Dynatrace, Inc. (DT) Earnings Call Transcript

Greetings, and welcome to Dynatrace's planned acquisition of Arize Conference Call. [Operator Instructions]. As a reminder, this conference is being recorded. It is now my pleasure to introduce your host, Noelle Faris, Vice President, Investor Relations. Thank you. Please go ahead.

Good morning, and thank you for joining us to discuss Dynatrace's planned acquisition of Arize. Joining me today are Rick McConnell, Chief Executive Officer; and Jim Benson, Chief Financial Officer. Before we get started, please note that today's comments include forward-looking statements such as statements regarding the expected benefits of the proposed transaction, expected financial impacts and deal timing. Actual results may differ materially from our expectations due to a number of risks and uncertainties discussed in Dynatrace's SEC filings, including our most recent annual report on Form 10-K and subsequent quarterly reports on Form 10-Q. The forward-looking statements contained in this call represent Dynatrace's views on August 13, 2026. We assume no obligation to update these statements as a result of new information, future events or circumstances. We also mention a non-GAAP financial measure in today's comments and refer you to our August 5, 2026, earnings release for additional information and related definition. Please note, we have included a supplemental presentation related to this morning's announcement on the Investor Relations website. And with that, let me turn the call over to our Chief Executive Officer, Rick McConnell.

Thanks, Noelle, and thank you all for joining us on such short notice this morning. We are very excited to discuss with you our proposed acquisition of Arize, the category leader in AI observability. From a strategic standpoint, we believe this acquisition will increase our exposure to the high-growth AI observability market, extend our end-to-end observability leadership position, advance our AI observability road map, expand our reach with developers, accelerate our ARR growth and add a world-class AI native team to Dynatrace. I'd like to cover a few of these areas in more depth to highlight our strategic rationale for this transaction, then turn it over to Jim to speak to some of the financial elements. We'll then open it up for your questions. First, the acquisition of Arize expands our market opportunity and strengthens our leadership position in AI observability and evaluations, a large and rapidly emerging category that we expect to exceed $10 billion by 2030. AI observability spans the full life cycle of an AI-powered application from continuous evaluation before and after release to real-time visibility into how LLMs, agents and orchestration layers behave in production to the impact they have on applications, infrastructure and business outcomes. During our earnings call last week, I indicated 3 core questions that AI observability must address, beginning with, is it working just as with traditional workloads. Second question is new. Is it accurate? Is the AI model delivering output that can be trusted and relied upon with confidence? And the third, are my agentic systems delivering the outcomes for which they were built. Enterprises are deploying agents to build software at a pace that wasn't possible before, and code must be built well, shipped safely and run reliably. Gartner describes the difference in AI observability well in their innovation insight on AI observability from May of this year. They say AI systems fail differently from traditional software. A misconfigured application typically produces an error that is visible, traceable and reproducible. An AI system can fail silently. It can generate confident, plausible sounding outputs that are biased or factually wrong with no corresponding alert in an infrastructure dashboard or application log. Back to our perspective, as AI evolves from simple prompts to autonomous multistep systems and increasingly operates without a human in the loop, visibility becomes increasingly critical. AI observability provides AI engineers, SREs and platform teams with the insights they need to debug, optimize performance, control costs and improve accuracy, helping to ensure AI-powered services remain reliable, efficient and trustworthy. A second area I'd like to cover is that acquiring Arize will accelerate our own AI observability portfolio and roadmap. Through this acquisition, Dynatrace will have an even stronger end-to-end observability solution from preproduction to production. Arize adds leading capabilities in AI and agent evaluation, experimentation and agentic workflow optimization across development and production. These complement Dynatrace's existing strengths in application and AI infrastructure observability, model performance and business impact. Together, these capabilities position Dynatrace to provide observability across the full AI stack, connecting model and agent quality with application performance, infrastructure health, AI usage and cost and business outcomes. This is not a point solution. It is a portfolio expansion that positions Dynatrace to better capture a greater share of AI spending in this rapidly emerging category. Third, Arize unlocks the developer audience for us. Through its widely adopted open source community, Arize has already earned the trust of AI developers who increasingly influence enterprise technology decisions. This acquisition will give Dynatrace direct access to this important audience while strengthening our position with AI-native companies. Horizon's strong engagement with developers, coupled with Dynatrace's deep enterprise relationships and global reach will create new opportunities to land, expand and deliver greater value as customers operationalize AI. Through millions of monthly downloads of Horizon's open source Phoenix platform, we believe there is a significant opportunity to accelerate ARR growth over time by further extending Dynatrace's reach into developer-led buying motions and AI-native workloads. And we have high confidence in our ability to sell our products together because numerous customers already use Dynatrace and ARS in unison, spanning industries from automotive to communications to e-commerce to financial services and more. We expect access to Dynatrace's customer base to further accelerate ARS's trajectory. And finally, to round out my remarks, as I mentioned, we're acquiring an exceptional team with deep AI expertise, strong roots in the Bay Area's AI ecosystem and what we believe is a terrific cultural match for Dynatrace. We're excited to welcome Arize's co-founders, Jason and Aparna, along with the broader Arize team to Dynatrace. We are focused on a thoughtful post-closing integration plan, and we intend to give the Arize team the runway to build on what they've created while leveraging Dynatrace's scale, engineering expertise and global reach to accelerate product innovation and customer impact. In summary, we are convinced that Arize is an excellent fit for Dynatrace. Adding Arize to the Dynatrace platform further reinforces our end-to-end leadership in the overall observability market and will create substantial customer and shareholder value. With that, I will turn it over to Jim to cover the financial aspects of this transaction.

Thanks, Rick. We are very excited about this acquisition. Under the terms of the agreement, we will acquire ARISE for a total consideration of $915 million, subject to customary adjustments, consisting of approximately $815 million in cash as well as replacement equity awards for Arize employees joining Dynatrace. We have sufficient cash on hand, along with our existing credit facility to fund the purchase price. In addition, our plan for ongoing share repurchases remains unchanged. We expect Arize to be immediately accretive to ARR growth and unlock significant cross-sell and upsell across our combined customer bases. While Arize is a small company, it is rapidly growing, and we expect it to add approximately 200 basis points to the Dynatrace ARR growth rate in fiscal '27. From a profitability perspective, we expect Arize to be approximately 175 basis points dilutive to Dynatrace non-GAAP operating margin in fiscal '27. For the anticipated synergies, we expect to generate incremental operating margin expansion from fiscal '27 levels into fiscal '28 and beyond. The acquisition remains subject to customary closing conditions, including regulatory approvals and is expected to close by the end of September or in early October. Given this timing, we do not expect any material impact to the Q2 guidance we provided last week. We will provide a more detailed update to our fiscal '27 guidance on our Q2 earnings call in early November. In summary, acquiring ARISE represents a significant opportunity to accelerate Dynatrace's leadership in AI observability, strengthen our long-term growth profile and create substantial value for both customers and shareholders. And with that, I'd like to open it up for questions.

[Operator Instructions]. Today's first question is coming from Matt Hedberg of RBC Capital Markets.

Congrats on the deal. Really, really exciting, I think, prospect for Dynatrace. I wanted -- something you said was super interesting to me, getting closer to AI-native customers. Obviously, that's an area that Dynatrace has been working on given kind of your existing global kind of 5,000 base. But I'm guess I'm curious, could you guys expand on how you see success there? And I guess, does it mean adding new sales reps to maybe better target some of these AI-native customers?

Yes. So let me take that, Matt, and Jim can add in. The first thing we want to do is we want to just continue to leverage the capabilities that Arize has already built. They have really strong growth. We want to continue to leverage that. Their sales force is focused on enterprise customers as well as AI natives, and they're expanding to include the benefit of this developer-led motion. We see the developer as being a quintessential part of this acquisition that we can then access not just for AI observability, but observability more broadly. We see developers being a core persona, if you will, in the observability decision. And so this brings that together as well. And then finally, back to the ICP or the overall customer profile, we absolutely do believe these capabilities enable us better access into the AI native cohort, and Arize is focused in this area as well. So I believe for a number of reasons, it really brings together this notion of selling into AI natives as an accelerant of our opportunity ahead.

The next question is coming from Will Power of Robert W. Baird.

Okay. Great. And I'll echo my congratulations as well here. Look, I mean, I guess, Rick, as you were evaluating opportunities to expand and bolster your AI growth opportunity, did you evaluate other acquisitions? And if so, what really made RISE kind of stand out among the options to go after this market more aggressively? And then maybe number two, for Jim, any other color you can share on ARR growth, what it's looked like over the last year? And is this ARR growth something we should expect to double, triple over the next year? I recognize it's still pretty early, but any other color there would be great.

I'll take the first one, Will, and Jim can take the second. On the first, relative to AI growth, it is fair to say that we have been watching the evolution of the AI observability market for some time. We have been investing in this area for the last 18 months in terms of internal investment, and this is an incredible catalyst to accelerating our road map to bringing in complementary capabilities that we haven't had on our road map. And as we look at a -- what we view as a 7-layer stack for AI-powered applications, the synergy with ARISE was simply better than anybody else in the market by far. Their offering is very sophisticated. We do see them as the category leader in AI observability from a pure-play standpoint. And that gives us capabilities, for example, in LLM experimentation, LLM observability -- so targeting both AI workloads as well as agentic workflows. It brings us the AI software delivery life cycle of components that we need to supplement the capabilities that we have at Dynatrace in model operations, cloud and infrastructure operations and elsewhere. So we -- as Jim has often put it, we're aggressive shoppers but very, very disciplined buyers. So Will, you can absolutely rest assured that we have spent a lot of time analyzing this market and believe fervently that ARISE is the most synergistic opportunity that we could have gone after and the biggest catalyst to the business for Dynatrace to come in the AI observability area. And maybe one last point is that we absolutely see observability entering a new era. And it is a new era in which it isn't just about business resilience. It is about AI reliability as well, and it is about ensuring that models and agents are working as expected. And these areas together are going to represent an explosion in observability opportunities as we look ahead. And for us, we wanted to play offense, and this is an opportunity to accelerate our ability to do so. Jim, on the second?

Very well outlined, Rick. A little color, Will, on their business that we're going to share more details about Horizon's ARR and revenue growth profile after the close. They're a small company, growing very rapidly. As I said in my prepared remarks, we expect it to contribute 200 basis points to our ARR growth, so call it, $40 million for fiscal '27. But just to give you a little bit more color beyond kind of just the ARR revenue stream, that isn't really the only reason why we were buying them. We're acquiring a category leader. There is huge...

I'm sorry, it seems like we lost Jim. Would you like me to move on to the next question?

Yes.

The next question is coming from Sanjit Singh of Morgan Stanley.

Dynatrace has historically had a pretty robust organic innovation engine pumps R&D. So I'd love to get a little more color, Rick, on the track that you guys are on in terms of autonomous operations, AI and more specifically how this acquisition Arize, which is the category leader, how that's significantly accelerated the road map. Just a little bit color behind the buy versus build decision.

Thanks, Sanjit. The way that we see the observability space is, on the one hand, we have the evolution of this $82 billion market for what we would think of as core observability or traditional observability, which is now getting supplemented by the end of the decade, this $10 billion AI observability space. Let me break those down into 2, and maybe it will help answer your question. In the traditional observability sense, the directional heading of that market is toward autonomous operations. And that involves agents leveraging deterministic AI and answers to be able to then to take action on those answers and insights to deliver a more automated outcome. And that is the holy grail, if you will. That's where we are headed. And we are spending, as you know, a lot of time on areas such as Dynatrace Intelligence to deliver both the deterministic AI elements of analytics and insights, along with the agentic AI capabilities and actions needed to deliver not only the intelligence engine, but also the AI control plane to provide for this automated operations outcome. So we've been spending within Dynatrace a huge amount of time there. But we've also been investing in the second area of AI observability in a number of different associated areas that I referenced earlier, cloud and infrastructure operations, for example, model operations, for example, business impact and application experience. But there are a number of areas where the Arize acquisition does fill in areas that we haven't been investing in at the same level of detail. For example, AI software development life or delivery life cycle. especially with regard to LLM experimentation and evals, LLM observability to make sure that we're dealing with things such as model drift and hallucinations. These are areas in which Arize simply leads in the market from our perspective as a category leader. And so we have been investing, as you suggest, we have been developing a really incredible innovation engine and an opportunity for acceleration in this area on our own, but it is such a critical moment in the era of evolution of observability that we wanted to take this opportunity to essentially become an AI observability category leader ourselves. And by putting together the innovation of Dynatrace with the innovation and product portfolio that exists with strong deployment at customers today by Arize, this is just an incredible opportunity to achieve both objectives.

The next question is coming from Ittai Kidron of Oppenheimer.

Congrats, guys. Looks super interesting. I guess, Rick, I wanted to ask more from just a pure technology standpoint. How do you see -- can you talk about the integration of the technology with your platform? How does this tie into? Help me understand how that process would work, the time line to completion? And is it -- what are the hurdles or challenges in doing this?

Sure. Well, the first element is that Arize is on a very strong growth trajectory all by itself, and we don't want to get in the way of that. So what we are not going to do in this transaction is go spend a year integrating immediately out the shoot all of the capabilities and lose that momentum. We have a solution with ARS or I should say, Arize has a solution with Phoenix with millions of deployments per month of LLM evals that is focused on open source. This is an incredible catalyst for the developer community and an opportunity for leverage growth into a PLG motion, product-led growth motion to come. We want to leverage that. We have 200 or so -- or I should say, again, Arize has a couple of hundred customers there in the enterprise category. We have obviously substantially more customers than in the same category at Dynatrace that we believe offer tremendous cross-sell, upsell potential of the Arize capabilities. So the first elements of business are to catalyze the Arize business by integrating really on the go-to-market side with Dynatrace and enabling Arize to continue on their own road map journey. Now you do correctly raise the issue of well, obviously, to get 1 plus 1 equals 3 over the course of time, you want to be able to integrate and leverage these technologies. And we will do so through a very thoughtful deployment and integration road map that we have put together as we look to the future, and that's going to evolve over the course of time at the appropriate time. You mentioned Grail, for example, that's a logical evolution of perhaps the ADB database that they use on the AX portfolio arise. And so that's something that we will look at. But again, that is not a day 1 focus. Day 1 focus is acceleration of the go-to-market opportunity and enabling them to continue to operate with the innovation engine and incredible velocity and speed at which they're developing today.

The next question is coming from Samik Chatterjee of JPMorgan Chase.

On the transactions here as well from my side. Maybe just a quick one. You did mention that there is a bit of customer overlap in the sense that you have customers that are using both Dynatrace and Arize. Can you just sort of talk to how much of a customer overlap do you see with ARISE already and flesh out the revenue synergy part of this a bit more when you sort of think about taking ARISE to your customers, what would be the sort of initial customer cohort that you think the product fits well with and where will we initially see -- which customer cohort would initially drive that revenue synergy?

Jim, we have you back?

Can you hear me?

I can. Yes. Do you want to take that one?

I can go back and finish up on Will's question from earlier before.

Yes.

So as you can imagine, this is -- Arize is relatively small. So they have 200 customers. I think the overlap between their customers and ours, I think, is about 20% to 30%. But if you think about it, I think Rick outlined it earlier, there is significant cross-sell and upsell opportunities within our installed base specifically to sell ARISE. This gives them immediate access to an enterprise customer base that they've already started to get penetration in. They're already in many Fortune 500 accounts. And so it's very complementary relative to Dynatrace from a customer base perspective. And then Rick also noted that they also have traction in the AI native builder community. So this gives us access to a community that we've been striving to get to. So we actually get a 2 for an ability to go after the AI native community, an ability to continue to penetrate Arize into the broader customer base. And the go-to-market motion is very synergistic with Dynatrace. And so we're quite optimistic that this is definitely a 1 plus 1 equals 3. And to finish off on Will's question around the ARR for the business, as I was saying, we are acquiring a category leader that the value is they -- it brings us continued AI observability leadership. It accelerates our road map. I mentioned the developer reach it gives us. I mentioned the customer expansion opportunity it gives us. And so Arize positions us in a clear leadership position and in a really attractive area of observability. And so we're quite optimistic about what this can bring. We mentioned 200 basis points of ARR growth. I might will cover upfront. It is near-term dilutive. But I want to be clear, we believe with synergies that this is near-term dilutive and that we will be able to drive operating margin accretion in fiscal '28 and beyond. So this is just a win-win across the board, and we couldn't be more excited.

The next question is coming from Eric Heath of KeyBanc Capital Markets.

I wanted to come back to one other element of Ittai's question, just get a better understanding of how similar or dissimilar is the data you're capturing for evals is to what you're capturing for production systems, whether it's logs, metrics, traces. And one other one, just if I could, on the AI native customers. Is there any frontier labs in this customer base? Any outsized customers to be aware of?

I'll take the first one on data. The primary data type that is used in evals is traces actually. And this is highly synergistic to, of course, the traces metrics, logs and capabilities that we store in Grail. So it all starts from the same foundation of core metrics, Eric, that we would be capturing otherwise. One of the differences is that, obviously, evals tends to happen in preproduction environment versus observability and what we do with Grail is primarily production-oriented. And that, of course, brings back one of the core motivations for the transaction is to really enable Dynatrace to radically extend left into the developer community because we do believe that observability starts with the first line of code. And that first line of code, by the way, as we've said in our earnings calls and elsewhere, is no longer coming from humans. That first line of code increasingly is going to be coming from agents. So the ability to capture evals on a preproduction basis using traces and other core data types of observability and then extending that all the way into a production environment to handle operations and then to triage issues and then to create a full loop, a full developer loop all the way back to the eval cycle becomes the domain of observability to come. It isn't just about throw a system into production and observe it and come up with and look at dashboards and try to create automated triage. It is so much more sophisticated than that in delivering not just resilient systems from the first line of code that's written by agents all the way through the ability to ensuring that AI is delivered reliably with answers that can be trusted to be provided to end users. And so this is really the cycle to come of what we're looking at delivering here on an integrated basis. And there's huge synergy in the underlying data types.

Yes. And Rick, I'll offer on the customer side. So they do not have any of the frontier model companies as customers. But what I will say is at their most recent customer conference, they had the frontier model companies actually speaking at their conference. So they are very well integrated into the AI community in a significant way. And then your second question around customer concentration, they don't have any customer concentration. Again, they sell to the enterprise and they also sell to these AI native companies. And so as I mentioned earlier, it's very synergistic to what we do, and it goes after an audience and a profile of companies that we've been aspiring to get to.

The next question is coming from Mike Cikos of Needham & Company.

Congrats on the announcement. I was just hoping to get a little bit more color on the negotiations that played out here, particularly because both Datadog and PagerDuty were obviously investors in the Series C round. Can you talk about what the competitive bidding dynamic was like or how competitive this deal was overall?

Do you want me to take that?

Yes.

Go ahead, Jim.

Sure. As you can imagine, Mike, in any situation like this, that this is a very attractive asset in a really exciting space, and they are a category leader. I will tell you that there was huge interest on their part of the combination of Dynatrace plus ARIS. So one of the benefits we had was they saw the potential of what they were doing and their vision of where they were and combined with Dynatrace, what they were going to be able to extend to. As Rick outlined in his earlier comments around kind of pre-praud to fraud, as they've been going within their eval models, they've been requested by customers, well, can you do this and can you do that? And so it was very synergistic with Dynatrace. And so in that regard, I think we were in a very good position that there was strong interest on their part to partner with Dynatrace.

Yes. I would -- it's a good question, Mike. I would just supplement Jim's comments to say this is a highly sought-after asset and company as being a category leader in AI observability, which is obviously a very hot space. Having said that, and I don't want to speak for Jason Aparna, the co-founders of Arize, but I would say that from the very beginning, we felt that this was just hugely synergistic on both sides. What's interesting is that I remember back to some of the earlier conversations with them, their comments that, geez, we're focused mostly on pre-prod and we're getting pulled into production, but that would entail really riding and evolving a substantial set of capabilities where Dynatrace already existed and vice versa. And we're each trying to fill in the missing pieces on the respective sides of pre-prod and Prad. Bringing these together was just always viewed by both of us as hugely synergistic with a team that is just an awesome, awesome AI native development team that is building at incredible velocity. And when we put all of that together, we just thought that this was, I would say, mutually just an exceptional combination. And I'm super excited to proceed for it to get it closed and get moving in the market.

The next question is coming from Matthew Martino of Goldman Sachs.