From a financial rationale, look, the business itself and the product of Lorne is going to continue as a stand-alone individual product, as we’ve said. As Scott mentioned in his remarks, over 200,000 customers now, it’s got a fantastic brand, and it’s the leader in that space and is a fast-growing standalone business in and of itself. Secondly, we believe for ourselves, there’s obviously a lot of opportunities in video and combining our video infrastructure team with Loom’s video infrastructure team. We have video as a first-class citizen across our platform family of products today. But obviously, the long capabilities will improve that in each of our spaces, whether that’s in service management or in broad business collaboration or, of course, in software teams.
And lastly, there’s obviously an opportunity for us to combine products, as you’ve seen us do a little bit already with Atlassian together to cross-sell Loom as a product into our existing base of more than 265,000 customers. So, we think it’s a fantastic deal. We’re super excited about the product we’ve been customers of it for a long time. I know think it can do great things as part of the Atlassian family.
Operator: Your next question comes from Kash Rangan from Goldman Sachs. Please go ahead.
Kash Rangan: Hi, thank you very much. Nice to see the stability in your end markets. I was curious to see, what do you think about the data center growth rate at 42%. It seems to be outpacing the Cloud, probably should be flipped the other way. I’m sure you would like that, and we would like that too. Any refined thoughts on how you view the data center business growth profile? And the things you might be doing incrementally in terms of functionality for the cloud product that would make it more of a compelling value proposition for the customer to go cloud as opposed to server products? Thank you so much and that’s it.
Joe Binz: Yes, Kash, this is Joe. I’ll start. You’re right. It was another strong quarter for data center at 42% growth. That was slightly ahead of our expectations, and it was driven by really strong renewals, migrations from server and seat expansion with an existing customers. It’s worth noting we’re growing a significant installed base on data center, which is a great stepping stone to the cloud for those who are currently blocked for moving to the cloud at the moment. And it’s a good sign of how committed customers are to the Atlassian road map and platform. And having a big installed base on data center is a high-class problem to have because that will fuel future migrations to the cloud. Cameron?
Cameron Deatsch: Yes. I’ve had dozens of conversations with many of our largest customers about this exact decision that many of them are making. And the reality is we see having both cloud and data center as a long-term competitive advantage. For Atlassian, we provide optionality for these customers in the coming years. As far as the functionality perspective, the good part is, there is very few customers where we have not been able to handle all their scale, their data requirements, their privacy requirements, their compliance requirements, or their needs for customization to cloud. So rarely is there a technical conversation where customers can’t go to cloud. It’s really just are they ready? Can we move the migration? Where is that — where are the stat in their business?
And is there the compelling functionality to move them over. In every one of those conversations, the customers understand cloud is in their future. It just comes down to the timing to get them over. But either way, an investment in data center investment in cloud is a longer-term strategic investment in Atlassian to get them further committed to Atlassian. And I know and we’ve shown with our track record that we can and we’ll move data center customers to the cloud along with their business needs.
Operator: Your next question comes from Fred Havemeyer from Macquarie. Please go ahead.
Fred Havemeyer: Hey, thank you. Good to be catching up on this call. I wanted to focus in on how you’re thinking about AI overall as an overarching strategy. And I can’t fail but notice, of course, your new Chief Marketing Officer has a PhD in Machine Learning. A number of your product offerings you’re describing, of course, including Loom, being able to integrate generate AI-related summaries. Just it seems like there’s an overarching theme here? Of course, you spoke to a part of it, but from top to bottom, it seems like you’re trying to become more like an AI-focused company as well. So perhaps, could you elaborate on that? And just how you think of the ongoing Atlassian branding and what value might be marked? And perhaps being more of an AI-first company. Thank you.
Mike Cannon-Brookes: Thanks, Fred. Look, I can take that first, and then Scott can follow-on. Yes, certainly. Great observation. I’m not sure if you or ChatGPT observe that, but Zenith does have a PhD in machine learning. She’s also our CMO and fantastic that will obviously be in addition to her capabilities in AA marketing, but obviously not the singular reason for bringing on board. Look, I think AI we couldn’t be more excited by AI and live language models at Atlassian, right. We take the view that it’s a huge opportunity for us for a number of different reasons. I think, in each of our markets, this technology transformation will be a huge change in the ability to deliver value to customers, which is where great software businesses are built.
We have a lot of very valuable data from our customers that we are the custodians of. And a lot of that data is textual and increasingly, video and audio effectively becoming text with AI. So we have a lot of their data, which is really important in AI to be able to give them fantastic answers or magical experiences. Secondly, we have a fantastic platform that we spent a lot of time building. So you see that in Atlassian Intelligence features that we’ve already shipped. Our ability to shift those features to all the products in the family simultaneously is a result of new on a decade of building a cloud platform, having the customers’ data centralized having singular editor and UI surfaces. So our ability to get features out to customers, we’re incredibly, incredibly bullish on beyond just our ability to build them.
And thirdly, obviously, with our world-class engineering team and our R&D capabilities, this is a technology transformation. And so you need to fundamentally build new products or build additions to existing products or build features or change the way features are built. That takes a lot of internal R&D and expertise, and we have that in space. So we feel incredibly excited about what AI can do for our customers fundamentally and what value we can deliver. Look, we’re in the business of amazing products and delivering the right customers. It’s like someone has given us a whole new painting set to paint with a whole new set of materials that we can create out with. And so we’re extremely excited. We are certainly placing that at the center of our philosophies on building products.
I think that’s what software companies are doing. I’m not sure when people say, AI first company exactly what that means, but we are certainly heavily investing in our AI capabilities, all of the governance and privacy and responsible technology principles that are required to do that well for customers and give them the right data providence when we give them answers of any form. But also making sure that we deliver those capabilities and that we are investing in and how we can do that. And this is going to take a few years to play out, but we’re certainly really, really excited. Scott, anything you’d add on to that?
Scott Farquhar: Yes. Just a couple of things. We all know that AI is driven by unique data sets, and you can provide unique experiences when you have unique data sets. And if you look at what like has done over the decades we’ve been in business and the data we have, it’s a really unique advantage for us. Firstly, our products are opened by default, which sounds like a simple thing, but — if you want to train AI on data inside your organization, is that data can’t be isolated to a few people. And if you use Confluence, you, as one of our customers, you have decades’ worth of data that’s available to train their AI on and help them make decisions. That’s a really big part of our advantage. The second one is that we have breadth across what we do in terms of the workloads and what people use our products for span the entire organization.
