03.821 Aravindan Jayachandran: Yeah, that that’s the idea. Microsoft has this that we call it
154 00:14:04.150 ⇒ 00:14:07.159 Uttam Kumaran: There’s there’s also one called Leap. Have you heard of that leap.
155 00:14:08.100 ⇒ 00:14:09.240 Aravindan Jayachandran: Elliot, B. Leave.
156 00:14:09.770 ⇒ 00:14:11.059 Uttam Kumaran: Yeah. Leap. AI,
157 00:14:11.867 ⇒ 00:14:16.789 Uttam Kumaran: yeah, I’ll I’ll I’ll cause I looked into like so many of these. So let me
158 00:14:16.940 ⇒ 00:14:21.219 Uttam Kumaran: let me try to send you. There’s 1 thing called Leap. I’ll send it to you on Whatsapp.
159 00:14:21.930 ⇒ 00:14:22.470 Aravindan Jayachandran: Okay. Sure.
160 00:14:25.250 ⇒ 00:14:27.692 Uttam Kumaran: There’s this lead. There’s also
161 00:14:36.330 ⇒ 00:14:41.439 Aravindan Jayachandran: The the beauty of it is right. The moment we we try to do is in India.
162 00:14:42.380 ⇒ 00:14:43.720 Aravindan Jayachandran: The whole
163 00:14:43.780 ⇒ 00:14:46.250 Aravindan Jayachandran: problem statement is
164 00:14:46.860 ⇒ 00:14:52.289 Aravindan Jayachandran: complex primarily because of the action. The line view is a big thing, right?
165 00:14:52.540 ⇒ 00:14:55.280 Uttam Kumaran: Yeah. So that’s that’s the thing that’s gonna be
166 00:14:56.180 ⇒ 00:14:57.030 Uttam Kumaran: yeah.
167 00:14:57.650 ⇒ 00:14:59.370 Uttam Kumaran: interesting to figure out.
168 00:14:59.680 ⇒ 00:15:01.849 Aravindan Jayachandran: So I’m I have asked them to do this.
169 00:15:02.441 ⇒ 00:15:08.230 Aravindan Jayachandran: See, this is also for me to kind of filter out who is actually working.
170 00:15:08.230 ⇒ 00:15:09.858 Uttam Kumaran: I agree. I agree, I mean.
171 00:15:10.340 ⇒ 00:15:11.180 Uttam Kumaran: yeah.
172 00:15:11.760 ⇒ 00:15:16.770 Aravindan Jayachandran: So the beauty of it is regularly okay. The siren. We have about 70 people or 80 people. Okay.
173 00:15:17.913 ⇒ 00:15:23.869 Aravindan Jayachandran: the beauty of it is, if if I know whether they’re performing well, I can give an offset up from, say.
174 00:15:23.990 ⇒ 00:15:25.440 Aravindan Jayachandran: August, right.
175 00:15:25.926 ⇒ 00:15:31.340 Aravindan Jayachandran: they will work with me for almost free using the laptops and the
176 00:15:31.410 ⇒ 00:15:33.099 Aravindan Jayachandran: I’m just worried about the college.
177 00:15:33.470 ⇒ 00:15:34.629 Uttam Kumaran: Yeah, yeah, yeah, yeah, yeah.
178 00:15:35.120 ⇒ 00:15:43.550 Aravindan Jayachandran: Right, and they will, they will join me as well. Okay, so that way it is, it is better to build that team is what I was thinking. So that’s why.
179 00:15:43.550 ⇒ 00:15:59.949 Uttam Kumaran: No, I think this is perfect. I mean, look, if you guys can afford to do that, then this is this is ideal, because also, if they’re if you’re able to teach them through these I actually have like. This insurance example is something that’s like, I pretty much cannot work on this because I don’t have the talent
180 00:16:00.408 ⇒ 00:16:13.540 Uttam Kumaran: and it’s honestly like a pretty contained idea that I have actually like. I have a stakeholder here that will be the product owner. And then, like, there’s actually like a clear path towards a like a proof of concept
181 00:16:13.630 ⇒ 00:16:16.109 Uttam Kumaran: that if he’s able to demonstrate
182 00:16:16.220 ⇒ 00:16:23.760 Uttam Kumaran: like there, it’s basically we’re sitting on this idea. And I have so much documentation and stuff that we tried. So I honestly think it’s.
183 00:16:23.760 ⇒ 00:16:24.210 Aravindan Jayachandran: The gender.
184 00:16:24.210 ⇒ 00:16:24.540 Uttam Kumaran: Very close.
185 00:16:24.540 ⇒ 00:16:25.140 Aravindan Jayachandran: Gonna do that.
186 00:16:25.140 ⇒ 00:16:26.779 Uttam Kumaran: And that all over basically.
187 00:16:27.440 ⇒ 00:16:34.930 Aravindan Jayachandran: No, we can do that. Yeah. So one of the things that that I am telling you is we should be able to do it. The idea is to develop several of
188 00:16:35.160 ⇒ 00:16:42.749 Aravindan Jayachandran: the product. The product studio is that right? The idea is to develop several of the product studios. This is a typical Pr that we follow.
189 00:16:43.363 ⇒ 00:16:47.496 Aravindan Jayachandran: If you want, I’ll send you the send you this as the friends, if you can.
190 00:16:48.003 ⇒ 00:16:48.530 Uttam Kumaran: You see.
191 00:16:49.460 ⇒ 00:16:50.090 Uttam Kumaran: Yeah.
192 00:16:50.406 ⇒ 00:16:54.210 Aravindan Jayachandran: We can, we can develop the desk is not a problem.
193 00:16:54.950 ⇒ 00:16:58.219 Aravindan Jayachandran: So one of the things that we are trout trying to develop for this is
194 00:16:58.830 ⇒ 00:17:00.590 Aravindan Jayachandran: a very generic
195 00:17:00.840 ⇒ 00:17:04.730 Aravindan Jayachandran: but continuable platform which can configure into multiple.
196 00:17:05.614 ⇒ 00:17:09.660 Aravindan Jayachandran: Multiple. Sas is what we are trying to do. Okay?
197 00:17:11.490 ⇒ 00:17:17.229 Aravindan Jayachandran: i i i i updated the this one as well architecture as well.
198 00:17:17.609 ⇒ 00:17:17.929 Uttam Kumaran: Okay.
199 00:17:18.235 ⇒ 00:17:22.200 Aravindan Jayachandran: So we are. We are currently going with the not going with Kafka.
200 00:17:22.730 ⇒ 00:17:34.869 Aravindan Jayachandran: Right? We are not going with Kafka. We are not going with Slink home. And we we I I tried with working with it for a couple of weeks. Then a really role is not for me.
201 00:17:35.130 ⇒ 00:17:36.480 Uttam Kumaran: Okay. Okay.
202 00:17:36.880 ⇒ 00:17:43.680 Aravindan Jayachandran: Yeah, so we are. Instead of Kafka, we are using Nats Nats jet stream.
203 00:17:44.170 ⇒ 00:17:45.820 Aravindan Jayachandran: Okay, have you heard of this?
204 00:17:45.820 ⇒ 00:17:47.050 Uttam Kumaran: No, no, no.
205 00:17:47.650 ⇒ 00:17:51.784 Aravindan Jayachandran: Yeah, that’s just stream. This is written in Golan. But they have a very specific
206 00:17:52.070 ⇒ 00:17:55.109 Aravindan Jayachandran: and for fling instead of fling, we are using fast stream.
207 00:17:55.460 ⇒ 00:17:56.045 Aravindan Jayachandran: Okay?
208 00:17:57.720 ⇒ 00:18:00.680 Aravindan Jayachandran: of course, for apas, we have fast. Apa. Okay.
209 00:18:00.680 ⇒ 00:18:01.869 Uttam Kumaran: Okay. Okay. Yeah, yeah.
210 00:18:02.146 ⇒ 00:18:06.853 Aravindan Jayachandran: So this is what we are currently working on. That’s Ivo is Ivo is our
211 00:18:08.060 ⇒ 00:18:12.350 Aravindan Jayachandran: this one. You can. You can look at it once. We once we have something ready, I can show you
212 00:18:12.570 ⇒ 00:18:17.570 Aravindan Jayachandran: you’re still in development. Once it is ready, I’ll just give you a give a download. This is one right.
213 00:18:17.790 ⇒ 00:18:26.070 Aravindan Jayachandran: Apart from this, we also have another university that we are kind of collaborating with, called Rb. University in Bangalore, which is very famous.
214 00:18:26.410 ⇒ 00:18:31.850 Aravindan Jayachandran: Our engineering colleges, apparently one of the older senior colleges open one of the one of the oldest colleges.
215 00:18:32.625 ⇒ 00:18:32.980 Uttam Kumaran: Okay.
216 00:18:33.380 ⇒ 00:18:36.180 Aravindan Jayachandran: Yeah, so they are asking for some Phd research
217 00:18:36.732 ⇒ 00:18:38.620 Aravindan Jayachandran: research problems to solve.
218 00:18:39.310 ⇒ 00:18:44.740 Aravindan Jayachandran: So we have given them a set of these. These, as the usage problems.
219 00:18:45.440 ⇒ 00:18:51.850 Aravindan Jayachandran: So we told them, you select one, and company will will kind of start helping you understand this work.
220 00:18:52.878 ⇒ 00:18:58.550 Aravindan Jayachandran: So we have given them like, see? Ideally, I didn’t want to give them any domain based thing
221 00:18:58.830 ⇒ 00:19:02.109 Aravindan Jayachandran: it eventually it. It went into domain based for some reason.
222 00:19:02.360 ⇒ 00:19:07.989 Aravindan Jayachandran: but I wanted to focus on. One thing that I really wanted for them to work on is this one
223 00:19:08.915 ⇒ 00:19:14.330 Aravindan Jayachandran: this is a pain point I know. Is there in the security space, right? So the security space.
224 00:19:14.820 ⇒ 00:19:17.429 Aravindan Jayachandran: So I wanted to see if we can actually
225 00:19:17.550 ⇒ 00:19:22.029 Aravindan Jayachandran: bring to the several models and automatically detect
226 00:19:22.786 ⇒ 00:19:23.680 Aravindan Jayachandran: detect anything.
227 00:19:23.983 ⇒ 00:19:24.590 Uttam Kumaran: Still enough!
228 00:19:24.780 ⇒ 00:19:25.770 Aravindan Jayachandran: Thanks, sir.
229 00:19:26.060 ⇒ 00:19:28.750 Aravindan Jayachandran: and then takes also, if they say I mean.
230 00:19:28.750 ⇒ 00:19:31.799 Uttam Kumaran: Like log, taking in logs and access requests, and all that.
231 00:19:31.800 ⇒ 00:19:40.289 Aravindan Jayachandran: Correct, correct, correct? Correct. Yeah. So this is this is something which I which I wanted to do. I have given them. I don’t think they will. I don’t know whether they’re going to pick it up, but.
232 00:19:40.290 ⇒ 00:19:43.709 Uttam Kumaran: Yeah, that seems like it seems like, ha, really hard.
233 00:19:44.250 ⇒ 00:19:50.852 Aravindan Jayachandran: Yeah, yeah, it. It’s going to be complex. So the Phd students are, they don’t want to pick up complex subjects like that.
234 00:19:51.140 ⇒ 00:19:54.040 Uttam Kumaran: Well, also like for them, like, how are they gonna know?
235 00:19:54.090 ⇒ 00:19:56.589 Uttam Kumaran: Yeah, I don’t know. I just feel like the students are like.
236 00:19:56.750 ⇒ 00:20:01.379 Uttam Kumaran: if they’re Phd students. They’re they’re used to working very slowly and methodically, and like.
237 00:20:01.510 ⇒ 00:20:06.799 Uttam Kumaran: I don’t know cause I for me, I only learned like data dog and all the observability
238 00:20:06.840 ⇒ 00:20:09.000 Uttam Kumaran: type tools on the job. So like.
239 00:20:09.210 ⇒ 00:20:12.099 Uttam Kumaran: you know, yeah, but maybe interesting for them.
240 00:20:12.110 ⇒ 00:20:16.739 Uttam Kumaran: And you know, it’s nice that they can probably get a student license for stuff to get it for free. So.
241 00:20:16.740 ⇒ 00:20:32.869 Aravindan Jayachandran: Well, the the the college provides some amazing amazing set of resources. They can have cloud access. They can have so many things. Okay? So if you, if they really want to do it, they can. They can build an Ea, and then kind of create
242 00:20:32.970 ⇒ 00:20:34.600 Aravindan Jayachandran: fake traffic.
243 00:20:34.870 ⇒ 00:20:41.650 Aravindan Jayachandran: And then and then feed bad traffic to it, and do all of this things. Not it’s not that it is not possible.
244 00:20:42.186 ⇒ 00:20:48.590 Aravindan Jayachandran: but whether they are going to pick it up I don’t know. So I really wanted them to pick one of these technical things
245 00:20:49.302 ⇒ 00:20:55.849 Aravindan Jayachandran: but whether they went to that, or they went to domain. We have not got got back anything, so we have few on healthcare.
246 00:20:56.721 ⇒ 00:21:01.869 Aravindan Jayachandran: So we have fewer healthcare, few on digital adoption and few on data science and but 36.
247 00:21:01.870 ⇒ 00:21:14.190 Uttam Kumaran: So. So then I have. So I have 2 other things. One is on the healthcare side. Me and Shang are starting to market some healthcare things here in the Us. We don’t have any like.
248 00:21:14.300 ⇒ 00:21:18.749 Uttam Kumaran: We don’t have any used cases yet, but maybe I’ll keep that in mind.
249 00:21:18.860 ⇒ 00:21:25.269 Uttam Kumaran: like if we have a Poc that we need to develop, and maybe we can add that the second thing is, I do have some real estate.
250 00:21:25.300 ⇒ 00:21:30.410 Uttam Kumaran: Us. Real estate related use cases that are related to almost like automating
251 00:21:30.680 ⇒ 00:21:35.060 Uttam Kumaran: like data analysis. Using AI basically like, can you take
252 00:21:35.070 ⇒ 00:21:59.189 Uttam Kumaran: Pete, for example, in the Us in a commercial real estate space. When a, when a commercial real estate, they try to buy a property, they try to do evaluation, which is basically they understand where the property is. They understand market comps. They understand the market. They understand like how what other things in the market sold for they understand who the buyer is. And basically they put together this like data sheet.
253 00:21:59.240 ⇒ 00:22:14.958 Uttam Kumaran: There’s an there’s an opportunity here where that process takes so long for these guys to do in the real estate industry and the clients when they’re asking questions about the property. There’s an opportunity to basically build a quick Qa bot on top of that
254 00:22:15.300 ⇒ 00:22:15.850 Aravindan Jayachandran: Yeah.
255 00:22:15.850 ⇒ 00:22:26.020 Uttam Kumaran: That that’s a great thing where it’s almost. It’s almost similar to the last idea where it’s like some sort of it’s 2 things. It’s 1 some sort of rag on top of Pdfs.
256 00:22:26.060 ⇒ 00:22:36.209 Uttam Kumaran: SQL. Databases things like that. And it’s also like almost like a excel formation. So their main analysis comes in the form of these excel documents that builds the data model
257 00:22:36.370 ⇒ 00:22:47.769 Uttam Kumaran: basically builds like the cash flow statement builds the investment model. So there is also a unique thing where it’s almost like you. You’re we’re building these Csv’s or Excel models using AI,
258 00:22:47.790 ⇒ 00:23:08.750 Uttam Kumaran: that’s the thing that there are some tools out. There are some open source explorations on this like financial analyst. AI. But there’s a huge opportunity for that. The rag stuff is similar to what we talked about before, which is kind of like extracting stuff from Pdfs extracting stuff from databases. Building an agent. Yeah.
259 00:23:08.990 ⇒ 00:23:09.790 Aravindan Jayachandran: So that’s like.
260 00:23:09.790 ⇒ 00:23:12.760 Uttam Kumaran: That’s like, yeah, I’ve been using rag for some stuff.
261 00:23:13.130 ⇒ 00:23:15.530 Aravindan Jayachandran: Llama Anders. Did you try Llama Anders.
262 00:23:15.530 ⇒ 00:23:19.579 Uttam Kumaran: No, we’re we use link chain for everything. But I built some agents, and
263 00:23:19.820 ⇒ 00:23:20.519 Uttam Kumaran: you know, was like.
264 00:23:21.050 ⇒ 00:23:22.110 Aravindan Jayachandran: Very interesting!
265 00:23:22.110 ⇒ 00:23:22.490 Uttam Kumaran: Yeah.
266 00:23:22.490 ⇒ 00:23:25.320 Aravindan Jayachandran: This specifically built for rack.
267 00:23:25.887 ⇒ 00:23:29.382 Aravindan Jayachandran: Very interesting. I I used it for one of the projects
268 00:23:29.870 ⇒ 00:23:31.109 Aravindan Jayachandran: very useful.
269 00:23:31.500 ⇒ 00:23:38.099 Uttam Kumaran: Yeah, I’m also, I’ve also tried. I’m also gonna try using flow wise. Look up, flow wise.ai.
270 00:23:38.100 ⇒ 00:23:39.290 Aravindan Jayachandran: James, okay.
271 00:23:42.620 ⇒ 00:23:54.199 Uttam Kumaran: this is like, I’m honestly having some people on my team start to use this instead of going. Actually, maybe it’s just I don’t know. It’s maybe flow wise. No, not only one. W.
272 00:23:54.850 ⇒ 00:23:55.179 Aravindan Jayachandran: Yeah.
273 00:24:00.302 ⇒ 00:24:02.800 Uttam Kumaran: I don’t know. Let me just Google it.
274 00:24:06.810 ⇒ 00:24:08.929 Uttam Kumaran: Yeah, that’s yeah. Yeah. Yeah.
275 00:24:10.850 ⇒ 00:24:28.530 Uttam Kumaran: So this is like a low, this is like a low code, Llm. Builder. And honestly, I’m having people start to use this because I have a lot of people that told me this is really great because it takes away a little bit of like I have to learn how to host cause. I don’t need people to learn devops. I want people to learn.
276 00:24:28.530 ⇒ 00:24:29.130 Aravindan Jayachandran: Exactly.
277 00:24:29.130 ⇒ 00:24:34.259 Uttam Kumaran: How these things work. You know. I don’t wanna learn devops either. So this one is like
278 00:24:34.540 ⇒ 00:24:37.639 Uttam Kumaran: has a lot of praise for how expansive it is.
279 00:24:37.690 ⇒ 00:24:39.489 Uttam Kumaran: For in the in the low code
280 00:24:39.610 ⇒ 00:24:44.840 Uttam Kumaran: space or AI building. So I’m having people start to use this instead of
281 00:24:44.850 ⇒ 00:24:57.560 Uttam Kumaran: writing notebooks and shit like that because I don’t care. I don’t want to cause most of the conversations I’m having actually about AI ends up being about devops and like where to host this, I don’t want to have those conversations. I only want to talk about logic
282 00:24:57.660 ⇒ 00:25:00.850 Uttam Kumaran: because I could hand this to any backend person and say, go, host this.
283 00:25:01.040 ⇒ 00:25:04.619 Uttam Kumaran: or like, decompose this. But teaching someone the logic is hard.
284 00:25:05.820 ⇒ 00:25:08.190 Aravindan Jayachandran: Yeah. Yeah. So that’s what I’m I’m trying to understand
285 00:25:08.210 ⇒ 00:25:11.540 Aravindan Jayachandran: for developers to be customized orchestration for.
286 00:25:12.620 ⇒ 00:25:13.960 Aravindan Jayachandran: yeah. But.
287 00:25:13.960 ⇒ 00:25:21.010 Uttam Kumaran: That’s why I think this may be a good place to tell everyone to start, because I don’t want them to like get bogged down and like.
288 00:25:21.010 ⇒ 00:25:26.160 Aravindan Jayachandran: This is. This is just an Llm. Architecture. Flow on a agent, if you want to fine tune an Llm. Still.
289 00:25:26.160 ⇒ 00:25:33.930 Uttam Kumaran: Yeah, the fine tune you still have to do on your own. And I’m sure they guys have something. But but again, like not. Everything needs to be done.
290 00:25:33.930 ⇒ 00:25:34.600 Aravindan Jayachandran: Yeah, fine.
291 00:25:34.600 ⇒ 00:25:36.930 Uttam Kumaran: Not. Everything involves the fine tuning, so.
292 00:25:36.930 ⇒ 00:25:40.940 Aravindan Jayachandran: Yeah, yeah, I think tensorflow kind of things is not necessarily fine. Fine.
293 00:25:40.940 ⇒ 00:25:52.509 Uttam Kumaran: Yeah, that sort of stuff. Yeah, you may have to get your own Gpu and things like that. But for this, this is purely like, if you’re just in the application layer, which is, for example, if you’re building the text classification, the Ocr thing.
294 00:25:52.750 ⇒ 00:25:53.210 Aravindan Jayachandran: Yeah, yeah, yeah.
295 00:25:53.210 ⇒ 00:25:58.279 Uttam Kumaran: Maybe some ways of using this to to handle some of that, or at least proof of concepts to start here.
296 00:25:58.380 ⇒ 00:26:03.000 Uttam Kumaran: And then we see the signal, and then it’s like, then move it. So I’m I’m having people start here, basically.
297 00:26:03.890 ⇒ 00:26:06.730 Aravindan Jayachandran: Oh, they haven’t even got an MPM. Interesting. Okay.
298 00:26:06.730 ⇒ 00:26:13.939 Uttam Kumaran: I talked to a lot. I talked to a lot of people here about the developers, and they told me that this has been really helpful for them.
299 00:26:14.341 ⇒ 00:26:20.820 Uttam Kumaran: Instead of like trying to mess around with lama index or link chain, especially cause I’m trying to get people who are like
300 00:26:21.090 ⇒ 00:26:34.139 Uttam Kumaran: basic technical into this. And so like, I can get through any challenge. But I’m trying to get other people just to focus on the AI piece, learn the languages, learn how to speak about this, and then handle the dev the devops and stuff. I’ll figure out later.
301 00:26:34.910 ⇒ 00:26:39.070 Uttam Kumaran: Cause again. These are all for local poc. So if we can run it off the laptop like.
302 00:26:39.290 ⇒ 00:26:40.090 Uttam Kumaran: or Ryan.
303 00:26:40.090 ⇒ 00:26:40.979 Aravindan Jayachandran: It’s basically it’s.
304 00:26:40.980 ⇒ 00:26:41.320 Uttam Kumaran: Fine.
305 00:26:41.320 ⇒ 00:26:47.350 Aravindan Jayachandran: That is the team I’m also preparing to build right? So you have got it’s fragrant to have joined us.
306 00:26:47.820 ⇒ 00:26:51.769 Aravindan Jayachandran: So you know, if we’re trying to build a team around devops. And Dave Ops.
307 00:26:51.920 ⇒ 00:26:53.189 Aravindan Jayachandran: I see, I see. Okay.
308 00:26:53.250 ⇒ 00:26:57.220 Aravindan Jayachandran: have some some people getting trained on Jenkins and Ann civil and.
309 00:26:58.570 ⇒ 00:26:59.040 Uttam Kumaran: Aye, so.
310 00:26:59.040 ⇒ 00:27:03.530 Aravindan Jayachandran: They are not reached this level yet. That’s something which I’m pushing them to.
311 00:27:03.860 ⇒ 00:27:08.149 Aravindan Jayachandran: But typical. Gcp, azure aws
312 00:27:08.785 ⇒ 00:27:14.110 Aravindan Jayachandran: handling the complete end to end infla. I think that we can handle now.
313 00:27:14.470 ⇒ 00:27:22.110 Aravindan Jayachandran: But a use cases we have to start. We don’t want to touch a currently, because the moment we touch it in cloud, the the bill will just fly.
314 00:27:22.110 ⇒ 00:27:23.179 Uttam Kumaran: Yes. Yeah. Yeah. Yeah.
315 00:27:23.462 ⇒ 00:27:30.810 Aravindan Jayachandran: That’s that. So we’re also trying to see in the office that we are building. If you can get some gpus for the local.
316 00:27:31.140 ⇒ 00:27:32.410 Uttam Kumaran: Oh, okay. Okay. Okay.
317 00:27:32.410 ⇒ 00:27:35.410 Aravindan Jayachandran: That is what we are. We are trying. So I have asked for some quotes.
318 00:27:35.630 ⇒ 00:27:38.249 Aravindan Jayachandran: So we are trying to create this ecosystem here, as you know.
319 00:27:38.250 ⇒ 00:27:41.919 Uttam Kumaran: No, that’s great. I mean, I’m jealous like, that’s amazing. Yeah.
320 00:27:42.490 ⇒ 00:27:43.180 Aravindan Jayachandran: Well, what?
321 00:27:43.180 ⇒ 00:27:49.960 Uttam Kumaran: I don’t. I don’t know how, yet. I don’t know how you have like the brain power to handle that many projects, and that many people, but
322 00:27:50.100 ⇒ 00:27:55.169 Uttam Kumaran: good for you. Cause I like, yeah, I’m like running around doing a million things. But
323 00:27:55.300 ⇒ 00:28:08.979 Uttam Kumaran: I also think it’s exciting. I some of these ideas. I think again, if you’re able to build the like teaching arm and like getting these guys up to speed, there’s so many used cases here that like, it’s basically 1st person that can put a proof of concept.
324 00:28:09.130 ⇒ 00:28:11.040 Uttam Kumaran: And we’ll get the we’ll get the contract.
325 00:28:11.620 ⇒ 00:28:12.220 Uttam Kumaran: I don’t.
326 00:28:12.220 ⇒ 00:28:17.599 Aravindan Jayachandran: That that is exactly what we want to do. Right? We last time we told you, right product as a product studio.
327 00:28:18.286 ⇒ 00:28:24.419 Aravindan Jayachandran: What we want to build is while while we have 2 products that you want to build right? Bgr and Cgr, right?
328 00:28:24.660 ⇒ 00:28:32.100 Aravindan Jayachandran: Everything else that we are building. We want to hold around 2023% Ebd and just develop the products for phone us, right?
329 00:28:32.540 ⇒ 00:28:37.979 Aravindan Jayachandran: So and if you have something which we can do like that main. I’ll tell you.
330 00:28:37.980 ⇒ 00:28:38.310 Uttam Kumaran: I have.
331 00:28:38.659 ⇒ 00:28:39.009 Aravindan Jayachandran: Department.
332 00:28:40.350 ⇒ 00:28:46.719 Aravindan Jayachandran: The other way around is building product is easier. Taking it to a market and making it a success is much more difficult
333 00:28:47.050 ⇒ 00:28:56.320 Aravindan Jayachandran: right? Technic technology to build a product is available. And with with the team that we are building, it’s much more easily available, right.
334 00:28:56.750 ⇒ 00:28:59.610 Aravindan Jayachandran: but making it a business success.
335 00:28:59.850 ⇒ 00:29:04.609 Aravindan Jayachandran: We need the business person. For example, you mentioned about the real estate person. Right?
336 00:29:04.680 ⇒ 00:29:05.960 Aravindan Jayachandran: One limit you have is.
337 00:29:05.960 ⇒ 00:29:24.300 Uttam Kumaran: So that’s what I’m that’s that’s exactly the people here is like, I’m very much plugged in on these old like very, very rudimentary industries where they don’t even talk to people like us. However, they don’t have any access to talent, and they have no access to innovation right? And they barely even have people interested in that. So
338 00:29:24.300 ⇒ 00:29:38.529 Uttam Kumaran: that’s what I’m trying to connect for both of those ideas the real estate idea and the insurance idea. I have people that are in those industries with, like all the business contacts to basically go pitch frankly, like, I’m not, gonna go, be the Ceos of these companies. I would.
339 00:29:38.530 ⇒ 00:29:38.990 Aravindan Jayachandran: Yeah.
340 00:29:38.990 ⇒ 00:29:55.679 Uttam Kumaran: They be the Ceos, or they appoint someone who’s in those industries. And then, basically, like, we either come in as a CTO or like again, like we do it like the product studio model where we get a cut and then basically run it. So that’s what I’m that’s what I’m thinking exactly. And then again, now that if we’re able to
341 00:29:55.810 ⇒ 00:29:58.110 Uttam Kumaran: 6 have successes on these.
342 00:29:58.130 ⇒ 00:30:07.500 Uttam Kumaran: it’s like it just opens up the world for me to go find these people and continue to ask for these proof of concepts. I guess my question is going to be like, How do you think about like handling it
343 00:30:07.520 ⇒ 00:30:13.340 Uttam Kumaran: like legally, in terms of putting together this proof of concept like, if we were to take this real estate thing, for example.
344 00:30:13.600 ⇒ 00:30:33.900 Uttam Kumaran: like if I if I go, if I go, tell him so. This guy is like a he was a former public company, CEO, he’s my friend here, and we’re we’re talking to different investment funds, real estate investment funds here in Austin about like building this product. However, he’s trying to get like maybe 100 or 200 grand investment to start this company to pay for engineers. I told him.
345 00:30:33.970 ⇒ 00:30:48.230 Uttam Kumaran: I told him. Like, that’s probably all we need to get started, but I actually think there’s an opportunity for us to even through. You build a proof of concept that we can take to pitches. However, he’s gonna ask about like, what do we wanna do legally? So what do you think is like? What do you think is the option.
346 00:30:48.230 ⇒ 00:30:55.910 Aravindan Jayachandran: So typically, what what we are doing is this this with them? So one we want to see the Mvp. What is the Mvp. That you want to build right?
347 00:30:56.340 ⇒ 00:31:10.019 Aravindan Jayachandran: And what the what we typically say is based on the Mvp. We we charge at cost. Right? We say, for that. Give me cost. I’m not making profit. I’m I am also going to invest something. Okay, you are also going to invest. I’m not going to invest right?
348 00:31:10.090 ⇒ 00:31:12.880 Aravindan Jayachandran: So when I say you, the person who is the founder, right.
349 00:31:12.880 ⇒ 00:31:13.319 Uttam Kumaran: Yeah, yeah.
350 00:31:13.320 ⇒ 00:31:21.950 Aravindan Jayachandran: And then and then he has to form a company. And the product studio will will own a percentage of the company.
351 00:31:22.230 ⇒ 00:31:22.930 Aravindan Jayachandran: Okay.
352 00:31:23.440 ⇒ 00:31:25.770 Aravindan Jayachandran: think of it as CD. As a service. That’s what I.
353 00:31:25.770 ⇒ 00:31:26.190 Uttam Kumaran: Yeah, yeah.
354 00:31:26.190 ⇒ 00:31:28.669 Aravindan Jayachandran: Yeah. So it’s best for you to say.
355 00:31:28.690 ⇒ 00:31:34.700 Aravindan Jayachandran: if you are bringing in a CTO founder CTO, he’s going to charge you anywhere between 30, 30%.
356 00:31:35.040 ⇒ 00:31:42.209 Aravindan Jayachandran: Right? So we we are saying, Hey, the the number that I’m speaking to people are 2525 to 20 to 90%,
357 00:31:43.350 ⇒ 00:31:49.059 Aravindan Jayachandran: right? 20 to 25% equity. We will, we will own the product for you end to end. Okay.
358 00:31:49.270 ⇒ 00:31:51.309 Aravindan Jayachandran: till you raise a series, a level.
359 00:31:51.810 ⇒ 00:31:52.350 Uttam Kumaran: Yeah.
360 00:31:52.770 ⇒ 00:31:58.519 Aravindan Jayachandran: After series. Ideally, you should have your own team. That also will help you build separately.
361 00:31:58.800 ⇒ 00:31:59.620 Uttam Kumaran: Yeah, yeah, yeah.
362 00:32:00.210 ⇒ 00:32:02.920 Aravindan Jayachandran: Yeah, that that is, that is how I’m I’m looking at it.
363 00:32:03.308 ⇒ 00:32:08.559 Aravindan Jayachandran: Ideally, we should be there from ide to series. A is what I I believe.
364 00:32:09.520 ⇒ 00:32:12.429 Uttam Kumaran: So for both of for so for the insurance idea, I’m
365 00:32:12.660 ⇒ 00:32:20.159 Uttam Kumaran: like, I’m the me and my friend. We’re the only people involved, so that I’m not worried about the realistic idea. I will have to speak with him. However.
366 00:32:20.190 ⇒ 00:32:39.909 Uttam Kumaran: like I think we like, I don’t know in my mind, like I’m basically gonna tell them, hey, we have the opportunity to develop this like right now for these pitch meetings. I think it’s I think we should go ahead and just do it. And then basically figure it out. I I definitely wanted to get some legal agreements in terms of the IP and everything. But
367 00:32:40.000 ⇒ 00:32:46.059 Uttam Kumaran: frankly, the stuff that we’re we’d work we’re working on for him is something we could work on anyways. So I’m not like.
368 00:32:46.370 ⇒ 00:32:50.539 Uttam Kumaran: I don’t know. He doesn’t have much claim over the idea. It’s a pretty con. It’s like pretty easy idea.
369 00:32:50.540 ⇒ 00:32:55.639 Aravindan Jayachandran: Ideally. What we do is that’s exactly why, right? For example, he wants he starts the company
370 00:32:56.339 ⇒ 00:33:04.100 Aravindan Jayachandran: the product studio gets 20% equity, then that the IP is going to be the the companies right?
371 00:33:04.462 ⇒ 00:33:08.459 Aravindan Jayachandran: We will. We cannot claim any IP, and even if we claim it is part of 20%.
372 00:33:08.810 ⇒ 00:33:19.310 Aravindan Jayachandran: So we can only claim 20% of the IP which is, anyway, we have linked to the company right? So that is how we should think. Think that is what we are thinking everywhere. So, for example, in fashion, tech
373 00:33:19.370 ⇒ 00:33:25.089 Aravindan Jayachandran: the number that I’m telling them is 25 to 20 right? Similarly, in health tech. I have not gone to that level yet.
374 00:33:25.270 ⇒ 00:33:27.679 Aravindan Jayachandran: but I’m I’m going to quote the same number right.
375 00:33:27.920 ⇒ 00:33:33.240 Uttam Kumaran: Quote. I think you quote 20. But then, what do you think about the capital needed? Let’s say it’s a 3 months.
376 00:33:33.240 ⇒ 00:33:37.460 Aravindan Jayachandran: Capital needed capital needed for A for a product I didn’t want.
377 00:33:37.710 ⇒ 00:33:41.279 Aravindan Jayachandran: Yeah for an Mvp. Typically it should not cross. Find a K.
378 00:33:42.110 ⇒ 00:33:42.710 Uttam Kumaran: Okay.
379 00:33:43.240 ⇒ 00:33:51.040 Aravindan Jayachandran: For for for a product that we are. That’s exactly why we want to start with the Pr right everywhere we go, we tell them. Please write down the Prd right.
380 00:33:51.040 ⇒ 00:33:52.670 Uttam Kumaran: Yeah, yeah, 100%. Yeah.
381 00:33:52.670 ⇒ 00:33:56.940 Aravindan Jayachandran: Unless you don’t think of. So what happens later example for fashion tech, right?
382 00:33:57.557 ⇒ 00:34:00.410 Aravindan Jayachandran: The designer is so involved in design.
383 00:34:00.560 ⇒ 00:34:03.709 Aravindan Jayachandran: She is not thinking about the business piece of it right? How do you.
384 00:34:03.710 ⇒ 00:34:04.720 Uttam Kumaran: Yeah, it used to.
385 00:34:04.820 ⇒ 00:34:08.670 Uttam Kumaran: No, it’s a bad client like, yeah, you have to really be clear. Yeah.
386 00:34:08.670 ⇒ 00:34:30.110 Aravindan Jayachandran: Correct. So that is why the 1st step is, write the prd, okay. And if you want to sign typically, the product should use to sign an nda with the, with the the company that we are going to work with. If the company is not that it is farming in us is like 2 days process free mantra, right company, Llp. Right Llc. And then you sign and can be with Lc.
387 00:34:30.360 ⇒ 00:34:32.610 Aravindan Jayachandran: And then we will. We’ll start working on it.
388 00:34:32.679 ⇒ 00:34:37.780 Aravindan Jayachandran: Once we come to the stage. Okay, this is the Mvp we want to develop. Then we will design on the estimate
389 00:34:37.960 ⇒ 00:34:40.650 Aravindan Jayachandran: and the and we start working on the product
390 00:34:42.010 ⇒ 00:34:42.889 Aravindan Jayachandran: right
391 00:34:43.130 ⇒ 00:34:46.430 Aravindan Jayachandran: with with the contract in place. That’s that’s how it should. It will work.
392 00:34:47.639 ⇒ 00:34:50.329 Uttam Kumaran: So so the other idea is.
393 00:34:50.829 ⇒ 00:34:55.489 Uttam Kumaran: I want to think about, is there any way where we can? We can have like
394 00:34:55.499 ⇒ 00:34:58.729 Uttam Kumaran: proof of concepts develop just for the pitch meetings.
395 00:34:58.829 ⇒ 00:35:03.139 Uttam Kumaran: because my ability to go pitch and secure the capital
396 00:35:03.329 ⇒ 00:35:13.519 Uttam Kumaran: like I need sometimes need these proof of concepts right? Which, let’s say the whole. Let’s say the Mvp. Takes 6 months to develop. The proof of concept may take 2 months
397 00:35:13.789 ⇒ 00:35:17.779 Uttam Kumaran: like, how do we? What do you think about our arrangement just for the proof of concept
398 00:35:17.819 ⇒ 00:35:37.539 Uttam Kumaran: again, this. But that’s the problem is that is like, I need that to go secure funding like for the insurance idea. I need the proof of concept in order to go get like 250 k. Half a million to go invest in the Id to go invest basically on the idea. But what do you think about like what what is like an add cost for like 2 months?
399 00:35:37.969 ⇒ 00:35:41.599 Uttam Kumaran: Cause then I can find the hash to the front that basically.
400 00:35:42.030 ⇒ 00:35:48.969 Aravindan Jayachandran: So if if you are going to ask me now whether I’m ready to say 2 people work on the Poc.
401 00:35:49.240 ⇒ 00:35:52.589 Aravindan Jayachandran: I would need another 2 to 3 months to start, start.
402 00:35:52.590 ⇒ 00:35:54.960 Uttam Kumaran: Okay, okay, yeah, okay, cool. Yeah, yeah.
403 00:35:54.960 ⇒ 00:35:58.168 Aravindan Jayachandran: Because, as I mentioned, I have taken a team. I am.
404 00:35:58.460 ⇒ 00:35:58.870 Uttam Kumaran: No, no, no.
405 00:35:58.870 ⇒ 00:35:59.380 Aravindan Jayachandran: And that’s.
406 00:35:59.380 ⇒ 00:36:02.070 Uttam Kumaran: I guess I’m just giving you what is in my mind, because.
407 00:36:02.070 ⇒ 00:36:02.450 Aravindan Jayachandran: Yeah, yeah.
408 00:36:02.450 ⇒ 00:36:17.119 Uttam Kumaran: There’s this is going to be 2 stages one is going to be. I can get any meeting we want. The the problem in AI right now is, there’s a lot of people promising, and there’s not a lot of showing right. And so I I wanted. If we come to the meeting with with. We come to meeting with the show.
409 00:36:17.432 ⇒ 00:36:22.569 Uttam Kumaran: It’s gonna really be great, but the thing is like, whatever your cost is for the folks.
410 00:36:22.590 ⇒ 00:36:40.690 Uttam Kumaran: I wanna make sure, like we understand that. And this will be all post prd like there’ll be a Prd. For the proof of concept and the Mvp. Done before this process, and then our goal is like what is the smallest amount of features we need for the demo in order to secure funding for the next stage. And that’s something that like
411 00:36:40.700 ⇒ 00:36:42.839 Uttam Kumaran: that is actually going to be the
412 00:36:42.920 ⇒ 00:36:52.750 Uttam Kumaran: way we do this. And again, because of because you’re in India, that, like, I. I want to take advantage of the cost, basically like the cost advantage there, and then drive towards that.
413 00:36:53.090 ⇒ 00:37:03.579 Aravindan Jayachandran: No, no, that that is exactly right. So what what we need in the Poc, what what we need in in the Mvp. If you can kind of put together, it’s a basic estimation. Yeah. So.
414 00:37:03.580 ⇒ 00:37:10.809 Uttam Kumaran: No, no, I’m not worried. I’m not worried, but I can do it. Yeah, I’ve done Prds for years, like I’m happy to do all that, and then basically hand it to you to say, like.
415 00:37:10.810 ⇒ 00:37:11.580 Aravindan Jayachandran: But yeah, d.
416 00:37:11.930 ⇒ 00:37:19.009 Aravindan Jayachandran: so once you have the pid, let’s take. We do. You have identified out of this Pid. We will will take, say 5 features and put it as a Poc.
417 00:37:19.290 ⇒ 00:37:25.370 Aravindan Jayachandran: What the this, when we, when we speak about fine tuning, the biggest problem is training costs in analytics.
418 00:37:25.770 ⇒ 00:37:26.660 Uttam Kumaran: Yeah, yeah.
419 00:37:26.660 ⇒ 00:37:39.050 Aravindan Jayachandran: Right. And and that also we want to try and try to keep low because we are. We are trying to get the hardware. In our in our data center, right, we want to create a small data center.
420 00:37:39.990 ⇒ 00:37:49.480 Aravindan Jayachandran: So to set up all of these things, we need 3 months, but after 3 months, if you come right Poc, we can. We can do it from, say, 150 K. Easily.
421 00:37:49.610 ⇒ 00:37:53.860 Aravindan Jayachandran: And then even even less than that. I don’t know what feature that I’m thinking about.
422 00:37:53.860 ⇒ 00:37:54.310 Uttam Kumaran: Sure, sure.
423 00:37:54.310 ⇒ 00:37:58.280 Aravindan Jayachandran: But ideally I am. I am telling telling my folks in fashion, tech
424 00:37:58.963 ⇒ 00:38:03.200 Aravindan Jayachandran: that. Anything that we are looking at an Mpp don’t don’t expect
425 00:38:03.737 ⇒ 00:38:08.169 Aravindan Jayachandran: more than final K. But keep perform 2 50 to final K as a range.
426 00:38:08.310 ⇒ 00:38:08.650 Uttam Kumaran: Okay.
427 00:38:08.780 ⇒ 00:38:13.400 Aravindan Jayachandran: Right. So that is necessary because of a coming into picture right.
428 00:38:13.400 ⇒ 00:38:16.180 Uttam Kumaran: No, no, no, totally totally yeah. 100%. And it’s also just.
429 00:38:16.180 ⇒ 00:38:16.690 Aravindan Jayachandran: Cheetahs.
430 00:38:16.690 ⇒ 00:38:23.130 Uttam Kumaran: It’s buffer. And it’s a good. Yeah, i i i think, yeah, I mean, we’ll I think we’ll figure it out. I’m gonna put both of these Prds together
431 00:38:23.160 ⇒ 00:38:43.610 Uttam Kumaran: and kind of get it to you. And then for the insurance idea, I’m talking to my friend who’s in the insurance idea. And he, basically, I’m gonna I’m basically gonna ask him like, Hey, do you wanna go run this company? And if you and then basically say, like, Hey, what would be the cut like 2 or 3 killer features. And like, can we get any capital basically short term to fund this?
432 00:38:43.730 ⇒ 00:38:49.250 Uttam Kumaran: And then we drive towards that. The real estate idea may take a little bit longer, because there’s someone else involved.
433 00:38:49.330 ⇒ 00:38:55.138 Uttam Kumaran: But let’s start there and then. I know you. You’ve mentioned like 2 months to kind of get up to speed. So it’s.
434 00:38:55.380 ⇒ 00:39:11.070 Aravindan Jayachandran: I would need that because e, especially with whatever we are raising. And we want to reach to few areas. Right? So one of the platforms we are developing. We want to launch the 1st version in 1st 1st week of July.
435 00:39:12.332 ⇒ 00:39:18.389 Aravindan Jayachandran: So that is going to take till July or August mid right.
436 00:39:18.510 ⇒ 00:39:24.809 Aravindan Jayachandran: By the time the team will also be in a in a working condition they’ll be up and running into speed.
437 00:39:25.100 ⇒ 00:39:30.780 Aravindan Jayachandran: I think. See that that’s what right it’s like pulling a temple card right the momentum is.
438 00:39:31.080 ⇒ 00:39:32.040 Uttam Kumaran: Totally, totally.
439 00:39:32.370 ⇒ 00:39:38.360 Aravindan Jayachandran: Yeah, the moment the momentum is there, I think we can just thrown out quite a bit of work.
440 00:39:38.700 ⇒ 00:39:39.910 Aravindan Jayachandran: That is what I’m hoping for.
441 00:39:39.910 ⇒ 00:39:45.265 Uttam Kumaran: Yeah. And I think I think you’re, I think also, it’s like again having the key capabilities which are gonna be
442 00:39:45.550 ⇒ 00:40:00.020 Uttam Kumaran: like, sometimes we need fine tuning, but the really the things around Ocr Pdf. Scraping like having, like a very robust Pdf scraping Ocr. Text classification, Pdf. Classification, and then having, of course, the speech to text.
443 00:40:00.418 ⇒ 00:40:10.919 Uttam Kumaran: having like able to do rag like all those fundamentals like, if you’re able to do even a couple of iterations on that, like any. Basically, most simple applications will be.
444 00:40:11.230 ⇒ 00:40:13.520 Uttam Kumaran: you know, hopefully plug and play into like.
445 00:40:13.520 ⇒ 00:40:18.339 Aravindan Jayachandran: Yeah, yeah. Yeah. So what I want to do is eventually, that’s exactly what I want to do. See? We we are
446 00:40:18.620 ⇒ 00:40:23.370 Aravindan Jayachandran: for better hours. We are logged in with. Gcp, okay?
447 00:40:23.764 ⇒ 00:40:31.549 Aravindan Jayachandran: And I, I like using these data capabilities as well as the Acup is, it’s best among the players what? I always believe?
448 00:40:32.337 ⇒ 00:40:34.982 Aravindan Jayachandran: You might like to defer that. Okay.
449 00:40:35.630 ⇒ 00:40:44.779 Uttam Kumaran: No, no, that’s fine. I mean, you work. You work for them. So you’re biased. But that’s okay. And also like, also Gcp, as a good Gcp. Has a good startup program. So.
450 00:40:45.120 ⇒ 00:40:49.469 Aravindan Jayachandran: Yeah, exactly. And and they have the connects as well connects as well to get or whatever that.
451 00:40:49.470 ⇒ 00:40:51.304 Uttam Kumaran: Yeah, yeah, no. That makes sense.
452 00:40:51.610 ⇒ 00:40:56.430 Aravindan Jayachandran: The Denver blue ecosystem is very, very robust for an enterprise. Use case.
453 00:40:56.901 ⇒ 00:41:02.539 Aravindan Jayachandran: And I, I believe, yeah, one of the things that they want to do the moment the fund comes in
454 00:41:02.780 ⇒ 00:41:07.000 Aravindan Jayachandran: is to create that the ecosystem. But that’s exactly why I’ll also need the time.
455 00:41:07.250 ⇒ 00:41:12.880 Aravindan Jayachandran: because these guys are going to run these models on laptop or something. It’s not going to be performant.
456 00:41:13.310 ⇒ 00:41:24.880 Aravindan Jayachandran: I want to create 2 things, one, a local server in the office for them to try thinking of getting to Gpus, and the some some servers there.
457 00:41:25.000 ⇒ 00:41:31.049 Aravindan Jayachandran: Similarly, we want to have at the Gcp level, we’ll have some tensor flow models and stuff.
458 00:41:31.050 ⇒ 00:41:31.440 Uttam Kumaran: Yeah.
459 00:41:31.440 ⇒ 00:41:33.660 Aravindan Jayachandran: So we will kind of plug and play
460 00:41:33.760 ⇒ 00:41:49.820 Aravindan Jayachandran: what you mentioned. Right? The text text summarization Po, context, wonderfulization. Then Ocr then also the chat board right based on rag. Right? If we can get these things aligned up, I think we can plug and play wherever we want.
461 00:41:51.420 ⇒ 00:41:52.219 Uttam Kumaran: Okay. Okay.
462 00:41:53.200 ⇒ 00:41:57.769 Aravindan Jayachandran: Yeah, I I did something in rg, like, 6 months back.
463 00:41:57.790 ⇒ 00:42:02.589 Aravindan Jayachandran: I use llama index. But it’s been quite some time. I have to also refresh and get back on track.
464 00:42:02.720 ⇒ 00:42:08.209 Aravindan Jayachandran: I’m currently working on the working on assigning tasks and stuff. So that’s where I’m kind of stuck.
465 00:42:08.210 ⇒ 00:42:14.090 Uttam Kumaran: Yeah, and I have a lot of, I have a lot of, I have a lot of like papers and resources to who like I can share on
466 00:42:14.160 ⇒ 00:42:23.189 Uttam Kumaran: basically lot of things. I’m just reading on Twitter for these things. So whenever you get organized around like, Hey, these are the I mean. I don’t know if you’re setting up like a
467 00:42:23.330 ⇒ 00:42:32.829 Uttam Kumaran: slack, or whatever for each of these guys or whatever. But let me know, because I have resources that I’d love to. Just. I’ll just streamline a ton of stuff that I’ve been reading to them.
468 00:42:34.750 ⇒ 00:42:36.779 Uttam Kumaran: so whatever project you want to get me involved in.
469 00:42:36.780 ⇒ 00:42:42.250 Aravindan Jayachandran: We are in the yeah, we are in the initial stages. We are. We are experimenting with you.
470 00:42:42.390 ⇒ 00:42:46.970 Aravindan Jayachandran: for now everyone is sitting on this this suit. Okay, so, but we are discussing.
471 00:42:46.970 ⇒ 00:42:50.619 Uttam Kumaran: Yeah. But Google chat is not like, I don’t know. Google. Chat is hard.
472 00:42:52.086 ⇒ 00:42:54.593 Aravindan Jayachandran: Yeah, no. But yeah.
473 00:42:55.220 ⇒ 00:42:58.530 Uttam Kumaran: Like for some documentation, but chat is difficult.
474 00:42:59.250 ⇒ 00:43:03.519 Aravindan Jayachandran: Yeah, notion. i i i’m not very keen on. No, I try notion also.
475 00:43:03.830 ⇒ 00:43:09.220 Aravindan Jayachandran: But I I felt the. The. The collaboration part is still not there, right
476 00:43:09.370 ⇒ 00:43:16.639 Aravindan Jayachandran: slack is something which we have to try. Yeah, we have to. That’s 1 of the things that I’m trying telling the team also to try a few things.
477 00:43:16.850 ⇒ 00:43:20.810 Aravindan Jayachandran: So they are. They’re they’re testing several tools as we speak.
478 00:43:21.525 ⇒ 00:43:25.679 Aravindan Jayachandran: We are testing clickup for project management. We are testing
479 00:43:25.830 ⇒ 00:43:26.999 Aravindan Jayachandran: D weaver for.
480 00:43:27.000 ⇒ 00:43:29.289 Uttam Kumaran: Yeah, yeah. Yeah. I heard, Clickup is very good.
481 00:43:30.020 ⇒ 00:43:31.000 Aravindan Jayachandran: Yeah. Sorry.
482 00:43:32.260 ⇒ 00:43:34.369 Uttam Kumaran: I heard. Clickup is probably the best.
483 00:43:34.830 ⇒ 00:43:39.620 Aravindan Jayachandran: Yeah, clickup is good. We are just testing it out. We are testing deepware.
484 00:43:39.770 ⇒ 00:43:48.860 Aravindan Jayachandran: We are testing pyjam for python we are looking at, because see visual studio board the extensions are becoming a pain in security wise.
485 00:43:49.290 ⇒ 00:43:57.740 Aravindan Jayachandran: So you’re thinking whether we should go for by jump that way it will be safe because we don’t want any quotation happening at the extension level. Right?
486 00:43:58.020 ⇒ 00:43:59.090 Aravindan Jayachandran: So
487 00:44:00.080 ⇒ 00:44:03.370 Aravindan Jayachandran: the the security is a pain with the PA. Yeah.
488 00:44:03.870 ⇒ 00:44:04.460 Uttam Kumaran: Yeah.
489 00:44:05.080 ⇒ 00:44:07.850 Aravindan Jayachandran: Especially the population skill program. Right? So.
490 00:44:08.000 ⇒ 00:44:08.460 Uttam Kumaran: Yeah.
491 00:44:08.460 ⇒ 00:44:10.879 Aravindan Jayachandran: Kind of 2 of you. Let’s see.
492 00:44:11.180 ⇒ 00:44:12.060 Aravindan Jayachandran: Yeah.
493 00:44:13.050 ⇒ 00:44:13.530 Aravindan Jayachandran: yeah.
494 00:44:13.530 ⇒ 00:44:14.283 Uttam Kumaran: Makes sense.
495 00:44:14.660 ⇒ 00:44:22.339 Aravindan Jayachandran: I think we should, we should sync up often. I will. What I will do is as a next step. I will send you the send you the
496 00:44:22.460 ⇒ 00:44:23.840 Aravindan Jayachandran: Pid template.
497 00:44:24.180 ⇒ 00:44:28.314 Aravindan Jayachandran: Have a look at it. Okay? And add to it. Okay.
498 00:44:28.690 ⇒ 00:44:32.683 Uttam Kumaran: But I’m gonna I’m gonna go ahead and I’ll just start 2 docs and then
499 00:44:33.050 ⇒ 00:44:44.539 Uttam Kumaran: send me. Also. I mean, I I took notes on the other projects that you mentioned. But let’s sync up again. I’m gonna just put a weekly call, maybe around this time, and let’s keep talking.
500 00:44:44.850 ⇒ 00:44:56.099 Aravindan Jayachandran: Yeah, yeah, let’s do that. I think motion also has a pure template. If you are using motion, please go ahead. That’s also is okay. I I saw that, and it is also good. You don’t have to worry about the template that they have.
501 00:44:56.590 ⇒ 00:45:05.820 Uttam Kumaran: Yeah, whatever is easiest for you. If I can do it in notion, it’s easy, because I’m gonna have some folks on my team also add some things to that, and I’m going to be sharing it. So
502 00:45:06.120 ⇒ 00:45:06.900 Uttam Kumaran: yeah.
503 00:45:07.020 ⇒ 00:45:07.640 Uttam Kumaran: that’s it.
504 00:45:07.640 ⇒ 00:45:09.499 Aravindan Jayachandran: Exactly what I’m saying. Give every notion.
505 00:45:09.800 ⇒ 00:45:13.350 Aravindan Jayachandran: and then I I can. You can give me access. I can go through it.
506 00:45:14.420 ⇒ 00:45:14.950 Aravindan Jayachandran: Okay.
507 00:45:14.950 ⇒ 00:45:20.239 Uttam Kumaran: Okay, perfect. And then, yeah, I suppose so, the interns and stuff are going well. So everybody is like
508 00:45:20.840 ⇒ 00:45:24.368 Uttam Kumaran: started doing stuff. And yeah, things are progressing.
509 00:45:25.150 ⇒ 00:45:26.829 Uttam Kumaran: so that’s all. That’s all great.
510 00:45:27.442 ⇒ 00:45:28.950 Uttam Kumaran: And then, yeah.
511 00:45:28.950 ⇒ 00:45:29.840 Aravindan Jayachandran: So, Michael.
512 00:45:29.980 ⇒ 00:45:31.549 Aravindan Jayachandran: yeah, go on. Go. Yeah. Go on.
513 00:45:31.550 ⇒ 00:45:32.689 Uttam Kumaran: No go you go for go for it.
514 00:45:33.350 ⇒ 00:45:39.880 Aravindan Jayachandran: No, I’m trying to see if we can get the other and Akshay to join us after their graduation as well.
515 00:45:39.880 ⇒ 00:45:40.360 Uttam Kumaran: Yeah.
516 00:45:40.360 ⇒ 00:45:48.940 Aravindan Jayachandran: So a 3rd is in Illinois, and I think he is in a 3 year post, or something like that. Okay, I think he will go for a highest redistime, or wrong.
517 00:45:49.525 ⇒ 00:45:53.549 Aravindan Jayachandran: Actually, I know for a fact that he’s ready to join us.
518 00:45:54.011 ⇒ 00:46:01.179 Aravindan Jayachandran: If we give an offer after whatever. Right? So I told I told them. Let’s see when it happens right when it happened.
519 00:46:01.540 ⇒ 00:46:01.930 Uttam Kumaran: Okay.
520 00:46:02.197 ⇒ 00:46:04.339 Aravindan Jayachandran: Priya, you know Priya is my spouse right.
521 00:46:04.340 ⇒ 00:46:05.440 Uttam Kumaran: Yes, yes, yes.
522 00:46:05.780 ⇒ 00:46:09.690 Aravindan Jayachandran: Yeah. So, Priya. Because of my career choices.
523 00:46:09.700 ⇒ 00:46:15.640 Aravindan Jayachandran: Her career has been screwed up as always. Right? So she has been doing so many things here and there.
524 00:46:15.690 ⇒ 00:46:23.889 Aravindan Jayachandran: so I know she likes, and she was a brilliant student than me. So in college I didn’t study. She studied right? So
525 00:46:24.000 ⇒ 00:46:30.739 Aravindan Jayachandran: so she’s she’s an 8 pointer. So I think she she will like that. There’s a big old okay. Go on prizes.
526 00:46:30.980 ⇒ 00:46:31.690 Aravindan Jayachandran: She has.
527 00:46:31.690 ⇒ 00:46:54.160 Uttam Kumaran: Yeah, I I think I think that’s exactly what we’re doing. So I’m basically giving everybody the building blocks to learn again. Some people are great. I’m not a good student, so like, I only learn by doing the job. Some people are good students, so they can take all these courses and learn. And so I basically, I’m like, tell me how you like to learn, and I’ll give you. I’ll give you all the resources. And then, probably in one or 2 weeks I’m gonna give them some real tickets, and then I pair.
528 00:46:54.160 ⇒ 00:46:54.730 Aravindan Jayachandran: Yeah, I’m sure.
529 00:46:54.730 ⇒ 00:46:58.999 Uttam Kumaran: Everybody up with mentors. And I’m having some people come and give presentation. So
530 00:46:59.050 ⇒ 00:47:04.739 Uttam Kumaran: typical typical stuff. I mean, ideally. Again, I want people to push code within the net within the month. So.
531 00:47:04.740 ⇒ 00:47:05.210 Aravindan Jayachandran: Hmm, yeah.
532 00:47:05.210 ⇒ 00:47:07.284 Uttam Kumaran: That’s what my hope is. And
533 00:47:07.820 ⇒ 00:47:22.609 Uttam Kumaran: yeah. And then we’ll kind of see it again. I basically gave opportunity to everybody all the way from data analysis all the way down to even helping on some AI stuff we need and even helping on the business side, if people are interested. So everybody’s kind of picked a different angle. And then kind of going.
534 00:47:22.630 ⇒ 00:47:24.640 Uttam Kumaran: So yeah, it’s it’s good.
535 00:47:25.020 ⇒ 00:47:32.570 Aravindan Jayachandran: Yeah, yeah, I think I I think that’s that’s exactly what I was telling telling both both 3 of them. Actually. So this is an opportunity, use it.
536 00:47:32.650 ⇒ 00:47:44.690 Aravindan Jayachandran: use it, and learn right? And based on the learning. If you want to continue, if you want to do something, I think we have enough opportunity instead, ecosystem of the companies that we have right.
537 00:47:44.690 ⇒ 00:47:46.464 Uttam Kumaran: Yeah, yeah, yeah, 100%.
538 00:47:46.760 ⇒ 00:47:52.149 Aravindan Jayachandran: Yeah. So that’s what I told them. So where are the opportunities? More than happy to happy to enable you?
539 00:47:52.380 ⇒ 00:47:55.439 Aravindan Jayachandran: Is what I told them. So we will be able to work on that. Yeah.
540 00:47:56.670 ⇒ 00:48:02.151 Uttam Kumaran: Yeah, yeah. Okay, okay. And then I spoke with Siby yesterday. He gave me like, Update a little bit on the business side.
541 00:48:02.390 ⇒ 00:48:03.110 Aravindan Jayachandran: Yeah.
542 00:48:03.650 ⇒ 00:48:05.020 Uttam Kumaran: So that was, that’s fine also.
543 00:48:05.020 ⇒ 00:48:08.129 Aravindan Jayachandran: He’s he’s kind of stressed, is telling him don’t get stressed.
544 00:48:08.300 ⇒ 00:48:11.940 Aravindan Jayachandran: He’s he’s he’s worried that he’s not able to take care of his help.
545 00:48:11.950 ⇒ 00:48:16.399 Aravindan Jayachandran: I told him. That will happen late. It’s it’s a matter of couple of weeks, right?
546 00:48:16.500 ⇒ 00:48:20.485 Aravindan Jayachandran: So yeah, he’s he’s lacking patience.
547 00:48:21.190 ⇒ 00:48:22.679 Aravindan Jayachandran: That’s expected. Yeah.
548 00:48:22.680 ⇒ 00:48:23.300 Uttam Kumaran: Yeah, yeah.
549 00:48:23.300 ⇒ 00:48:30.130 Aravindan Jayachandran: If you. If you’re an action, it is easier. But you are waiting for something to start the action, and it is paying right. That’s what he’s going to have.
550 00:48:30.690 ⇒ 00:48:31.190 Aravindan Jayachandran: I don’t.
551 00:48:31.190 ⇒ 00:48:33.460 Uttam Kumaran: Yeah, yeah, yeah, yeah. Yeah.
552 00:48:33.540 ⇒ 00:48:43.460 Uttam Kumaran: I told him. I cause what I do is I just take 2 HA day and I try to go work out or walk, or something. I said, just block off the time to do that, and just don’t take any calls or anything.
553 00:48:43.560 ⇒ 00:48:46.019 Uttam Kumaran: So yeah, that’s what I tried to say, but it’s hard. It’s hard.
554 00:48:46.020 ⇒ 00:48:58.450 Aravindan Jayachandran: Exactly what he’s trying to do. So currently, the the our calendar is based on somebody else’s calendar, and that that person’s calendar is also not something which you can control. That is where he is facing issues.
555 00:48:58.948 ⇒ 00:49:04.420 Aravindan Jayachandran: Eventually, I think. In a couple of couple of weeks, I think you should, you should tell us.
556 00:49:04.980 ⇒ 00:49:05.860 Uttam Kumaran: Yeah, yeah, yeah.
557 00:49:06.790 ⇒ 00:49:08.490 Aravindan Jayachandran: Yeah. Good. Good.
558 00:49:08.650 ⇒ 00:49:15.389 Aravindan Jayachandran: No nice talking to you. Let’s let’s keep touch basing, I think, some of these things one way when we discuss it, we kind of.
559 00:49:15.390 ⇒ 00:49:25.129 Uttam Kumaran: Yeah. Only if we talk, it’s gonna go. So yeah, let’s talk every I’m gonna put. I’ll just make this recurring meeting. And then, yeah, we’ll we’ll keep going on this. This is great. And then, yeah, I’m basically freeing up all my time for sales.
560 00:49:25.140 ⇒ 00:49:34.520 Uttam Kumaran: So like all these things, will these, all these things will take like one or 2 months to kind of figure out. And so I wanted to basically just start building some momentum around these ideas.
561 00:49:34.580 ⇒ 00:49:37.219 Uttam Kumaran: And yeah, no, I’m excited. This is great.
562 00:49:37.960 ⇒ 00:49:41.079 Aravindan Jayachandran: Yeah, i i i’m also trying to build this team.
563 00:49:41.513 ⇒ 00:49:46.039 Aravindan Jayachandran: We should be up and running with full momentum by couple of months. Right?
564 00:49:46.040 ⇒ 00:49:46.490 Uttam Kumaran: Yeah.
565 00:49:46.490 ⇒ 00:49:52.030 Aravindan Jayachandran: And I’m also trying to see if we can subvert it into data.
566 00:49:52.180 ⇒ 00:49:55.260 Aravindan Jayachandran: Yeah, visualization. And all of this stuff.
567 00:49:55.360 ⇒ 00:49:59.360 Aravindan Jayachandran: Yeah, they’re not there yet. Okay, so because that’s that’s
568 00:49:59.890 ⇒ 00:50:00.879 Aravindan Jayachandran: that’s a trial. So.
569 00:50:00.880 ⇒ 00:50:07.810 Uttam Kumaran: So, John, that’s yeah for me. It’s the same thing like I basically, I’m letting people learn instead of me doing things. And then I come in.
570 00:50:07.840 ⇒ 00:50:10.650 Uttam Kumaran: I come in, and where necessary, you know, but.
571 00:50:10.850 ⇒ 00:50:11.400 Aravindan Jayachandran: Yeah, like.
572 00:50:11.400 ⇒ 00:50:14.930 Uttam Kumaran: It’s it’s tough, you know. So that’s what it takes a few months.
573 00:50:15.730 ⇒ 00:50:19.919 Aravindan Jayachandran: Exactly it. It’s it’s going to take some months. Let’s.
574 00:50:19.920 ⇒ 00:50:24.609 Uttam Kumaran: Yeah, it’s painful. It’s so painful. I hate it, but I don’t know what to do. So like.
575 00:50:24.610 ⇒ 00:50:25.290 Aravindan Jayachandran: Yeah.
576 00:50:27.020 ⇒ 00:50:29.412 Aravindan Jayachandran: let me, we get there. We get there.
577 00:50:30.130 ⇒ 00:50:31.809 Aravindan Jayachandran: really get that eventually. Yeah.
578 00:50:31.910 ⇒ 00:50:32.980 Aravindan Jayachandran: okay.
579 00:50:32.980 ⇒ 00:50:34.093 Uttam Kumaran: Okay. Alright!
580 00:50:34.967 ⇒ 00:50:38.772 Aravindan Jayachandran: Have a have a nice day, and we’ll catch up again. Yeah.
581 00:50:39.090 ⇒ 00:50:39.909 Uttam Kumaran: Yeah, okay, perfect.
582 00:50:40.270 ⇒ 00:50:41.230 Aravindan Jayachandran: Take care it’s a goodbye.
583 00:50:41.230 ⇒ 00:50:41.820 Uttam Kumaran: Next back.