Enterprise Brain Scrum - Notes by Gemini
Meeting Date: 2026-03-23
Google Doc: https://docs.google.com/document/d/1yMizFRTOw2tL-kOk5QaYczpQrnTeFnqYok1oYmbW3F8/edit?usp=meet_tnfm_email
Gmail Message ID: 19d1dfa9890404f5
Gmail Link: https://mail.google.com/mail/u/0/#all/19d1dfa9890404f5
Video Recording: https://drive.google.com/file/d/1_x0LBCCfkWkK3DYM7G4784ajnsPxZVO3/view?usp=drive_web

========== NOTES TAB (Gemini Auto-Generated) ==========

Enterprise Brain Scrum
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Summary
Data structure decisions focused on delayed summarization until the final user
email stage for data richness and organization, with schema and UI flow documentation planned for immediate action.

Data Structure and Summaries
The team decided that data should be combined and sent directly to the snapshot without pre-generation of summaries. The summary generation must occur only at the final user level before sending an email to maintain rich data structure until that point.

Deployment and UI Status
Deployment strategy now involves combining 3 branches into 1, with feature flags being implemented to control the Enterprise brand and experience center. The experiential UI and identical agent setup tasks are actively in progress, with clarification needed for specific Copilot kit integration.

Alerts, Testing, and Agent Development
The alert life cycle is being implemented, including adding sentiment scores and sending alerts to the user-aware agent based on real-time snapshot data. Testing is currently blocked by the core agent knowledge base, leading to plans to create a basic user-aware agent skeleton with mock data for ticket closure.

Details

Data Structure and Summary Generation: The team decided that when gathering data from different sources based on the project, they should combine the data and send it directly to the snapshot without generating a summary beforehand. The summary should only be generated at the very last stage, specifically at the user level, just before sending an email, to ensure no information is lost (00:00:00). Until that point, the data should maintain a rich structure with bullet points, hashtags, user information, and privacy details (00:04:18).

Documentation and Schema Updates: Abhilash Adunuri was confirmed to be ready to drop off from the current discussion (00:06:15). The team decided that they must write the database schema for both the organization and snapshot components, and Rajashekar G confirmed that they would enhance the document regarding this starting today (00:04:18).

UI Flow and Visualization Logic: Vara Kumar Jagarapu inquired about the flow for the UI, specifically how the agent's response is used as input for the pilot and if the response should be returned to the front end (00:06:15). Yeshwanth Reddy Yerraguntla suggested checking the network tab of the current repo's UI, which launches the pylog with all three agents, to observe how the front end sends and receives information via a websocket connection (00:08:33). It was clarified that the visualization process involves the server generating the HTML, and React will use a JSON payload to determine what needs to be rendered using UI visualization functions (00:10:01).

Status of Experiential UI and Copilot Kit Tasks: Rajashekar G provided an update on the UI task, noting that the experiential UI task and the identical agent setup for UI are in progress. A specific task (DB308) concerning a valid Copilot kit for dashboard and chart integration was mentioned, and Rajashekar G noted that they need to ensure Anita's work is taken care of under this task, as her tasks were not currently listed (00:12:02).

Gmail Rollout Implementation: Pawani is working on the task to implement and roll out Gmail integration, and Rajashekar G plans to sync with them since they were unavailable recently. Once the work is done, the entire story will be reviewed, and one version will be given to Prabhakar for initial testing before moving forward with Naru (00:14:14). The implementation involves sending alerts with all necessary tags and details, which Vara Kumar Jagarapu agreed they would sit down to review (00:15:35).

Deployment and Branching Strategy: Rajashekar G is responsible for the deployment and branching strategy, having completed the task of combining three branches into one and is now working on feature flags. They confirmed that the entire story related to Pawani's work will be linked with this deployment work, and feature flags will be used to enable or disable the Enterprise brand and experience center (00:15:35).

Testing and User-Aware Agent Development: Yeshwanth Reddy Yerraguntla is blocked on testing the question and answer life cycle, specifically concerning how to test with multiple users (00:17:15). Yeshwanth Reddy Yerraguntla is blocked by core agent knowledge base and the organization snapshot elements, as they have not yet created a user-aware agent to test the RT agent communication (00:19:02). They plan to create the basic skeleton of the user-aware agent with mock data to close the current ticket (00:21:03).

Alert Life Cycle Implementation: Vara Kumar Jagarapu detailed that Yolia is working on the alert life cycle, which includes adding a sentiment score to emails and Jira information at the data source level. The real-time (RT) agent receives data from the RT snapshot, and based on this data, Yolia will send the alerts to the user-aware agent, which then displays the information on the user interface based on roles (00:21:03).

End-to-End Testing Discussion: Yeshwanth Reddy Yerraguntla clarified that end-to-end testing means testing from the user interface back to the user interface, primarily in Docker (00:24:56). Vara Kumar Jagarapu noted that they spoke with Prabhakar about automation testing for the GenHRX project, and it was suggested not to undertake heavy test automation immediately due to potential iteration burdens. Vara Kumar Jagarapu plans to look into automatically generating test cases using agents, possibly leveraging a sample website where this was done previously, and will provide an update next week (00:25:59).

Knowledge Base and Alert Life Cycle Progress: Abhilash Adunuri is working on the knowledge base setup and CRUD operations for organization information, having prepared and updated the Low-Level Design document. Other tasks related to the organization snapshot, knowledge graph, and alert life cycle back end are assigned to Hashith Rao, Rahul, and Rakesh (00:27:31). Rajashekar G concluded the updates, and the team planned to sync again in the office to review the details further (00:27:31).

Suggested next steps
- Vara Kumar Jagarapu will look into the P from another resource regarding automation testing using agents and will return back with information next week.
- Abhilash Adunuri will write the DB schema for both organization and snapshot.
- Yeshwanth Reddy Yerraguntla will create the skeleton of user aware agent using mock data and close the ticket.
- Yeshwanth Reddy Yerraguntla will write test cases for the mock data related to testing and unit testing.
- Rajashekar G will work on deployment and branching strategy, combining three into one branch, and working on feature flags.
- Rajashekar G will sync up with Pawani to review the entire implement and roll out Gmail story.

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Enterprise Brain Scrum - Transcript

00:00:00

Vara Kumar Jagarapu: Rashi all good.
Rajashekar G: Hi. All good.
Vara Kumar Jagarapu: Okay.
Rajashekar G: How are
Vara Kumar Jagarapu: Good. Good.
Rajashekar G: you? Hi Abby. Hi. s***.
Abhilash Adunuri: Listen.
Rajashekar G: Hi. Good morning.
Yeshwanth Reddy Yerraguntla: Now watch them now.
Vara Kumar Jagarapu: When it's
Yeshwanth Reddy Yerraguntla: favorite check. Okay, Abilash, I saw your document. Uh, everything seems fine. Uh-huh.
Abhilash Adunuri: uh was understood that based on project wise from different sources agent we want to send the ids reference id then agent so in that way I can design the organizations and snapshot and based on different sources we should not able to generate summary because uh we might lost the information for which point a particular user can be accessed.
Yeshwanth Reddy Yerraguntla: It's correct.
Abhilash Adunuri: So we just group from all the sources and we just directly pass this to the snapshot.
Yeshwanth Reddy Yerraguntla: Summary is the in other words summary is the very last thing that you have to generate before sending to the user.

00:04:18

Abhilash Adunuri: Okay.
Yeshwanth Reddy Yerraguntla: Until then you try to maintain as much uh structure and u richness in the data as you
Abhilash Adunuri: Okay.
Yeshwanth Reddy Yerraguntla: can
Abhilash Adunuri: So can I say uh once we get the data from different sources based on the project we just combine them and we'll send it to the art snapshot then while giving to the
Yeshwanth Reddy Yerraguntla: correct.
Abhilash Adunuri: user we'll we'll do that All right.
Yeshwanth Reddy Yerraguntla: Yes. only at the user level just before you're sending the email you'll summarize whatever he needs
Abhilash Adunuri: Here's your
Yeshwanth Reddy Yerraguntla: to listen to in the form of English in good grammar and send it until then everything is bullet points with uh all the hashtags user information privacy details Everything. If you see the e body is perfectly aligned right.
Rajashekar G: Anything else? Dependencies clear. So we are going to enhance the document only today
Abhilash Adunuri: Start on first half.
Rajashekar G: also.
Abhilash Adunuri: Second half
Rajashekar G: Uh DB schema we have to write
Abhilash Adunuri: Yes,

00:06:15

Rajashekar G: right.
Abhilash Adunuri: for both organ.
Rajashekar G: Okay.
Yeshwanth Reddy Yerraguntla: Okay.
Rajashekar G: So Abi Abby can drop off.
Yeshwanth Reddy Yerraguntla: Yeah.
Rajashekar G: Hashet you have any dependencies?
Kalakonda Harshith Rao: data
Rajashekar G: So
Kalakonda Harshith Rao: table. Yeah.
Rajashekar G: check
Kalakonda Harshith Rao: for
Rajashekar G: it.
Kalakonda Harshith Rao: us. Okay,
Rajashekar G: Okay.
Kalakonda Harshith Rao: every final question
Rajashekar G: Okay. Sure. Okay. Manishaka.
Manisha Gundapuneedi: A second.
Rajashekar G: So we will be we will be discussing everything in this karma like oxide board to the micro.
Yeshwanth Reddy Yerraguntla: short.
Vara Kumar Jagarapu: Anita question. So
Yeshwanth Reddy Yerraguntla: Sorry.
Vara Kumar Jagarapu: hello.
Rajashekar G: Yes.
Vara Kumar Jagarapu: Okay.
Rajashekar G: Yes.
Vara Kumar Jagarapu: Okay. So uh so we are having pyog right. So we're like generating uh the UI and all. So she is working on the react like how should be the flow uh because like whether we are removing the toilet. So that is what she asked.

00:08:33

Vara Kumar Jagarapu: I just uh mentioned something like whatever the response uh the agent is giving you are using uh the response to provide uh as input to the uh pilot. Right? So you ask to return the same thing uh to the uh front
Yeshwanth Reddy Yerraguntla: Visualize
Vara Kumar Jagarapu: end then uh you can use that information to feed uh another agent which can which can convert to know kind of transformation logic we can write it there if needed that is what I have mentioned but yeah I think just want to check with that part of floats with you. Jason.
Yeshwanth Reddy Yerraguntla: chess calls. You can go through the repo make UI. It is launching pylog with all three all the three agents.
Rajashekar G: Same.
Yeshwanth Reddy Yerraguntla: Right? So you can always ask a question.
Vara Kumar Jagarapu: Okay.
Yeshwanth Reddy Yerraguntla: See the network tab how that front end is sending information to the agent and how agent is sending back information
Vara Kumar Jagarapu: Okay. HTML tag.

00:10:01

Yeshwanth Reddy Yerraguntla: response webocket connection maintain it is pushing uh
Rajashekar G: Oh,
Yeshwanth Reddy Yerraguntla: tokens actually the front end
Vara Kumar Jagarapu: Okay.
Yeshwanth Reddy Yerraguntla: rod property I am also not I'm only 50% sure how exact it works
Rajashekar G: it was like server side rendering like uh completely server is generating the
Yeshwanth Reddy Yerraguntla: okay correct the that
Rajashekar G: HTML HTM
Vara Kumar Jagarapu: Yeah. Yeah. All
Yeshwanth Reddy Yerraguntla: is fast
Vara Kumar Jagarapu: right.
Yeshwanth Reddy Yerraguntla: HTML
Rajashekar G: It will be like we need to send the JSON payload to react. The React itself uh figure it out like what needs to render, what needs to there will be functions UI visualization what needs to be rendering.
Vara Kumar Jagarapu: Yeah, they clear. Okay.
Rajashekar G: You need to forget that.
Vara Kumar Jagarapu: visualization intelligence.
Rajashekar G: Oh,
Vara Kumar Jagarapu: So for
Rajashekar G: right.
Vara Kumar Jagarapu: right or some other thing mostly
Rajashekar G: and
Vara Kumar Jagarapu: Sorry.
Rajashekar G: okay.
Vara Kumar Jagarapu: Okay.
Rajashekar G: Okay.
Vara Kumar Jagarapu: Yeah, I think we can

00:12:02

Rajashekar G: I go to second act.
Yeshwanth Reddy Yerraguntla: Yeah.
Rajashekar G: So check the first thing on experential
Yeshwanth Reddy Yerraguntla: Yeah.
Rajashekar G: UI task in progress is working on identic agent set up for UI and just story start I'm starting Next. This a
Vara Kumar Jagarapu: update. Not about this.
Rajashekar G: proper
Manisha Gundapuneedi: Then
Vara Kumar Jagarapu: related.
Manisha Gundapuneedi: okay.
Vara Kumar Jagarapu: So that should already
Manisha Gundapuneedi: Okay. just content documents. Okay.
Vara Kumar Jagarapu: set. Yeah. Yeah. Sure.
Rajashekar G: I got this DB308. Right. A valid copilot kit for dashboard and chart integration. Nothing is in intro.
Vara Kumar Jagarapu: Sorry.
Rajashekar G: So this we need to take care of like whatever Anita is working on.
Manisha Gundapuneedi: already share some use.
Rajashekar G: So at least like how we will take it forward like Anita is working on still this
Manisha Gundapuneedi: Uh my activity is true. Okay.
Vara Kumar Jagarapu: Okay.
Rajashekar G: But she her tasks are not in this need to be

00:14:14

Vara Kumar Jagarapu: Yeah. Not listed here. Yeah.
Rajashekar G: added. Let's say this story is still in internal review. So if you are still working on this story only we can add another task and move forward or else we will close this story and take another story for
Manisha Gundapuneedi: Okay,
Rajashekar G: another.
Manisha Gundapuneedi: I should
Rajashekar G: So implement and roll out Gmail. So Pawani is working on these tasks. I synced up with him on Thursday. He is not available yesterday also and I'm also not available. He'll come back today. I'll sync with him. So rolling out with Gmail. So once everything is done like we'll sync and review this entire story once then we will give one version to
Vara Kumar Jagarapu: Yeah.
Rajashekar G: Prabhakar first. So he'll test few things then we will take this forward to
Vara Kumar Jagarapu: Yeah.
Rajashekar G: Naru.
Vara Kumar Jagarapu: Yeah, we need to get that how it is implemented and how you are going to implement here.

00:15:35

Vara Kumar Jagarapu: So yeah
Rajashekar G: H.
Vara Kumar Jagarapu: like he thought of sending those alerts and all that.
Rajashekar G: Okay.
Vara Kumar Jagarapu: Uh so yeah every point is having all the tags and everything on top of it like you'll be having that thing. Yeah how it got
Rajashekar G: Okay.
Vara Kumar Jagarapu: implemented. Okay, we can sit on
Rajashekar G: Okay.
Vara Kumar Jagarapu: it.
Rajashekar G: This one is on me deployment and branching strategy. Uh this task is done combining three into one branch and I'm working on feature flags right now. So while doing this few changes are coming in this one also like so I kept these two tasks in in progress. So once this is done this one and paw's entire story also we'll link with this and then we'll move forward with this
Vara Kumar Jagarapu: Okay. Enterprise brand plus experience center. We should enable or disable based on feature flag.
Rajashekar G: okay
Vara Kumar Jagarapu: That is how they wanted it. So Okay.
Rajashekar G: language

00:17:15

Vara Kumar Jagarapu: Okay.
Rajashekar G: but
Vara Kumar Jagarapu: Okay.
Rajashekar G: okay
Vara Kumar Jagarapu: If that is fine.
Rajashekar G: sure
Vara Kumar Jagarapu: Okay.
Rajashekar G: next this is on you add a question and answer life cycle one
Yeshwanth Reddy Yerraguntla: So testing writing test
Rajashekar G: I mean
Yeshwanth Reddy Yerraguntla: cases and testing on it.
Rajashekar G: Okay.
Yeshwanth Reddy Yerraguntla: So that is one uh thing blocking and uh like I said testing like how can I test with multiple users is something I'm also not clear on because um should I use dummy data or uh how can we get multiple people's emails or what is the way to go forward clarity actually I wanted to talk about this.
Rajashekar G: Okay,
Yeshwanth Reddy Yerraguntla: Yeah,
Rajashekar G: we continue now.
Yeshwanth Reddy Yerraguntla: we can talk. So, open RT agent test cases
Rajashekar G: Okay.
Yeshwanth Reddy Yerraguntla: to
Rajashekar G: The RT agent communication with user agent to send consitation
Yeshwanth Reddy Yerraguntla: actually
Rajashekar G: questions.
Yeshwanth Reddy Yerraguntla: Okay, second neighbor. Okay, let it be
Rajashekar G: This one is to test.

00:19:02

Yeshwanth Reddy Yerraguntla: RT user agent. I think uh uh
Vara Kumar Jagarapu: context.
Yeshwanth Reddy Yerraguntla: basically we didn't create user aware agent yet to test that out
Vara Kumar Jagarapu: Okay.
Yeshwanth Reddy Yerraguntla: we we I'm also I'm blocked on core agent knowledge base arc snapshot all those things and second blocker is we need to have multiple users or maybe I
Vara Kumar Jagarapu: Huh?
Yeshwanth Reddy Yerraguntla: don't need multiple users to build that user aware agent.
Vara Kumar Jagarapu: Okay. Then present us table and table
Yeshwanth Reddy Yerraguntla: Okay,
Vara Kumar Jagarapu: you can walk that you can filter it for
Yeshwanth Reddy Yerraguntla: got
Vara Kumar Jagarapu: now.
Yeshwanth Reddy Yerraguntla: it.
Vara Kumar Jagarapu: what I'm thinking. Yeah. I mean everything
Yeshwanth Reddy Yerraguntla: Correct.
Vara Kumar Jagarapu: should be there on top of it.
Yeshwanth Reddy Yerraguntla: Correct. I think I'll mark both snapshot
Vara Kumar Jagarapu: Yeah.
Yeshwanth Reddy Yerraguntla: and user preferences.
Vara Kumar Jagarapu: Yeah. Um
Yeshwanth Reddy Yerraguntla: Fresh branch.
Vara Kumar Jagarapu: I

00:21:03

Vara Kumar Jagarapu: don't
Rajashekar G: test.
Yeshwanth Reddy Yerraguntla: Sorry. Uh, you're asking.
Vara Kumar Jagarapu: basic
Yeshwanth Reddy Yerraguntla: Uh,
Vara Kumar Jagarapu: skeleton.
Yeshwanth Reddy Yerraguntla: got it
Vara Kumar Jagarapu: So that will be
Yeshwanth Reddy Yerraguntla: right.
Vara Kumar Jagarapu: easy.
Yeshwanth Reddy Yerraguntla: Got it.
Vara Kumar Jagarapu: Okay. So two things.
Yeshwanth Reddy Yerraguntla: Ba. One second. I'm sorry. Let's talk in English only because I'm constantly tracking every meeting.
Vara Kumar Jagarapu: Oh, sorry. Sorry. Okay.
Yeshwanth Reddy Yerraguntla: So
Vara Kumar Jagarapu: Okay. Sorry.
Yeshwanth Reddy Yerraguntla: yeah.
Vara Kumar Jagarapu: Uh yeah. So, one thing is uh she is working on this alert life cycle. Okay. So as a part of it is at data source level uh whatever the emails or uh Jiraa information that we are receiving right she is adding sentiments to that sentiment score that is one part of it and uh at real time is uh RT agent is there right there she is receiving data from the R snapshot okay

00:22:32

Yeshwanth Reddy Yerraguntla: Okay.
Vara Kumar Jagarapu: so which is getting stored by uh the sablash they are in sync currently
Yeshwanth Reddy Yerraguntla: Okay.
Vara Kumar Jagarapu: okay based on that uh received data whatever the alerts are there right she is going to send those alerts to user aware so based on the role and
Yeshwanth Reddy Yerraguntla: Okay.
Vara Kumar Jagarapu: uh roles so she is going to uh send those information to user interface that part currently Yolia is working on not implementation
Rajashekar G: Uh she's not working on implementation right she's only working Abby and uh
Vara Kumar Jagarapu: but yeah she's going to
Rajashekar G: Amula both are still working on like how the schema needs to be how tables need to be
Yeshwanth Reddy Yerraguntla: Got it. Boiler bloods.
Rajashekar G: trained.
Vara Kumar Jagarapu: Yeah.
Yeshwanth Reddy Yerraguntla: Sorry. I'll just create the skeleton of user aware agent with mock data and I'll close the
Vara Kumar Jagarapu: Yeah.
Yeshwanth Reddy Yerraguntla: ticket.
Vara Kumar Jagarapu: Yeah. Uh yeah, that is what my intention is
Rajashekar G: Okay,
Yeshwanth Reddy Yerraguntla: Yeah.

00:23:28

Vara Kumar Jagarapu: actually.
Yeshwanth Reddy Yerraguntla: Yeah. So, testing will be pending. I think it'll probably go to the next print or something.
Rajashekar G: I'll add
Yeshwanth Reddy Yerraguntla: Yeah. Sure.
Rajashekar G: here.
Yeshwanth Reddy Yerraguntla: Yeah. Thank you.
Rajashekar G: Shall I put some estimate on?
Yeshwanth Reddy Yerraguntla: Okay.
Rajashekar G: test cases and unit testing also is
Yeshwanth Reddy Yerraguntla: Yeah,
Rajashekar G: there
Yeshwanth Reddy Yerraguntla: this is the only place where I'm confused because everything is marked here. This will probably go to the next print.
Rajashekar G: right shall keep it like only data
Yeshwanth Reddy Yerraguntla: Yeah.
Rajashekar G: testing
Yeshwanth Reddy Yerraguntla: mock data. Okay. Okay. Okay. Okay. I can then write the test cases uh just for the mock data then
Vara Kumar Jagarapu: uh han the I just want to understand test cases and unit testing is
Yeshwanth Reddy Yerraguntla: yeah
Rajashekar G: Okay.
Vara Kumar Jagarapu: fine end to end testing in the sense like you're talking about automation testing or

00:24:56

Yeshwanth Reddy Yerraguntla: uh I'm talking about from the user interface back to user interface both mainly in docker
Vara Kumar Jagarapu: Okay. Uh uh mainly in Docker like you'll be having headless chrome and you're executing the test. That is what you're thinking uh as
Yeshwanth Reddy Yerraguntla: I will send a uh okay headless chrome part.
Vara Kumar Jagarapu: a
Yeshwanth Reddy Yerraguntla: I'm not sure how can I do that. You can write it down actually if if you suggest that is how it should be done. I'll do that. I'll learn and do that.
Vara Kumar Jagarapu: I mean generally the play rate is there but uh I mean we can take it as a later item if that is what you mean by end to end testing
Yeshwanth Reddy Yerraguntla: Are they
Rajashekar G: All right.
Yeshwanth Reddy Yerraguntla: on?
Vara Kumar Jagarapu: because
Manisha Gundapuneedi: Jen HRX uh Banker is asking us to join for a call but I think uh this will take
Yeshwanth Reddy Yerraguntla: Yes.
Manisha Gundapuneedi: another 20 30 minutes or
Yeshwanth Reddy Yerraguntla: My points are done.

00:25:59

Manisha Gundapuneedi: 5 minutes.
Yeshwanth Reddy Yerraguntla: Anyway, we have five more minutes, right? Yeah.
Manisha Gundapuneedi: Um.
Yeshwanth Reddy Yerraguntla: Yeah.
Vara Kumar Jagarapu: Do I require their
Yeshwanth Reddy Yerraguntla: I think you need to be there
Vara Kumar Jagarapu: okay?
Yeshwanth Reddy Yerraguntla: also.
Manisha Gundapuneedi: Um.
Vara Kumar Jagarapu: Yeah, then that is fine.
Rajashekar G: So I'm putting as testing and unit testing here. I'm testing with mount
Yeshwanth Reddy Yerraguntla: Okay. Yeah.
Rajashekar G: data
Yeshwanth Reddy Yerraguntla: So, main goal of this ticket is to write the test suit.
Rajashekar G: should be
Vara Kumar Jagarapu: I spoke to uh Prabhakar yesterday uh regarding this automation testing for the genrex point of view actually but yeah they
Yeshwanth Reddy Yerraguntla: Okay. Okay.
Vara Kumar Jagarapu: s they also like not suggesting uh undergo uh automation uh writing tests actually. because um uh when we get some iterations right like it will be huge burden uh uh but like one end to end I mean kind of like uh one version is released right on top of it like if we have this uh test cases listed down we can automatically generate uh uh all those things using some agents and they have some P uh doing this uh for one sample website.

00:27:31

Vara Kumar Jagarapu: So I will look into that uh most probably in the next week. They mentioned the one resource worked on it like currently not in the office.
Yeshwanth Reddy Yerraguntla: Okay.
Vara Kumar Jagarapu: So they plan to give it as a KT in uh the all hands actually that is not happened but yeah I'll get that and we'll return back here once I get some regarding testing.
Rajashekar G: Okay,
Yeshwanth Reddy Yerraguntla: Okay.
Rajashekar G: next this one. Knowledge base setup and credit operations on knowledge base for organ info. Ablash is working on this. So right now he prepared the LLD and updated the LLD. It's still in process. So today once done he'll work on this. Next this is for org snapshot and knowledge graph. Same one. This is for knowledge base or info. This is for knowledge base or snapshot knowledge graph. So right now he is it here constant. He'll pick this task either that story or this story. Next alert life cycle back end. Hashit is working on this data source agent ad lifestyle to one. Akai they have an idea on the Rahul working on what and RP is working on what. Okay. So we will sync up with them and I know what dark working on this one also same this is for he's working on like rack cache I think next life cycle agent the intelligence part A is working on this right That's it. End of the course.
Yeshwanth Reddy Yerraguntla: Okay,
Rajashekar G: These are the updates right now.