Meeting Title: Data Ingestion Issue Resolution Sync Date: 2026-01-07 Meeting participants: Zoran Selinger, Awaish Kumar, Ashwini Sharma, Demilade Agboola
WEBVTT
1 00:00:43.240 ⇒ 00:00:48.669 Awaish Kumar: Yeah, I… I wanted… Zora, or Damelare, and…
2 00:00:48.920 ⇒ 00:00:50.020 Zoran Selinger: Oh yeah, so…
3 00:00:50.230 ⇒ 00:00:51.010 Awaish Kumar: Nope.
4 00:00:51.210 ⇒ 00:00:52.860 Zoran Selinger: The Milan, Israel, yeah.
5 00:00:53.030 ⇒ 00:00:54.850 Zoran Selinger: Does he have the link now?
6 00:00:57.930 ⇒ 00:01:01.090 Awaish Kumar: Okay, I’m sending him the link as well.
7 00:01:01.910 ⇒ 00:01:12.949 Awaish Kumar: Yeah, send the link in the channel so that… Demi, Ashwini, and casey needs to join.
8 00:01:51.390 ⇒ 00:01:54.390 Zoran Selinger: She’s replying, let’s see if he’s available.
9 00:02:08.590 ⇒ 00:02:09.940 Awaish Kumar: Hello?
10 00:02:11.500 ⇒ 00:02:22.709 Awaish Kumar: So, Demilade, you worked on this uplift task ingestion and the modeling. I just wanted to know, like, we are bringing in data from uplift’s platform, right?
11 00:02:23.150 ⇒ 00:02:24.160 Demilade Agboola: Yes, we are.
12 00:02:25.720 ⇒ 00:02:31.930 Awaish Kumar: So, Ashwini, like, or Zoram, why… Isn’t that…
13 00:02:32.040 ⇒ 00:02:36.420 Awaish Kumar: useful, or why isn’t that working? Like, why you need it from Google Sheets?
14 00:02:36.420 ⇒ 00:02:50.050 Zoran Selinger: I don’t know how the data from affluence that you have looked like, so if I do, we can compare what I see in the spreadsheet that is the actual source of truth that they want to see.
15 00:02:50.490 ⇒ 00:02:52.889 Zoran Selinger: Let… we can compare. We can compare the data.
16 00:02:53.310 ⇒ 00:02:55.600 Awaish Kumar: Can you show me the Google Sheet?
17 00:02:55.730 ⇒ 00:02:57.780 Zoran Selinger: I can, I can show you the sheet, yes.
18 00:03:27.110 ⇒ 00:03:32.679 Zoran Selinger: Casey cannot join at the moment. Okay, cool, sharing my screen.
19 00:03:33.620 ⇒ 00:03:34.830 Awaish Kumar: Cool. Hope.
20 00:03:41.380 ⇒ 00:03:51.930 Zoran Selinger: Okay, so this is the screen that they… that they are looking, looking at, and you can see that, they are in the… in here constantly, and they are…
21 00:03:53.460 ⇒ 00:03:54.590 Awaish Kumar: All friends of…
22 00:03:54.590 ⇒ 00:03:56.330 Zoran Selinger: They’re putting influencers.
23 00:03:56.770 ⇒ 00:04:01.149 Zoran Selinger: That… They sign, and you see.
24 00:04:03.140 ⇒ 00:04:03.570 Awaish Kumar: That’s fine.
25 00:04:03.570 ⇒ 00:04:09.720 Zoran Selinger: deliverables, they are things that they need to post. We have a monthly retainer.
26 00:04:09.970 ⇒ 00:04:17.060 Zoran Selinger: For each influencer, so this is the number they pay, pay fixedly, on, on a fixed, basis.
27 00:04:17.459 ⇒ 00:04:20.270 Zoran Selinger: Every month, and then for every
28 00:04:20.860 ⇒ 00:04:24.830 Zoran Selinger: Every purchase, every conversion, they have some
29 00:04:26.070 ⇒ 00:04:30.509 Zoran Selinger: some value, in most cases, is going to be $50.
30 00:04:30.660 ⇒ 00:04:37.019 Zoran Selinger: that they’re gonna pay… they’re going to pay off. So, the numbers they want to see in… in NordBeam.
31 00:04:37.960 ⇒ 00:04:39.130 Zoran Selinger: is this.
32 00:04:39.240 ⇒ 00:04:46.980 Zoran Selinger: So this is the total for, for example, for December. This is the total that was paid to influencers.
33 00:04:47.490 ⇒ 00:04:48.630 Zoran Selinger: in December.
34 00:04:49.040 ⇒ 00:04:59.260 Zoran Selinger: What we agreed on is that this retainer can be split over… over the… Number of days, equally.
35 00:04:59.680 ⇒ 00:05:02.190 Zoran Selinger: And this will be different each day.
36 00:05:02.300 ⇒ 00:05:09.149 Zoran Selinger: So anytime a new commission, comes in, this number, obviously, will change.
37 00:05:09.860 ⇒ 00:05:15.730 Zoran Selinger: And we can… we need to see that reflected in, Norbim.
38 00:05:16.180 ⇒ 00:05:17.989 Zoran Selinger: As an example.
39 00:05:19.120 ⇒ 00:05:26.090 Zoran Selinger: As an example, I was trying to do this here, so let’s say we have a 30,000
40 00:05:26.240 ⇒ 00:05:31.319 Zoran Selinger: retainer for that month. This This can change.
41 00:05:31.500 ⇒ 00:05:39.099 Zoran Selinger: During the month. So, mid-month, they will sign, you know, 5 new influencers, so the retainer will change.
42 00:05:39.870 ⇒ 00:05:46.289 Zoran Selinger: Okay? But… the previous days can be overwritten. That is fine with us.
43 00:05:46.450 ⇒ 00:05:47.300 Zoran Selinger: Okay?
44 00:05:47.730 ⇒ 00:05:54.600 Zoran Selinger: So if the… so you can… when you do… when you do the data upload, you can overwrite the previous days.
45 00:05:55.100 ⇒ 00:06:01.910 Zoran Selinger: to increase the number a little bit, you know? So if that goes to 31,000,
46 00:06:02.480 ⇒ 00:06:15.559 Zoran Selinger: previous days can be overwritten. That is absolutely fine. Then the commission will be different every day, okay? Will be different every day, and then this will be the total for that day.
47 00:06:15.970 ⇒ 00:06:21.590 Zoran Selinger: So, a fixed retainer plus commission, whatever happens that day.
48 00:06:21.990 ⇒ 00:06:24.120 Demilade Agboola: And then that’s the total for the day.
49 00:06:25.430 ⇒ 00:06:35.139 Awaish Kumar: Okay, so I… I just want to give you some context. So, before you joined, we were getting data from another sheet.
50 00:06:35.440 ⇒ 00:06:38.539 Awaish Kumar: So let me share that.
51 00:06:39.910 ⇒ 00:06:43.279 Demilade Agboola: But we have the data from Uploine, so that’s what I’m saying.
52 00:06:43.280 ⇒ 00:07:00.870 Awaish Kumar: Well, yeah, I’m coming to that point. So, what I’m trying to say, Zoran, is that we were getting data from a sheet, and now we have another sheet where they are maintaining their invoices from where you want us to get the data, like,
53 00:07:01.430 ⇒ 00:07:12.280 Awaish Kumar: But what Mitesh said, but what Mitesh said previously, why we wanted to get it from Upfront’s platform, because these invoices are, like.
54 00:07:12.460 ⇒ 00:07:16.700 Awaish Kumar: On some day, you have an invoice, and you, like, get it, like, for…
55 00:07:16.830 ⇒ 00:07:33.599 Awaish Kumar: for that month, or 15 days, this is the invoice, and this is what we paid. But instead of that, we wanted to get more granular data, like, on each day, how much we spend. That’s why we chose to go back from these sheets to directly uploads platform.
56 00:07:33.810 ⇒ 00:07:45.680 Awaish Kumar: So we have, like, daily spend information. And that’s why Demolade worked on that. But if you, if you have any doubt on the numbers, we can obviously, QA that.
57 00:07:46.130 ⇒ 00:07:52.510 Zoran Selinger: I mean… I don’t see any numbers, that’s why I have doubt, because I don’t see it in there.
58 00:07:54.240 ⇒ 00:08:02.560 Demilade Agboola: Yeah, so I know, like, part of why I showed Ashwini the tables that it’s coming from was so that he’ll be able to show
59 00:08:02.790 ⇒ 00:08:05.240 Demilade Agboola: Anybody who asks for the numbers, so…
60 00:08:05.480 ⇒ 00:08:10.540 Demilade Agboola: The models are there, like, the spend might not, because the table has a lot of, like.
61 00:08:10.870 ⇒ 00:08:19.780 Demilade Agboola: numerical columns, so the calculation of the spend might not exactly be correct, so that’s part of the QA process to be sure that we’re calculating the spend
62 00:08:20.030 ⇒ 00:08:31.430 Demilade Agboola: the right way. But once that’s done, we’ll have all the numbers that, you know, that are here, and we can use it to be able to, just automatically get the spend.
63 00:08:34.510 ⇒ 00:08:38.590 Awaish Kumar: Okay, so Dominaria is saying that we have some data coming in.
64 00:08:39.130 ⇒ 00:08:43.180 Awaish Kumar: From Upfront’s platform, and it has data, right? Demonade?
65 00:08:43.360 ⇒ 00:08:44.639 Demilade Agboola: Yes, yes, he has data.
66 00:08:45.250 ⇒ 00:08:47.150 Awaish Kumar: What we… what, like…
67 00:08:47.370 ⇒ 00:08:49.910 Demilade Agboola: Why Zoran is not seeing it? Because…
68 00:08:49.910 ⇒ 00:08:54.250 Awaish Kumar: There might be some calculation differences or discrepancies, right?
69 00:08:54.700 ⇒ 00:08:56.750 Demilade Agboola: I mean, it’s live already, it’s in BigQuery.
70 00:08:56.990 ⇒ 00:08:59.270 Demilade Agboola: So, we can actually look at you right now.
71 00:08:59.850 ⇒ 00:09:01.799 Awaish Kumar: Okay, so can you…
72 00:09:02.370 ⇒ 00:09:07.519 Zoran Selinger: Yeah, let’s, let’s look at it. I have, let me just quickly, change my.
73 00:09:07.520 ⇒ 00:09:09.269 Awaish Kumar: Can you open a vacation here?
74 00:09:09.930 ⇒ 00:09:13.309 Zoran Selinger: I just wanna show you what I’m looking at.
75 00:09:17.510 ⇒ 00:09:19.279 Zoran Selinger: This is what I’m looking at.
76 00:09:20.600 ⇒ 00:09:22.530 Zoran Selinger: this influencer.
77 00:09:23.270 ⇒ 00:09:25.310 Awaish Kumar: Oh, you are looking at the North Beam?
78 00:09:25.580 ⇒ 00:09:26.430 Awaish Kumar: Okay.
79 00:09:26.750 ⇒ 00:09:27.260 Zoran Selinger: I guess…
80 00:09:27.260 ⇒ 00:09:31.100 Demilade Agboola: So NotBeam would have to point to BigQuery.
81 00:09:31.490 ⇒ 00:09:33.109 Demilade Agboola: Because that’s where the data is.
82 00:09:33.790 ⇒ 00:09:43.470 Awaish Kumar: Yeah, so… so… so, actually, the whole flow is that, MLRA, you are bringing in data to BigQuery, and actually then taking it from BigQuery and putting it into Node 3.
83 00:09:43.730 ⇒ 00:09:46.300 Awaish Kumar: Right? And in that case, it should show here.
84 00:09:46.650 ⇒ 00:09:53.009 Awaish Kumar: So it’s not here, because… Either pipeline is not working, or the data is just zero.
85 00:09:53.220 ⇒ 00:09:54.680 Ashwini Sharma: Yeah, so, yeah, if…
86 00:09:54.680 ⇒ 00:09:59.739 Zoran Selinger: And the data is not zeroed. This is why I brought that point up. The data is not zero.
87 00:10:00.100 ⇒ 00:10:01.610 Awaish Kumar: In BigQuery, we have data.
88 00:10:02.110 ⇒ 00:10:02.940 Awaish Kumar: Right?
89 00:10:03.230 ⇒ 00:10:06.860 Ashwini Sharma: No, in BigQuery, we don’t have that data, so, like,
90 00:10:07.260 ⇒ 00:10:14.119 Ashwini Sharma: the model that is used to feed the data into this influencer thing that Zoran is looking into.
91 00:10:14.320 ⇒ 00:10:17.880 Ashwini Sharma: That model does not have the data that was needed.
92 00:10:18.990 ⇒ 00:10:26.980 Awaish Kumar: that could be the problem, right? So, Ashwini, like, I don’t know which model you are using, we can… you can… if you can show here right now, we can…
93 00:10:27.940 ⇒ 00:10:29.180 Ashwini Sharma: Fix it, because…
94 00:10:29.330 ⇒ 00:10:37.190 Awaish Kumar: If, like, I, like, before we were getting data from a sheet, which, which now will have all zeros.
95 00:10:37.430 ⇒ 00:10:46.720 Awaish Kumar: So if you’re using the wrong model to get the data, then you will get all zeros. What we need is that… we need to get data from where DevLada is putting.
96 00:10:47.580 ⇒ 00:10:49.790 Ashwini Sharma: Hold on a second.
97 00:10:52.870 ⇒ 00:10:55.400 Ashwini Sharma: So, silly…
98 00:11:00.590 ⇒ 00:11:02.510 Ashwini Sharma: Silence Friends.
99 00:11:03.390 ⇒ 00:11:04.989 Ashwini Sharma: You can see my screen, right?
100 00:11:06.090 ⇒ 00:11:06.640 Awaish Kumar: Yes.
101 00:11:06.640 ⇒ 00:11:11.440 Ashwini Sharma: So affluent spend data comes from this one, right?
102 00:11:12.120 ⇒ 00:11:14.580 Ashwini Sharma: Interfluence Campaign.
103 00:11:15.210 ⇒ 00:11:19.030 Ashwini Sharma: End of lunch campaign, and this is coming from these three.
104 00:11:19.320 ⇒ 00:11:21.150 Ashwini Sharma: tables.
105 00:11:22.200 ⇒ 00:11:33.219 Ashwini Sharma: of friends campaign, upfront’s campaign contributions, and upfront’s campaign orders, right? But if I go to this one, and friends, just go to this one, right?
106 00:11:33.340 ⇒ 00:11:44.810 Ashwini Sharma: Or if I just look into this one, because here the query is, like, get this stuff from this thing, where the query is this one, right? Where contribution status is authorized for payment.
107 00:11:44.940 ⇒ 00:11:51.849 Ashwini Sharma: Now, if I just run this one in BigQuery, I probably will get just one record.
108 00:11:51.960 ⇒ 00:11:59.110 Ashwini Sharma: And that’s the reason why, we don’t push it to not being, because it’s only one record that is being pushed.
109 00:11:59.580 ⇒ 00:12:03.739 Ashwini Sharma: Right? That’s it. And since this is prior to,
110 00:12:04.050 ⇒ 00:12:07.889 Ashwini Sharma: I think it’s prior to December, so that’s why we don’t upload it.
111 00:12:09.540 ⇒ 00:12:11.830 Awaish Kumar: So, what if… what are other contributions
112 00:12:16.400 ⇒ 00:12:17.750 Awaish Kumar: Well, look, interesting.
113 00:12:25.640 ⇒ 00:12:27.159 Awaish Kumar: No, just see the distinct.
114 00:12:27.160 ⇒ 00:12:28.790 Demilade Agboola: Thanks.
115 00:12:28.790 ⇒ 00:12:31.540 Ashwini Sharma: Okay, yeah, yeah, right.
116 00:12:41.790 ⇒ 00:12:48.369 Awaish Kumar: authorized for payment, we have, processed. We have.
117 00:12:49.070 ⇒ 00:12:52.000 Demilade Agboola: Because it might have to be processed and stuff. Can we try processed?
118 00:12:54.840 ⇒ 00:12:57.930 Awaish Kumar: You can see processed seems like we…
119 00:12:58.300 ⇒ 00:13:02.940 Zoran Selinger: And these statuses are coming from… Awful.
120 00:13:03.340 ⇒ 00:13:04.000 Zoran Selinger: update.
121 00:13:04.200 ⇒ 00:13:06.440 Demilade Agboola: Yes, this is… this is all plans that we’re.
122 00:13:06.440 ⇒ 00:13:08.410 Zoran Selinger: Directly from them, okay.
123 00:13:09.700 ⇒ 00:13:10.600 Demilade Agboola: API.
124 00:13:11.470 ⇒ 00:13:15.129 Zoran Selinger: I want to see what I see in the interface of UpFluence.
125 00:13:15.130 ⇒ 00:13:16.570 Ashwini Sharma: Still not enough, right?
126 00:13:16.590 ⇒ 00:13:19.119 Demilade Agboola: Just 3 records. Yeah.
127 00:13:19.720 ⇒ 00:13:20.460 Awaish Kumar: Okay.
128 00:13:21.560 ⇒ 00:13:22.430 Demilade Agboola: Thunder.
129 00:13:22.430 ⇒ 00:13:24.699 Awaish Kumar: Can we see the number, like,
130 00:13:24.860 ⇒ 00:13:28.719 Awaish Kumar: Group by, by contribution status, and count steric.
131 00:13:28.940 ⇒ 00:13:32.779 Awaish Kumar: So we see how much… Rows are assigned to each.
132 00:13:34.060 ⇒ 00:13:35.000 Awaish Kumar: Status?
133 00:13:48.040 ⇒ 00:13:49.520 Zoran Selinger: I’m missing some…
134 00:13:49.520 ⇒ 00:13:50.389 Awaish Kumar: Okay, huh?
135 00:13:53.830 ⇒ 00:13:54.690 Zoran Selinger: women.
136 00:13:55.800 ⇒ 00:13:57.599 Demilade Agboola: Okay, so most are in drafting…
137 00:13:57.600 ⇒ 00:13:58.870 Ashwini Sharma: Maybe, yeah.
138 00:14:00.420 ⇒ 00:14:04.999 Awaish Kumar: But there is not… there are… not enough rows, right?
139 00:14:09.780 ⇒ 00:14:19.229 Ashwini Sharma: Yeah, not in a flows. And that’s what makes me feel that we might not be getting the data that Zoran is looking into in the BigQuery, in the Google password.
140 00:14:20.070 ⇒ 00:14:24.379 Awaish Kumar: Are we running… did we run the script for historical ingestion?
141 00:14:24.820 ⇒ 00:14:26.030 Awaish Kumar: Demonade?
142 00:14:26.190 ⇒ 00:14:34.100 Demilade Agboola: Yes, I… I’m not… I’m not sure about historical, but I know if we look at the first date, we have up to, like, October.
143 00:14:34.730 ⇒ 00:14:45.959 Awaish Kumar: I have one more… I have one more thing for you, Double RA. I think I sent you a Slack, but there is an issue with polyatomic connector for upfronts.
144 00:14:46.240 ⇒ 00:14:46.950 Awaish Kumar: Okay.
145 00:14:47.560 ⇒ 00:14:52.740 Awaish Kumar: like, galib said, like, it’s not working.
146 00:14:53.000 ⇒ 00:14:57.950 Awaish Kumar: Because either it is… yeah, I think I sent that to Zoran to confirm with…
147 00:14:58.590 ⇒ 00:14:59.870 Demilade Agboola: Okay.
148 00:14:59.870 ⇒ 00:15:03.079 Awaish Kumar: Confirm with the client, right? So we…
149 00:15:03.330 ⇒ 00:15:05.780 Awaish Kumar: We have two connectors for Eden, one is Circle.
150 00:15:06.000 ⇒ 00:15:09.780 Awaish Kumar: And it is not working either, because they, they…
151 00:15:10.220 ⇒ 00:15:17.439 Awaish Kumar: They unsubscribe. Second, then, uplifts. I logged in using our…
152 00:15:17.630 ⇒ 00:15:33.040 Awaish Kumar: marketing internal email, which is in OnePass, so I… I can see, I can go into the platform, and I can see all these things, but the Gallip said he’s not able to get the spend and campaigns data using the token.
153 00:15:33.200 ⇒ 00:15:37.710 Awaish Kumar: Which you have set up in Polytomic, so maybe worth looking into it.
154 00:15:38.480 ⇒ 00:15:45.949 Demilade Agboola: Yeah, I think that might be it. So, I don’t want to get too involved, because then they might start reaching out to me.
155 00:15:47.720 ⇒ 00:15:53.740 Awaish Kumar: Yeah, just guide, like, Casey is looking into it right now. Maybe you can just guide him what to do.
156 00:15:54.540 ⇒ 00:15:55.739 Demilade Agboola: Alright, I think…
157 00:15:55.900 ⇒ 00:16:01.999 Demilade Agboola: I’ll just ask Casey. So, Casey just needs to reach out to the Aiden team. I believe it was…
158 00:16:03.220 ⇒ 00:16:07.000 Demilade Agboola: It was… Cutter? I’m not sure it was Kota or it was Vanessa.
159 00:16:07.160 ⇒ 00:16:10.720 Demilade Agboola: that I was talking to for the access…
160 00:16:11.450 ⇒ 00:16:18.260 Demilade Agboola: So, I will look through, just once I can confirm who it was, I’ll send it to Casey, let Casey know that he needs to reach out to confirm that we still have
161 00:16:18.490 ⇒ 00:16:21.370 Demilade Agboola: Like, the user still has access to the API.
162 00:16:22.180 ⇒ 00:16:24.399 Demilade Agboola: So that we can use it for…
163 00:16:25.280 ⇒ 00:16:29.469 Awaish Kumar: But we need an API token, so, like, they generate it for us, right?
164 00:16:30.490 ⇒ 00:16:35.210 Demilade Agboola: So it was an API token. We used the username and, like, login.
165 00:16:35.690 ⇒ 00:16:50.009 Demilade Agboola: And it was that username, and, like, marketing had tried and saw something, and then they gave us the necessary details, so we just filled it in, used it to hit the API, and that’s what we’re using to get the data, I believe.
166 00:16:51.210 ⇒ 00:16:51.970 Awaish Kumar: Okay.
167 00:16:52.040 ⇒ 00:16:53.110 Demilade Agboola: Yeah. Home.
168 00:16:54.520 ⇒ 00:16:59.290 Awaish Kumar: Okay, so yeah, just brief Casey, and who to contact, and
169 00:16:59.880 ⇒ 00:17:06.859 Awaish Kumar: And that’s the ticket, like, I don’t know who is the EP for this project, but that’s the ticket for KC.
170 00:17:07.900 ⇒ 00:17:15.810 Demilade Agboola: I’m also trying to look at the history in polyatomic, but I can’t… I can’t even see the history, because if you look at the high level, it says it was completed
171 00:17:15.940 ⇒ 00:17:23.619 Demilade Agboola: This morning, uploads to Google BigQuery Sync, but I can’t see any of the historical syncs.
172 00:17:24.349 ⇒ 00:17:27.089 Demilade Agboola: So I don’t know why it’s being weird.
173 00:17:27.380 ⇒ 00:17:28.730 Demilade Agboola: In polyatomic.
174 00:17:29.460 ⇒ 00:17:36.959 Awaish Kumar: Yeah, polyatomic is showing successful, but internally it’s not working, right? That’s what Galib’s saying. He’s not over to get the data.
175 00:17:37.460 ⇒ 00:17:46.060 Demilade Agboola: Alright, sounds good. So, yeah, I will just draft it, and I will tag Zoran as well as Casey, so you… you’ll know what to do with the data.
176 00:17:48.760 ⇒ 00:17:50.670 Awaish Kumar: Okay, so we have action plan.
177 00:17:51.330 ⇒ 00:17:55.759 Awaish Kumar: Casey is going to look into it with WRS guidance, and then we…
178 00:17:56.530 ⇒ 00:18:01.629 Awaish Kumar: we look into it further. Once that connector is set up, we’ll see, like.
179 00:18:01.920 ⇒ 00:18:06.920 Awaish Kumar: If data looks good. So, like, maybe we can give a day.
180 00:18:07.070 ⇒ 00:18:18.550 Awaish Kumar: on that, and then if… if… and QA it, if it is work… it works, then okay, otherwise we might, start ingesting from that Google Sheet you are… you shared, Zora.
181 00:18:21.340 ⇒ 00:18:21.970 Zoran Selinger: So…
182 00:18:21.970 ⇒ 00:18:22.530 Demilade Agboola: Sounds good.
183 00:18:23.220 ⇒ 00:18:28.979 Awaish Kumar: We already have a script ready, like, I used to read from that other’s… Yeah.
184 00:18:29.330 ⇒ 00:18:31.330 Awaish Kumar: Google Sheet. Yeah.
185 00:18:31.330 ⇒ 00:18:31.710 Zoran Selinger: No.
186 00:18:31.710 ⇒ 00:18:35.669 Awaish Kumar: With minor tweaks, we can just, like, can deploy it.
187 00:18:35.670 ⇒ 00:18:38.410 Zoran Selinger: Okay, excellent, excellent, thank you, thank you.
188 00:18:38.980 ⇒ 00:18:39.580 Awaish Kumar: Okay.
189 00:18:41.560 ⇒ 00:18:42.869 Awaish Kumar: Okay, great, thank you.
190 00:18:42.870 ⇒ 00:18:43.989 Zoran Selinger: I appreciate it, guys.
191 00:18:45.010 ⇒ 00:18:45.700 Awaish Kumar: Right.
192 00:18:47.020 ⇒ 00:18:47.850 Zoran Selinger: Take care.