Meeting Title: Uttam <> Hector: Follow Up Date: 2025-06-04 Meeting participants: Hector Torres, Uttam Kumaran
WEBVTT
1 00:05:54.670 ⇒ 00:05:55.800 Uttam Kumaran: Hey!
2 00:05:56.560 ⇒ 00:05:57.809 Hector Torres: Good Tom, how you doing, man?
3 00:05:57.810 ⇒ 00:05:59.560 Uttam Kumaran: Good. How are you? How’s the week?
4 00:05:59.740 ⇒ 00:06:03.870 Uttam Kumaran: Good. Sorry about the last minute? Mutual nda, but hey, it’s it’s.
5 00:06:03.870 ⇒ 00:06:05.340 Hector Torres: It’s a mutual mda.
6 00:06:05.610 ⇒ 00:06:06.403 Uttam Kumaran: No problem.
7 00:06:06.800 ⇒ 00:06:10.300 Hector Torres: I was looking at my calendar. I’m like, Oh, crap! I forgot to do that.
8 00:06:10.300 ⇒ 00:06:11.452 Uttam Kumaran: No problem at all.
9 00:06:12.044 ⇒ 00:06:15.085 Hector Torres: So yeah, man, just give you a quick heads up.
10 00:06:15.937 ⇒ 00:06:28.429 Hector Torres: master Service agreement is is in play, and it’s it’s it’s I’m hoping that we can get through that this week, so we can. So the so Lone Star can. And and and
11 00:06:28.700 ⇒ 00:06:51.060 Hector Torres: we collectively has. There’s a lot of. There’s lots of. There’s lots of moving parts and just so, you know, let me just share with you a quick timeline so they’re looking to do a launch on July 1st of care management. But you know what. Maybe I should back up a little bit. I’m trying to remember, because I’ve been sharing a lot of stuff with different people. Have I shared our slide deck with you?
12 00:06:51.350 ⇒ 00:06:55.990 Uttam Kumaran: Yep, you, we just you just shared it with me, over, video, yeah, last time.
13 00:06:56.780 ⇒ 00:06:58.230 Hector Torres: Oh, okay.
14 00:06:58.230 ⇒ 00:06:59.550 Uttam Kumaran: I have a copy of it.
15 00:06:59.800 ⇒ 00:07:02.156 Hector Torres: I’m happy to shoot it to you.
16 00:07:05.160 ⇒ 00:07:08.940 Hector Torres: And I’ll also run through. Did I share our mirror board with you?
17 00:07:09.780 ⇒ 00:07:11.120 Uttam Kumaran: No, that would be great.
18 00:07:11.490 ⇒ 00:07:12.730 Hector Torres: Okay, I’ll do that.
19 00:07:13.920 ⇒ 00:07:15.809 Hector Torres: Let me share my screen real quick.
20 00:07:17.960 ⇒ 00:07:22.779 Hector Torres: yeah, you know what. And we haven’t talked in a bit. So let me just kind of do a recap with you. Okay.
21 00:07:23.080 ⇒ 00:07:23.660 Uttam Kumaran: Okay.
22 00:07:24.929 ⇒ 00:07:25.839 Hector Torres: So
23 00:07:26.710 ⇒ 00:07:34.015 Hector Torres: I got the like a great compliment. The Vice President of Population health for this federally qualified Health Center.
24 00:07:34.820 ⇒ 00:07:39.219 Hector Torres: Said he, ran through my slide deck and said, Man, that
25 00:07:39.640 ⇒ 00:07:50.740 Hector Torres: the content in your slide deck aligns very well with my big vision of what they want to accomplish, and so what they want to accomplish is quite a bit
26 00:07:51.570 ⇒ 00:08:01.492 Hector Torres: The the Master Service agreement that I have in front of them is to do all of these things not upfront, but eventually over time, we’ll cover
27 00:08:02.110 ⇒ 00:08:13.870 Hector Torres: all of this. So we have an agreement, and the initial phase, the the initial. The initial engagement is to do some consulting, you know. Do some discovery operational assessment of the organization
28 00:08:14.460 ⇒ 00:08:19.730 Hector Torres: with the, with the what, with the main focus of understanding, where they are with care, management.
29 00:08:19.890 ⇒ 00:08:32.154 Hector Torres: And so what I mean by care management, so care, management can be mean many, many different things to different people. For us. It’s remote, patient, monitoring, chronic care management, that’s what that’s their top priority out of the gate is getting those
30 00:08:32.659 ⇒ 00:08:45.790 Hector Torres: in a better state. They have a. They have a vendor in place now that they’re just not happy with, and so we’ll be taking over what they’re doing in the Rpm remote, patient, monitoring and chronic care management space along the lines of
31 00:08:46.336 ⇒ 00:09:03.759 Hector Torres: sending devices out to patients. Blood pressure monitors, weight scales, oximeters, glucose monitors. There’s about 300 devices, we could potentially send the patients based on our agreement and partnership with smart meter. Well, so we we leverage their
32 00:09:03.960 ⇒ 00:09:19.889 Hector Torres: distribution system inventory blah blah, and we also from time to time depending on the engagement, the customer, you might leverage their their care management platform. So data from the devices go to their cloud, and then we just use it to do reports and billing
33 00:09:20.638 ⇒ 00:09:37.389 Hector Torres: for this engagement. Since the Fqhc. Is the Lone Star Circle of care. They are larger, more robust. So we’re actually gonna leverage our other partner chronic care, IQ for all of the all of that data collection reporting and billing.
34 00:09:38.330 ⇒ 00:09:39.410 Hector Torres: So
35 00:09:40.450 ⇒ 00:09:49.199 Hector Torres: this month we’re looking to create the scope of work of what care management will look like for us for a 12 year, a 12 month engagement.
36 00:09:50.380 ⇒ 00:10:05.920 Hector Torres: Once we get that to a somewhat steady state. We’ll then start talking about web, social media, mobile and contact center. And in a minute I should switch over to the A visual to cover this as well.
37 00:10:06.573 ⇒ 00:10:08.190 Hector Torres: And as you can imagine.
38 00:10:08.970 ⇒ 00:10:20.072 Hector Torres: all of those things are different data sources that we need to somehow organize and compile and harmonize, to provide ultimately, a health data dashboard,
39 00:10:20.740 ⇒ 00:10:28.089 Hector Torres: ideally, AI enabled. So we can do more things efficiently for the organization such that they understand the individual better.
40 00:10:28.760 ⇒ 00:10:35.189 Hector Torres: the population health that they manage, which is about a hundred 1,000 people over a year.
41 00:10:36.095 ⇒ 00:10:52.300 Hector Torres: And we’ll be. We’ll we’re hoping to provide them better insights so they can make better decisions around risk stratification with the goal of creating healthy, sustainable communities. That’s our vision and mission for us, and we align super well with them.
42 00:10:53.264 ⇒ 00:10:55.720 Hector Torres: So AI has a
43 00:10:55.960 ⇒ 00:11:04.870 Hector Torres: has a key role to play relative to the long term strategic growth roadmap for them. Right?
44 00:11:05.380 ⇒ 00:11:15.630 Hector Torres: So let me go to the mural board real quick. That’ll give a better understanding of all of this, and then, you know you’re welcome to pepper me with some questions. So
45 00:11:18.090 ⇒ 00:11:21.510 Hector Torres: in some in in some semblance, I’ve done
46 00:11:21.860 ⇒ 00:11:26.379 Hector Torres: bits and pieces of this bits and pieces of this throughout my health tech career, so to speak.
47 00:11:26.961 ⇒ 00:11:33.820 Hector Torres: We’re starting for for Lone Star circular care. We’re starting here with chronic care or with care. Management.
48 00:11:34.763 ⇒ 00:11:39.480 Hector Torres: Like, I said. Chronic Iqs are vendor partner
49 00:11:40.350 ⇒ 00:11:50.850 Hector Torres: to do all data collection from the devices into their platform. So we can do reporting and billing smart meters. We’re just using them to purchase and distribute devices.
50 00:11:51.110 ⇒ 00:11:59.150 Hector Torres: So as you can imagine, that data is gonna live. It technically lives in their own space. But we wanna pull data into our
51 00:11:59.480 ⇒ 00:12:03.320 Hector Torres: centralized data house data warehouse data lake.
52 00:12:03.540 ⇒ 00:12:08.467 Hector Torres: Another key facet of this project is actually health. Next,
53 00:12:09.720 ⇒ 00:12:28.270 Hector Torres: we have. So we have agreements with chronic care. IQ. Already smart meter, and then health. Next is a new partner of ours. And there’s a lot of press releases that are about to go out. We’re just waiting for us to sign with Lone Star. But health. Next is a medical nutrition therapy mobile app as a device.
54 00:12:28.610 ⇒ 00:12:36.170 Hector Torres: Right? So technically, they’re standalone. They don’t live in the chronic care. Smart meter world yet. That’s a whole nother play
55 00:12:36.420 ⇒ 00:12:37.710 Hector Torres: long term thing.
56 00:12:38.590 ⇒ 00:12:45.910 Hector Torres: So health next has its own data that we’re gonna have to capture. As well.
57 00:12:46.130 ⇒ 00:12:47.550 Hector Torres: North lake
58 00:12:47.680 ⇒ 00:13:04.399 Hector Torres: analytics is our billing partner. Part of the this month’s engagement is to understand. Okay, care management. We’re gonna do one through 10 or one through 20. And then of all that activity, there’s all this data that’s going to be collected. The reporting that’s going to be collected. Well, how are you guys doing billing today?
59 00:13:04.680 ⇒ 00:13:20.970 Hector Torres: What’s the gaps? What are the inefficiencies? How can we leverage partners like North Lake to help us with billing and reporting. They have their own proprietary AI system to do all the billing, and that’s all they do. All they do all day long is focus on billing.
60 00:13:21.090 ⇒ 00:13:35.649 Hector Torres: They got a lot of expertise in that space claims and billing not a space. I want to be in. That’s cool. That’s why we partnered with them. We want to do other things, and it’s a great symbiotic relationship. And similar similarly, with health. Next, they don’t have their own
61 00:13:35.750 ⇒ 00:13:39.600 Hector Torres: billing. So I’m I’m connecting those dots together.
62 00:13:39.790 ⇒ 00:13:48.020 Hector Torres: and that’s potentially maybe where y’all can support us. There’s a i think there’s a lot of ways y’all can support us. Let me just kind of keep running through this real quick.
63 00:13:48.988 ⇒ 00:13:58.079 Hector Torres: Athena. Health is their ehr emr of choice and those Emre ehr platforms.
64 00:13:59.480 ⇒ 00:14:04.750 Hector Torres: They do a good job to help manage healthcare organizations, but they don’t do everything. Well.
65 00:14:04.980 ⇒ 00:14:12.130 Hector Torres: there’s gaps. So there’s oper and gaps mean opportunity for us, and then internally, for the Fqhc. They have their own
66 00:14:12.752 ⇒ 00:14:30.929 Hector Torres: business intelligence analytics. They’re a Microsoft shop, so as you can imagine they don’t have any AI, and they only know what they know and don’t know what they don’t know. So there’s going to be some gaps and needs there as well to be more efficient with data capture and analyzing that data. So I covered the clinical data
67 00:14:31.340 ⇒ 00:14:35.710 Hector Torres: structured data right? The other piece that’s exciting for them.
68 00:14:36.020 ⇒ 00:14:43.470 Hector Torres: Specifically, the Vp of population health is the non-clinical data, the unstructured data which can be encapsulated
69 00:14:43.650 ⇒ 00:15:04.819 Hector Torres: as social determinants of health. Right? So that’s data that comes through web social media, as you can imagine. Just with those interactions I can get a different understanding of who Tom is relative to Hector relative to Mary Jane or Whatnot. And then there’s a contact center. When you make phone call. Whenever you have to make a phone call to your physician.
70 00:15:05.660 ⇒ 00:15:08.310 Hector Torres: appointment, scheduling person, whatever.
71 00:15:08.430 ⇒ 00:15:09.350 Hector Torres: There’s that
72 00:15:09.470 ⇒ 00:15:17.198 Hector Torres: data from the natural language processing that we can capture as well, and then mobile health app data. As well, right?
73 00:15:18.340 ⇒ 00:15:32.780 Hector Torres: which we’re gonna we’re looking for a good solid ios and android mobile app shop. Because, chronic care, IQ has their own mobile app. That’s patient customer facing health. Next, has their own
74 00:15:32.980 ⇒ 00:15:40.010 Hector Torres: customer. Doesn’t want 3, 4 different apps. So we’re actually gonna be working on encapsulating everything into one app for the customer.
75 00:15:40.150 ⇒ 00:15:43.750 Hector Torres: Okay, so that’s it. In a nutshell of
76 00:15:44.400 ⇒ 00:15:49.780 Hector Torres: everything we’re trying to accomplish, which. It’s very doable, because I’ve done.
77 00:15:49.980 ⇒ 00:16:00.540 Hector Torres: I’ve done 2 thirds of this over my over the time of my, you know career in different roles.
78 00:16:01.560 ⇒ 00:16:02.670 Hector Torres: I’ll pause.
79 00:16:03.780 ⇒ 00:16:25.770 Uttam Kumaran: Yeah. So I guess. Give me a sense of like your you mentioned, you know, potentially bringing on a couple of partners, and then to give you a sense of like what we excel at. And I’ll be frank with the stuff that we’re we don’t really do so. One. We are back my background. And the company’s sort of DNA is all in data. So anything related to data, engineering data integration
80 00:16:25.890 ⇒ 00:16:41.370 Uttam Kumaran: data modeling. You know, reporting and analytics. Whether that’s you know, all this stuff kind of stuff we’ve typically done is on cloud. But just like moving data via any etl tool into a data warehouse, modeling it and creating insights.
81 00:16:41.850 ⇒ 00:16:48.150 Uttam Kumaran: The second piece that we do typically is making that available for AI agents or agentic workflows
82 00:16:48.598 ⇒ 00:17:11.529 Uttam Kumaran: so ability to take that data, have AI have some reasoning over it and then make a jurisdiction. Or you know, basically making that available as context for for AI we do a lot of AI workflow work as well, which is just like, take a document, summarize it, take some actions. But those are the 2 areas that our company really really excels in and where we have some.
83 00:17:11.770 ⇒ 00:17:23.696 Uttam Kumaran: you know, great wins and case studies that I can share. I guess. Tell me, like, how, if that one, if that sort of like fits the kind of partner that you’re you’re looking for, and then
84 00:17:24.180 ⇒ 00:17:27.279 Uttam Kumaran: yeah, maybe we can start there and just sort of talk through that.
85 00:17:27.480 ⇒ 00:17:34.009 Hector Torres: Yeah, no, I think so. And actually, let me share some other insight. So what are we’re collecting all this data.
86 00:17:35.090 ⇒ 00:17:39.749 Hector Torres: what do we really want to do with it? Or how do we want to leverage? AI. Well, what we want to do
87 00:17:39.950 ⇒ 00:17:46.149 Hector Torres: is capture that data to do some better care Gap reviews
88 00:17:46.630 ⇒ 00:17:55.400 Hector Torres: better, better medical record reviews all to support care, management. Better all to support the individual patient. Better right?
89 00:17:55.917 ⇒ 00:18:10.080 Hector Torres: At the end of the day. That’s that’s our. That’s the intellectual property that we’re looking to develop with some of the some of these partners. And now I think about it, having you on the call. The way I see my strategy playing out is, I may just pit databricks
90 00:18:10.460 ⇒ 00:18:14.989 Hector Torres: with Snowflake and say, here’s a small limited scope, Poc.
91 00:18:15.240 ⇒ 00:18:15.640 Uttam Kumaran: Yeah.
92 00:18:15.640 ⇒ 00:18:22.579 Hector Torres: Minimum valuable product we want you to work on and focus on for us in this space. Care Gap review, Care gap, Review.
93 00:18:22.870 ⇒ 00:18:31.050 Hector Torres: and see how and where they land with the product that they develop, that we might take on. And so
94 00:18:31.310 ⇒ 00:18:36.909 Hector Torres: I think we’ll need a partner to help us kind of evaluate that one. Help us like. Stand up that.
95 00:18:37.400 ⇒ 00:18:37.730 Uttam Kumaran: Yeah.
96 00:18:37.730 ⇒ 00:18:46.348 Hector Torres: Competitive analysis for lack of a better description, and and see how we might can leverage them moving, moving forward. And there’s
97 00:18:48.180 ⇒ 00:18:56.200 Hector Torres: there’s a. So the data breaks, introduced me to one of their partners, and then there’s another partner that I reached out to
98 00:18:56.811 ⇒ 00:19:03.159 Hector Torres: and you know they’re all interested in doing some kind of health. AI thing which is cool.
99 00:19:03.160 ⇒ 00:19:06.340 Hector Torres: Yeah, I think graphable, graphical, capable.
100 00:19:06.750 ⇒ 00:19:17.419 Uttam Kumaran: Yeah, so anything on like procurement, support and sort of procurement. Consulting is a big thing of what we do. You know the part of the reason I think a lot of our clients like working with us is we’re not just like
101 00:19:17.790 ⇒ 00:19:28.550 Uttam Kumaran: we’re not just like a dev shop. We actually don’t do any work that’s like super staff augmentation, all of our stuff where we sort of partner with our clients, meaning.
102 00:19:28.660 ⇒ 00:19:45.509 Uttam Kumaran: you know, typically there’s a web of solutions that they, their web of software that they’re like. There’s so much stuff that we need to connect together or 2. It’s like, Hey, I don’t have sort of a super senior data person who I can trust to sort of go into these conversations. But we need that right. And so that’s where.
103 00:19:45.690 ⇒ 00:20:03.440 Uttam Kumaran: for example, we come in and do a lot of like, yeah, like, basically pitting vendors against each other, understanding like, what’s the scalability cost budget like, why or why not? Basically like trying to skip past the jargon and actually give you like a fair understanding of like, what
104 00:20:03.620 ⇒ 00:20:33.279 Uttam Kumaran: you need to do, and why, the other thing is very strategic. Like, look, if you’re embarking on this, you want to go with a vendor that’s gonna also help you maybe make introductions to clients, or do case studies or co-marketing like there’s a lot of advantages that you guys can take care. Take advantage of as well, so that’s that’s, you know, a lot of the work that we’ve done. So I could see us really being helpful there, you know, I would love to take a crack at even doing the implementation, whether it’s data bricks or snowflake work, you know. But of course, at minimum, I think
105 00:20:33.630 ⇒ 00:20:58.829 Uttam Kumaran: with with just my time. I’m I’m happy to support any of those sort of initiatives on like an hourly basis. And then, if it gets to a point where we’re also doing development work. You know, we have a full stack data team and we have. We do a ton of AI work as well, so I don’t know. I feel like we’re. I try to be pretty honest with, like what we work on and like what we’re seeing on the on the field.
106 00:20:59.410 ⇒ 00:21:06.699 Uttam Kumaran: but also again, like, I think it’s nice, because I was on the I was inside a company making these decisions. So I know, sort of like what
107 00:21:06.950 ⇒ 00:21:16.308 Uttam Kumaran: the sales people from their end they’re gonna do. And it’s nice to have like another person on your side that’s that can assist with that so totally hear you.
108 00:21:16.800 ⇒ 00:21:21.350 Hector Torres: Cool man. Well, I just sent you the slide deck so you can, you know.
109 00:21:21.890 ⇒ 00:21:28.539 Hector Torres: chew on that, and that can help inform some of our next conversations. So just to recap real quick
110 00:21:28.660 ⇒ 00:21:43.550 Hector Torres: databricks, snowflake graphable, sunny data, new vista are pretty much the 5 tech partners, potential partners that
111 00:21:43.690 ⇒ 00:21:48.609 Hector Torres: we’re working. We could work on different projects for for
112 00:21:49.094 ⇒ 00:21:55.820 Hector Torres: Lone Star. I’m happy to see where you fit into that might fit in just like
113 00:21:56.170 ⇒ 00:22:05.460 Hector Torres: across the board with a specific initiative. Or who knows? Maybe we can. You guys, we can leverage you guys to help us assess them. And seeing who who really does? What?
114 00:22:05.910 ⇒ 00:22:06.740 Hector Torres: What are the.
115 00:22:06.740 ⇒ 00:22:18.629 Uttam Kumaran: That’s honestly even short term. That’s probably where we’re very valuable. I mean, you’re talking to a lot of vendors you’re talking about the vendors and the people that implement them. Both of those folks are in bed with each other.
116 00:22:19.019 ⇒ 00:22:33.039 Uttam Kumaran: And just like, when I reviewed the sunny data thing, I was like, this is sort of overkill. That’s the sort of stuff that I think you could just have access to. I think, you know, for this, maybe some sort of monthly retainer model works best where you just have like
117 00:22:33.240 ⇒ 00:22:41.419 Uttam Kumaran: hours, where I can support either to come on those meetings to brainstorm with you to come onto client meetings and talk through data stuff.
118 00:22:41.882 ⇒ 00:22:53.500 Uttam Kumaran: But also just have access to me because we’re doing a ton of stuff on the ground and then I can let you know, like sort of what our pricing is to do implementation. And you can consider us for that as well. You know, across your other options?
119 00:22:55.860 ⇒ 00:23:01.810 Uttam Kumaran: yeah. And I’m also here in town. So if you’re doing local stuff here, like events, or whatever like, we should totally do stuff
120 00:23:02.010 ⇒ 00:23:04.089 Uttam Kumaran: and drum up some business. So.
121 00:23:06.290 ⇒ 00:23:10.042 Hector Torres: Yeah, no, no, for sure. Let’s do this.
122 00:23:11.380 ⇒ 00:23:32.188 Hector Torres: I think you shared your slide deck with me. Maybe. I’m I’m actually doing quite a few slide deck reviews from our partners this weekend next week. So if you can shoot me your most updated slide deck and let’s maybe also 0 in on. And if we need to do like another 30 min session with you, and maybe one of your some of your team members that’d be cool.
123 00:23:33.540 ⇒ 00:23:41.889 Hector Torres: I kind of see on the same plane with graphable. Correct me if I’m wrong, you said, so. You guys have done. Have you guys done databricks work and or snowflake work.
124 00:23:42.350 ⇒ 00:23:47.080 Uttam Kumaran: Yeah, we do a lot of stuff on Snowflake, on databricks, on bigquery.
125 00:23:47.240 ⇒ 00:23:52.270 Uttam Kumaran: on azure. So we worked with all the core data, lake data warehouse vendors.
126 00:23:52.774 ⇒ 00:24:04.615 Uttam Kumaran: On top of that we’ve done for each of those their AI offerings. I think Snowflake, probably the weakest azure databricks have, you know a little bit better. AI offering
127 00:24:05.140 ⇒ 00:24:05.740 Uttam Kumaran: but the a.
128 00:24:05.740 ⇒ 00:24:06.110 Hector Torres: 2 weeks.
129 00:24:06.110 ⇒ 00:24:13.510 Uttam Kumaran: If there’s like we, the Snowflake AI offering isn’t as good as databricks and azure
130 00:24:14.290 ⇒ 00:24:15.120 Hector Torres: That’s what I’m hearing.
131 00:24:15.120 ⇒ 00:24:18.969 Uttam Kumaran: But we’ve also done data aws, like data, lake
132 00:24:19.220 ⇒ 00:24:26.580 Uttam Kumaran: sort of AI work. We just like tried everything and cause I do. We do a lot of AI in the inside the company as well. So I’ve tried a lot of the tooling
133 00:24:27.950 ⇒ 00:24:45.309 Uttam Kumaran: But again, it sort of depends on the types of workflows that you’re talking about. But we’ve worked with most of those data platform work and a lot, I would say a lot of our skill set is on the insights piece. So actually, like building up the analytics. And then we’ve done some customer facing analytics work. But really a lot of our stuff is like
134 00:24:45.460 ⇒ 00:24:53.280 Uttam Kumaran: modeling data, making it available for either reporting or for applications to pull from.
135 00:24:53.480 ⇒ 00:25:00.420 Uttam Kumaran: You know that that actually provides insights. Whether it’s you providing insights to your client whether it’s within the application.
136 00:25:02.210 ⇒ 00:25:04.329 Uttam Kumaran: Yeah, that’s that’s where we’ve landed.
137 00:25:06.450 ⇒ 00:25:11.571 Hector Torres: Okay. Thanks for sharing that that bit of background.
138 00:25:13.750 ⇒ 00:25:20.519 Hector Torres: yeah. Right now is the calm before the storm, so to speak. So I’m trying to get in as much assessment and analysis as possible, and that’s.
139 00:25:20.520 ⇒ 00:25:20.860 Uttam Kumaran: Yeah.
140 00:25:20.860 ⇒ 00:25:25.338 Hector Torres: Vendors, but planning and playbook development.
141 00:25:26.310 ⇒ 00:25:49.629 Hector Torres: so yeah, there’s quite a bit. And you know it’ll all evolve over time. So as I mentioned some other folks, you know. Let’s get some more time on the calendar, maybe for Friday or early next week. You know. Shoot me a slide deck. Let’s review that a little bit more. And and you know, just yeah. Take take your time to review the deck that I sent you that should inform you about potentially
142 00:25:50.310 ⇒ 00:25:52.200 Hector Torres: one or 2 or 3 team members. Do you think
143 00:25:52.200 ⇒ 00:25:53.509 Hector Torres: you may bring to the table
144 00:25:53.520 ⇒ 00:25:54.810 Hector Torres: able to make some of this happen?
145 00:25:55.376 ⇒ 00:25:55.943 Uttam Kumaran: Sure.
146 00:25:56.510 ⇒ 00:25:58.318 Hector Torres: Okay? That’s what
147 00:25:59.650 ⇒ 00:26:04.460 Hector Torres: Oh, graphable. There’s I mean, with our team yesterday. So they have
148 00:26:05.110 ⇒ 00:26:09.530 Hector Torres: bit of a healthcare experience. They are databricks, databricks partner.
149 00:26:09.530 ⇒ 00:26:10.540 Uttam Kumaran: But yeah.
150 00:26:10.540 ⇒ 00:26:11.519 Hector Torres: Kind of agnostic, so.
151 00:26:11.520 ⇒ 00:26:12.020 Uttam Kumaran: How come?
152 00:26:12.020 ⇒ 00:26:15.624 Hector Torres: Glad that you’re little agnostic as well. So
153 00:26:16.080 ⇒ 00:26:17.810 Uttam Kumaran: 800 degree, or 2.
154 00:26:17.810 ⇒ 00:26:22.109 Hector Torres: Keep the conversation going, and you know, let me know when you can reconnect, and we’ll go from there.
155 00:26:22.310 ⇒ 00:26:26.728 Uttam Kumaran: Okay. Okay, definitely. Alright, alright, thank you so much.
156 00:26:27.220 ⇒ 00:26:28.240 Hector Torres: Likewise. Man talk soon.
157 00:26:28.240 ⇒ 00:26:29.309 Uttam Kumaran: Talk soon bye.