Stop Letting Revenue Insights Die In Dashboards

Julia Nimchinski:
And now we welcome Sriharsha, the co-founder and CEO of Hyperbound. Welcome to the HSC stage, how are you doing?

Sriharsha Guduguntla:
Hey, can you hear me fine, Julia?

Julia Nimchinski:
Yeah.

Sriharsha Guduguntla:
Awesome, cool. Thank you so much for having me. I’m excited.

Julia Nimchinski:
Our pleasure. What’s the latest and greatest? And, yeah, let’s get into it.

Sriharsha Guduguntla:
Cool, yeah, I was just listening to the previous conversation, and, you know, it’s very interesting, it’s so innovative, and I love how, you know, especially in the last 6 months, the industry has completely changed, especially with these models.
getting as good as they have, so… that’s a very exciting point in time right now, and I’m excited to talk a little bit about, you know, our worldview here at Hyperbound, and how we’re thinking about, this shift right now.

Julia Nimchinski:
Amazing. Agentic Sales Enablement. Let’s go.

Sriharsha Guduguntla:
Awesome, cool. Well, thanks for having me. So, I’m gonna go ahead, I’ll share my screen. I’m not a big deck guy, but, you know, I figured it’s always good to have a visual. So, I’m gonna go ahead. Can everyone see that?

Julia Nimchinski:
Yep.

Sriharsha Guduguntla:
Amazing. Cool. Well… Again, so thank you so much for having me. Sri Harsha, I go by Sai, co-founder and CEO here at Hyperbound. You know, this, what I’m about to talk about today is, you know, a… something that Atul… Atul’s my co-founder, by the way. It’s something that we’ve been thinking about for the last 3 years.
You know, sleepless nights, trying to figure out, you know, how we can kind of attack, some of the day-to-day problems that revenue leaders are facing, frontline managers are facing, and candidly, reps are also dealing with in the field every day, and you know, at the end of the day, you’ll notice, like, one of the things in here is stop letting insights die in dashboards.
We’ll talk a little bit about what we mean by that, but we’ve been really thinking critically and trying to come at it from an interesting angle here at Hyperbound, so… Just a little bit of background by myself, I’m a conversational AI engineer.
you know, that means I’ve been spending about, you know, the last decade of my life trying to figure out how to get an AI model like ChatGPT to be as realistic and human-like as possible. And, you know, I’ve been… my co-founder and I have been working on LLMs before people even knew what a large language model was.
So, glad to be here and, you know, talking about the future of revenue tech. and the age of AI. So, today, let me level set here, right? So, I wanted to talk a little bit about the problem we’re solving. Now, obviously. Everyone knows that coaching is important.
You know, if you go to any revenue leader and ask them if they believe coaching’s important, almost 100% of them will agree that it is, but the reality, and by the way, these are real stats that are pulled from research reports from Gartner, Forrester, and a couple other sources.
What they found is that managers today, they’re spending almost less than 5% of their time coaching. And, when they surveyed managers, 60% of managers say they don’t have the time to coach effectively. Right? And, the reality is, even when the coaching happens, often what happens is about 87% of coaching, it’s forgotten within the first month.
And there’s that key piece without reinforcement, so we’ll get into what I mean by that in a second here. But, you know, there’s also been research that’s shown that Good coaching actually leads to 27% increase in win rates.
And, So the question is, okay, we know coaching works, and the data shows it, but how do we actually put that into practice and make it scalable? Because most of the orgs we work with today, they’re at a scale where you just can’t do with humans.
You know, once you get to 2,000, 3,000, 4,000 salespeople, you just don’t have the manpower to give every rep the one-on-one time that they need And that’s where AI is really changing things. So, before we go into this, you know, most of you that might have heard about Hyperbound in the past, I’m just gonna go back here for a second.
Most of you that have heard of Hyperbound in the past, you might know us for AI roleplay.
And we were one of the first companies to bring AI sales roleplay technology to the market, and, you know, that’s been our bread and butter, and… One of the things that we learn from building AI roleplay is You know, practice is great, you know, everyone loves practice, but at the end of the day, practice has to lead to revenue. Right?
It’s practice. revenue. So, how do we actually make that connection from practice to revenue? And that’s been, what Otto and I have been primarily focused on in the last year and a half.
So, you’ll see we work with some of the largest enterprises in the world, like LinkedIn, IBM, Autodesk, Monday.com, and most of these companies, the main thing that we’ve noticed is, one. reps, they don’t naturally want to practice. You know, when… how often do you have reps coming to you saying, hey, give me more practice, give me more training?
It’s very rare, right? I’m sure, you know, you’re gonna have your new hires that are very eager to learn, and they’re gonna come in. wanting that. But most of your in-seat reps, who are usually, like, 70-80% of the company, they’re not asking for practice. So, that’s assumption number one. With our business. Assumption number two.
is about the frontline managers, right? The frontline manager job, it’s the hardest job in the revenue org today. And the number one reason why it’s so hard is because there’s so many different things that a manager could be doing, but it’s always a struggle to prioritize the right thing. Right? So, do I focus on this specific deal?
Do I focus on this specific call, or this specific rep? or do I focus on reporting up to my leadership and making sure my forecast is accurate? Like, where do I put my time?
And so, the frontline manager role is very difficult, because at the end of the day, by the time you figure out what you’re focusing on, it’s like decision paralysis, and you end up doing none of those things. And guess what? coaching is often the first thing that gets dropped at the end of the day.
So, that’s the gap that we’re solving here at Hyperbound.
So… just to iterate a little bit more, right, the life of a frontline manager, they… realistically, you know, a lot of sales orgs, they now have a call recorder like Gong, and, you know, the reality is, you could be recording every conversation, and most people are not listening to even 1% of them. Right?
And realistically, managers don’t have the time to listen to every call. And also, you know, sales, we often think backwards in many ways. What do I mean by that? We tend to be very retroactive. Oh, that deal, we lost that deal. Let’s go figure out why, right?
But the question is, how can we become more proactive so that we can get ahead of it and make sure we don’t lose that deal? So, the shift that we’re seeing with AI is going from retroactive to becoming more proactive. And also doing that in such a way that managers, you know, know exactly where to focus their time and attention.
Another thing to mention is managers. they’re often not trained to be people leaders. These are top reps that were promoted in many cases, and I’m not saying this about everyone, but in many cases, they, you know, they don’t receive formal training, and so it’s really hard to be doing all these different things as a frontline leader.
So, we have a saying at Hyperbound, you know, you could be recording every email, every conversation, but conversation intelligence, as a concept, it captures everything. And the reality is it actually solves nothing.
And all it does is it takes all your… it takes all these conversations, surfaces some insights, throws them in a dashboard, and then nothing happens after that. And so, that’s how this concept of insights dying in dashboards was born. So, our… Our worldview at Hyperbound is we want to activate that data.
We want to figure out what we can do with all that call data, all that email data, so that we can help managers focus on the highest leverage activities, and help reps. Save a deal. Before it’s all over. So, here’s kind of the workflow that, we follow at Hyperbound.
So, people, you know, our customers are using us for hiring, they’re using us for onboarding and certifications. This is, this is where the AI roleplay piece comes in. And the part that we’ve really innovated on in the last year and a half to two years is, our… our CI plus activation platform is what I call it, right?
So, now our AI has the ability to score every conversation. It has the ability to… Proactively identify what are the scale gaps, which deals are at risk, and it can use that to automatically create the right types of personalized coaching, personalized role plays that are specific to the deal, but also specific to every rep.
And this is a constant feedback loop. This is actually the scientific method in action. And at the end of the day, you are ultimately looking to create behavior change. So, these are our 3 products. It’s Hyperbound Practice, Hyperbound Perform, and Coda Activate. Hyperbound Practice as our AI roleplay platform.
That’s… that’s where reps go in and practice with our AI roleplays. And then Hyperbound Perform is what actually verifies that that practice is being applied in the field. So, we can hook into a call recorder, we have our own call recorder that can record your conversations and tell you if a rep is actually applying the practice in the field.
Then we’ve got Coda Activate. Coda Activate is our orchestration layer on top of these… on top of Practice and Perform. So it has the ability to answer any type of complex question that you have about your rep’s performance, and it also has the ability to fix them.
So, if you find that a certain team is struggling on a certain objection over and over again, you can go assign that practice to that team, and make sure they’re up to speed. So… That’s kind of the overview.
Julie, I’m gonna pause there real quick if there’s anything that, you’re curious about, clarifications, and then I can jump into a quick lightning demo. I’d love to show. Some of the things that people are doing with the platform.

Julia Nimchinski:
Yeah, this is amazing. My question, and it’s directly connected to your demo. Would be, how would you define your uniqueness? We just have so many different sales enablement, coaching platforms, so would love to hear it from you.

Sriharsha Guduguntla:
Yeah, that’s a great question. You know, every platform that I see, and there’s literally 2 or 3 new ones every day that pop up in the market, everyone has a different, unique spin on it. I’ll say, you know, the biggest… Difference with the way we’re approaching is we’re taking it with adoption as the number one metric in mind. Right?
Because at the end of the day, you can deploy all of this stuff, and if no one uses it, and that’s including managers and reps, leadership, right? It’s all of the different stakeholders, they all need to actually use it to drive real outcomes in the field. So, our goal is, how do you engage each of these stakeholders?
And the way to do that is they have to see, They have to see the value of recording these conversations. using that data to actually get better on the next conversation. Managers have to use this as a way to get visibility that they never could have gotten in the past. So, once you start kind of showing that value, people start using the platform.
I know it sounds simple, but, you know, I talk to revenue leaders every day, and the number one problem that everyone has is adoption. You know, they’re rolling out things and people don’t use it, and when you ask why people aren’t using it, it’s because they don’t see the value in it.
So that’s… that’s… that’s where you have to start with the outcome. What is the value we’re looking to drive first, and then use that to… To build out the right use cases within the platform, so…

Julia Nimchinski:
Amazing, I can’t wait to…

Sriharsha Guduguntla:
Peace.

Julia Nimchinski:
Yeah, 100%, you… We’re one of the first, if not the first, to actually create this category, so… I mean, you saw this from the early innings, when it was, like, quite gimmicky from the technology perspective, and possibilities back in the day, and, you know, it’s so good now. So, curious to see it in action, and yeah, and your learnings.

Sriharsha Guduguntla:
Sure, yeah, so let me just… jump into a quick demo here, so… Yeah, what I’m gonna do is… I… I want to actually… so, you know, most people know about our AI roleplay. platform. We actually have a free demo on our website as well, so if you wanted to try an AI roleplay, and you haven’t tried it yet, I’d be surprised if you haven’t tried one yet.
It’s been around for two and a half years, and most people have tried, some form of AI roleplay already. But please do go try that out. But today, I wanted to focus a little bit on, what what the life of a frontline manager inside of Hyperbound looks like, and I’m gonna switch orgs here. And also, what the rep’s perspective looks like.
So, I’m actually going to start off with our deal dashboard here. So, you’ll see in our deal dashboard, this is actually integrated into HubSpot here, which is a CRM we use, but we can also, you know, hook into Salesforce or your CRM of choice.
Pull in your opportunities, and… You know, we can immediately, identify, for example, let’s go into… One of these deals here. So, when I go into this deal, you’ve got, you know, a full summary of what’s going on in this deal. We’ve got a full timeline, you know, we’ve got what emails were sent in this deal, what conversa- what meetings happened.
We can also automatically fill your CRM with, based on those conversations, we have a quick analysis of the top risks That could slow down this deal. We have suggested next steps. We’ve got stakeholder, identification.
So this is where our AI is actually looking through all this conversational data, automatically identifying who are the top stakeholders. Are they champions? Are they influencers, right? How engaged are they? What’s their sentiment? Right?
And if I want to go and deep dive into Bella, I can actually see what all of Bella’s activities like, you know, what emails were sent, what were her top concerns. What were her positive takeaways?
So this is like a, you know, your deal dashboard, where either a manager could go in here, a rep could go in here, just to get a quick view of what’s going on in this deal.
Now, there’s this piece where we have this next meeting, and I’ll actually come back to that towards the latter half of this demo, but you can actually prep for the next meeting with roleplays and coaching. I’ll show what that looks like. But I want to just highlight CODA real quick. So Coda is our AI agent.
Essentially, it has access to emails, conversations. has access to your opportunity data, and if you also hook in your LMS or CMS, it has access to that as well. And, you know, Coda, it’s not just something that has access to a specific deal or a specific call. It actually has access to all your opportunities.
So, you know, I can actually just go into Coda here and ask something like, hey, what are the… Top. 3 deals… That are at risk right now. And why, and which reps are most likely to not You know, not… not close… close those deals. Right? And this is… this is, like, a pretty complex question, right?
Like, there’s so many factors to figuring out, how… how risky a deal is. And so what the AI is doing is it’s actually, deploying multiple agents.
So this is not… even though it looks like one agent here, it’s actually multiple agents underneath the hood, being deployed into your various data sources, and it’s filtering down and querying that data to identify these top 3 deals.
And the interesting part is I can actually… when I… I didn’t put it into this prompt up here, but I could have also told it given it, like, a time limit. I could have said, hey, in the last 3 days, or in the last week. I could even specify a specific team. I can say, hey, I just want to know this for my SMB team, or just my enterprise team in EMEA.
Right? And we’ll actually put in all those filters and give you data that’s aligned to just those… those teams. So, let’s look at what it generated here, right? So, these were the top 3 deals here. You can see the… some metadata about it, why it’s at risk, how much activity there’s been, you know, which stakeholders have had low engagement, right?
And now, if I want to… I’ll just out, even did a rep risk assessment between Luke and Isaac as well, right? So these are the combined values that are at risk right now, and key coaching recommendations for each of them, right? So… this could be a manager, this could be a leader, like a RevOps leader, doing this analysis.
Now, let’s say I’m like, okay. Let’s look at the biggest deal here. Okay, river… River Trail. Data is… is a pretty big deal. What is the biggest blocker, and do you think there’s a path forward? And I can keep going back and forth with our AI here, and has the ability to, you know, dive even deeper into the river trail data opportunity.
to… to figure out, you know, what’s the real blocker at hand, right? So it says, the core issue isn’t technical, it’s momentum death. You know, there was a lukewarm leadership reception. These were all the meetings that happened. Right?
And there’s a point on February 19th where, you know, we were actually in a negotiation phase, or so we thought, and it got pushed back to validation. And, especially in the last 2 months, there’s been, like, zero activity. and the pilot.
And especially their CRO, who joined one of the calls, Oscar Watkins, he’s neutral, and he didn’t seem as bought in. And out of the 15 stakeholders, 10 of them have low engagement, which is never a good sign. Right? So, is there a path forward? Yes, but it’s fundamentally different, the approach.
And, you know, it might be, like, re-engaging people, building the ROI case, and so on. Right? So I can say, now, if I’m a manager, and I see this, right, what’s my immediate reaction? It’s, okay, let me go talk to this rep, let me figure out if some of this stuff adds up, or why there has been such low activity, right?
And so, I can take a couple actions here, too. I can say, hey. you know, is there… is there something… The rep said that… Made them feel less trustworthy. Can you point me… into the… To the exact point of the call. Especially if there were… multiple moments. So, this is… this is, again, going even deeper, right?
So we were just looking at the deal holistically before, now it’s actually going into every call.
identifying specific moments where the rep might have positioned something slightly differently, or maybe they didn’t say something the right way, and they… they pissed off the CRO, whatever it might be, and so… yeah, this… this, personally, it’s been extremely useful for me. I do this every day.
I come into Hyperbound because, you know, I… and I’ll admit to it, I don’t have time to go listen to every single call that my reps are having. In fact, nobody does. But the AI does. AI can listen to every conversation, and it can point me to the exact moments that actually matter for me to go coach my rep.
And that’s where the time-consuming part is for most managers. It’s not the actual coaching piece, it’s identifying what do I even coach on? And where do I even start? So this is interesting. No answer to the Big Brother concern. So, Oscar is the CRO, he raised a serious concern.
If you’re in the field, this could be perceived as a Big Brother approach. I think we have to be very careful in terms of the dashboarding side. So, the CRO was worried about being called Big Brother, and Isaac, who was the rep on this deal, he said, you know, we could consider this to be a health score, too.
And then he talked about, like, analytics and insights and all that stuff, and you know, Oscar said, I understand, but it’s a massive cultural shock. shift. And, you know, the problem was that, you know, Isaac was just trying to objection handle rather than empathizing, right?
So now, as a manager, during my next one-on-one, I can… I can even ask Hyperbound, I have a… I have a one-on-one tomorrow, Isaac. Can you help me prepare for it with some quick coaching points? Based on the steal. And it will just go create, like, a prep doc for you before that one-on-one meeting with Isaac. Any questions, Julia?
I know I’ve been talking for a while.

Julia Nimchinski:
This is awesome. I love the holistic approach, and you know, that it’s not just an enablement, essentially, platform, but you’re approaching way wider. I’m curious, if… if we are seeing all this coaching, can we immediately deploy the roleplay, or how would that work?

Sriharsha Guduguntla:
That’s an amazing question. That’s where, actually, I was about to go right now. So, it’s essentially, as it builds out this coaching prep, right? I can even go one step further, so I’m gonna let it finish here, but I’m gonna say… Let’s see… oh wow, this is really going all out. So… you know, the language answer hurt you with, with Roman.
Oscar raised a real concern. So let’s just say, when Oscar raised the concern. concern about Big Brother. Isaac didn’t know. How to respond. Can you build me… Can you build me a quick… roleplay of Oscar again, of that exact moment. And a sanitize it. how to do by Friday this week. Send me, send me a quick Slack notification once he completes it.
Boom. So, Hyperbound’s gonna go build that roleplay of Oscar. It knows everything about Oscar, it has his LinkedIn, it has all the notes from the opportunity, it has what he said in the calls and his emails as well, and it will go build this agent.
And so, it kind of just gave you the summary of what it’s gonna build, and it said, should I build it? Yes, please. And I can deploy this roleplay agent right away.

Julia Nimchinski:
Wow.

Sriharsha Guduguntla:
And you can build multiple. So I can say, hey, build a roleplay agent for every stakeholder on here. I can say, build me a rude version of Oscar, build me a nice version of Oscar, and build me a very guarded version of Oscar. Three… I want 3 roleplays, all assigned.

Julia Nimchinski:
It’s extremely impressive, so it’s essentially like an agent’s form of various personalized coaching experiences. Very cool.

Sriharsha Guduguntla:
Yeah, and you know, it’s interesting, too, because every time someone sees this, they’re like, is it just the frontline managers that do this, or do the reps use this, or who’s using this day-to-day? Is it enablement? Is it RevOps? The answer actually is all of them.
So, because the platform has access to all the data, you can essentially go as wide as you want, or as narrow as you want. And this is actually interesting, and I’ll show you, like, one of the things that I like to do. and this product teams or CROs will really like this one.
I can actually go in here and I can say something like, hey, how many… How many different competitors come up on our calls? And can you build me… A quick pie chart of the frequency of each competitor, and also tell me which reps Do vest against each competitor. And so, Coda, actually, Coda, by the way, is our AI agent, here.
So, Coda actually has the ability to graph things, too. So, he’s gonna graph a pie chart now, he’s gonna build out tables. So let’s see, it’s broadening the research here. So, by the way, I want to point out, for some of you watching this, you’re probably thinking, can it be a little faster? Why is it taking so much time?
If you ever see an AI taking a prompt like this, as complex as this, and responding immediately, you should be very skeptical. Of the response. What our AI is actually doing underneath the hood is it’s cross-checking itself over 10 times to make sure that the data that it’s producing is actually accurate.
And even then, I’m not guaranteeing that’s always 100% accurate. Ai’s not perfect. But it’s trying its best to get down to the nitty-gritty, so it’s not giving you inaccurate information. So, what a lot of people have been telling us is, so what I used to do with the data science team of, like, 3 people.
and took days, I can now do with a single prompt on Hyperbound. to have it build out entire reports for me. So, there you go. So mention, like, you know, CAPTCHA, Crestline, these are, competitors that are coming up in conversations. This is how often they’re coming up, these are the calls they came up on, these are the reps they came up on.
you know, key findings for each of them, and then also which reps are doing the best with each competitor. So for… Eche Luke, which ones need improvement? And then I can even say for each of these competitors. Build me… build me roleplay agents. for HA and Luke. And I will go do that. Yeah.

Julia Nimchinski:
So this is essentially your secret sauce and the answer to adoption. Correct me if I’m wrong.

Sriharsha Guduguntla:
Exactly, because now you’re no longer searching through dashboards, like, I didn’t show you a single dashboard today, if you noticed.

Julia Nimchinski:
Yep.

Sriharsha Guduguntla:
Like, even if you ask me, hey, do you have an analytics dashboard? We do, and I’m not gonna show it to you, because there’s no point. The point is you go into Coda, and you ask for what you want, and it builds you the dashboard that you dream of, so…

Julia Nimchinski:
Really cool.

Sriharsha Guduguntla:
Any other questions? Curious.

Julia Nimchinski:
Yeah.

Sriharsha Guduguntla:
cares about?

Julia Nimchinski:
Yep, we have a couple questions from the community. One is, what metrics actually prove enablement ROI in an AI-native org?

Sriharsha Guduguntla:
That’s a fantastic question. I actually had slides on this as well, but I’m not going to bore you with slides. But, you know, the way we think about it is, I said this at the beginning, practice dot dot dot revenue, right?
Ultimately, if I’m an enablement leader, and I’m running a certification, let’s say, I want to prove that that certification actually had an impact on the field. I want to show that the competencies and the skills that I taught my reps during the certification are being applied in the field. How do I do that? In action?
You actually have to show in the data that, there’s, there’s real improvement. So, you know, this is actually a good question, because one of the things that enablement leaders will do will say, they’ll say, hey, the SMB, the, you know, let’s just say Luke, one of the reps, Luke. How many hours did Luke practice last week?
And how many of the skills that he showed in that practice are showing up in his actual calls? Can you build me a quick report? With, with some graphs as well. Right? And now it’s literally directly connecting practice to revenue. I can even ask how many closed-won deals have resulted because of those skills being shown on those calls.
And it can make the connection.

Julia Nimchinski:
Very cool. One more question here. How do you reinforce, behavior change continuously versus episodically, as, you know, with the majority of enablement platforms?

Sriharsha Guduguntla:
So, let me… let me show you that. Well… The problem is, in my demo… so I have, like, a demo instance. And I don’t want to show real data, but otherwise, I would show… the way people do it on the platform, and for some reason, I don’t have it in this demo instance. I was hoping to… let me see if I can show it in a different one. That’s okay.
But what we… we have this feature, essentially, like, let’s say I have this Cloud9 deal, and I have a meeting coming up. Right? Our AI actually, because it’s already analyzed every conversation in the deal, it can actually build me bite-sized roleplays before the next meeting. And so that I can practice for that meeting.
And what it does is it doesn’t build me one roleplay of that meeting, it builds me multiple 3-5 minute ones. So I can practice the exact objections that are gonna come up on that call, I can practice specific skills that are gonna come up on that call.
Like, for example, I have a call tomorrow, and I’m gonna have to talk about liability caps with a procurement manager. And so, actually, Hyperbound built me a roleplay where I could just practice with that procurement manager, talking about liability caps, and, you know, him pushing back on our caps, and me being able to handle that pushback.
So, I wish I could show it, I don’t have it. This is… this is not real data, so, for some reason it’s not populated here, but, you know, whoever asked that question, I’d love to show it to you separately if you reach out.

Julia Nimchinski:
try to like. And lastly, what’s your favorite customer story?

Sriharsha Guduguntla:
Fantastic question. Favorite customer story? Well, you know, LinkedIn is one of our top customers, and you know, one of the things that they did really well was they actually rolled out Hyperbound to their managers before they even rolled it out to their reps.
In fact, it wasn’t even the managers, it was their… it was leadership, so their COO actually did a roleplay on Hyperbound. And then their SVPs did it, then their heads of sales did it, then their frontline managers did it.
And what they were actually doing was, it wasn’t even… they were doing this roleplay where the managers had to practice how to coach a rep. And that’s what got the reps excited about going into Hyperbound, because they saw their leadership doing it.
So, this was a pretty unique use case where, you know, most people are like, let’s just give it out to all our reps and make them do it, versus, let me lead by example, do it myself, and show. Show reps that it’s valuable.

Julia Nimchinski:
Love it. Sriharsha, where should our community go? What’s the best next step? Yeah. How can we test it?

Sriharsha Guduguntla:
For sure. So, the best next step, honestly, is, you know, reach out to me on LinkedIn. If you just search up Sriharsha Garagunla, you can find me, or go to Hyperbound.ai, we actually have a free demo on our website right here. I don’t know why, I’ve tried every possible color, I’ve tried every possible.
copy here, but it’s this big green button right here, so click into it, you can try a demo out yourself, and if you are interested, just book a demo with us, we’re happy to chat and show you more than you saw today.

Julia Nimchinski:
Awesome. Thank you so much.

Sriharsha Guduguntla:
Thank you, appreciate it.