Meeting Title: Uttam-Kumaran <> Michael-Mallmann Date: 2024-11-07 Meeting participants: Michael Mallmann, Uttam Kumaran
WEBVTT
1 00:00:56.290 ⇒ 00:00:59.210 Michael Mallmann: Did you? Did you go to the San bed, bubble?
2 00:00:59.340 ⇒ 00:01:00.150 Michael Mallmann: No.
3 00:01:16.530 ⇒ 00:01:17.440 Michael Mallmann: Hello!
4 00:01:30.260 ⇒ 00:01:31.130 Uttam Kumaran: Hey! Michael!
5 00:01:32.450 ⇒ 00:01:34.019 Michael Mallmann: Hello! How are you doing.
6 00:01:36.620 ⇒ 00:01:37.723 Uttam Kumaran: Hey! How are you?
7 00:01:38.310 ⇒ 00:01:40.209 Michael Mallmann: Oh, good thanks for
8 00:01:40.340 ⇒ 00:01:42.229 Michael Mallmann: this last minute! Call
9 00:01:42.600 ⇒ 00:01:44.669 Michael Mallmann: so! How do I pronounce your name?
10 00:01:44.670 ⇒ 00:01:46.054 Uttam Kumaran: No problem at all.
11 00:01:46.450 ⇒ 00:01:47.460 Uttam Kumaran: Yeah. Fine.
12 00:01:47.460 ⇒ 00:01:47.860 Michael Mallmann: Hasn’t.
13 00:01:47.860 ⇒ 00:01:48.600 Uttam Kumaran: Utah.
14 00:01:49.200 ⇒ 00:01:49.740 Michael Mallmann: You, Tom?
15 00:01:50.920 ⇒ 00:01:52.439 Michael Mallmann: Oh, perfect! Thank you.
16 00:01:52.700 ⇒ 00:01:56.670 Michael Mallmann: So I read your email, and you describe.
17 00:01:56.670 ⇒ 00:01:57.832 Uttam Kumaran: Thanks again for
18 00:01:58.630 ⇒ 00:02:16.000 Uttam Kumaran: yeah. Yeah. Thanks again for taking the time. I know. Philip is a good friend of mine. But he’s he’s starting his own company right now. But we’ve been friends for a while. But yeah, I’m really excited just to dive into you know your I your idea, and of course hear more more about you and your opportunity.
19 00:02:16.300 ⇒ 00:02:24.100 Michael Mallmann: Yeah, that that’s fine. Thank you. So I read your email, and you got everything right
20 00:02:25.410 ⇒ 00:02:25.890 Uttam Kumaran: Okay.
21 00:02:25.890 ⇒ 00:02:30.240 Michael Mallmann: So. So you described so well, I was like, Wow.
22 00:02:30.540 ⇒ 00:02:40.057 Michael Mallmann: it. It sounds like he was in the meeting, you know, but you probably got the recording or something, and you mapped the the needs right.
23 00:02:40.410 ⇒ 00:02:40.900 Uttam Kumaran: Yeah.
24 00:02:40.900 ⇒ 00:02:41.480 Michael Mallmann: So.
25 00:02:41.480 ⇒ 00:02:45.620 Uttam Kumaran: And and we’ve worked with erp systems and stuff like that. So yeah.
26 00:02:46.770 ⇒ 00:02:53.090 Michael Mallmann: I see. So you said you had some questions about the Erp system and the language requirements. Right?
27 00:02:54.990 ⇒ 00:02:55.365 Uttam Kumaran: Yes.
28 00:02:56.240 ⇒ 00:02:58.930 Michael Mallmann: So our erp system.
29 00:02:59.000 ⇒ 00:03:04.729 Michael Mallmann: It’s it’s based on an open source erp
30 00:03:04.820 ⇒ 00:03:08.460 Michael Mallmann: and made in India called Erp next.
31 00:03:10.160 ⇒ 00:03:13.310 Michael Mallmann: So I can create web hooks.
32 00:03:13.480 ⇒ 00:03:13.845 Uttam Kumaran: Okay.
33 00:03:14.210 ⇒ 00:03:18.580 Michael Mallmann: Everywhere. And I can create, customize everything.
34 00:03:18.590 ⇒ 00:03:20.019 Michael Mallmann: And I have
35 00:03:20.570 ⇒ 00:03:21.830 Michael Mallmann: Api.
36 00:03:22.496 ⇒ 00:03:30.409 Michael Mallmann: it’s a hundred percent open. Basically, okay? And I have a team who does all the customization for us.
37 00:03:30.440 ⇒ 00:03:31.780 Michael Mallmann: So basically.
38 00:03:32.170 ⇒ 00:03:34.969 Michael Mallmann: if you tell me what you need, I
39 00:03:36.270 ⇒ 00:03:49.249 Michael Mallmann: I raise a ticket internally with them and they set it up. Okay and be because I really would like to see at least one scenario, because I have many scenarios for different calls.
40 00:03:49.710 ⇒ 00:03:57.140 Michael Mallmann: Right? I really would like to say at least one scenario in the next. I don’t know. 60, 90 days, let’s say
41 00:03:57.540 ⇒ 00:04:01.360 Michael Mallmann: I already told them, and they already waiting for like
42 00:04:01.450 ⇒ 00:04:04.470 Michael Mallmann: what do I? What do they need to do, you know?
43 00:04:04.500 ⇒ 00:04:05.860 Michael Mallmann: So
44 00:04:06.030 ⇒ 00:04:13.539 Michael Mallmann: so yeah, so this is the point and language requirements. That’s a very good question. So it’s Brazilian, Portuguese.
45 00:04:15.410 ⇒ 00:04:20.517 Michael Mallmann: If this is the language you are talking about, not a coding language.
46 00:04:20.910 ⇒ 00:04:22.710 Uttam Kumaran: Not the coding language, not the.
47 00:04:22.930 ⇒ 00:04:27.859 Michael Mallmann: Yes, so it’s Brazilian, Portuguese, right? We would need to check
48 00:04:27.920 ⇒ 00:04:28.890 Michael Mallmann: if
49 00:04:30.000 ⇒ 00:04:35.100 Michael Mallmann: if that accent is is fine. I I checked some of
50 00:04:36.520 ⇒ 00:04:41.119 Michael Mallmann: open AI native voices that they have.
51 00:04:41.650 ⇒ 00:04:42.800 Michael Mallmann: and
52 00:04:42.820 ⇒ 00:04:50.000 Michael Mallmann: but I checked in English, you know nowadays I do most of my things in English as well. So in English, they sound perfect.
53 00:04:50.200 ⇒ 00:04:58.159 Michael Mallmann: I never really checked them in Portuguese. I mean, I did check them in Portuguese, but like a year ago, and I know that they just released the new.
54 00:04:58.160 ⇒ 00:05:01.967 Uttam Kumaran: Way better, so much better. I’m telling you like
55 00:05:02.390 ⇒ 00:05:06.110 Michael Mallmann: I saw I saw a video of the new releases.
56 00:05:06.260 ⇒ 00:05:09.560 Michael Mallmann: and you could say, like, Oh.
57 00:05:09.610 ⇒ 00:05:11.335 Michael Mallmann: do the Texas
58 00:05:11.910 ⇒ 00:05:13.438 Uttam Kumaran: Yeah. Do the accent.
59 00:05:13.820 ⇒ 00:05:15.810 Michael Mallmann: And it’s perfect.
60 00:05:15.810 ⇒ 00:05:26.060 Uttam Kumaran: No, I use every day I cause I run my business, and I I don’t know. I’ll be driving, and I have thoughts or ideas, and I talk to it just because I.
61 00:05:26.060 ⇒ 00:05:26.610 Michael Mallmann: Wow!
62 00:05:26.610 ⇒ 00:05:32.590 Uttam Kumaran: Because I sometimes that you want to type or you just sometimes when you want to just get something out verbally.
63 00:05:32.610 ⇒ 00:06:01.179 Uttam Kumaran: And it’s so nice, you know. I I tell everybody I’m telling everybody to use it, because it’s so nice to just be driving or talking to say like. And and you actually see, so that technology they use not only they have it. As like Api, there are actually a lot of other Apis that are available that are basically built on top of that to create these flows. So exactly like kind of what you mentioned. Where it’s like, there may be different sort of use cases there’s confirming. There’s rescheduling. There’s canceling.
64 00:06:01.180 ⇒ 00:06:01.650 Michael Mallmann: Hmm.
65 00:06:01.650 ⇒ 00:06:26.860 Uttam Kumaran: And you want. You don’t want it to you. It’s like the the open AI version. It’s supposed to handle everything right. But in your use case. There are some fixed flows, and so it makes it really easy to handle objections to have these different trees. And there are some really great, you know, tools that make that super easy to do, especially compared to even earlier this year. That we for clients already so.
66 00:06:26.860 ⇒ 00:06:30.703 Michael Mallmann: Oh, that’s that’s that’s good good to know. So
67 00:06:31.470 ⇒ 00:06:34.794 Michael Mallmann: yeah, so, but basically, that’s it, you term
68 00:06:35.950 ⇒ 00:06:42.269 Michael Mallmann: I, I found the call fluent.com. I think that’s the name. Do you know them?
69 00:06:42.270 ⇒ 00:06:46.549 Uttam Kumaran: I don’t know call fluent but is it like kind of like a call building like.
70 00:06:46.550 ⇒ 00:07:00.799 Michael Mallmann: Yes, exactly. So, the basically they get like a J. Zoom. I could send to a web hook right? They and I could build like an AI agent with like a certain documentation or script.
71 00:07:01.200 ⇒ 00:07:06.770 Michael Mallmann: and then, based on that knowledge, they would place the call using twilio api.
72 00:07:06.770 ⇒ 00:07:07.200 Uttam Kumaran: Yes.
73 00:07:07.200 ⇒ 00:07:09.590 Michael Mallmann: Okay? And
74 00:07:10.840 ⇒ 00:07:14.740 Michael Mallmann: and basically, that’s it. And then at the end, they would summarize that.
75 00:07:14.850 ⇒ 00:07:21.790 Michael Mallmann: Let’s say what they discussed and send it back to my European, right? Because
76 00:07:24.130 ⇒ 00:07:30.359 Michael Mallmann: yeah, that that’s it, basically what they do. So so there are some tools that are ready made.
77 00:07:30.570 ⇒ 00:07:34.590 Michael Mallmann: I I haven’t tried. I haven’t tested them. To be honest.
78 00:07:37.260 ⇒ 00:07:49.290 Michael Mallmann: the issue is that you know, we are trying to do something like with a Brazilian phone number, you know. So I know twilio does have a Brazilian numbers, but it has to be localized, you know.
79 00:07:49.290 ⇒ 00:07:59.259 Uttam Kumaran: Yeah, you need the local numbers. So otherwise people aren’t gonna pick it up. I sent some. I sent 2 links in the chat. There’s a company called bland.ai! If you go to the zoom, chat.
80 00:07:59.410 ⇒ 00:08:02.600 Michael Mallmann: I’ve I’ve read about them. I’ve read about the 2 of them. Yeah.
81 00:08:02.600 ⇒ 00:08:06.018 Uttam Kumaran: Yeah, and and vappy. So we have familiarity with both.
82 00:08:06.850 ⇒ 00:08:22.899 Uttam Kumaran: Both are really great. It kind of depends on sort of the use case and the budget but both are really great. There are a couple of others. The nice thing is, there’s a lot of people competing in this space. So as a consumer, you can just use the best one, or whatever.
83 00:08:22.900 ⇒ 00:08:23.700 Michael Mallmann: Yes.
84 00:08:23.700 ⇒ 00:08:47.600 Uttam Kumaran: We’re open to. You can try multiple of these. And again, they’re all integrate will with twilio they all have web hooks. And again, we can facilitate that transfer of information just like you said. It’ll have a knowledge base of information that it can pull from. And then there’s also it’s very easy to do testing, you know, to test the calls and then get those records back. So this is certainly something that’s like we’ve done.
85 00:08:47.810 ⇒ 00:08:56.538 Uttam Kumaran: You know a bunch of times. I guess my question for you would be 2 things, one about like budget and timeline to kind of give you.
86 00:08:56.850 ⇒ 00:09:06.437 Michael Mallmann: So the timeline I kind of gave you like, but that that’s like an ideal goal, you know. If if that’s not possible, then that’s not possible. Right?
87 00:09:06.850 ⇒ 00:09:15.709 Michael Mallmann: about the budget. This is a little bit more open to be honest. Because I’m still talking to different
88 00:09:16.360 ⇒ 00:09:17.780 Michael Mallmann: possible
89 00:09:18.730 ⇒ 00:09:24.750 Michael Mallmann: agencies. Let let me call you an agency. Right? Yes, because
90 00:09:24.830 ⇒ 00:09:25.930 Michael Mallmann: you know.
91 00:09:26.600 ⇒ 00:09:28.199 Michael Mallmann: as I told Philip.
92 00:09:28.460 ⇒ 00:09:34.179 Michael Mallmann: yes, I understand that, you guys rating dollars. I I totally understand that.
93 00:09:34.330 ⇒ 00:09:35.200 Michael Mallmann: But
94 00:09:35.500 ⇒ 00:09:45.080 Michael Mallmann: we cannot compare just rates. You know I need to to compare deficiency as well, because if I go you, you might understand what I’m saying.
95 00:09:45.080 ⇒ 00:09:45.580 Uttam Kumaran: Totally.
96 00:09:45.580 ⇒ 00:09:47.040 Michael Mallmann: The local market.
97 00:09:47.040 ⇒ 00:09:47.590 Uttam Kumaran: I totally.
98 00:09:48.054 ⇒ 00:09:52.700 Michael Mallmann: Instead of a hundred hours. I need 500 h.
99 00:09:52.700 ⇒ 00:09:53.040 Uttam Kumaran: Thank you.
100 00:09:53.040 ⇒ 00:09:56.810 Michael Mallmann: Work, and then and then it doesn’t work at the end, you know. So
101 00:09:57.830 ⇒ 00:09:59.410 Michael Mallmann: you know what I mean. Right?
102 00:09:59.410 ⇒ 00:10:01.230 Uttam Kumaran: Yeah, so it’s so.
103 00:10:01.230 ⇒ 00:10:12.760 Michael Mallmann: I. I have experience to manage projects, and I like I’m the person who needs to deliver at the end of the day to to my CEO. Right? So when I bring him the
104 00:10:12.820 ⇒ 00:10:14.919 Michael Mallmann: let’s say the the quote
105 00:10:15.010 ⇒ 00:10:21.130 Michael Mallmann: that each agency quoted a project. Right? I I will have to wait like. Look.
106 00:10:21.500 ⇒ 00:10:26.040 Michael Mallmann: this is a bit more expensive, but I trust this team more that they will.
107 00:10:26.110 ⇒ 00:10:27.360 Michael Mallmann: that they will handle.
108 00:10:27.360 ⇒ 00:10:46.320 Uttam Kumaran: Totally understand. And to give you a sense of even my background. I started the company about a year ago. I’m a data engineer. I ran data teams, and product teams. I hired a lot of agencies I really don’t like like. I can’t believe I’m a consultant. But I will say that, like
109 00:10:46.320 ⇒ 00:11:14.190 Uttam Kumaran: the the one thing I do want to share is that I’m happy to even do like a free trial, or at least show you like a proof of concept of what we can do, like no strings attached whatever. Because I do think this is something that’s totally in our warehouse we can totally work, you know, with. I would love to see if there’s a budget that can work. But of course, you know, we want to make sure that it’s demonstrating value, and that it’s actually saving you guys and bring you guys more money? And so I totally hear you on.
110 00:11:14.190 ⇒ 00:11:19.305 Uttam Kumaran: You know. Yeah, you can. I think they’re in the agency game. You’ll get a lot of people that can say they can do things
111 00:11:19.820 ⇒ 00:11:47.319 Uttam Kumaran: but and I and I know that’s like who we compete with. But for me, like I’m like, I’m an engineer. I just happen to run a consultancy now and you know, these are these are the exact types of problems that we love solving, that we can solve super super quickly. I know there’s gonna be a long tail of interactions with the Erp, and things like that that definitely would rely on an external team will take time. But for something like this, even it’s a small proof of concept. We can put something together.
112 00:11:47.320 ⇒ 00:11:56.410 Uttam Kumaran: you know, this month, and at least have you play around with it, and we can just have you like what you like, what you don’t like? I don’t want to charge for that, because for me it’s
113 00:11:57.050 ⇒ 00:12:02.156 Uttam Kumaran: it’s showing you that we we can we have the capability, but also that, like we all work great together, and
114 00:12:02.400 ⇒ 00:12:13.290 Michael Mallmann: That’s that’s great to hear. So you know about the costs and saving money. To be very honest to you, I don’t think this solution will save us money, and I tell you the reason
115 00:12:13.760 ⇒ 00:12:19.440 Michael Mallmann: all the minute quotes everything is in dollars right? And we pay local salaries
116 00:12:19.901 ⇒ 00:12:28.530 Michael Mallmann: to our team. But what we are looking for is not saving money with the human behind the the phone.
117 00:12:28.790 ⇒ 00:12:35.189 Michael Mallmann: What we are looking for is to it’s a way to handle the peak, you know, because we have.
118 00:12:36.760 ⇒ 00:12:40.830 Michael Mallmann: And we have. And we have like 2025
119 00:12:41.180 ⇒ 00:12:58.499 Michael Mallmann: people working there. And sometimes we have so many calls that we have to make, that that we can’t handle the the calls, you know. And then patients don’t get the notifications. And so in September we started integrating Whatsapp because Whatsapp is massive in my country.
120 00:12:58.500 ⇒ 00:12:59.759 Uttam Kumaran: Yeah, it’s great, for sure.
121 00:12:59.760 ⇒ 00:13:00.350 Michael Mallmann: Even though.
122 00:13:00.616 ⇒ 00:13:03.279 Uttam Kumaran: That bots and telegram. I feel like also pretty big.
123 00:13:03.280 ⇒ 00:13:24.719 Michael Mallmann: Yeah. So we integrated Whatsapp already with the buttons. So people can click yes or no for the Confirmation. So most of the clients, 66% of them already confirm or cancel the appointments using the Whatsapp, but because because we we still have
124 00:13:25.140 ⇒ 00:13:32.390 Michael Mallmann: at least like, if you add back everything we need. We need at least like, I guess, a thousand call calls a week.
125 00:13:33.150 ⇒ 00:13:35.499 Michael Mallmann: It’s not something huge.
126 00:13:35.690 ⇒ 00:13:46.100 Michael Mallmann: But if if you think of humans doing the calls. It’s a lot. And if you, if you think that they have to do it in a certain time to make sense, it’s a lot right.
127 00:13:46.100 ⇒ 00:13:46.850 Uttam Kumaran: Yeah. And it’s only.
128 00:13:47.170 ⇒ 00:13:53.840 Uttam Kumaran: And I cause I have some friends that work in sales that call. And yeah, they’re like, on a great day. They’ll do like a hundred, you know.
129 00:13:53.840 ⇒ 00:13:54.770 Michael Mallmann: Yeah, exactly.
130 00:13:54.770 ⇒ 00:13:56.040 Uttam Kumaran: And it’s really so.
131 00:13:56.520 ⇒ 00:14:10.319 Michael Mallmann: Yeah, yeah, so that’s it. So that’s interesting. So look, even though you mentioned that. Yes, we could do like a trial. Or let’s say a quick Mvp. To try right
132 00:14:10.761 ⇒ 00:14:15.580 Michael Mallmann: I still would like, if possible, of course, to to see like
133 00:14:16.240 ⇒ 00:14:19.800 Michael Mallmann: what would be the budget for this project that you’d require.
134 00:14:19.800 ⇒ 00:14:20.150 Uttam Kumaran: Okay.
135 00:14:20.150 ⇒ 00:14:20.660 Michael Mallmann: Okay.
136 00:14:21.563 ⇒ 00:14:34.660 Michael Mallmann: just to see if it would make sense for us. Because even even though you do this test and to validate the technology. I wouldn’t like to lose your time to make you waste your time.
137 00:14:34.660 ⇒ 00:14:36.449 Uttam Kumaran: Yeah, no, thank you. I appreciate that.
138 00:14:36.450 ⇒ 00:14:38.600 Michael Mallmann: If the budget is, is something
139 00:14:38.820 ⇒ 00:14:40.610 Michael Mallmann: undoable, right.
140 00:14:40.610 ⇒ 00:15:00.139 Uttam Kumaran: And and to give you even a couple of more data points. So you mentioned, you know, it’s about you’re saying about like 35 or 40% is still kind of happening during doing via calls. And then you mentioned like, about volume. So you mentioned on a given day. It’s about a thousand calls per day during Peak. Is that like.
141 00:15:00.840 ⇒ 00:15:02.029 Michael Mallmann: Yeah, let me give you the right
142 00:15:02.690 ⇒ 00:15:03.430 Michael Mallmann: a little bit.
143 00:15:03.430 ⇒ 00:15:06.500 Uttam Kumaran: About the volume. And then also, yeah.
144 00:15:06.980 ⇒ 00:15:14.139 Michael Mallmann: Just just let me open the erp, and I can tell you then, because there are different flows, and I will tell you.
145 00:15:15.740 ⇒ 00:15:23.730 Michael Mallmann: I can. I can tell you which how many per flow. Okay, I think it makes sense. So look to
146 00:15:24.460 ⇒ 00:15:27.899 Michael Mallmann: let me get this 1, 3, 7, 4,
147 00:15:28.320 ⇒ 00:15:29.870 Michael Mallmann: just a second.
148 00:15:31.830 ⇒ 00:15:34.320 Michael Mallmann: 5, 3, 7.
149 00:15:35.090 ⇒ 00:15:36.659 Michael Mallmann: I know none. Goodbye.
150 00:15:37.560 ⇒ 00:15:41.870 Michael Mallmann: Okay. So look, we have 300 calls a day
151 00:15:41.880 ⇒ 00:15:43.960 Michael Mallmann: for confirmation
152 00:15:43.990 ⇒ 00:15:45.860 Michael Mallmann: that still needs to be done.
153 00:15:45.880 ⇒ 00:15:47.130 Michael Mallmann: Okay.
154 00:15:47.320 ⇒ 00:15:48.480 Michael Mallmann: then
155 00:15:48.950 ⇒ 00:15:50.440 Michael Mallmann: we have
156 00:15:51.830 ⇒ 00:15:56.219 Michael Mallmann: around 80 calls a day that still need to be done
157 00:15:56.430 ⇒ 00:16:02.260 Michael Mallmann: for patients who missed their appointment. They still confirm.
158 00:16:02.280 ⇒ 00:16:04.830 Michael Mallmann: and they don’t go, you know, like.
159 00:16:05.648 ⇒ 00:16:08.721 Michael Mallmann: I don’t get these people. But anyway.
160 00:16:09.290 ⇒ 00:16:16.109 Michael Mallmann: so we have another that this is not much, but it’s like 20 a day.
161 00:16:16.510 ⇒ 00:16:18.979 Michael Mallmann: This is. This is like the
162 00:16:19.170 ⇒ 00:16:24.319 Michael Mallmann: this could be done by human. But this is like an emergency. Let’s say, a doctor
163 00:16:24.650 ⇒ 00:16:30.160 Michael Mallmann: who has the morning shift, so you would have an appointment with the doctor. Right?
164 00:16:30.240 ⇒ 00:16:36.599 Michael Mallmann: So the doctor has an emergency, and he needs to head to a hospital to do a surgery. Let’s say
165 00:16:36.950 ⇒ 00:16:42.089 Michael Mallmann: so he cancels that morning, you know. So we need to to
166 00:16:42.800 ⇒ 00:16:50.919 Michael Mallmann: to tell the patient as soon as we can, to avoid the patient driving to the clinic. You know, it’s it’s not nice. So
167 00:16:50.970 ⇒ 00:16:52.940 Michael Mallmann: okay, then we have
168 00:16:56.150 ⇒ 00:16:58.400 Michael Mallmann: let me get it daily.
169 00:17:00.500 ⇒ 00:17:02.839 Michael Mallmann: Okay, then we have around
170 00:17:03.120 ⇒ 00:17:28.209 Michael Mallmann: a hundred calls a day that this is for, like let’s say you go to an appointment, and the doctor ask you for like lab lab tests, or an MRI or something. So nowadays we send an automated text to the patient. But you know, because we are like a Mini hospital. When we provide all these services, we want to make sure that the patient
171 00:17:28.400 ⇒ 00:17:35.040 Michael Mallmann: closes the deal with us. Right? So so we try to. It would be amazing if we could call.
172 00:17:35.090 ⇒ 00:17:46.080 Michael Mallmann: You know the reason we have, like 1010 people in the room is probably just to do this job, you know, and all of this. So it’s this is 500 calls a day.
173 00:17:46.620 ⇒ 00:17:47.230 Uttam Kumaran: Okay.
174 00:17:47.460 ⇒ 00:17:57.350 Michael Mallmann: Right now. Okay. And then and then there are other flows that we we could automate as well right. But just here 500
175 00:17:57.830 ⇒ 00:17:59.350 Michael Mallmann: I don’t know how much.
176 00:17:59.360 ⇒ 00:18:02.190 Michael Mallmann: how many calls this system can handle.
177 00:18:02.190 ⇒ 00:18:07.790 Uttam Kumaran: Yeah, so and then is, I guess another is this like, is this peak? Is this like an average day? Can you.
178 00:18:07.790 ⇒ 00:18:11.399 Michael Mallmann: No, this is this is, this is across the day
179 00:18:12.530 ⇒ 00:18:24.879 Michael Mallmann: The only the only call that really needs like a priority is those 20 calls, which is like the emergency. The doctor needs to cancel that. That’s the priority. Apart from that
180 00:18:25.230 ⇒ 00:18:30.160 Michael Mallmann: look, the call confirmation, the appointment confirmation. We run 24 h
181 00:18:30.200 ⇒ 00:18:31.800 Michael Mallmann: prior to the appointment.
182 00:18:31.800 ⇒ 00:18:32.590 Uttam Kumaran: Okay. Okay.
183 00:18:32.590 ⇒ 00:18:36.329 Michael Mallmann: Okay, so only 20, only 34%
184 00:18:36.760 ⇒ 00:18:44.709 Michael Mallmann: do not confirm. So we could spread it out a little bit. The calls, you know. No need to do it all at once.
185 00:18:44.720 ⇒ 00:18:47.140 Michael Mallmann: for sure. Yeah. So.
186 00:18:47.140 ⇒ 00:18:52.820 Uttam Kumaran: The thing is, you know, so will you take those slots and re and book new people? Or what happens to those empty slots.
187 00:18:53.590 ⇒ 00:18:57.910 Michael Mallmann: Yes. So your question is very interesting. So our
188 00:18:58.050 ⇒ 00:18:59.400 Michael Mallmann: imagine.
189 00:18:59.430 ⇒ 00:19:03.579 Michael Mallmann: imagine we use the concept of perishable, do you know perishable.
190 00:19:03.580 ⇒ 00:19:04.370 Uttam Kumaran: Yes, yes.
191 00:19:04.370 ⇒ 00:19:12.829 Michael Mallmann: Yeah. So our appointment is perishable. We either sell it on that day or it’s gone right? So
192 00:19:13.010 ⇒ 00:19:17.349 Michael Mallmann: for us, it’s better if the patient cancels it.
193 00:19:17.350 ⇒ 00:19:18.000 Uttam Kumaran: Yes, as.
194 00:19:18.000 ⇒ 00:19:23.590 Michael Mallmann: Then. Yes, as early as possible, because it’s the same thing as you scheduling a meeting.
195 00:19:23.590 ⇒ 00:19:35.529 Uttam Kumaran: So we, we are talking to some other clinics right now with the same problem where basically, they’re they’re losing revenue because of the cancellations, and their their utilization is is hit by that.
196 00:19:35.530 ⇒ 00:19:35.920 Michael Mallmann: Exactly.
197 00:19:35.920 ⇒ 00:19:46.500 Uttam Kumaran: And a lot of this is really just like someone just needs to call and confirm. You’re totally right. And the Whatsapp strategy, I think is great. But you’re still gonna have some people that you can’t get a hold of, and.
198 00:19:46.500 ⇒ 00:19:47.280 Michael Mallmann: Yeah.
199 00:19:47.280 ⇒ 00:19:57.109 Uttam Kumaran: These are like very low hanging fruit. And for us, that’s this is something we’re talking to a few other people on, just on the clinic side for scheduling, rescheduling confirmation.
200 00:19:57.110 ⇒ 00:20:03.319 Michael Mallmann: So look just just to give you a number. So from the 100% that confirm.
201 00:20:03.740 ⇒ 00:20:04.460 Uttam Kumaran: Yeah.
202 00:20:04.460 ⇒ 00:20:07.609 Michael Mallmann: Plus the 34%. That doesn’t. So let
203 00:20:07.670 ⇒ 00:20:10.469 Michael Mallmann: that doesn’t react. So if they don’t react.
204 00:20:10.560 ⇒ 00:20:13.549 Michael Mallmann: we keep them as not confirmed. But booked.
205 00:20:13.570 ⇒ 00:20:14.720 Michael Mallmann: Okay, okay.
206 00:20:14.720 ⇒ 00:20:15.760 Uttam Kumaran: Don’t give it up so.
207 00:20:15.760 ⇒ 00:20:27.039 Michael Mallmann: So yeah, we don’t give it up, because if they show up we have to. They can say, Oh, but I booked, you know, so we keep them there. So let’s call it a hundred percent confirmed plus
208 00:20:27.730 ⇒ 00:20:31.829 Michael Mallmann: didn’t react right? So from these ones.
209 00:20:32.522 ⇒ 00:20:36.460 Michael Mallmann: Before we implemented the Whatsapp confirmation.
210 00:20:36.750 ⇒ 00:20:39.330 Michael Mallmann: 68% would show up.
211 00:20:39.660 ⇒ 00:20:40.330 Uttam Kumaran: Oh, wow! Okay.
212 00:20:40.330 ⇒ 00:20:48.800 Michael Mallmann: To the appointment. Okay, now, it’s 71 last month. That was the 1st full month with the operation running
213 00:20:49.548 ⇒ 00:20:57.689 Michael Mallmann: we. We reached 40 71 point something. So this 2, 3%. That doesn’t
214 00:20:57.860 ⇒ 00:20:59.549 Michael Mallmann: seem too much.
215 00:20:59.870 ⇒ 00:21:07.300 Michael Mallmann: It’s a lot, you know, because we have like a thousand appointments a day. Can you imagine? Like a thousand a day? Times, whatever.
216 00:21:07.817 ⇒ 00:21:13.120 Michael Mallmann: So it’s it’s like, it’s an extra day of revenue, you know. So
217 00:21:13.280 ⇒ 00:21:14.200 Michael Mallmann: so yeah.
218 00:21:14.510 ⇒ 00:21:17.990 Uttam Kumaran: To give you a sense of to give you a sense of the. The.
219 00:21:18.240 ⇒ 00:21:21.970 Uttam Kumaran: The nice thing about using these voice agents is they can work in parallel
220 00:21:22.120 ⇒ 00:21:22.650 Uttam Kumaran: like.
221 00:21:23.040 ⇒ 00:21:25.259 Uttam Kumaran: That’s just based on the amount of numbers you have.
222 00:21:25.310 ⇒ 00:21:31.310 Uttam Kumaran: So again, 5 numbers, they can all call 5, 5, 5, 5. So.
223 00:21:31.310 ⇒ 00:21:31.719 Michael Mallmann: I see.
224 00:21:31.720 ⇒ 00:21:42.489 Uttam Kumaran: Have a breakdown. So then, you so the nice thing is for me when I when I break down the project and I’ll I’ll kind of send you my ideas. There’s some stuff which is like replicating existing processes during Peak, right? Because
225 00:21:42.850 ⇒ 00:22:07.819 Uttam Kumaran: never get a call, just because there’s nobody to call them. There’s also some new processes that you want to add, maybe start doing that. AI native. And so there’s this is kind of I’m thinking about. There’s existing process where there’s this existing flows, that people are handling, that maybe it’s just during peak hours, some portion that goes. Or maybe you start with one phone that it just handles it, and then 2 and sort of go. Then then there’s a 3rd item. There’s a second item, which is.
226 00:22:07.850 ⇒ 00:22:20.939 Uttam Kumaran: we have some new phone calls we’d like to make. But of course there’s they’re already booked doing 500. You’re you’re already doing 500 a day. If you imagine you have to add another 100 or 200. You probably have to go get somebody to do that. Can we offer.
227 00:22:21.750 ⇒ 00:22:28.913 Uttam Kumaran: So we’ll try to break down the. We may have a couple of other questions about, typically, like, How long are these phone calls or
228 00:22:29.200 ⇒ 00:22:33.102 Michael Mallmann: So these, these, yeah, so these outbound calls,
229 00:22:34.410 ⇒ 00:22:36.330 Uttam Kumaran: And like the pickup rates and stuff like that.
230 00:22:36.330 ⇒ 00:22:36.940 Michael Mallmann: Yes.
231 00:22:38.230 ⇒ 00:22:42.428 Michael Mallmann: yeah, I I wouldn’t know the pickup rate to be honest.
232 00:22:42.810 ⇒ 00:22:44.539 Uttam Kumaran: Standard like ideas.
233 00:22:44.935 ⇒ 00:22:49.279 Michael Mallmann: But I know that they’re very short. Okay, this confirmation call
234 00:22:49.560 ⇒ 00:22:50.440 Michael Mallmann: it’s tuition.
235 00:22:50.440 ⇒ 00:22:54.389 Uttam Kumaran: Like a normal hospital confirmation call like, 2030 seconds. Okay?
236 00:22:54.390 ⇒ 00:23:03.349 Michael Mallmann: Yes, exactly. It’s it’s very, very short. Yeah. So what happens is that the the way we thought is that if they would.
237 00:23:03.640 ⇒ 00:23:10.325 Michael Mallmann: even Phillip brought this idea again. But then I was reviewing my notes, and I had already this idea. Okay,
238 00:23:11.210 ⇒ 00:23:19.389 Michael Mallmann: his idea is a little bit different than mine, but it’s the same concept. So he said that if the patient would say that he wants to reschedule
239 00:23:19.820 ⇒ 00:23:27.199 Michael Mallmann: instead of trying to reschedule, we would just say, Okay, some human will call you in the next minutes.
240 00:23:27.560 ⇒ 00:23:28.680 Michael Mallmann: because
241 00:23:28.990 ⇒ 00:23:31.160 Michael Mallmann: doing the rescheduling
242 00:23:31.230 ⇒ 00:23:35.740 Michael Mallmann: automated, it’s it’s very complex and just grabbing the date
243 00:23:35.860 ⇒ 00:23:38.970 Michael Mallmann: and the time that the patient wants wants.
244 00:23:39.550 ⇒ 00:23:42.439 Michael Mallmann: It’s not enough for us, you know, because
245 00:23:42.540 ⇒ 00:23:53.409 Michael Mallmann: there are 120 doctors. Each doctor has a different speciality. Each doctor sees different patients in different addresses in different locations and time. It’s very complex.
246 00:23:53.590 ⇒ 00:24:00.420 Michael Mallmann: So it’s better. It’s bet it’s better if a human calls it back and and handles this appointment. So
247 00:24:00.750 ⇒ 00:24:04.920 Michael Mallmann: you know, we could still interact with our Erp.
248 00:24:05.260 ⇒ 00:24:13.409 Michael Mallmann: maybe just changing the status to something like requires attention or whatever right?
249 00:24:13.460 ⇒ 00:24:16.470 Michael Mallmann: And then our team would handle it.
250 00:24:16.900 ⇒ 00:24:21.019 Uttam Kumaran: That’s like a that is a more human, intensive process than.
251 00:24:21.020 ⇒ 00:24:21.550 Michael Mallmann: Yes.
252 00:24:21.550 ⇒ 00:24:24.409 Uttam Kumaran: Calling, because a lot of those will be yes or no.
253 00:24:24.590 ⇒ 00:24:25.940 Michael Mallmann: Yes, and then if.
254 00:24:25.940 ⇒ 00:24:31.749 Uttam Kumaran: That’s that’s actually enough for you to take the slot. That’s about that the tomorrow and free it.
255 00:24:31.920 ⇒ 00:24:32.939 Uttam Kumaran: and then reschedule.
256 00:24:32.940 ⇒ 00:24:33.360 Michael Mallmann: Exactly.
257 00:24:33.360 ⇒ 00:24:34.289 Uttam Kumaran: A different problem.
258 00:24:34.290 ⇒ 00:24:43.220 Michael Mallmann: Exactly. Exactly. So, once the person says, Yeah, I want to reschedule. We understand that that time is free, right?
259 00:24:43.220 ⇒ 00:24:50.410 Uttam Kumaran: That’s the thing. It’s like, Okay, cool. Then when you’re booking someone that’s open like, that’s the key. In the 24 h period. That’s the key opening.
260 00:24:50.660 ⇒ 00:24:53.270 Michael Mallmann: Yeah. And and the issue is that
261 00:24:53.450 ⇒ 00:25:06.390 Michael Mallmann: you know, some doctors go to the practice expecting 20 customers patients, and then 10 show up. You know, that’s exactly the same problem as the other clinics you’ve been talking to. So.
262 00:25:06.390 ⇒ 00:25:06.860 Uttam Kumaran: 100%.
263 00:25:06.860 ⇒ 00:25:07.710 Michael Mallmann: So, yeah.
264 00:25:08.120 ⇒ 00:25:10.199 Michael Mallmann: so that’s it, I guess.
265 00:25:10.200 ⇒ 00:25:29.499 Uttam Kumaran: Let me let me take let me give me a day or 2, and I’m gonna put something together. And again thank you for the transparency on the on the budget. Everything. I’m also gonna research, at least want to check out. I’m gonna I’m gonna ask some of the porch, find some Portuguese ones that work? And then yeah, go ahead.
266 00:25:29.500 ⇒ 00:25:31.080 Michael Mallmann: One question, where are you based.
267 00:25:31.080 ⇒ 00:25:32.600 Uttam Kumaran: I’m in Austin, Texas.
268 00:25:32.910 ⇒ 00:25:36.370 Michael Mallmann: Wow. Okay. Very. Republican.
269 00:25:36.741 ⇒ 00:25:41.199 Uttam Kumaran: Well, I thought, Brazil is Republican now, like that’s what I thought.
270 00:25:41.200 ⇒ 00:25:42.559 Michael Mallmann: I’m not in Brazil.
271 00:25:42.560 ⇒ 00:25:43.750 Uttam Kumaran: Oh, really. Okay, okay.
272 00:25:43.750 ⇒ 00:25:45.680 Michael Mallmann: No, I know I’m New York. I live in.
273 00:25:45.680 ⇒ 00:25:54.910 Uttam Kumaran: Oh, great, okay. I was. I thought I thought you were in Brazil. Okay, then, yeah. I mean, I lived in New York for 5 years. I moved here. 2 years ago.
274 00:25:55.260 ⇒ 00:26:00.729 Michael Mallmann: Okay, cool. I’ve been living here since 2,017. My husband. Yeah.
275 00:26:00.730 ⇒ 00:26:01.759 Uttam Kumaran: Where do you live?
276 00:26:02.800 ⇒ 00:26:04.400 Michael Mallmann: Now I like it.
277 00:26:05.150 ⇒ 00:26:06.770 Michael Mallmann: I hated it
278 00:26:07.180 ⇒ 00:26:15.559 Michael Mallmann: so we we used to live in London. I I studied my undergrad there, and I met my husband.
279 00:26:15.810 ⇒ 00:26:17.290 Michael Mallmann: and
280 00:26:17.440 ⇒ 00:26:19.310 Michael Mallmann: and because of the Brexit
281 00:26:19.470 ⇒ 00:26:25.519 Michael Mallmann: he was his bank, he worked for an American company. So they basically brought him to to New York.
282 00:26:25.520 ⇒ 00:26:26.190 Uttam Kumaran: Okay.
283 00:26:26.190 ⇒ 00:26:30.000 Michael Mallmann: And and I hated it like I I hate.
284 00:26:30.000 ⇒ 00:26:31.610 Uttam Kumaran: What did you hate? What did you hate the most.
285 00:26:31.610 ⇒ 00:26:32.780 Michael Mallmann: I hated everything.
286 00:26:33.170 ⇒ 00:26:34.010 Uttam Kumaran: Okay.
287 00:26:34.010 ⇒ 00:26:35.550 Michael Mallmann: So so basically.
288 00:26:35.680 ⇒ 00:26:37.260 Michael Mallmann: have you been to London.
289 00:26:37.390 ⇒ 00:26:38.020 Uttam Kumaran: Yes.
290 00:26:38.540 ⇒ 00:26:43.269 Michael Mallmann: So you know the buildings are shorter. You walk in the streets, and you feel like.
291 00:26:43.270 ⇒ 00:26:44.640 Uttam Kumaran: It looks so nice. There’s.
292 00:26:44.640 ⇒ 00:26:45.100 Michael Mallmann: It doesn’t.
293 00:26:45.100 ⇒ 00:26:46.130 Uttam Kumaran: Bad.
294 00:26:46.300 ⇒ 00:27:04.980 Michael Mallmann: Yeah. And then, and then, when you are here, sometimes you walk the streets, and you don’t even see the sunlight, you know, like it’s it’s different. The people are different, too. Right? Anyway, it’s been years. I’m used to it. Yeah. So I haven’t lived in Brazil for 13 years.
295 00:27:04.980 ⇒ 00:27:06.080 Uttam Kumaran: Okay, okay, okay. But
296 00:27:06.690 ⇒ 00:27:09.190 Uttam Kumaran: like, how did you get involved with the company?
297 00:27:09.390 ⇒ 00:27:11.790 Michael Mallmann: That’s a good question. So
298 00:27:12.060 ⇒ 00:27:13.330 Michael Mallmann: so.
299 00:27:13.340 ⇒ 00:27:19.559 Michael Mallmann: my friend is the chief Operations officer of this company. It’s a
300 00:27:19.810 ⇒ 00:27:21.520 Michael Mallmann: friend from my childhood.
301 00:27:21.860 ⇒ 00:27:23.030 Michael Mallmann: and
302 00:27:23.080 ⇒ 00:27:29.139 Michael Mallmann: and she always mentioned my name to the CEO. Oh, you should meet Michael
303 00:27:29.210 ⇒ 00:27:45.420 Michael Mallmann: like for 2 years. And then the CEO had a a marketing agency with another person, the the owner of this marketing agency called Giuliani, and she was always mentioned. Oh, I have a friend called Michael. You should my meet Michael. He’s so intelligent.
304 00:27:45.500 ⇒ 00:27:52.160 Michael Mallmann: but he didn’t know it was the same Michael. And then one day he figure out that the 2 people
305 00:27:52.320 ⇒ 00:27:55.129 Michael Mallmann: we’re talking about the same Michael and he.
306 00:27:55.340 ⇒ 00:27:57.830 Michael Mallmann: He had an issue with his company.
307 00:27:58.785 ⇒ 00:28:00.390 Michael Mallmann: And I have.
308 00:28:00.420 ⇒ 00:28:04.849 Michael Mallmann: I founded many companies, and and I still own companies, you know.
309 00:28:04.910 ⇒ 00:28:12.280 Michael Mallmann: and and I work for him as a consultant for 2 years now, so he called me. He’s we set up a meeting.
310 00:28:12.330 ⇒ 00:28:14.990 Michael Mallmann: and at the end of the meeting. He was like
311 00:28:15.720 ⇒ 00:28:18.099 Michael Mallmann: he he was clear, like he said.
312 00:28:18.420 ⇒ 00:28:20.269 Michael Mallmann: something like Luke.
313 00:28:20.440 ⇒ 00:28:21.940 Michael Mallmann: I’ve been hearing
314 00:28:22.270 ⇒ 00:28:24.750 Michael Mallmann: about you for like 2 years.
315 00:28:25.120 ⇒ 00:28:28.989 Michael Mallmann: I had the idea that you would be like impressive.
316 00:28:29.140 ⇒ 00:28:32.340 Michael Mallmann: But fuck like you broke like.
317 00:28:33.486 ⇒ 00:28:35.780 Uttam Kumaran: You expect.
318 00:28:35.780 ⇒ 00:28:45.152 Michael Mallmann: Yes, and I was like, Oh, thank you. And then he asked for help for his company, and I was like, look, and I need to be very honest with you. I don’t have time.
319 00:28:45.470 ⇒ 00:28:53.969 Michael Mallmann: and he was like, just help me with this project like not many hours a week, and that’s how I started. And he, he bought my soul.
320 00:28:55.730 ⇒ 00:28:57.459 Michael Mallmann: basically. So yeah.
321 00:28:57.720 ⇒ 00:29:01.060 Michael Mallmann: so I work directly with the Coo and the CEO.
322 00:29:01.310 ⇒ 00:29:03.109 Michael Mallmann: And since then.
323 00:29:03.760 ⇒ 00:29:09.080 Michael Mallmann: so I work. I started to review their finances. But they’re
324 00:29:09.640 ⇒ 00:29:19.310 Michael Mallmann: systems, the erp. Everything that they used to were so broken like there was no single source of truth, like everything, was so fucked up.
325 00:29:19.310 ⇒ 00:29:20.050 Uttam Kumaran: Yes.
326 00:29:20.260 ⇒ 00:29:29.930 Michael Mallmann: That I said like it’s impossible to manage this company like. How the fuck did you open 5 practices and and got this.
327 00:29:29.930 ⇒ 00:29:37.979 Uttam Kumaran: It’s just like they. They just it works like, I’m not that way because I’m an engineer. So you look at my company. There’s processes operating procedures.
328 00:29:37.980 ⇒ 00:29:39.349 Michael Mallmann: Yes, everything needs to be working.
329 00:29:39.350 ⇒ 00:29:42.550 Uttam Kumaran: You also need someone who’s like a risk taker. You know, you need someone.
330 00:29:42.550 ⇒ 00:29:49.560 Michael Mallmann: Oh, totally totally yeah. And and then I presented him with this erp
331 00:29:49.620 ⇒ 00:29:51.850 Michael Mallmann: because I knew the team behind it.
332 00:29:52.301 ⇒ 00:29:57.520 Michael Mallmann: I had implemented in other companies totally different industries, but they customize everything.
333 00:29:58.100 ⇒ 00:30:09.309 Michael Mallmann: and I told him, look, the budget will be high because we need to build the whole healthcare inside, but but it will work exactly as we want, you know, like we’re gonna
334 00:30:09.580 ⇒ 00:30:20.800 Michael Mallmann: embed all the business rules inside, so we won’t be counting if the team is doing the right thing or not, because we will teach the the Erp to know if it’s the right thing or not, you know.
335 00:30:20.870 ⇒ 00:30:23.350 Michael Mallmann: and that’s it. So it’s been
336 00:30:23.560 ⇒ 00:30:25.289 Michael Mallmann: 2 crazy years.
337 00:30:25.290 ⇒ 00:30:26.300 Uttam Kumaran: Awesome.
338 00:30:26.300 ⇒ 00:30:26.650 Michael Mallmann: Yeah.
339 00:30:26.650 ⇒ 00:30:39.170 Uttam Kumaran: They’re lucky to have you. And yeah, I’m I I miss New York a lot. I also felt the same way when I moved there. I grew up in California, never lived in the city. I went to school in the East coast, and then lived in.
340 00:30:39.620 ⇒ 00:30:44.949 Uttam Kumaran: And I felt like my life was a movie every day like I lived in the East Village.
341 00:30:45.010 ⇒ 00:30:50.629 Uttam Kumaran: and then I my office was in chat I worked for we work. If you’re familiar with the
342 00:30:52.736 ⇒ 00:30:53.630 Uttam Kumaran: Coworking company.
343 00:30:53.950 ⇒ 00:30:58.825 Michael Mallmann: I see we work, we work. Oh, of course I know, of course.
344 00:30:59.200 ⇒ 00:31:09.059 Uttam Kumaran: So I work. That was my 1st job out of college. I worked for them the data team there and then. Yeah, I lived in New York and I worked in Soho. I worked in Chelsea. It was crazy.
345 00:31:09.685 ⇒ 00:31:10.250 Uttam Kumaran: But.
346 00:31:10.250 ⇒ 00:31:21.159 Michael Mallmann: So. So the 1st place, we lived that our most sentimental was very close to the east village. It was in the 5th Avenue with the 21st Street.
347 00:31:22.520 ⇒ 00:31:26.119 Michael Mallmann: and they they call it iron, a flat iron district, because
348 00:31:26.820 ⇒ 00:31:32.000 Michael Mallmann: to the flat iron right? I almost went mad in that place.
349 00:31:32.060 ⇒ 00:31:34.279 Michael Mallmann: It’s so noisy, I think.
350 00:31:34.280 ⇒ 00:31:37.590 Uttam Kumaran: But I mean, yeah. And there’s like 5 streets that like, go.
351 00:31:37.590 ⇒ 00:31:44.970 Michael Mallmann: Yes, exactly, and and we lived in a very nice building like it. We were the 1st people to move into the apartment.
352 00:31:45.470 ⇒ 00:31:55.690 Michael Mallmann: and it was in the 15th floor, but there were 2 nightclubs in that block. So from Thursday on we we needed like earplugs to sleep like
353 00:31:56.210 ⇒ 00:31:59.770 Michael Mallmann: very bad. Then on the second year after one year
354 00:32:00.207 ⇒ 00:32:04.930 Michael Mallmann: we decided to move to Long Island City, which is just outside of Manhattan.
355 00:32:05.890 ⇒ 00:32:15.160 Michael Mallmann: Wow! Best change ever we have the the Manhattan view, and very high up building. Yes.
356 00:32:15.160 ⇒ 00:32:15.850 Uttam Kumaran: Oh, okay. Okay.
357 00:32:15.850 ⇒ 00:32:21.799 Michael Mallmann: So I can see Manhattan. I can see the United Nations building the Empire State. Everything’s beautiful.
358 00:32:22.060 ⇒ 00:32:33.109 Michael Mallmann: Yes, price. We paid for a 2, you know. Prices here are crazy. Right? So now for a 2 bedroom, 2 bathroom apartment
359 00:32:33.790 ⇒ 00:32:39.869 Michael Mallmann: quite big. It’s very spacious. We pay the same thing as we were paying for a studio in Manhattan.
360 00:32:39.870 ⇒ 00:32:45.420 Uttam Kumaran: I mean, you’re a studio in flat iron like you’re in the middle of it all. Yeah, it’s.
361 00:32:45.420 ⇒ 00:32:46.690 Michael Mallmann: That’s 5 k.
362 00:32:46.850 ⇒ 00:32:47.380 Uttam Kumaran: Yeah.
363 00:32:47.380 ⇒ 00:32:48.180 Michael Mallmann: Yeah.
364 00:32:48.180 ⇒ 00:32:52.860 Uttam Kumaran: I mean, it’s that’s also why I moved to Austin. I have a house for 4 K.
365 00:32:52.860 ⇒ 00:32:54.489 Michael Mallmann: I see. Wow!
366 00:32:55.750 ⇒ 00:32:56.270 Uttam Kumaran: You know.
367 00:32:56.270 ⇒ 00:33:02.339 Michael Mallmann: I have a I have my cousin living in in Florida, but just to make it quick. She has a
368 00:33:02.900 ⇒ 00:33:04.730 Michael Mallmann: 8 years old, son.
369 00:33:04.910 ⇒ 00:33:14.249 Michael Mallmann: and they came to visit us once, and when he opened the door of our apartment he said, Whoa! That is more than my bedroom.
370 00:33:17.840 ⇒ 00:33:21.170 Michael Mallmann: you know, because they use Florida. You know big houses.
371 00:33:21.170 ⇒ 00:33:35.899 Uttam Kumaran: Oh, my God, same in Texas. Everything is so big like I’m not even used to it. It’s like people just want big amount of space. But I’m just New York. I come to New York for work so often. A lot of my connections and work still comes from New York. So I miss that.
372 00:33:35.900 ⇒ 00:33:36.490 Michael Mallmann: That’s cool.
373 00:33:36.830 ⇒ 00:33:37.420 Uttam Kumaran: Yeah, yeah.
374 00:33:37.420 ⇒ 00:33:39.430 Michael Mallmann: That’s cool. Well, we’ve done.
375 00:33:39.710 ⇒ 00:33:45.189 Michael Mallmann: It was a pleasure talking to you. You’re very, very nice. I really liked you. Sorry for talking a little.
376 00:33:45.190 ⇒ 00:33:59.490 Uttam Kumaran: No, I mean, I’m also the same way. I I I really appreciate the time, you know, hopefully, we’re able to to help you all out, but I will. I’ll just send you something over, and you know I appreciate you giving us all the information we’ll put together a proposal, and then let’s go from there.
377 00:33:59.690 ⇒ 00:34:02.440 Michael Mallmann: That’s perfect. Thank you so much. Have a good one.
378 00:34:02.660 ⇒ 00:34:03.180 Uttam Kumaran: Great Day.
379 00:34:03.180 ⇒ 00:34:04.410 Michael Mallmann: Bye-bye, bye-bye.