JFrog at Bank of America Global Technology Conference: Balancing Innovation and Profitability

On Thursday, 05 June 2025, JFrog (NASDAQ:FROG) presented its strategic vision at the Bank of America Global Technology Conference 2025. The company highlighted its dual role as a disruptor and protector in the software supply chain, emphasizing a strong Q1 performance and strategic investments in AI and security. However, JFrog also noted the challenges of large deals and uncertain market conditions.

Key Takeaways

• JFrog reported a strong Q1 2024, driven by enterprise sales and security product adoption.
• The company is focusing on managing large language models (LLMs) through its QuocAI acquisition.
• JFrog is taking a cautious approach to guidance due to market uncertainties.
• Security products, particularly JFrog X-ray, are emerging as significant growth drivers.
• JFrog aims to balance innovation with profitability, adhering to the "rule of 40" framework.

Financial Results

• Q1 2024 showcased robust performance, largely due to investments in enterprise sales and security.
• Cloud usage exceeded minimum commitments across a diverse customer base.
• Security revenue contributed 3% to total revenue, 5% to ARR, and 12% to RPO.
• The free cash flow margin stood at 26% for Q1 2024.
• A notable enterprise customer reached $30 million in ACV.

Operational Updates

• JFrog’s acquisition of QuocAI aims to enhance its capabilities in managing LLMs.
• The first phase of QuocAI’s product was released on the cloud, with a self-hosted version expected by the end of Q2.
• The company supports the Hugging Face repository, offering security scanning for the community.
• JFrog has over 7,000 customers, with more than half utilizing JFrog X-ray.
• Customers are exploring Docker, Hugging Face, and Python packages, indicating AI-related developments.

Future Outlook

• JFrog remains cautious in its guidance, excluding large self-managed cloud migrations.
• MLOps presents a significant opportunity, with continued investment in AI platforms.
• The company prioritizes generating strong free cash flow while fostering innovation and profitability.
• Future M&A efforts will focus on AI technology rather than security.
• JFrog anticipates continued growth in its security business.

Q&A Highlights

• JFrog’s platform migrations typically come from competitors like Sonatype, not hyperscalers.
• Security solutions are sold to a diverse panel of stakeholders, including developers, CIOs, and CSOs.
• The company maintains a focus on profitable growth, balancing innovation and financial health.

For more details, please refer to the full transcript below.

Full transcript - Bank of America Global Technology Conference 2025:

Koji Keda, Software Analyst, Bank of America: Everybody, my name is Koji Keda. I am one of the software analysts here at Bank of America. Welcome to day three of our technology conference. I am absolutely thrilled to have JFrog doing a fireside chat with us. We have the CFO, Ed Grabshied, and we also have IR, Jeff Schreiner here.

So thank you so much for being here. We appreciate it. I always ask the obligatory introductory comments or question of, you know, what is JFrog? What do you guys do? What problems are you addressing today?

And what problems are you addressing for the future? Well, first of all, thank

Ed Grabshied, CFO, JFrog: you for having us. It’s great to be back here in San Francisco. I see some new faces in the in the audience here, so I’ll give a background of JFrog. JFrog was brought to this world to make developers more efficient. So as code, source code becomes a machine language, that’s a binary.

JFrog manages the binary. So today we are the only company in the world that has binary and artifactory as a platform. We also have DevSecOps, which is our security product and now JFrogML. So three applications in a platform, only company in the world to be able to do that. We’re focused today primarily on managing those assets, ensuring that they are brought into your organization, they are secure, and then they are delivered in the form of an update.

We also will start working the future with large language models. It’s very nascent technology today, but the focus is on delivering value for the AI and large language model world in the future.

Koji Keda, Software Analyst, Bank of America: You guys dubbed yourselves as the one of the disruptors and protectors of the supply chain of software. What exactly does that mean for being the supply chain of software?

Ed Grabshied, CFO, JFrog: Yeah. The supply chain of software is really the the motion of taking a language that’s written in a source code in English or Spanish or German and putting that into machine language. And what is different today than what we saw maybe a decade or two decades ago was the pace of updates. So if you recall, maybe if you use Microsoft and you did an update in Microsoft, you would do that once a year or every other year, they would do an update. They can manage that update.

Somebody would write the code, they would turn it into a language. They would test it. They’d bring it to market. There might be an error that’s found. They would fix that.

And maybe six months down the road, would update that again. Today updates are being done ten, twenty, even a hundred times per day. The pace of those updates because of open source packages coming into your organization today, source code, 80, let’s say 80 to 90% of that is an open source package. You’re only writing 10 to 20% of your code, but it has to convert into a binary software supply chain. And the management of that binary was brought to this world because of these open source packages.

And this is what JFrog does. It manages the process of taking those binaries, those updates, and bringing them through your organization, testing them, securing them, and distributing those binaries, those updates.

Koji Keda, Software Analyst, Bank of America: When I was preparing for the conference and I was kinda looking at the first quarter my my first quarter result notes, I was kinda reviewing them. I’m like, man, you guys had a pretty good quarter. And so so tell me a little bit about the quarter. What was kind of the highlights of the quarters? And, you know, what have investors have been kind of asking about the quarter that they’ve been pointing to pointing to from a bull case?

Ed Grabshied, CFO, JFrog: Yeah. Yeah. So q one was a culmination of not just one quarter. It was a culmination of many quarters that we built to the results that you saw during q one. So we really saw this transformation that was happening early on where we wanted to penetrate at the C suite.

We saw there was an opportunity to move from a developer sale into the enterprise. We invested heavily two to three years ago with security, I’m sorry, with enterprise, with strategic sales, with building the infrastructure around that architects and solution engineers. Now Q1 is a result of those efforts, the efforts of the acquisition of Vidoo, where we have security and security going from a point solution to a platform and adding that on top of Artifactory. And then in Q3 of last year, closing three of the largest deals in the history of the company. Three or four years ago, if we did a half a million deal, that was considered a mega deal within JFrog.

Today, we’ve closed deals that are 8 figures. We have a customer that’s over $30,000,000 on an ACV value. So when you say Q1 was a great result, that wasn’t because it was just one quarter. These were multiple quarter efforts. And we really started to see that momentum happening in Q3 of last year with these large wins with security.

If you recall at the end of twenty twenty four, we disclosed the metrics and security. We delivered more than, or we delivered 3% revenue, 5% of ARR and 12 of our RPO, which is coming from security where we had essentially zero in the year before. So we’ve really started to penetrate the security budgets as well. And then the last piece of what we saw during Q1, which was a bit of a surprise to us was the amount of usage in our cloud. So we have customers that commit to JFrog minimum commitments in data consumption.

So they may commit to two petabytes, 10 petabytes, ten, fifteen petabytes, whatever that usage is. And we take that revenue ratably. When the customer exceeds those minimum commitments and usage, then we have an overage. In 2024, the vast majority of our customers were not spending or using above the minimum commits. In q one, we had this robust usage across a diverse set of our customers in our portfolio, across multiple geographies and distributed linearly across all three months of the quarter.

So this was something that was not expected. It’s historically a slow quarter, q one, as many budgets are being built, as sales kickoffs are happening. So it was a bit of a surprise to us, but it ended up being a great result for JFROM.

Koji Keda, Software Analyst, Bank of America: I want to focus on the the large deals for a second. Just a point of clarification, make sure I heard it right. You said 30 you have customers that are 30,000,000 in size on an ACV basis. That’s

Ed Grabshied, CFO, JFrog: We have one customer that’s 30,000,000 in size on an ACV basis. Wow.

Koji Keda, Software Analyst, Bank of America: Okay. Okay. Okay. And then on the cloud usage front, got asked the question. Right?

Yes. I’m sure you’ve been getting the question a lot. AI coming into play with that? I mean, is there any sort you know, you guys should be a beneficiary of AI driving more binaries good for JFrog? I mean, I don’t wanna get ahead of my skis here, but it does feel like, you know, is AI playing into that just a little bit?

Ed Grabshied, CFO, JFrog: Well, we’re just we’re going through the circuit this we were telling you before the the the fireside chat, how many of the fireside chats we’ve had. So you’re not getting ahead of your skis because this is the third question. We typically get it on the first or the second around AI.

Koji Keda, Software Analyst, Bank of America: I waited a little bit. Yeah.

Ed Grabshied, CFO, JFrog: Well, let me tell you a little bit about the usage. We, well, first off AI, what we believe and why we’re so excited about this opportunity. When you bring a large language model into your organization, it’s a binary. And we are the company that manages the binaries. So we believe we should win this market.

We made an acquisition at the end of Q2. We acquired a company called QuocAI. That is the platform that manages large language models to bring those models into your organization to train, to secure and distribute large language models. We released the first phase of the product, which is on the cloud in Q1, and we’re planning to release the self hosted version at the end of this quarter. Now what are we seeing?

I’ll be honest. We’re we’re not a company that’s gonna deliver a message of fluffiness. It’s very early. If we talk about a baseball game, we’re singing the national anthem at this point. We’re not even exiting the dugout to start playing the game.

We see some things that would believe lead us to believe that there could be a tailwind and that thesis around it is that more binaries means more, more code means more binaries and more binaries is going to be beneficial to JFrog. Now in Q1, during this over usage period, we did track the packages that were being used by the customers. And we saw three packages that seemed to have the most significant usage on a sequential basis. That was Docker, Hugging Face, and Python, PyPy. So when you think about what the developers are using, you could make some assumptions that there’s experimentation that’s going on right now with AI.

You mentioned Hugging Face. I believe that’s a customer or a relationship that you highlighted on the last quarter call. You mentioned it right there. What’s going on with with Hugging Face? Why did you guys talk about it so much on the call?

Jeff Schreiner, IR, JFrog: Yeah. Sure. I’ll take that question, Koji. I think the Hugging Face relationship is unique in the sense that it’s a repository for large language models, much in the same fashion that you would garner a repository for NPM Maven on the package side that we’ve already been doing with Artifactory today. And so when you look at what we’ve been doing here and what was the I apologize.

What was the topic again? It was the Hugging Face. Sorry. Apologize. Guys, a long week.

I apologize. Hugging Face is a relationship in which they came to us, Koji. Yeah. They had had another company that was reviewing the repository and securing that repository, but that company had told them that 80 plus percent of the models were malicious. Okay?

And so they asked JFrog to come in and scan those models, and we said that those were false positives. So in an essence, maybe some of that Hugging traffic that Ed had alluded to could be that JFrog customers felt that this was a more secure repository from which they could pull from. So the Hugging Face relationship is us supporting the community today and supporting that repository. But, obviously, there could be indirect benefits as customers start to utilize that Hugging Face repository and use the proxy function that’s within JFrog Artifactory today. So we view that as kind of the first motion of what you’re seeing where the repository is more focused on an LLM than it is on an individual package technology.

Ed Grabshied, CFO, JFrog: And I think there’s, I’m going to just jump in real quick. I think there was something very important that Jeff mentioned was that Hugging Face came to us, JFrog, to scan and ensure the confidence that the models that are being stored in Hugging Face to pull into your organization are secure. So that brings a lot of confidence to the community that JFrog is is the system of record in terms of the scanning and the level of confidence that these models are secure. So even if you’re not a customer today of JFrog, you know that JFrog is going to be the system of record in terms of the scanning capabilities. Therefore, if you’re going to bring a large language model, and this is where the intangible benefit that Jeff talked about, you’re going to bring that as a data scientist into your organization to make sense to store that in JFrog.

So we believe that there could be some opportunity coming from that. Today, it’s not a monetized relationship. It’s a matter of proxy between similar, like Jeff said, let’s say Maven or NPM, but it’s a relationship of bringing large language models into your organization through a proxy. But we do believe it could create some in intangible benefit for us. Got it.

Let’s talk about the guidance for a second.

Koji Keda, Software Analyst, Bank of America: Sure. You guys you know, we just talked about big deals. We talked about cloud usage. But how does that I mean, I know. Let’s talk about it.

Right? We know it’s not incorporated into the guide. Right? You guys are not including big self managed transition migrations Mhmm. To the cloud in the guide, and you’re not including usage, upside usage in the guide.

So why is that not included in the guide this year?

Ed Grabshied, CFO, JFrog: Yeah. First, let me explain why we chose to do this. And I talked a little bit about the transformation of the company four or five years ago when we went public to where it is today. A deal of a half a million dollars. If that deal pushed out, I could pull two or three deals from an out quarter into the quarter, and it didn’t have a significant impact on my revenue.

Today, when I take an 8 figure deal and that deal, because of the complexity of the deal, if I forecast for that deal to happen in a quarter and it pushes out, I don’t have deals, tens of deals that I can pull into the quarter to backfill that push. And so what we see with these large complex deals that you’re talking about that are a migration that have security elements on top of it, It’s not a matter of if, but a matter of when, and we must be patient. We saw this in Q2 of last year where we had forecasted a deal that was 99% of the time would close. It didn’t, and it had a significant impact to our ability to overachieve on the revenue side. Therefore we took a very cautious approach by de risking those deals and allowing those deals to mature and then come in as upside potential.

The second piece is the usage. And why don’t we include the usage? Well, we saw this in q one. The usage created a tailwind for us. It created a significant over outperformance in our revenue, but they can turn it off as well very quickly because it is not a commitment.

So today we have a bit of a disconnect between the developer that’s been pushed to innovate, to bring in new technology. And the other side, my office of the CFO and procurement that’s saying, hold on, I don’t necessarily have the budget yet. So let’s maybe ratchet down the usage until we can secure the budget. And so those discussions right now are a bit of a tug of war innovation that’s happening budgets and a very tight rigid purchasing environment that’s pushing back. So it doesn’t make sense for us to put that type of assumption into our guidance.

So we exclude that. The last piece is as we stepped into Q2 coming off of our guidance in February, it became incrementally uncertain. The market changed. You had tariffs on tariffs, not the liberation day. There was all kinds of things that were happening.

We had to take a more cautious approach and we balanced the over performance in Q1 with our prudence. And and this is why we took a more conservative approach going forward. And we believe that that’s the best approach, not only for us,

Koji Keda, Software Analyst, Bank of America: but for investors and shareholders. I’m gonna try. It is June. So, you know, it’s been a while since you guys reported. Any sort of update in the demand environment you could share with us?

Ed Grabshied, CFO, JFrog: It’s worth the effort to try because you will never know unless you try, but, no, I will provide an update after we close q two. I tried. Yeah. Okay.

Koji Keda, Software Analyst, Bank of America: Competition. Wanted to ask you a bit about that. You guys are we consider you guys next generation. Yeah. But JFrog is not new.

You guys were made last year, year before, you know, five year you’ve been around. Yep. And whenever we do our checks, it seems like the pool of competition is is quite small for you guys, and you guys are one of the disruptors and leaders there. And so why hasn’t another competitor emerged? What is it about the category that is difficult?

Mhmm.

Ed Grabshied, CFO, JFrog: Yeah. That’s a a great question. So let me give the competitor landscape first, and then we can talk about the differentiators. We are the only publicly traded company in that DevOps binary management tool infrastructure space. The closest competitor is a private company, PE backed company called Sonotype.

We also compete with a very, very small startup that is a cloud native tool. We don’t see them often, not even worth mentioning the name, but that they’re sub $10,000,000 So we’ve seen them kind of pop up. We’re not naive to think that somebody could come into that market. We also have the hyperscalers. They offer some type of container registry, very basic container registry technology as well.

So what is the differentiator for JFrog and how we built the moat and actually probably widen the moat is through our technology and the number of languages we support. We have a very deep technology stack in terms of the languages that we support, the security elements. At the end of the day, when you own the most critical asset, which is the binary. So JFrog owns that binary, it’s being stored with Artifactory. You are the company that can secure that asset as well.

And so now we’ve created a differentiator with our platform in security. Point Solutions today cannot operate on the security of binaries without having a proxy to JFrog. So we want to please the community and continue to delight the community. So therefore you maintain those relationships, but essentially you could cut them off. You could cut the oxygen off to these point solutions.

We choose not to do that, but most customers see advantage to two things, consolidation and to secure the most, the critical asset, which is your binary. And so as we continue to add more technology like MLOps, that moat becomes deeper and wider.

Jeff Schreiner, IR, JFrog: And I’ll just add quickly, Koji, I think on your question about why there haven’t been more, this is a fairly new technology. And I think the, you know, in the time that I’ve been at JFrog now almost, you know, over three years, I think the importance of the binary has grown. And so I think part of that is that it’s taken time to get to a level of sophistication and software development where individuals that are working on this technology are realizing the importance of the binary asset. And so I think that’s the unique part because I think binaries are the newest form of the software development software supply chain. GIT’s been there, observability production environments have been there.

This is kind of

Koji Keda, Software Analyst, Bank of America: a new aspect to the whole development process. You mentioned two things in your answer there that I wanted to touch upon, one, ML Ops, but two, you mentioned the hyperscalers and container registry. And so, you know, maybe good knowledge for me. I just kind of wanna understand when we think about the hyperscalers, do customers sometimes start with the hyperscaler option and then eventually graduate to JFrog? Or do they, you know, start with JFrog from the beginning and the ones that are on that container registry from an AWS or a hyperscaler, do they just kind of stick with it over time?

Yeah.

Ed Grabshied, CFO, JFrog: Yeah. We don’t necessarily see migrations coming from the hyperscalers to JFrog. What we would typically see if they’re sophisticated, they’re coming either from a competitor like Sonotype that have scalability issues or want to migrate to the cloud and are unable to do that, or they’re coming from a homegrown tool where they’ve built something to manage their binary, manage their binaries and distribute the binaries. They have a large organization. They’re unable to scale on the homegrown tool.

So they come to an automated tool like JFrog provides. You probably have smaller organizations that are using the hyperscalers for container registry that maybe want to operate on one or two languages. Those are not necessarily the right customers for JFrog. We’d happily take them, but because of the depth of our technology, the number of languages that we support, the complexities that we support. So less sophisticated organizations typically go to the hyperscalers.

They have different metrics in us. They’re looking at trying to generate as much traffic as possible. So they, by the way, we operate and work on the marketplaces of all three of the hyperscalers. And we work very closely in a partnership with those hyperscalers. They’re really looking for traffic.

They’re not looking to take the business from us, but they would happily bring a customer into their container registry solution if it’s a very simple basic case. Okay.

Koji Keda, Software Analyst, Bank of America: What’s the opportunity with NL Ops for you guys? Tell us a little bit about that.

Ed Grabshied, CFO, JFrog: Yeah. I’ll start and then Jeff, you can talk about the technology piece. Sure. As I mentioned in the beginning, we acquired Quark AI in Q of last year. We saw this as a huge opportunity for JFrog at that time, because we said, as this market is shifting more towards large language models, we’re creating there’s a new buyer here in the data scientists.

The data scientist is now creating these large language models in order to deploy those large language models, they become a binary. So they have to train them. They have to secure them and they have to deploy them as a binary. And we wanted to win that market. We saw it shifting and we made that acquisition in Q2 of last year.

We also saw that we wanted to get ahead of it because we were worried that valuations could change very, very quickly, which they have. So when we did the acquisition, maybe there was questions around it. Why are you doing the acquisition now? We did not get questioned at all around valuation, around the decision to acquire JFRA, I’m sorry, QuocAI. And the last piece of that is we saw an opportunity here with a product that we can integrate into our platform very quickly.

Unlike the acquisition we did with VDO on the security side, where it took a significant investment in terms of building the application to be a platform and integrate with JFrog. This was a product that we could add to our platform very quickly. As you saw, we released the cloud native version in Q1 and we’re getting ready to release the self hosted version this quarter. So it was the right decision from us and we believe we should win that based on the binaries. Yeah.

Jeff Schreiner, IR, JFrog: And to Ed’s point, when we talked about singing the national anthem as a comparison to the baseball game of where we’re at, What we have right now is that a lot of companies are tinkering and experimenting with ML in their organization. Perhaps we think that’s some of what we saw in the over usage in in q one. And what they would really like to do is look at the various platforms that they could use within the organization. So to Ed’s point, I think another key aspect there is that within six months, we were able to take this technology and meet the market when it’s ready to start utilizing and bringing this into organizations. I would say that we view that there are two gating factors right now before we see mass adoption of this technology across, you know, many enterprises.

And that’s within the industry determining what the monetization will be, How will JFraud be compensated for the value we provide? And what is the buyer willing to pay for that value? And on top of that, and given the rapid change, the speed of innovation that you’re seeing on the MLSEC op side and what AI can allow that hacker to try to do and bring into the organization, that will be another gating factor to a much more broader adoption. So we think that there’s people that are working within this today, but I don’t think that we’re really at a mass scale yet until some of these other broader gaining factors are really relieved.

Koji Keda, Software Analyst, Bank of America: Got it. Maybe a question here on the m and a strategy going forward. I mean, you guys did buy Quoc last year. You bought Vito a couple years ago. I think there’s a couple of other acquisitions in between.

Keep me honest there. I can’t remember. Yeah. How do we think about your m and a strategy going forward? Well, you

Ed Grabshied, CFO, JFrog: know, even before I talk about the m strategy, one of the strategies that we have is a focus on delivering free cash flow so that we have the capability of being able to react quickly. So we delivered 26% free cash flow margin in Q1. We continue to generate a significant amount of cash. This gives us that flexibility as when, as when to a shift in the market that we can react very quickly and do a transformational or even a tuck in type M and A acquisition. So we continue to focus on that to ensure that we’re nimble and agile.

We’re always looking at the market. I don’t know that we’ll do something transformational per se, but as we release JFrog ML and customers begin to use the platform, feedback will start to come back to our engineering team. We’ll identify if there’s holes in the platform and see how we would go and address that. That could be with the tuck in, but most of the focus today would be on ML and AI, not so much on the security side. We believe we’re well positioned in the security side.

We’ve invested heavily over that, in that domain over the last three plus years. And the focus will really be about delivering AI technology. But let’s talk about security for a second.

Koji Keda, Software Analyst, Bank of America: So you guys have delivered good revenue from security from essentially zero. Right? And so what how do we think about security as a growth vector over the next twelve to twenty four months?

Ed Grabshied, CFO, JFrog: It’s a big opportunity for us. There’s big budgets and security and we want to continue to penetrate that, but we’re still at the early stages of penetration. We don’t have, we have thousands of customers over 7,000 customers today. We’ve got more than half of those customers using JFrog X-ray, which is our tier zero security products. So we have an opportunity to penetrate through those customers that we know today are using X-ray.

You need to use X-ray to be able to use our advanced security products. So, you know, our focus is on that. We believe we have a long runway. It should be a huge growth driver for us going forward. And we continue to see that as a big piece of our business in the future.

Koji Keda, Software Analyst, Bank of America: Okay. How do we think about how you’re selling security? One of the things that we there’s often debated within DevOps is the ability for a a dev tool to sell into ops or security, security tool to sell the other way, ops. You get where I’m going with this. So how how are you

Ed Grabshied, CFO, JFrog: selling security? Yeah. You know, it’s interesting. Three years ago when we started to build our security team, we built a security overlay team. We brought security based architecture and solution engineers, and we’ve integrated those into our process.

So we have that overlay team, but we also saw a shift in the way that the customer is buying. Before you had the DevOps side, you had the CISO and the CIO, two separate budgets. You’re now starting to see that come together as a panel. So when we sell, it’s a matter of selling to a panel. You’ve got the developer that you’re selling to.

You’ve got the CIO and the CSO budget. Those are coming together to make a decision. So you have one point of contact in terms of your sales now that is selling an opportunity, the value proposition of JFrog. The the dev upside, the dev sec op side brought together as one value. Got it.

Got it. Got about a

Koji Keda, Software Analyst, Bank of America: minute and a half here, and we briefly touched upon free cash flow margins. You talked about how to how to how you guys think about free cash flow and m and a. But how how do we think about free cash flow overall? I mean, you guys just did 26%. Yep.

You know, your targets are 26 to 29. Right? So you’re kind of there. So how do we think about free cash flow generation and balancing that against growth, growth potential? Yeah.

That’s that’s a

Ed Grabshied, CFO, JFrog: great point. Balance. I’m gonna I’m gonna focus on that word. We’ve always had a focus on profitability and free cash flow. This was not something that all of of a sudden we, you know, this year or last year we said, Hey, the shift is going to be now on profitability and free cash flow.

That’s always been part of our DNA. In fact, you know, three or four years ago when the focus was around profitable growth and durable growth, we were being questioned about that. Today, there is no question. Companies are focused on profitability. We continue to balance innovation with profitability.

I’m not going to spend $3 to earn one. That’s never been part of the way that we operate as a company. I’ve been with the company for six years, CFO for one and a half, but that will remain part of my DNA. And and we will continue to look at generating value through free cash flow and profitability. Yeah.

Jeff Schreiner, IR, JFrog: And I’d I’d just add quickly, Koji. We think that as a rule of 40 that is driving what Ed and I and the management team at JFrog are trying to do, that now that portion of the rule of 40, a greater portion of that is coming from the free cash flow margin. Yep. And so that’s that was something that we thought would happen over time a few years back and the focus that we’ve put on that metric.

Koji Keda, Software Analyst, Bank of America: Got it. Jeff, Ed, we are all out of time. Thank you so much for doing this. This has been great, fun conversation. Yeah.

Thanks so much for being here. Thank you. You for having

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