Meeting Title: Brainforge x ABC Home and Commercial: Weekly Project Check Date: 2026-01-08 Meeting participants: read.ai meeting notes, Yvette’s Notetaker (Otter.ai), YvetteRuiz, Uttam Kumaran, JanieceGarcia, Amber Lin
WEBVTT
1 00:00:41.740 ⇒ 00:00:42.800 Uttam Kumaran: Hello!
2 00:00:43.450 ⇒ 00:00:44.270 YvetteRuiz: Bye!
3 00:00:44.270 ⇒ 00:00:44.830 Uttam Kumaran: Hi!
4 00:00:44.990 ⇒ 00:00:45.870 YvetteRuiz: Thank you!
5 00:00:45.870 ⇒ 00:00:47.580 Uttam Kumaran: How are you? Good to see you!
6 00:00:47.750 ⇒ 00:00:51.780 YvetteRuiz: Good to see you, too! I’m doing good! Happy New Year!
7 00:00:51.780 ⇒ 00:00:54.140 Uttam Kumaran: Yeah, Happy New Year! How was holidays?
8 00:00:54.410 ⇒ 00:00:58.510 YvetteRuiz: It was good. It was a good time to take some time off, take a break.
9 00:00:58.810 ⇒ 00:01:06.620 YvetteRuiz: I enjoyed my grandson. He’s, first time Christmas, first New Year, all that stuff, so that was exciting.
10 00:01:06.880 ⇒ 00:01:08.160 Uttam Kumaran: Great, awesome.
11 00:01:08.390 ⇒ 00:01:09.479 YvetteRuiz: What about you?
12 00:01:09.950 ⇒ 00:01:11.200 Uttam Kumaran: Things are,
13 00:01:11.440 ⇒ 00:01:19.750 Uttam Kumaran: Things are good. I think, we are just excited for this year. We have a lot of, you know, new team members joining.
14 00:01:21.340 ⇒ 00:01:29.289 Uttam Kumaran: That’s great, like, I think really the last… the end of last year was really, really busy, so I took a good break, and I think a lot of the company took a good break.
15 00:01:29.550 ⇒ 00:01:35.299 Uttam Kumaran: But it’s hard for me to not think about Brainforge and our clients, so that’s all it works.
16 00:01:35.300 ⇒ 00:01:37.520 YvetteRuiz: Yeah.
17 00:01:37.520 ⇒ 00:01:41.040 Uttam Kumaran: But I got a chance to meet, I met Joe from Monkey Boy.
18 00:01:41.400 ⇒ 00:01:41.730 YvetteRuiz: Okay.
19 00:01:41.730 ⇒ 00:01:45.540 Uttam Kumaran: I was in office last week, met up with,
20 00:01:45.760 ⇒ 00:01:49.749 Uttam Kumaran: Beau and Steven on some… and Matt on a couple more things.
21 00:01:49.900 ⇒ 00:01:56.080 Uttam Kumaran: I know we… we didn’t get a chance this week to kind of put in our new meeting structure, but I think by next week.
22 00:01:56.260 ⇒ 00:02:01.109 Uttam Kumaran: We can go ahead with that. I did have a question on that, like, I wanted to try to loop in…
23 00:02:01.220 ⇒ 00:02:08.219 Uttam Kumaran: David and Brian on more things. Should I just loop in David? Like, does Brian also need to be on everything, or…
24 00:02:08.220 ⇒ 00:02:25.270 YvetteRuiz: So I talked to David, and David, said that he would start it, I mean, and then, you know, depending on what the agenda is, they may swap out, but, I mean, if we want to probably include both of them in there, I don’t think there’s any harm to start off, and then if we need to make any changes, we should be okay.
25 00:02:25.400 ⇒ 00:02:26.669 Uttam Kumaran: Okay, okay, great.
26 00:02:26.900 ⇒ 00:02:31.130 YvetteRuiz: Yeah. So, but he’s aware, and he’s excited about joining.
27 00:02:31.130 ⇒ 00:02:32.540 Uttam Kumaran: Okay, okay, perfect.
28 00:02:32.540 ⇒ 00:02:35.139 YvetteRuiz: Joining in. So, that’s good, that’s exciting!
29 00:02:35.140 ⇒ 00:02:54.320 Uttam Kumaran: Yeah, I’m excited, yeah, I think it… I think we’re making really good progress. I will… we will show a couple of those items on the discovery side that we’re working on, but I will… I’m also planning, you know, some… some larger emails with some of our insights. So, yeah, and really what I talked to Amber about is, like, I want to loop in…
30 00:02:54.370 ⇒ 00:03:08.060 Uttam Kumaran: David to kind of come alongside of us as we start to do analysis, and honestly try… hand him some of the reins so that he can keep helping all daily, you know? So that’s one of our goals. And we also, you know.
31 00:03:08.060 ⇒ 00:03:15.459 Uttam Kumaran: we’re breaking down all of the goals, that you spoke with Amber about, and kind of creating that clean roadmap.
32 00:03:15.530 ⇒ 00:03:19.130 Uttam Kumaran: So that’s something, Amber, you know, on our side, we can even go through.
33 00:03:19.350 ⇒ 00:03:21.359 Uttam Kumaran: that later today.
34 00:03:21.360 ⇒ 00:03:21.870 YvetteRuiz: Okay.
35 00:03:21.870 ⇒ 00:03:23.710 Uttam Kumaran: But yeah, we have a lot, lot to cover.
36 00:03:24.090 ⇒ 00:03:43.050 YvetteRuiz: Yeah, I know, Bobby had Bo and Steven just kind of give a quick update on y’all’s meeting, so that was all really good. Everyone’s really excited about that, so thank you for that. Steven is out, he’s an A&M, and I’m not sure if… I know Matt was… I met with him earlier, but I don’t know if he’s… if he’s still here or not, so…
37 00:03:43.050 ⇒ 00:03:43.680 Uttam Kumaran: Okay.
38 00:03:46.410 ⇒ 00:03:48.069 YvetteRuiz: Hi, Amber. Hi, Denise.
39 00:03:48.330 ⇒ 00:03:49.380 Amber Lin: Hello!
40 00:03:53.060 ⇒ 00:04:03.229 Amber Lin: Yeah, I just invited David to our weekly calls, and I asked him to book, our separate data call so we can have progress on that side as well.
41 00:04:04.270 ⇒ 00:04:05.150 YvetteRuiz: Awesome!
42 00:04:05.150 ⇒ 00:04:13.449 Amber Lin: Yeah, let me share screen. A few exciting updates this week.
43 00:04:14.290 ⇒ 00:04:15.420 Amber Lin: Alright.
44 00:04:15.850 ⇒ 00:04:16.550 Amber Lin: Oh.
45 00:04:16.769 ⇒ 00:04:17.490 Amber Lin: Oh.
46 00:04:18.570 ⇒ 00:04:19.430 Amber Lin: Here.
47 00:04:20.380 ⇒ 00:04:21.250 Amber Lin: Okay.
48 00:04:27.650 ⇒ 00:04:38.660 Amber Lin: Our usage has been very consistently high, I’m very happy to see that. We’ve been able to clear out most of the unknowns other than the new hires.
49 00:04:38.660 ⇒ 00:04:47.690 Amber Lin: So, if you guys can tell me what departments they’re from, and their emails, then we can fill in the last, the last four that’s missing.
50 00:04:47.760 ⇒ 00:04:57.860 Amber Lin: And then, mechanical is still in the lead. I think they’re doing a great job, and maybe we can ask Tara to share with other departments of what they have been doing.
51 00:04:58.270 ⇒ 00:05:09.279 YvetteRuiz: Oh, she did. She came in… I had my one-on-one with her this day, and she was sharing… well, her trainer is really rallying everybody up. I mean, she was sending… they send them regular messages, and what she has is
52 00:05:09.280 ⇒ 00:05:18.540 YvetteRuiz: She has accountability, like, every time she’s asking them, hey, send me screenshots of what you asked Andy today. So she’s really driving, engagement on that side.
53 00:05:18.540 ⇒ 00:05:19.999 Amber Lin: Yeah, that’s great to hear.
54 00:05:21.440 ⇒ 00:05:22.649 Amber Lin: It’s almost double.
55 00:05:23.040 ⇒ 00:05:25.020 Amber Lin: Of the next in line.
56 00:05:25.020 ⇒ 00:05:28.809 YvetteRuiz: Yeah, and I talked to Shannon today, too, we had a while.
57 00:05:28.840 ⇒ 00:05:40.090 YvetteRuiz: today’s one-on-one day for me with all my leaders, so, Shannon also had some really great feedback, because she did, new hire training this time around with, we had how many, Janiece? Three, four new hires?
58 00:05:40.090 ⇒ 00:05:50.979 YvetteRuiz: three, three new hires, so it gave her a good opportunity to see, hey, what are some things that we can really work on to better the new hire experience? I think she shaved off a week.
59 00:05:50.980 ⇒ 00:05:52.500 YvetteRuiz: Which is positive.
60 00:05:52.810 ⇒ 00:06:02.829 YvetteRuiz: But she also had a lot of good feedback, and what I asked her to do is I said, go ahead and start working on that, and then get with Amber, so then that way we can start making whatever tweaks need to be made.
61 00:06:02.830 ⇒ 00:06:05.139 Amber Lin: Yeah, let her know if she wants to…
62 00:06:05.340 ⇒ 00:06:21.079 Amber Lin: book a meeting with me, feel free to, like, send me an email, and then we… because I think that’s a more effective way to talk through, all the stuff that she wants, and ideally, if she can write it down so that we don’t forget a lot of stuff that comes in, that would be even better.
63 00:06:22.510 ⇒ 00:06:23.469 YvetteRuiz: You got it.
64 00:06:23.470 ⇒ 00:06:32.629 Amber Lin: Awesome, okay. So, the next part, I’m gonna open this up, and then maybe, Utam, you can walk us through.
65 00:06:32.710 ⇒ 00:06:35.489 Uttam Kumaran: Sure. This, so this is a timeline.
66 00:06:35.920 ⇒ 00:06:40.639 Amber Lin: Would you like to share screen, or I can share screen, and then…
67 00:06:40.640 ⇒ 00:06:43.589 Uttam Kumaran: I’m more than happy to share, and then I can pass it back to you.
68 00:06:44.090 ⇒ 00:06:44.709 Amber Lin: Yeah, sounds good.
69 00:06:44.710 ⇒ 00:06:46.689 Uttam Kumaran: Give me a sec, let me just bring it up.
70 00:06:48.250 ⇒ 00:07:05.860 Uttam Kumaran: So yeah, I mean, on our side overall, like, even across all of our clients, we are getting a lot more organized. I just… one thing I’m pushing the team is, like, I would like us to see what the next 3 months look like, and especially, you know, as we talk about, Andy, and let me know if this is,
71 00:07:06.280 ⇒ 00:07:15.980 Uttam Kumaran: like, too big, but I’ll zoom in a bit. Especially as we talk about, Andy, part of the… part… there’s two things that are happening right now. One is, like.
72 00:07:16.640 ⇒ 00:07:22.470 Uttam Kumaran: Fortunately, unfortunately, like, the AI world is moving very fast, meaning even the stuff we built.
73 00:07:22.470 ⇒ 00:07:28.230 YvetteRuiz: like, last year, on what we knew was, like, very modern technology has changed, and so…
74 00:07:28.230 ⇒ 00:07:38.459 Uttam Kumaran: Part of our job as engineers is to consistently find opportunities to make the system faster, more and more resilient,
75 00:07:38.460 ⇒ 00:07:53.900 Uttam Kumaran: But as well as, like, really continue to solve, and actually expand the realm of problems that we’re solving. In addition to that, though, we are consistently trying to ship new features, and so the way I describe it to the team is, like, we have maintenance, and we have upgrades, and then we also have…
76 00:07:53.900 ⇒ 00:08:06.229 Uttam Kumaran: like, new features, and so our job is to balance that, because ultimately, we can ship a bunch of features, but if we’re doing it on a shaky foundation, then things will start to fail. Similarly, like, if we just
77 00:08:06.270 ⇒ 00:08:24.740 Uttam Kumaran: maintain things, and we never grow, that’s also a challenge. And so this is… this is the fun of, engineering. And so, really, what we’re seeing here is, like, these are the various components of what we’re describing as, like, the Andy migration, but really what it is, is just upgrading different parts, and…
78 00:08:24.820 ⇒ 00:08:36.539 Uttam Kumaran: part of the… the other thing I mentioned to the team is, like, commonly when you hear migration or, like, upgrades, it’s, like, the tech team sort of using jargon to just, like, say, like, yeah, we’re fixing a bunch of things. You’re like, how does this affect.
79 00:08:36.940 ⇒ 00:08:37.549 YvetteRuiz: with the CSR.
80 00:08:37.559 ⇒ 00:08:50.679 Uttam Kumaran: are getting. And so, one thing that we’ll go through today is, like, each of these actually does affect features and parts of the goals that the team has requested, and so it’s not only just to make
81 00:08:50.679 ⇒ 00:09:02.659 Uttam Kumaran: you know, easier for us to make changes and keep the system stable, but it is actually accomplishing things that we’ve already asked. And so, this is, you know, just simple Gantt chart. We have a couple sections.
82 00:09:02.659 ⇒ 00:09:03.989 Uttam Kumaran: The first thing is.
83 00:09:03.989 ⇒ 00:09:20.259 Uttam Kumaran: We’re migrating a really core piece of the Andy logic to a new system. This is gonna allow us, one, to prevent downtime, so, we should no longer see what was happening kind of frequently with Andy being down, and sort of know a way for us to know that.
84 00:09:20.319 ⇒ 00:09:35.129 Uttam Kumaran: And so this is, like, really just a major shift of technology that we’re doing. And really, then we kind of move into logging. Logging, these are all the ways that we know the answer-response pairs between CSRs and,
85 00:09:35.319 ⇒ 00:09:55.049 Uttam Kumaran: And Andy, and back and forth, and actually, this is allowing the data to now live in a new system called BigQuery. BigQuery is what we’re gonna use, actually, on the discovery process side as well, for analyzing all of our sales data, and this is actually what I’m gonna give access to David and Brian to start to run queries on top of.
86 00:09:55.049 ⇒ 00:10:05.639 Uttam Kumaran: So, this is going to be what powers the dashboards. We already have a version of this, we’re just moving this to a new software, but as you can see,
87 00:10:06.099 ⇒ 00:10:25.869 Uttam Kumaran: moving this from Snowflake, which is our existing database to BigQuery, is not the highest priority. What is the highest priority is that, we are able to get logs landed accurate somewhere. And so, I pushed the team to say, hey, like, if moving this is not the highest priority, then just, like, let’s do that, you know, later next month.
88 00:10:25.869 ⇒ 00:10:34.019 Uttam Kumaran: Instead, what is really the highest priority and what is the meat of this project, is making sure that we are retrieving accurate data
89 00:10:34.019 ⇒ 00:10:51.189 Uttam Kumaran: from the central dock, we are able to measure that we are retrieving accurate data, like, what is accurate, right? We confirm whatever the new central dock structure is in order to kind of do that. And we start to load tests, right? What happens if, like, we go from
90 00:10:51.189 ⇒ 00:11:09.109 Uttam Kumaran: 30 to 50 to 200 people hitting Andy, right? Because one of the things we’re also considering is, can other people at ABC use Andy for other use cases, right? To ask about any document, right? And so we need to understand… my push for this team is, like, we came in, we just talked about Andy in this one use case, but of course, as things are growing.
91 00:11:09.109 ⇒ 00:11:28.969 Uttam Kumaran: we need to reconsider some of the backend. And so, we’re also doing load testing, and we’re also looking at, like, general performance, so continue to try to get the response times, down. The other piece is we actually have, like, interesting, types of responses that we’re managing, right? Where we have, like, fixed copy responses.
92 00:11:28.969 ⇒ 00:11:35.379 Uttam Kumaran: We’re like, hey, what is the script that I need to say on templates and cancellations? But then we also have things that are more dynamic.
93 00:11:35.379 ⇒ 00:11:41.179 Uttam Kumaran: And so, our system needs to support both of those, and so that are the… that’s these two items.
94 00:11:41.209 ⇒ 00:11:44.169 Uttam Kumaran: below here. This is, like, the meat…
95 00:11:44.229 ⇒ 00:11:51.369 Uttam Kumaran: Of, like, a lot of, like, what sets us up to really do well on any future data source
96 00:11:51.659 ⇒ 00:11:55.739 Uttam Kumaran: That we want to support as part of the ANDI project.
97 00:11:56.169 ⇒ 00:12:03.359 Uttam Kumaran: And so the next piece we’re working on is, evaluation and alerting. So ideally, what I told the team is, like, when…
98 00:12:03.419 ⇒ 00:12:19.199 Uttam Kumaran: we’re gonna define what accuracy means, and when accuracy starts to fall, we need to get an alert. And our current system alerting is just a little bit difficult to do, and so we’re moving to this new system, which you’ll see this word Mastra everywhere.
99 00:12:19.199 ⇒ 00:12:26.369 Uttam Kumaran: This just allows us to get better logging and better alerting, so we can start to see immediately within Slack
100 00:12:26.369 ⇒ 00:12:42.439 Uttam Kumaran: when, like, either the system is down, or our accuracy starts to dip. And this could be, like, hey, you guys are getting a bunch of thumbs down, which we’re getting some of this right now. But we want to see, like, hey, out of, like, at a daily level, our accuracy dipped, okay, we need to investigate.
101 00:12:43.569 ⇒ 00:12:53.779 Uttam Kumaran: The next piece we’re working on is our text-to-SQL accuracy. So text-to-SQL is really how we are, querying the database. So this is everything around,
102 00:12:53.899 ⇒ 00:13:11.989 Uttam Kumaran: Validating that we’re able to pull data out of the database accurately, and also migrating the oh-by-the-ways and the thumbs up, thumbs-down, sort of, like, chat-based features, to this new system. So, what you’ll see here is everything is a week. Some of these are actually, like, one day.
103 00:13:12.119 ⇒ 00:13:14.249 Uttam Kumaran: We try to, like,
104 00:13:14.569 ⇒ 00:13:31.859 Uttam Kumaran: what do they say? Under-promise, over-deliver. So I usually say, like, assume things are gonna take a week, but some of these are actually, like, one-day tasks. And the way that we indicate this is you can see there’s a lot of things we’re working on in parallel, and so this is really where, like, our team’s time is going now.
105 00:13:31.859 ⇒ 00:13:48.359 Uttam Kumaran: And then the last piece is, like, this migration happens in phases, but we’re working with Tim, and we’re actually going to be creating both a development and a staging, Andy version of Andy, meaning we’re going to be able to test changes before releasing it to everybody.
106 00:13:48.369 ⇒ 00:13:55.639 Uttam Kumaran: So our engineers are gonna be able to test things with a version of Andy, just on whatever code they’re working on.
107 00:13:55.709 ⇒ 00:14:09.729 Uttam Kumaran: we’re gonna be able to push it to, like, this group, and whoever else wants, like, sort of beta access to new features. That way, like, previously, we were just, like, sort of like, okay, it’s working, let’s get it to everybody, and then we… we sort of don’t know an edge case, and so…
108 00:14:10.009 ⇒ 00:14:29.759 Uttam Kumaran: we ultimately want to try to give at least one week of testing where a small group of people can test, or maybe we release it to, like, a smaller testing group of CSRs, so that they can basically break it in a safe environment for us to see. And so, these are all things that we worked on Tim to enable, so now we do have, like, three versions of Andy that will be
109 00:14:29.779 ⇒ 00:14:30.839 Uttam Kumaran: releasing.
110 00:14:32.019 ⇒ 00:14:37.049 Uttam Kumaran: And it’s just gonna make this, like, process of, like, pushing new code out, you know, a lot smoother.
111 00:14:38.279 ⇒ 00:14:50.209 Uttam Kumaran: The other piece that you’ll see here at the bottom, which is helpful just to be aware of, is at any moment, we have, like, 3 kind of core maintenance tasks that, like, always have to happen, meaning
112 00:14:50.209 ⇒ 00:14:58.339 Uttam Kumaran: They may not… they may or may not be happening every day, but it is something that we’re budgeting time for, which is, zip code changes.
113 00:14:58.429 ⇒ 00:15:16.489 Uttam Kumaran: just any type of system outage, and then the maintenance of the central dock. And then the last piece we’re also going to be adding here is, like, aliases. So, acronyms and aliases, as we need to keep that sort of list up to date, that’s just something that our team is making sure that we just have time budgeted to do those things.
114 00:15:16.569 ⇒ 00:15:36.049 Uttam Kumaran: Below here, we have, like, all of our, sort of, goals, you know, that… these are, like, new feature goals that we talked about, right? Which is, for example, looping in David to reporting workflows, you know, starting to, create dashboards so that when in our meetings, we’re no longer looking at screenshots, we can just go directly to the dashboard.
115 00:15:36.049 ⇒ 00:15:46.849 Uttam Kumaran: There’s things like loading all the transcripts, classifying all the transcripts, suggesting improvements based on those, right? There’s consolidating, like, cancellations across departments.
116 00:15:46.849 ⇒ 00:16:02.589 Uttam Kumaran: Andy asking better probing questions, so the inputs, right? So, all of those things, these are what I would describe as, like, net new features. And so, most likely, we are gonna start that towards the end of, you know, this month.
117 00:16:02.609 ⇒ 00:16:05.469 Uttam Kumaran: So really, this… these two pieces.
118 00:16:05.709 ⇒ 00:16:13.389 Uttam Kumaran: I… I told the team, I don’t want to ship new features until we’re confident in the fact that Andy’s retrieving the right data.
119 00:16:13.419 ⇒ 00:16:26.919 Uttam Kumaran: and that we can measure at any moment, like, how right it is, and that we can get that alerting if it’s not right. Because ultimately, the adoption of all of these new features sort of hinges on that. Like, if we put something out into the world.
120 00:16:26.969 ⇒ 00:16:44.399 Uttam Kumaran: Even though it’s very fancy, if it doesn’t work, and then it doesn’t work a couple times, then people are gonna say, no. We already know that, you know? I think our… our customers in the CSR department are very cunning, so they’re… they’re gonna… they’re just gonna say it’s not working, right? And so we always need to be understanding of, like, what that means, and
121 00:16:44.399 ⇒ 00:16:49.539 Uttam Kumaran: I think we did a good job going into the end of the year of understanding, like, okay, not working…
122 00:16:49.539 ⇒ 00:16:53.329 Uttam Kumaran: We have to categorize that into, like, several different
123 00:16:53.329 ⇒ 00:17:05.699 Uttam Kumaran: error modes, and some of those, not… a CSR may just say not working, but it’s like, okay, maybe they asked the question in the wrong way, maybe it actually isn’t working, it’s something ABC team is handling, it’s something our team is handling, so…
124 00:17:05.819 ⇒ 00:17:11.429 Uttam Kumaran: Those are kind of, like, all the things that we’re gonna sort of iron out here, and then…
125 00:17:11.909 ⇒ 00:17:19.839 Uttam Kumaran: this week, Amber and I are working on seeing what part of these new features, we can work on in parallel.
126 00:17:19.939 ⇒ 00:17:30.319 Uttam Kumaran: and this is sort of, like, how we’re planning the next, you know, 3 months of work. The problem right now is that we do have to get through this phase.
127 00:17:30.319 ⇒ 00:17:42.269 Uttam Kumaran: So what we’re working on is what part of the new features that are requested can we work on? Like, either myself or Amber or the team as they free up, start to work through.
128 00:17:42.269 ⇒ 00:17:55.199 Uttam Kumaran: In parallel with some of these items. But I’m hopeful that in the next few weeks, we will… we will know, like, what’s on the roadmap for Andy in the next 3 months, in terms of development, and that way.
129 00:17:55.199 ⇒ 00:18:05.889 Uttam Kumaran: Yvette, when you present to the rest of the company, you have a clear… clear view of what that is. And so every week, we’re just sort of like, okay, where are we according to plan? What’s changed?
130 00:18:06.079 ⇒ 00:18:15.979 Uttam Kumaran: And so we can start to keep track of these new features, and then, ideally, we go into next quarter, right before that, with a list of things that we want to ship in the next quarter as well.
131 00:18:15.989 ⇒ 00:18:35.169 Uttam Kumaran: And then similarly, as I’m working with, Bo, Steven, everybody, I also have some asks of Andy to help some of their teams, and so I’m gonna be getting that into this list. And so, yeah, this is kind of, like, how we’re thinking of, like, the future, a little bit of, like, planning for this project.
132 00:18:35.689 ⇒ 00:18:46.499 Uttam Kumaran: I just did a lot of talkies, I’m happy to answer any questions about, like, any piece of this, but did want to just, like, give you guys a view into, like, how we’re thinking about, planning for this.
133 00:18:47.580 ⇒ 00:18:55.019 YvetteRuiz: I mean, you did an excellent job breaking that down. If I could say anything, it’s like, we feel so heard.
134 00:18:55.020 ⇒ 00:19:08.379 YvetteRuiz: On some of those things, and you’re absolutely right, Uten, on the… I absolutely love the beta testing piece of it, to be able to get that. I mean, earlier when I was meeting, again, with one of the girls.
135 00:19:08.390 ⇒ 00:19:21.869 YvetteRuiz: the feedback that comes back is, like, it’s not working. I don’t… it’s giving me the wrong information, and one of the things that we’re really working on is, okay, but you gotta tell us, like, what exactly it is, so then that way… because we have control over that, so…
136 00:19:21.870 ⇒ 00:19:22.500 Uttam Kumaran: Yeah.
137 00:19:22.500 ⇒ 00:19:23.409 YvetteRuiz: of that.
138 00:19:23.890 ⇒ 00:19:42.490 YvetteRuiz: that beta testing piece of it before we start putting it out there, because then it will really be able to… once we roll it out, it’s the accurate information, it’s the right information on that. And then the next phase is, I can’t wait to get the next phase. It’s particularly on the cancellation piece of it, because I know that’s been a…
139 00:19:42.490 ⇒ 00:19:50.320 YvetteRuiz: big focus that we’ve been really trying to get going, to really help our CSRs and really work on saving the customers.
140 00:19:50.320 ⇒ 00:20:01.569 Uttam Kumaran: Okay, great. Yeah, and one of the things that, you know, we’re working on, I think Amber will actually probably get into this data, is looking at all the past cancellation data. And so, Amber, most likely.
141 00:20:01.580 ⇒ 00:20:15.210 Uttam Kumaran: we will kind of meet this project somewhere in the next month, where we’re gonna… the… really, this… this BigQuery piece, which is, like, creating a place for us to land all this data, is what’s gonna allow us to do our analysis, and
142 00:20:15.210 ⇒ 00:20:22.909 Uttam Kumaran: it’s what we’re gonna end up handing off to… to David, for sure, for him to start to pick up. So this is all the things we’re thinking about, is like.
143 00:20:22.910 ⇒ 00:20:33.940 Uttam Kumaran: We do the first version, we get it all landed, and the data’s modeled, produce the analysis, and then try to hand it to David and Brian so that they can start to kind of own and run with that.
144 00:20:33.970 ⇒ 00:20:35.470 Uttam Kumaran: On a daily basis.
145 00:20:35.710 ⇒ 00:20:43.719 Uttam Kumaran: So, for example, there are pieces of, like, loading transcripts and classifying that we will do over the next month. I… I just don’t know…
146 00:20:43.850 ⇒ 00:20:49.580 Uttam Kumaran: What… for example, suggesting improvements based on the transcripts is something that, like.
147 00:20:49.750 ⇒ 00:20:54.479 Uttam Kumaran: It’ll… we just need to think about, like, that a little bit more, and it may take a few weeks.
148 00:20:55.710 ⇒ 00:21:01.950 Uttam Kumaran: And so this is kind of how we’re thinking of it, but again, like, as… as I think back to when we started this project, right?
149 00:21:02.140 ⇒ 00:21:21.710 Uttam Kumaran: Yes, I assume this is going to be very complicated. It is as complicated as I thought it would be, right? So part of the way we designed it was not with this level of complexity in mind, so we have to make some of these upgrades and changes in order to understand, hey, we are scaling to a bunch of departments, we have
150 00:21:21.830 ⇒ 00:21:37.800 Uttam Kumaran: structured spreadsheet database kind of data. We also have text data. The system needs to also take in inputs, right? So Janiece and others are adding data to the system in a structured way. We need to… now that it’s being used by a lot of people.
151 00:21:37.800 ⇒ 00:21:43.169 Uttam Kumaran: very, important that it doesn’t go down, right? So there’s just these… these things that, like.
152 00:21:43.270 ⇒ 00:22:02.050 Uttam Kumaran: with maintaining any system that… that happened over time, so that’s, like, really what this next, like, four weeks is about. And then also, our team is growing, by the way, so we have more people that will be sort of working and sort of creating redundancy on the ABC, like, AND system, and
153 00:22:02.280 ⇒ 00:22:09.150 Uttam Kumaran: people are also starting to work on a lot of the data work for the things that we’re working with Bobby and Bo and Matt on, so…
154 00:22:09.300 ⇒ 00:22:17.110 Uttam Kumaran: all of the stuff we’re learning there will sort of converged, and so it’s like a… I’m really excited. This next month, especially, there’ll be, like, a lot of collaboration.
155 00:22:17.270 ⇒ 00:22:19.980 Uttam Kumaran: So, yeah.
156 00:22:20.160 ⇒ 00:22:26.220 YvetteRuiz: Oh, no, that’s really good. I… the transcript piece of it, that’s the other one. I mean, you know that we’ve been itching for that right there.
157 00:22:26.220 ⇒ 00:22:26.670 Uttam Kumaran: Yes.
158 00:22:26.670 ⇒ 00:22:36.030 YvetteRuiz: is to be able to… for us to be able to get that data is just… it’s huge, you know what I mean? To be able to say, okay, where do we need those improvements? What are we missing?
159 00:22:36.540 ⇒ 00:22:37.510 YvetteRuiz: Yeah.
160 00:22:38.350 ⇒ 00:22:42.950 YvetteRuiz: Yeah. Janiece? I know you’re smart, smiling over there.
161 00:22:42.950 ⇒ 00:22:51.230 JanieceGarcia: I know, I’m just… I’m so excited for what’s to come about with Andy, and I have seen a lot of… I will say, with
162 00:22:51.760 ⇒ 00:23:02.249 JanieceGarcia: everything, Utam, I mean, the entering of the central dock, I know there’s still, you know, some things that come about, and it’s like, why is it not reading it? But…
163 00:23:02.620 ⇒ 00:23:09.049 JanieceGarcia: you’re hearing us, you have heard us, so I’m… I’m excited for these next several steps, big time.
164 00:23:09.450 ⇒ 00:23:10.000 Uttam Kumaran: Yeah.
165 00:23:10.740 ⇒ 00:23:34.009 YvetteRuiz: And I think it’s really good. Utam, I mean, again, you already got to spend time with, different players of ABC, so really, I mean, like you said earlier, the complexity, I mean, just kind of putting all that stuff together, because there is so much. And in the beginning, when we first spoke, it was kind of hard to share all that information because it’s too overwhelming, right? It’s like, we’re gonna take bites of those elephants and start putting it together, but…
166 00:23:34.010 ⇒ 00:23:37.889 YvetteRuiz: I mean it all makes sense. I mean, it’s all coming together, so…
167 00:23:37.890 ⇒ 00:23:41.819 Uttam Kumaran: Yeah. And as a, as a, you know, for us as an engineering team, like.
168 00:23:42.090 ⇒ 00:23:47.569 Uttam Kumaran: what I don’t want us to do is… is… is continue to build on, like, a foundation that we’re not…
169 00:23:47.600 ⇒ 00:23:58.159 Uttam Kumaran: sure can handle all this, because our engine… our team will always tell me, like, hey, we need to upgrade this piece, like, it’s not able to handle what we want it to do. And, again, like.
170 00:23:58.180 ⇒ 00:24:07.940 Uttam Kumaran: this is a very tough, environment right now, because the AI world is just changing very fast. Like, some of these technologies I listed were… did not exist
171 00:24:08.080 ⇒ 00:24:21.810 Uttam Kumaran: like, 12 or 18 months ago. Not to say that, like, we’re building things on, like, brand new, like, stuff that’s not gonna get supported, but more it’s, like, it’s just moving very fast, and so…
172 00:24:21.860 ⇒ 00:24:34.519 Uttam Kumaran: We… we take the best guess at, like, how to build, but it is something that, like, this is innovation, like, this is something that y’all are pioneering in your industry, so it comes with these, like.
173 00:24:34.670 ⇒ 00:24:41.960 Uttam Kumaran: expectations of, hey, we may have to sort of roll with the punches. But again, this system has evolved, like.
174 00:24:42.380 ⇒ 00:24:43.890 Uttam Kumaran: Pretty significantly.
175 00:24:44.350 ⇒ 00:25:01.699 Uttam Kumaran: And I think what we’re gonna find is, like, a lot of other people are gonna be able to use ANDI for their use case, because it rhymes with… with a lot of the stuff to the CSRs, and in fact, I think that probably the CSRs are the most… are gonna be the most demanding use case out of all of the ones, which means, like.
176 00:25:02.100 ⇒ 00:25:05.009 Uttam Kumaran: I don’t… I feel fine that we’ll solve their problem.
177 00:25:06.010 ⇒ 00:25:06.750 Uttam Kumaran: You know.
178 00:25:06.920 ⇒ 00:25:07.970 YvetteRuiz: Yeah. So…
179 00:25:08.300 ⇒ 00:25:17.759 YvetteRuiz: No, definitely. I mean, you, again, we already know, like, the salespeople, the technicians, I mean, there is a lot of stuff that
180 00:25:17.760 ⇒ 00:25:30.340 YvetteRuiz: I mean, having this, and having the right information, and everybody getting the same information is going to be just, you know, priceless, because no, we’re all speaking the same language. Yes, this is the protocol. Yes, this is the way, instead of having that.
181 00:25:30.380 ⇒ 00:25:34.070 YvetteRuiz: You know, adding to that that’s… That’s great.
182 00:25:34.670 ⇒ 00:25:35.300 Uttam Kumaran: Great.
183 00:25:35.830 ⇒ 00:25:42.160 JanieceGarcia: It is, I mean, and even going through, like, some of the triage questions and knowing that the CSRs will ask
184 00:25:42.600 ⇒ 00:25:55.670 JanieceGarcia: how do I submit, you know, how can I submit a PTO? Or, how do I take a screenshot and share it, or, you know, anything like that. It’s not just about what our customers are calling in for, it’s everything, so…
185 00:25:56.270 ⇒ 00:25:57.100 JanieceGarcia: Right. Pute.
186 00:25:57.100 ⇒ 00:25:57.770 Uttam Kumaran: Perfect.
187 00:26:00.690 ⇒ 00:26:01.470 Uttam Kumaran: Okay.
188 00:26:01.470 ⇒ 00:26:01.980 Amber Lin: Awesome.
189 00:26:01.980 ⇒ 00:26:03.490 Uttam Kumaran: I could pass it to you, yeah.
190 00:26:03.490 ⇒ 00:26:04.740 Amber Lin: I can share screen.
191 00:26:07.630 ⇒ 00:26:08.470 Amber Lin: So…
192 00:26:08.600 ⇒ 00:26:26.709 Amber Lin: I have this, actually, because we were working on the zip code database quite a lot, and we’re still working on it. We’ve already added the mechanical and home improvement text, and Casey’s working on adding the last piece, which is the commercial pest technicians. I don’t know if you guys have seen this.
193 00:26:26.710 ⇒ 00:26:28.140 Uttam Kumaran: Yeah, this is, like, awesome.
194 00:26:28.140 ⇒ 00:26:33.359 Amber Lin: It is so cool. Yeah, I think you should go. Because it makes our lives so much easier.
195 00:26:33.720 ⇒ 00:26:42.599 Amber Lin: So, I can… I can walk you through super quickly. This is still in testing, but… so, if we can start with
196 00:26:43.060 ⇒ 00:27:01.050 Amber Lin: super basic things. If you enter in all the people, right, and then you can edit them of what their name is, and edit their assignments, and then you can have… we have crew, inspector, technicians, and all the different services.
197 00:27:01.560 ⇒ 00:27:07.350 Amber Lin: So, we can see, like, what… what we might be missing.
198 00:27:07.470 ⇒ 00:27:09.359 Amber Lin: Also here…
199 00:27:10.130 ⇒ 00:27:24.350 Amber Lin: And lastly, this is the assignments table, and I think this was really, really helpful this morning. I was going through some of the triage tickets, and I was able to say, okay, it’s from this department, it’s this person, he’s a technician.
200 00:27:24.940 ⇒ 00:27:28.630 Amber Lin: How do I… How do I find it? How do I know?
201 00:27:29.030 ⇒ 00:27:34.989 Amber Lin: what zip codes he’s in, and then it tells me, okay, it’s all the Austin zip codes.
202 00:27:35.340 ⇒ 00:27:40.959 Amber Lin: And then… He’s a technician. Then we can edit…
203 00:27:41.270 ⇒ 00:27:45.920 Amber Lin: We can edit all of these, just with one click, and then it’s really, really easy.
204 00:27:46.110 ⇒ 00:28:03.619 Amber Lin: to… to do. So, I think this will be really helpful, especially, Janice, if you… in the future, you need to update anything, like, you won’t be able to see what we actually have, instead of just submitting forms. And maybe in the future, this could also be something that…
205 00:28:03.830 ⇒ 00:28:20.939 Amber Lin: the CSR is used directly, I’m not sure how that would be, but this will make Andy’s queries a lot more accurate, because it’s, because we can go back and see, okay, what’s actually available, and it’s much clearer than what we had before.
206 00:28:21.310 ⇒ 00:28:27.500 JanieceGarcia: That’s awesome. So, anything that’s in the triage right now for zip codes, then…
207 00:28:28.120 ⇒ 00:28:33.719 JanieceGarcia: Sending it to Casey to double check, or will you be giving me access to that?
208 00:28:35.280 ⇒ 00:28:37.999 JanieceGarcia: Or… I know you said it’s still in testing, but…
209 00:28:38.000 ⇒ 00:28:50.500 Amber Lin: Yeah, this is not fully ready yet, but feel free to tag Casey in them, or assign it to him, so that he knows that these are something we can use to test with. So, probably…
210 00:28:51.470 ⇒ 00:28:59.030 Amber Lin: I think he’s still adding the commercial tech, so maybe next week we’ll give you a better answer of, if it’s ready or not.
211 00:28:59.780 ⇒ 00:29:00.380 JanieceGarcia: Okay.
212 00:29:01.100 ⇒ 00:29:02.589 JanieceGarcia: Wow, that is amazing.
213 00:29:02.590 ⇒ 00:29:05.599 YvetteRuiz: That is a pretty cool tool.
214 00:29:05.600 ⇒ 00:29:08.139 JanieceGarcia: We actually replace our pest division skills.
215 00:29:08.140 ⇒ 00:29:09.939 YvetteRuiz: No, I know, it’s those, like, all…
216 00:29:10.420 ⇒ 00:29:16.000 Amber Lin: It makes, like, if someone needs to update things, like, it’ll be so much easier.
217 00:29:17.180 ⇒ 00:29:23.579 JanieceGarcia: and certain people, we could… we would be able to say, okay, myself, Yvette, trainers would be the only ones that can edit
218 00:29:24.050 ⇒ 00:29:27.380 JanieceGarcia: that… At all, right?
219 00:29:28.340 ⇒ 00:29:29.000 JanieceGarcia: Nice.
220 00:29:30.100 ⇒ 00:29:30.750 Amber Lin: Yeah.
221 00:29:30.780 ⇒ 00:29:41.329 Amber Lin: Last piece I have here is I want to share a little bit on the discovery. So, starting from next week, our meetings will be a bit longer, so we get another half to go through
222 00:29:41.330 ⇒ 00:29:54.760 Amber Lin: non-Andy-related, so purely discovery stuff, because we usually take about 30 minutes for Andy-related work. So I just want to go through what we are doing this week, and what we plan to do next week.
223 00:29:55.250 ⇒ 00:30:11.220 Amber Lin: So this week, I went through the sales data that Julie had, and to look at the distribution of, like, sales across the services. We started on Google Analytics to look at the marketing, and then some follow-ups from last week’s meeting
224 00:30:11.240 ⇒ 00:30:15.849 Amber Lin: Where Clarence was there, so in person, so some follow-up questions there.
225 00:30:15.920 ⇒ 00:30:17.649 Amber Lin: And I have some…
226 00:30:18.400 ⇒ 00:30:26.800 Amber Lin: some of the analysis here, I just want to flash them through. They’re… these are just findings, and when I… when we booked the meeting to…
227 00:30:26.910 ⇒ 00:30:31.029 Amber Lin: present next week. I’ll walk you through what these actually
228 00:30:31.030 ⇒ 00:30:47.149 Amber Lin: can mean, so the insights from these. But this is just the analysis I did based on the data, and that will tell us information that we didn’t have before, and what that may mean for opportunities or things we can do for
229 00:30:47.410 ⇒ 00:30:49.879 Amber Lin: To make ABC better.
230 00:30:50.030 ⇒ 00:30:55.690 Amber Lin: So… Quickly, so I looked at the distribution.
231 00:30:55.910 ⇒ 00:30:59.369 Amber Lin: Of sales across the different services.
232 00:30:59.470 ⇒ 00:31:07.150 Amber Lin: And, which HVAC is… Very high, right behind residential pest.
233 00:31:07.290 ⇒ 00:31:15.009 Amber Lin: Which makes sense, because most of business is in a very hot area out of America. And then, I also looked at
234 00:31:15.680 ⇒ 00:31:27.020 Amber Lin: So for each service, what’s the distribution of revenue across the different branches? So that tells me, okay, why is it so high in a particular…
235 00:31:27.200 ⇒ 00:31:39.569 Amber Lin: branch, so excluding Austin, we can look at, okay, seems that for a mosquito, Kemphrey has a lot of mosquito services, or say, for Holiday Lights, it’s
236 00:31:39.570 ⇒ 00:31:53.950 Amber Lin: very high in, other, say, other than San Antonio, it’s very high in College Station, where we can look at commercial and see, okay, seems like Corpus has a lot of commercial, so that… I think that tells us of…
237 00:31:53.990 ⇒ 00:32:07.050 Amber Lin: What we can look into to see why certain services are better in certain areas, and maybe inform how we do those services in all areas to make it even better.
238 00:32:07.050 ⇒ 00:32:11.320 YvetteRuiz: Or even add, like, a, you know, hey, oh, by the way, buildings, like, hey.
239 00:32:11.740 ⇒ 00:32:27.659 YvetteRuiz: focus areas for Oh By the way, search, because I think that’s when we were talking about, like, how do we… this year, how do we make up, our new milestone for Oh By the Ways? We want to get to 5,000 this year. I mean, if we’re able to go in there and say, okay, let’s target XX, but…
240 00:32:28.060 ⇒ 00:32:47.120 Amber Lin: Yeah, totally. And I also looked at some of the… so for different branches, what are their top services? And the small… the small branches, Waco was very, very small in 2024. It had 50% of their sales was in commercial pests, and that’s very, very different from
241 00:32:47.140 ⇒ 00:32:52.440 Amber Lin: The overall percentage of Like, commercial was 8%?
242 00:32:52.870 ⇒ 00:33:11.299 Amber Lin: Overall, but it’s very big in Waco. So, that let us see what… what are we doing differently there? Why is a certain service more popular? Is it because we have less competitors in that area? So, just… just from the data itself.
243 00:33:11.300 ⇒ 00:33:25.390 Amber Lin: We’re able to see a lot of… or answer a lot of questions we weren’t able to before, so hopefully next week when we book that meeting, I can dive deeper on what I found and what we can do based on that.
244 00:33:26.720 ⇒ 00:33:27.120 YvetteRuiz: Oh, I’m.
245 00:33:27.120 ⇒ 00:33:41.850 Uttam Kumaran: So we would… we’re trying to, you know, we’re trying to answer questions about the segmentation of revenue across different services, across different branches. Ultimately, we’re trying to find what’s working, what’s not, how do we do more of what’s working? Like, and so…
246 00:33:41.850 ⇒ 00:33:55.390 Uttam Kumaran: We’re trying to answer that with a couple of what we call, like, dimensions. So, we have our branch, we have our services, but we’re also going to look at customer information. We’re also going to look at customers with one service versus a basket of services.
247 00:33:55.390 ⇒ 00:34:04.629 Uttam Kumaran: We’re gonna look at, like, customer length, so if they’ve been with a customer for us with a long time. It’s actually funny. I called ABC and had them come to my house.
248 00:34:04.630 ⇒ 00:34:24.270 Uttam Kumaran: over… over break. I need to look and evolve for my… for my thing, but I went through… I forgot which CSR I chatted with, but I went through the process of… of booking a call and seeing that, so a lot of that insight is what we’re bringing, and so this is really what Amber is presenting is just on the post-sale.
249 00:34:24.270 ⇒ 00:34:32.449 Uttam Kumaran: Right? So we’re also looking at the awareness. So, like, how do people find out about ABC? How do they get to the
250 00:34:32.460 ⇒ 00:34:49.039 Uttam Kumaran: the various purchasing channels that we have, the website, click to buy, or through the phone. And then, of course, like, what happens after that. So, I think, ultimately, we’re very confident in the service that’s getting delivered. I think it’s either ends of that that we’re trying to figure out, right? So.
251 00:34:49.040 ⇒ 00:34:55.500 Uttam Kumaran: Post-service, how are folks continuing to buy additional services? How are we continuing to stay top of mind?
252 00:34:55.510 ⇒ 00:35:14.900 Uttam Kumaran: And how do we get people to buy more services and stay with us longer, right? And then we’re also going to go through the cancellation reasons as part of this exercise. So, that’s going to help, I know, this team as well, and I hope that even as part of this, if there’s a chance that we can use some of the transcript data as part of our discovery work, we’ll do that as well.
253 00:35:15.010 ⇒ 00:35:29.980 Uttam Kumaran: But this is sort of, like, how we’re breaking it down. So we did… we did a presentation on, sort of, like, competitors. We’re gonna do one purely on, like, sort of sales and revenue data. We’re going through and looking at all the website stuff as well, so kind of going piece by piece.
254 00:35:30.550 ⇒ 00:35:34.220 YvetteRuiz: Yeah, that’s impressive stuff, that’s good information.
255 00:35:34.220 ⇒ 00:35:34.590 Uttam Kumaran: Yeah.
256 00:35:34.590 ⇒ 00:35:36.030 YvetteRuiz: But, yeah.
257 00:35:36.650 ⇒ 00:35:37.020 JanieceGarcia: Am I?
258 00:35:37.020 ⇒ 00:35:55.420 YvetteRuiz: I think, like, and just looking at some of those, like, you look at the Waco piece of it, I mean, we already kind of already know some of them, because, you know, you get some big cells in some areas, you know, like the schools, like, we just got these big ol’ schools and stuff, so you know some of the things that are triggering it, but to your point, Udom, is like, how do we get more of those on that end? So, a lot of good.
259 00:35:55.970 ⇒ 00:35:57.839 YvetteRuiz: Lot of good insight, for sure.
260 00:35:57.840 ⇒ 00:35:58.510 Uttam Kumaran: Perfect.
261 00:35:59.610 ⇒ 00:36:14.869 Uttam Kumaran: Okay, great. So yeah, Amber, I think I look forward to, like, yeah, having an hour. I think we got plenty to talk to… plenty to talk about, and then let’s also plan on doing, like, I know y’all do a weekly KPI, maybe we could either do another data one, and I don’t know.
262 00:36:15.130 ⇒ 00:36:31.560 Uttam Kumaran: Denise, if you necessarily need to be on that one, or if we want to combine, but I would like to talk to David at least once a week about data stuff, and then I think we should totally include David on this meeting as well, and then… because we’re going to be going through probably a lot of the work that we’ll collaborate on, so…
263 00:36:31.560 ⇒ 00:36:42.940 YvetteRuiz: Yep, yep, yep. I think David has, well, they have data puddles, and he may want to probably… if, you know, once he does this, maybe you guys can join in with their data team and meet with them.
264 00:36:42.940 ⇒ 00:36:43.500 Uttam Kumaran: Yeah, okay.
265 00:36:43.500 ⇒ 00:36:49.180 YvetteRuiz: with all of them as a whole, you know, because it’s Brian, and then there’s Austin, and then there’s David.
266 00:36:49.710 ⇒ 00:36:51.059 Uttam Kumaran: Okay, okay, great.
267 00:36:52.610 ⇒ 00:37:00.679 YvetteRuiz: Yep, yep, yep, all good stuff! Well, thank you guys so much! Exciting the new year! Yeah, me too. Thank you so much.
268 00:37:00.680 ⇒ 00:37:01.060 JanieceGarcia: Thank you.
269 00:37:01.060 ⇒ 00:37:03.780 YvetteRuiz: Thank you, Amber, for everything you’re doing.
270 00:37:03.780 ⇒ 00:37:04.730 Uttam Kumaran: Thanks, Amber.
271 00:37:05.140 ⇒ 00:37:06.010 JanieceGarcia: Thanks, y’all.
272 00:37:06.010 ⇒ 00:37:06.920 YvetteRuiz: Alright, bye. Bye, guys!
273 00:37:06.920 ⇒ 00:37:07.710 Amber Lin: Bye!