Teradata - Earnings Call - Q2 2025

Executive Summary

• Q2 delivered a clean headline beat: non-GAAP EPS $0.47 vs S&P Global consensus $0.40*, revenue $408M vs $400M*, with results at the top end of revenue guidance and EPS above expectations; recurring revenue and total revenue declined YoY as services remained a headwind. Values retrieved from S&P Global.*
• Management reiterated full-year Cloud ARR growth (14–18% cc), Total ARR (flat to +2% cc) and FCF ($250–$280M) and tightened FY25 total revenue to -5% to -7% cc; GAAP EPS to $1.04–$1.12 and non-GAAP EPS to $2.17–$2.25.
• Mix continues to shift toward recurring (87% of revenue) and cloud (Cloud ARR +17% YoY to $634M; cloud net expansion rate 112%), while services pressure weighed on gross margin; cost actions aim to restore positive services gross margin in 2H25.
• Near-term setup: management flagged ARR linearity (pulled-forward deals) which implies a softer Q3 ARR before re-accelerating in Q4; however, ARR/FCF outlooks were reaffirmed, while the FY revenue range was lowered on services bookings softness—key stock catalysts balance EPS beat/AI momentum vs. cautious revenue/linearity commentary.

What Went Well and What Went Wrong

What Went Well

• EPS and revenue execution: “finished above the high-end of our recurring revenue outlook range, at the top end of our total revenue range, and EPS outperformed our expectations” (CEO); non-GAAP EPS $0.47 vs $0.40* estimate; revenue $408M vs $400M*. Values retrieved from S&P Global.*
• Cloud momentum and retention: Cloud ARR reached $634M (+17% YoY as reported; +15% cc); cloud NER 112%, driven by balanced migrations and expansions (~50/50).
• Hybrid/AI product cadence: Newly launched AI Factory (on‑prem with NVIDIA), MCP Server for agentic AI, and expanded LLM Ops/ModelOps underpin the hybrid AI thesis and new workloads cited across banks, logistics, and financial services (prepared remarks).

What Went Wrong

• Topline/margins under pressure YoY: Total revenue down 6% YoY; non-GAAP gross margin 58.3% vs 62.2% last year; services revenue -19% YoY and negative services gross profit dragged consolidated gross margin lower.
• Services mix headwind: CFO highlighted services as a clear headwind to revenue and margins; cost actions taken to return services gross margin to positive in 2025.
• Linearity creates near-term air pocket: Pulled-forward deals improved Q2, but management expects Q3 cloud ARR below the annual target range and a modest sequential decline in total ARR dollars in Q3 before a step-up in Q4.

Transcript

Speaker 4

Thank you all for standing by. Today's conference call with Teradata will be starting shortly.

Speaker 0

Good afternoon. My name is Breaker, and I will be your conference operator today. At this time, I would like to welcome everyone to the Teradata second quarter 2025 earnings call. All lines have been placed on mute to prevent any background noise, and after the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you would like to withdraw your question, please press star then two. Thank you. I would like to hand the conference over to your host today, Chad Bennett, Senior Vice President of Investor Relations and Corporate Development. You may begin your conference.

Speaker 3

Good afternoon and welcome to Teradata's 2025 second quarter earnings call. Steve McMillan, Teradata's President and Chief Executive Officer, will lead our call today, followed by John Ederer, Teradata's Chief Financial Officer, who will discuss our financial results and outlook. Our discussion today includes forecasts and other information that are considered forward-looking statements. While these statements reflect our current outlook, they are subject to a number of risks and uncertainties that could cause actual results to differ materially. These risk factors are described in today's earnings release and in our SEC filings, including our most recent Form 10-K and in the Form 10-Q for the quarter ended June 30, 2025, that is expected to be filed with the SEC within the next few days. These forward-looking statements are made as of today, and we undertake no duty or obligation to update them.

On today's call, we will be discussing certain non-GAAP financial measures, which exclude such items as stock-based compensation expense and other special items described in our earnings release. We will also discuss other non-GAAP items such as free cash flow, constant currency comparisons, and 2025 revenue and ARR growth outlook in constant currency. Unless stated otherwise, all numbers and results discussed on today's call are on a non-GAAP basis. A reconciliation of non-GAAP to GAAP measures is included in our earnings release, which is accessible on the Investor Relations page of our website at investor.teradata.com. A replay of this conference call will be available later today on our website. I will turn the call over to Steve.

Speaker 1

Thanks, Chad, and hello everyone. Teradata delivered well in Q2 as we continue to see improved execution across the company. We delivered a total ARR of $1.49 billion in Q2, up 2% year over year as reported. This gives us additional confidence in our ability to achieve our full-year targets. We are seeing improvements in linearity in both expansions and renewals, resulting from the go-to-market actions that started in the middle of 2024 to improve our sales execution. We experienced better deal execution in Q2, with some deals closing in the quarter that had been expected in Q3. We see customers recognizing the importance of and the value of strong data management capabilities to underpin their AI and GenAI initiatives. We meaningfully improved overall retention rates again in Q2, and we expect this to continue for the full year 2025.

Thanks to the team's positive efforts in managing ongoing contracts with customers, we were able to extend some contracts into the back half of the year. From a cloud perspective, we delivered ARR of $634 million as we see continued migrations and expansions. The solid 15% constant currency cloud ARR growth is in line with our full-year guidance range of 14% to 18%. I'll start the quarterly update with the new executive leadership members we recently brought on. During our last earnings update, we introduced Sumeet Arora, our new Chief Product Officer, and I'm pleased to have John Ederer, our new CFO, on the call today. In the quarter, we also announced Scott Rogers as our new Chief Administrative Officer as we streamlined our people and law functions.

These veteran executives are here to help our ongoing strategic execution as we position the company to accelerate growth and deliver ongoing durable free cash flow. They have proven track records and have acted with urgency to make important marks on the business in a short period of time as we work to return to growth and drive long-term returns for our investors. Additionally, we realigned our marketing function into our GTM and product organizations. Integrating these functions is designed to gain operational efficiency and increase agility and speed in execution as we unify our approach to developing our pipeline and serving our customers. This restructuring supports our growth objectives while removing costs to optimize our operating margin. I'm confident that we've got the right leadership team to address the market's changing priorities and to take advantage of AI as a value driver.

The pervasive interest in AI and GenAI is leading to growth across the industry and increasingly in a hybrid environment. We see companies incorporating the deployment option that works best for each need, whether cloud, on-prem, or a hybrid approach. We are building on our cloud growth and leveraging our strength in on-prem to provide customers with the hybrid data and analytics environments they need. We believe that customers' investments in high-quality trusted data will pay dividends in high-quality trusted AI outcomes. Our differentiated capabilities are designed to deliver consistent, world-class data and analytics across an open and connected ecosystem. We help customers incorporate what is right for their business, regardless of the deployment option they choose. Agentic AI is the now industry topic, and we introduced a number of innovation advancements that we believe are keeping us ahead of the curve.

With our recent Teradata AI Factory announcement, we are bringing AI and machine learning capabilities on-prem. Integrated with NVIDIA AI Enterprise, companies in regulated industries or those that have data sovereignty requirements or want more control over their AI deployments can now have private AI with the security, governance, and cost control of on-prem. Enterprise Vector Store that we announced last quarter is now generally available. It is aimed to cost-effectively combine structured and unstructured data with the speed needed to get value out of complex business challenges. This is a crucial infrastructure component for building trusted and efficient AI systems. It is designed to help customers move beyond basic GenAI implementations towards sophisticated agentic AI use cases like customer complaint analyzer and augmented call center. We also recently announced our open-source MCP (Model Context Protocol) server.

MCP is the industry-standard technology that enables AI agents to interact with backend data platforms to get the context needed to make smart decisions. In developing agentic AI initiatives, the challenge is not just about building smarter models; it's about giving those models access to the right context. With this technology, we expect to enable our customers' AI agents to connect to the Teradata systems and leverage ClearScape analytics to both report on and build predictions around business processes and operations, ultimately significantly increasing the usage of the Vantage platform. This is designed to be enabled through trusted enterprise data cost-effectively and at any scale. This combination can empower organizations to move beyond isolated AI experiments and deploy intelligent context-aware agents that drive real business outcomes and value. We also introduced LLM Ops, enabling enterprises to accelerate how they deploy, manage, and monitor language models.

LLM Ops is a capability in Teradata ModelOps 8.1. It is designed to support rapid deployment of NVIDIA inference microservices and enable users to select from over 80 models and deploy them directly into GPU environments. We believe that this technology supports rapid deployment of GenAI applications, including RAG pipelines, and is designed to accelerate time to market for AI/ML initiatives. We have expanded support for Teradata OTF with access to Iceberg and Delta Lake tables across AWS, Azure, and Google Cloud. This enables Vantage Cloud Enterprise customers to begin OTF testing and application development as they build future-ready enterprises. Of course, we deliver these innovations in support of one goal: helping our customers achieve massive value from the data and analytics, which in turn helps us continue to grow. I'll walk through a few examples.

We're helping one of the largest banks in the world and a longstanding customer to build an anti-money laundering analytics capability for its financial claims division. Here, our customer-focused innovation base helped co-develop this analytics platform to the customer's needs. This is an example of how we are leveraging AI and ClearScape analytics to enhance sales to our base. A multinational bank in APJ is using GenAI with Teradata to improve its customer experience. In this AI for CX use, we are processing 50,000 interactive text conversations a week on complex data. This helps rapidly identify friction points with customers to improve customer satisfaction and unlock significant value for the bank. We're helping a large European logistics company deliver on its strategic initiative to drive digital transformation across its broad set of operations by integrating relevant data to accelerate and innovate its business. A U.S.

financial services company established a new on-premises Vantage ecosystem in their new private cloud data center to modernize current platforms with growth from increased workloads driven by operationalizing AI with Teradata ClearScape analytics. Finally, a Middle Eastern financial institution added Teradata, replacing a longstanding competitor to improve its customer's experience. We're also gearing up for our annual customer event, Possible, the trusted AI and data conference. We'll have a robust suite of speakers from many fantastic customers, as well as leading partner companies and industry experts. We will be hosting this event in LA on October 6 through 8. There are many more details on our website. We remain focused on accelerating innovation and value for our customers across an open and connected ecosystem as they implement AI initiatives. We do this with a global network of industry-leading partners, and Q2 was a great quarter of partner collaborations.

In May, we announced a new data integration with ServiceNow's Workflow Data Fabric. This integration is designed to connect, understand, and activate customer data on the ServiceNow AI platform to fuel AI agents, autonomous workflows, and analytics at scale. Teradata also participated in the Salesforce announcement, expanding its AI agent ecosystem, Agent Exchange. Agents built in Agent Exchange can easily discover and connect to our MCP server through Agent Exchange. This is designed to provide the enterprise context that powers trusted decisioning. For instance, an agent could request the next best recommendation based on customer history, sentiment, and/or behavior in order to deliver a relevant offer to our customers in real time. In Q2, we also announced a new partnership with Fivetran to transform data pipelines for rapid AI insights.

Together, we expect to simplify data integration for our customers by automating data movement from hundreds of sources across the enterprise into Teradata. With this integration, Teradata and Fivetran can empower customers to leverage all of their data for complex AI workloads and drive trusted AI at scale, reducing engineering overhead so teams can focus on insights, not pipelines. We will continue to invest in innovations and partnerships that make it easy for our customers to build and achieve value from their agentic AI solutions with Teradata. As I turn the call to John, I'll summarize Q2 as a quarter of progress on many fronts. As we have restructured the company and executed, we built a solid foundation for longer-term durable free cash flow growth for the company. Our deep data and analytics capabilities position us well to address the secular drivers in technology resulting from AI.

After solid execution in the first half of the year, we have increased confidence, and we are reiterating our outlook for ARR and free cash flow metrics for the year. As we look ahead, we see the opportunity for greater operating leverage and free cash flow growth from our ongoing work to optimize our expense envelope. I'll pass the call to John.

Speaker 3

Thank you, Steve, and good afternoon, everyone. In the second quarter, we finished above the high end of our recurring revenue outlook range, at the top end of our total revenue range, and earnings per share outperformed our expectations. Total ARR grew 2% year over year on a reported basis and was flat from a constant currency perspective. Our cloud ARR growth rate was 17% reported and 15% in constant currency, and our cloud net expansion rate was 112%, performing in line with expectations. We continue to see a balanced mix of migrations and expansions driving our cloud ARR. While acknowledging the boost from currency this quarter, we did achieve total ARR growth sooner than anticipated this year as we were able to pull in a few deals early and extend to other customers from a retention perspective.

The timing of these deals will have some impact on our Q3 ARR metrics, but we continue to believe that we are on track to achieve total ARR growth in Q4 on a constant currency basis, and we are reiterating our FY25 outlook for total ARR, cloud ARR, and free cash flow. In terms of our detailed financial results for the second quarter, total revenue was $408 million, down 6% year over year as reported and 7% in constant currency, which was at the high end of our outlook. Recurring revenue was $354 million, down 4% year over year as reported and in constant currency, which was one point above the high end of our outlook. Upfront recurring revenue had a negligible impact on the growth rate. Recurring revenue as a percentage of total revenue was 87%, up from 84% in Q2 last year.

Services revenue was $51 million, down 19% year over year as reported and 20% in constant currency. While the services business has been a headwind this year for total revenue growth, we expect that a higher mix of recurring revenue will ultimately provide a stronger business model with better margins. Looking at profitability and free cash flow, please note that I will be referencing non-GAAP numbers for expenses and margins, and a full reconciliation of the GAAP results is provided in our press release. For the second quarter, total gross margin was 58.3%, which was down year over year, primarily due to the headwinds in our services business.

In line with our ongoing focus to proactively manage productivity, we've taken cost actions in Q2 to enable us to return to positive service gross margin in the second half of 2025, and we will continue to optimize costs as we manage the business. Recurring gross margin was also impacted by year-over-year revenue, primarily due to headwinds stemming from our ARR performance last year and increasing cloud mix. Operating margin for Q2 was 16.4%, which was impacted by lower revenue and gross margins. Looking specifically at operating expenses, the actions that we took last year resulted in lower SG&A expense in dollar terms that was partially offset by investments in R&D. Non-GAAP diluted earnings per share was $0.47, exceeding the top end of our outlook range. The outperformance is primarily from higher revenue.

We generated $39 million of free cash flow in the quarter, which is flat on a year-over-year basis. Finally, in the second quarter, we repurchased approximately $28 million of our stock, or 1.3 million shares, and we continue to expect to return at least 50% of our free cash flow to shareholders in the form of share repurchases. Turning to our outlook for the remainder of the year, for the third quarter of 2025, we expect recurring revenue to be in the range of -4% to -6% year over year on a constant currency basis. We expect total revenue to be in the range of -7% to -9% year over year on a constant currency basis. We expect non-GAAP diluted earnings per share to be in the range of $0.51 to $0.55.

While we do not typically provide quarterly guidance on total ARR and cloud ARR, I did want to point out a shift in linearity that we are seeing in the business. As noted, we were able to pull in some deals into Q2 and extend some other customers, which resulted in Q2 total ARR and cloud ARR coming in above our expectations. However, due to this shift, we anticipate that Q3 cloud ARR will dip below our target range for the year, but we are still reaffirming our full-year target. For total ARR, we anticipate a modest sequential decline in dollars from Q2 to Q3. For FY25, we reaffirm our guidance for cloud ARR, total ARR, recurring revenue, and cash flow, and these ranges can be found in our Q2 press release. We are tightening the ranges for the full year on the following metrics.

For total revenue, we are updating the range to -5% to -7% year over year in constant currency due to lower services bookings and anticipated revenue. For earnings per share, our updated outlook for GAAP EPS is $1.04 to $1.12, and for non-GAAP EPS is $2.17 to $2.25. Based on FX rates at the end of July, our reported total ARR and cloud ARR growth rates should be approximately 100 to 200 basis points above our constant currency growth rates in Q4 2025. For revenue, we do not anticipate any currency impact to our full-year outlook. Finally, we expect the non-GAAP tax rate to be approximately 23.1% and the weighted average shares outstanding to be $96.5 million for the full year. Again, please refer to our Q2 earnings presentation on our Investor Relations website for a complete list of our 2025 outlook ranges.

In closing, I'm very excited to join the company at a time when our hybrid trusted AI platform is becoming increasingly important in the market. I look forward to working with Steve and the rest of the team as we continue to transform Teradata and drive a profitable growth strategy. I believe we are taking the necessary steps to set ourselves up for improved profitability and durable free cash flow growth, which should, in turn, drive shareholder value. Thank you all for your time today. Now, let's open the call up for questions.

Speaker 0

At this time, I would like to remind everyone, in order to ask a question, press star then the number one on your telephone keypad. We'll pause for a moment to compile the Q&A voiced there. In the interest of giving everyone the opportunity, we appreciate that you limit yourself to one question and one follow-up. The first question we have on the line comes from Erik Woodring with Morgan Stanley. Erik, your line is open.

Great. Thanks so much for taking my question, guys. John, welcome aboard officially now. Steve, I wanted to circle back with you. You made a comment right before you passed it to John that I thought was interesting, and you said, you know, we see an opportunity for greater operating leverage and free cash flow looking forward as you optimize your OpEx envelope. Can you maybe just unpackage that comment a bit for us, just to kind of help us understand what you mean either from a size, a texture, or even a timing perspective? I have a follow-up, please. Thank you.

Speaker 1

Yeah, thanks for the question, Eric. Maybe John could add a little bit of color commentary as well. Clearly, as we're going through the year, we've optimized our cost and expense envelopes, and we're going to continue doing that as we go through the rest of the year. The key driver for us, though, and something that we're pretty confident in given our execution in the first half, is clearly returning the company to growth. The execution that we've had in the first half of the year has given us some assurity in terms of our outlook to returning to total ARR growth in the fiscal year 2025. From an operating perspective, I think we've built the foundations for durable free cash flow growth, and that is then being compounded by our ARR, our outlook to grow our ARR in the full year.

As those both reflect into our outlook for fiscal year 2026, we see that durable free cash flow growth is a real opportunity for us to drive forward into the future. John, I don't know if you want to add anything.

Speaker 3

No, I think that's very well said. I wouldn't add much in terms of specific numbers for FY 2026, but I would say that I think we are laying the foundation this year. We're taking the action that we need to. We talked about some of the things specifically in the second quarter, but we're really setting ourselves up to have a strong finish to this year and then look out to next year as well.

Okay, thanks. Maybe I should have asked these questions in reverse order because, you know, Steve, I wanted to get after kind of what you alluded to, which is from a kind of top line and demand perspective and client engagement perspective, what's next, right? You highlight solid execution in the first half of the year, obviously a couple moving pieces between 2Q and 3Q, but solid execution is what you need to do today. What's next? How are you playing kind of offense from here? Help us understand, you know, help us kind of dream the dream, so to speak, of where this model in this story can go as you think about the changes you've made over the last 12 months and the dividends that they could pay out over the next 12 months, so to speak. Thank you.

Speaker 1

Yeah, thanks, Eric. I think the changes that we put in place in terms of go-to-market execution mid-year last year have made a good delta in terms of our overall execution and sales execution in the market. Underpinning that really is the underlying demand for the Teradata technology set, and especially in our abilities to execute in a hybrid environment. That open and connected ecosystem that can expand across both on-premises environments and cloud environments is something I think that's resonating very well in the marketplace and very well with our customers. I think the age of AI and agentic AI is really powering that as well. I think that is setting us up to address a new target addressable marketplace from an AI workload perspective.

Our most recent announcements with Teradata AI Factory, which is an on-prem solution to deliver AI solutions for our customers in their most trusted environment behind the firewall, as well as having those capabilities extend out into the cloud, gives us some real opportunity to drive growth and workload usage on the Teradata platform, both in the cloud and on-premises. Those two factors together will enable us to drive forward. In addition, we've done a really good job over the last four to five years growing our cloud business to over $630 million now. Still got really good growth rates from a cloud perspective. We reported 15% year-on-year growth in Q2. Really solid growth there. We do see the AI workloads from an on-premises perspective helping stabilize and actually get some growth in the on-premises marketplace. These together actually set us up for good subsequent future growth.

Thanks so much, Steve. Good luck.

Speaker 0

Your next question comes from Tyler Radek with Citi. Your line is open, Tyler.

Speaker 3

Thank you for taking the question. Steve, maybe first one for you, encouraging to hear some outperformance on ARR in the quarter. Sounds like a lot of it was timing related, pulling in some deals from Q3. I was just curious, was this driven by the customer? Was this more just better execution in terms of managing the sales pipeline? Did you see these deals come in stronger than you expected as well, just in terms of the expansion potential? I assume these were cloud deals because the cloud sequential growth was pretty strong. Anything you could expand upon in terms of the deals that came in? Are you expecting now any type of headwind in terms of sequential growth into Q3? Thank you.

Speaker 1

Yeah, thanks, Tyler. We're really happy with the team's performance in Q2. Deal execution was clearly ahead of the pace. Obviously, whenever the sales team can, they will close a deal as early as they can. The team's been doing a lot of work on linearity and making sure that we improve linearity. Therefore, our execution in the first half and in Q2 in particular has given us a lot of confidence in terms of execution for the full year and getting back to total ARR growth for the full year. The dynamics that we see is actually our customers want to take advantage of the Teradata platform. They want to do that both on-prem and in the cloud. We saw good growth in the quarter in both of those facets, both behind the firewall and also in the cloud.

The hybrid capabilities of our platform and how we're positioning that platform in our customers' environments in terms of being the trusted custodians of some of the customers' most valuable data, making that available to AI solutions inside the customer environment, I think is really driving some interest and workload for us. It's given the sales teams an opportunity to take a really powerful value proposition to our customers, especially when we combine that with the offers and capabilities that we've got. What I would say is as we execute through and look at the second half of the year, it has given us some faith in terms of returning the company to that total ARR growth in FY 2025.

Speaker 3

Okay, great. Then on the margin side, it sounds like there were some optimizations in the quarter. I know you talked about the move away from service, lower margin services revenues, and then some consolidation within the go-to-market function. It didn't look like you really raised profitability guidance too much. Just curious, is there more conservatism in that? Are you sort of redeploying some of those savings into R&D and just help us understand, as you assess the cost space here, what the timing for additional steps and unlocks could be. Thank you. Yeah. Sure. This is John. I'll take a stab at that one. I would start off by saying I think we're doing a good job overall on managing expenses up and down the P&L.

If you look at some of the revenue headwinds that we have this year that are implied from our guidance, to be able to be tracking towards an operating margin percentage that's on par with last year is no small feat. I think the team has done a great job of managing this along the way. In terms of some of the specific operating expenses on the SG&A side, Steve mentioned some of the actions that we took last year that actually resulted in a year-over-year decline in terms of dollars spent on SG&A. We did reinvest some of that back on the R&D side of things. We're going to continue to invest in innovation that will support our profitable growth strategy. Overall, I think we're doing a good job of managing expenses and, like we said earlier, laying the foundation for durable free cash flow growth.

Speaker 0

Thank you.

Speaker 3

Thank you.

Speaker 0

Your next question comes from the line of Radi Sawson with UBS. You may proceed.

Awesome. Thank you. Maybe first for Steve, as you think about the second half of the year, just curious, what do you see as the biggest catalyst behind migrations to Vantage? Is there any way to think about what portion of those migrations are related to a GenAI use case?

Speaker 1

Yeah, thanks for that question. I think I would point to two market shifts of note in terms of our customer conversations that we're having. The first one is, you know, we're starting to track a significant pipeline of AI influence growth for the Teradata platform. We're seeing these workloads being deployed both on-prem and in the cloud. That's really playing to our strength of having a hybrid platform, having a platform that can run these workloads on-prem and give customers real capabilities around AI with trusted data and great data management on-prem. A lot of our customers that migrate and deploy in the cloud with us retain a hybrid model. That's something that really differentiates us from an execution perspective.

I think the second shift in terms of cloud migrations is we are seeing a reduction in the number of what I would call pure play cloud migrations where the customer is looking to migrate to the cloud to generate some form of cost optimization. I think a lot of customers are realizing the value of the cloud comes from the flexibility and agility and the services that are available in the cloud rather than a cost play. I think our customers are being more sensitive to where they are migrating their data to make sure that they get the best value out of that. We've talked in the past about some stage migrations. That is really manifesting now in our use of Teradata's hybrid capabilities.

There's a bank in Australia which is deployed across the cloud and on-prem utilizing Query Grid to link all of its data together across, you know, a fairly complex environment. I think we're seeing our customers start to take advantage of those hybrid capabilities that only Teradata can bring to the marketplace. I think these together, those market shifts together are helping us deliver that cloud growth of 15% in Q2 and also pointing us in the right direction for total ARR growth for this year.

Awesome. Super clear. A follow-up for John. Given this is your first quarter as Chief Financial Officer, just curious, what did you see in your first few months at Teradata that gave you confidence in underwriting the current guidance framework, especially those linearity comments around Q3 and Q4?

Speaker 3

Yeah, I mean, I think there's almost two different questions in there. Just in terms of the guidance overall, I think we looked at several things, but if I kind of step back and take a look at where we are at the midpoint of the year, I feel like we're in good shape. We've actually executed well against the plan and did a little bit better than anticipated on the ARR metrics in Q2. That certainly helps. I think a second factor is the work we've been doing on erosions. Last year was a difficult year from an erosion perspective. We've actually had quite a bit of improvement this year, and when you think about that from a modeling standpoint, that really helps in terms of the overall visibility.

I think as we sit here at the midway point, we feel good about the execution we've had over the first half, and that gives us a better sense for how well we can do over the course of the year. The last couple of things I would point to is just the new products are really starting to generate some interest, especially AI. Steve just talked through all of those, but we're starting to see those come into the opportunities that the sales team is working on. I think all of those factors come together to help support the second half outlook. Obviously, we need to still go out and execute, but the opportunity is there.

Awesome. Super clear. Thank you, guys.

Speaker 0

Your next question comes from Chirag Ved with Evercore ISI. Your line is open, Chirag.

Hi, thanks for taking the question. Steve, what are you noticing about how companies are thinking about on-premises versus cloud deployments in this AI world, especially when it comes to modernizing their data estates, and how this might be similar or different from what you might have seen or heard over the past year? Thanks.

Speaker 1

Yeah, thanks, Chirag. I think the world of agentic AI is really powered by access to data across environments. I think we're seeing a lot of our customers, especially the very large customers across the world, thinking about how their data estate is deployed and then working out what the modern access and management capabilities that they want to put in place to actually execute AI workloads against those data. The great thing about the Teradata platform is that we can preserve data gravity. We give customers the choice of deploying either on-prem or in the cloud and get the same capabilities and the same great function and features and functions both behind the firewall and in the cloud, operating in that hybrid environment. I think we're tending to see an increase in the interest in terms of our on-prem platform.

Indeed, we're seeing some new logo activities where we're selling net new systems on-prem, especially in regions and markets where data sovereignty is incredibly important. Having a capability that enables customers to take advantage of the most recent AI models, be it large language models, operating on-prem and executing that with a trusted data management and governance capability, which Teradata supplies, is really driving some customers' decisions about where they place their data and how they get access to those AI applications.

Thanks, Steve. Maybe one quick one for John. It looks like cloud net retention rates drop sequentially. Do you see cloud growth in fiscal year 2025 being more driven by new cloud customers and net new migration or by stabilization and/or expansion in the metric? Thanks so much.

Speaker 3

Sure. No, thanks for the question. I would say it's probably more of the latter. We've continued to see pretty consistent results in terms of the drivers of growth. We've got roughly 50% of our cloud ARR growth coming from migrations and about 50% coming from expansions. That can vary a little bit by quarter, but in general, that's the trend line that we see, and that's what we would expect to see for the rest of this year.

All right. Thank you so much.

Speaker 0

Thank you. We now have Matt Hedberg with RBC Capital Markets. Please go ahead.

Great. Thanks for taking my questions. Steve, you started the prepared remark talking about agentic AI and how you're thinking a lot about it from a Teradata perspective. I'm curious how would you expect to monitor usage or success from a customer basis there? It seems obviously it's a topical conversation among customers. How would you define success there?

Speaker 1

Yeah, I think we're defining success on a couple of dimensions. One, I'll talk about partner. From a partner perspective, we're engaging with a number of partners that are very successful and critical in terms of executing this AI world. The two examples I gave were ServiceNow and Salesforce. We're super excited about the partnership that we have with ServiceNow, and ServiceNow are excited about the partnership with Teradata because they see the opportunity to utilize, analyze, and for Teradata to develop the signals out of the customer data is an example that we have in the Teradata platform, and then to trigger workflows in the ServiceNow platform or trigger workflows in the Salesforce platform to actually get some form of execution. I think one of the dimensions is the work that we're doing with partners in terms of leading-edge use cases and the development of the leading-edge use cases.

The second is the proof of concept that we're doing with customers. Early customer engagement in terms of the advanced technologies that we've got. Some of the work that we're doing in terms of customer complaint analyzer, taking some of our vector capabilities and utilizing vector capabilities as well as running language models both inside the Teradata environment, but also sitting next to the Teradata environment. I gave some examples in the prepared remarks of a bank in Australia that's doing just that in terms of combining structured SQL-based insights from a data perspective with some language model capabilities to look at how they impact their overall customer satisfaction is a great use case. The third dimension is really looking at our opportunity pipeline. We started measuring and managing the opportunity pipeline in terms of opportunities that are being influenced by AI workloads inside our customers.

That's really driving utilization for the Teradata platform inside our customers. As we look at holistic execution in this AI and agentic AI marketplace, we're really rapidly advancing some of the capabilities that we need. For example, we recently announced our new MCP server that will enable us to work in the agentic space. That was as a direct result of some of the work that we're doing with our customers and the deployments that we're getting engaged in. Super excited about really an incremental target addressable marketplace for us from an AI perspective.

Great, thanks for that. John, for you, curious if you, you know, what sort of the thought process on the recent R&D tax changes, you know, do you think that might have an impact for you guys next year? Any way to kind of think about the potential benefit of that?

Speaker 3

I do think there could be some impact from that, and it'll probably show up on the cash flow side of things. It's a little too early for me to give you specifics on that, but it's definitely something that we're taking a close look at, and it's something that could impact, positively impact cash flow this year as well as next year.

Great. Thanks, guys.

Speaker 0

Thank you. Your next question comes from Wamsi Mohan with Bank of America. Please go ahead.

Hi. Thank you so much. Steve, on the Teradata AI Factory, how do you see the revenue there evolving, and how much revenue uplift could you see from this over time? Curious if you could share maybe any color on the pipeline, the type of customers, because investors have generally been waiting for some traction in enterprise AI adoption. Given your comments about that fitting in on-prem, how do you think that evolves? I have a follow-up.

Speaker 1

Yeah, just as thanks for the question, Lamsey. Just to educate all, Teradata AI Factory is our capability that brings the power of AI to enterprise. They're looking to deploy and scale artificial intelligence solutions with trust, control, and speed into hybrid environments. That's both on-prem and in the cloud. There are a lot of benefits that that gives to our customers in terms of enabling them to actually really deploy real production-oriented workloads and solutions from an AI perspective. Clearly, it's early days in terms of our release of the Teradata AI Factory, but we are very excited, especially when we look at our partnership with organizations like NVIDIA, where we can take an NVIDIA GPU farm and essentially place a dedicated Teradata instance running our capabilities from the AI Factory perspective, leveraging that GPU instance to run real AI workload on-prem with trusted data for our customers.

Early days from a revenue perspective and ARR perspective, certainly seeing a lot of interest in that in the marketplace. We're excited about how that's going to drive in the short term usage of the Teradata platform, but then longer term dedicated Teradata instances both in the cloud and on-prem to deliver these workloads.

Okay, thanks, Steve. Maybe one for John. Sorry if I missed this, but can you talk about the magnitude of what you think were deals that got pulled forward from Q3 to Q2? Clearly, obviously, you highlighted some on the public cloud side, but in overall terms, how would you quantify that magnitude? Should we expect to see some of that behavior persist given some of the more broader macro uncertainty around tariffs and other things like that? Thank you.

Speaker 3

Yeah, sure. We did not quantify the magnitude, and I won't give you a specific number here, but I will describe kind of the shape of what we're talking about. I think this was an earlier question. My apologies, I neglected to come back to it. In terms of cloud ARR, we actually made great progress in Q2, and we were a little ahead of schedule as we were able to pull in a few of these deals early and extend some other customers. I think the company had previously commented that we expected the first half of the year to be toward the bottom end of our annual guidance range for cloud ARR growth. We came in a little bit better than anticipated in Q2. With some of that timing, we've effectively changed the slope of the curve for cloud ARR this year.

At the beginning of the year where we were expecting a more linear path from Q2 to Q3 to Q4, we've now had a bigger step up in Q2. We'll be a little flatter in Q3, and then we'll step up again in Q4. I think that's probably the best that I can quantify it for you here. We don't typically provide quarterly guidance on these metrics, but we did want to give you all the heads up in terms of this change in dynamic.

Okay, thank you so much.

Speaker 0

Your next question comes from Derek Wood with TD Cowen. Your line is open.

Speaker 2

Hi, team. This is Jared Jungjohann on for Derek Wood. Thanks for taking my questions. I'm understanding that eight-figure deals have been excluded in guidance. Can you talk to what you've been seeing with these larger engagements?

Speaker 1

Yeah, thanks for the question, Jared. I think we characterize it by really de-risking our outlook from an eight-figure deal perspective. The good news is that from an exit sales execution, our go-to-market team has a number of paths to get to our outlook for the year, both from a cloud perspective and a total ARR perspective. Our absolute focus, though, is to drive growth in total ARR because that's really going to give us the profitable revenue growth into next year in terms of growing a recurring revenue stream. The profitability of a recurring revenue stream is certainly the most profitable segment that we have, and that will obviously lay the groundwork for some durable free cash flow growth as we move forward.

The execution that we've seen in the first half of the year in terms of both a retention perspective and getting meaningful improvement in retention against that outlier from a retention perspective in 2024, as I said, is in good stead in terms of that execution. In terms of just taking advantage of the market opportunity that's in front of us, the hybrid opportunities, I've seen that on-prem has some real strength in terms of being able to deliver meaningful growth. The fact that we've now got that big cloud business, we've got over $630 million, and as we grow that at, you know, mid-double digit, mid-teens in terms of growth for this year, that has some meaningful growth impact to our numbers as well. A number of different paths to execute in terms of both eight-figure deals and some smaller deals as well.

We're pretty confident about the execution as we move into the second half, and the sales team's doing a great job.

Speaker 2

Okay, I appreciate that caller. One more for me. I believe you guys started to introduce open table formats in early 2024. Now that we're a little bit along with those efforts, can you just talk to, for the customers that have adopted these, how have those companies' ACVs been trending? Thank you.

Speaker 1

Yeah, our OTF strategy has always been to support both Apache Iceberg and Delta Lake without locking any of our customers into one structure or another, giving them that real choice of deployment. I've always stated that I believe that OpenTable format would actually be a tailwind for us in terms of the more data that you make available to the Teradata platform and the Teradata engines, the more usage of the platform that we'll get, and therefore that incremental usage driving bigger Teradata systems and execution. Certainly, as we've continued to increase our analytics capability and portfolio, I talked about the ability to bring your own language models into the Teradata environment and combining that and opening up as much data as possible inside a customer environment really does give us a tailwind from an execution perspective.

I think as our customers are looking at OpenTable format and the OpenTable formats that they've got inside their environment, they're working out how to use the Teradata platform to execute that analytics strategy and all of the analytics functions that we've got inside the Vantage platform against that data source. Just as an example of doing that, we've got a customer in Latin America who actually replaced the Databricks analytics solution with using Vantage analytics to actually run highly performant analytic capabilities at a fraction of the cost and incremental improvement in performance. We see the opportunity to help customers modernize their data and analytic environments, and OpenTable format continues to be a tailwind for us.

Speaker 0

Thank you. We now have Raymond Lenschau with Barclays. Your line is open.

Hi, this is Sheldon McMeans on for Raymo. Thanks for taking our question. First, for Steve, can you help further contextualize the improvements in retention rates you discussed in your prepared remarks? Maybe how should we think about the drivers of that between better sales execution, maybe some of the AI-related solutions that you've come out with that shows your future-proof roadmap, and just general improvement in the macro environment because it does seem like we're past kind of the peak uncertainty on the tariff front.

Speaker 1

Yeah, I think just from a retention perspective, as we said all along, we did know that 2024 was going to be an outlier from an erosion perspective, particularly in our on-premises business. Looking back, we actually started to see those improvements in the second half of 2024. We saw that improvement continue in 2025. As we said all along, as we looked at the guidance that we gave for our full year at the start of the year, we're going to see that, and we expect to see that meaningful improvement to our retention rates for FY 2025 overall. I think you're absolutely right from a tariff and a macro perspective. We've done an assessment as our cloud business grows, that is a little bit more immune from a tariff perspective.

From a macroeconomic environment, I think there has been some scrutiny on discretionary spend that's impacted our consulting billings at the start of the year, as we've spoken to already. I think we are starting to see a little bit more confidence from a macroeconomic perspective, and we're expecting good execution to continue and deliver a good full year 2025 result.

Understood. Thanks for that. I believe in the prepared remarks, it included commentary about a quarter-over-quarter decline in ARR expected in Q3. We'd love to hear what are some of the driving factors of that, as I would think that the pull forward from Q3 into Q2 would be relatively neutral as that would still be in the Q3 balance there.

Speaker 3

Yeah, that was some of the comments that I made just a few minutes ago. In general, we're expecting to see a change in the slope, if you will, for this year. Where we had expected to see a more gradual climb, particularly in cloud ARR through the year, we saw a bigger step up in Q2, a little flatter in Q3, and then we expect to see it step up again in Q4. In terms of total ARR, we're actually tracking a little ahead of the plan. We were hoping to get back to positive territory by the end of the year. We actually got to positive growth this quarter, now with a little bit of help from currency, but even on a constant currency basis, got back to flat this quarter. I think we're tracking pretty well.

We may see a slight decline in total ARR in Q3, but feel like we're very much on track for the full year.

Got it. Thanks.

Speaker 0

Thank you. We now have Pat Walravens with Citizens Bank. Your line is open, Pat.

Hi, guys. Thank you for taking the question. This is Nick on for Pat. Steve, one for you to start. NVIDIA recently published a research paper highlighting the efficiency of SLMs for handling more routine agentic tasks. Is this consistent with what you're seeing across your customer base, and are you noticing increased interest or adoption of SLMs for enterprise agentic AI workloads?

Speaker 1

Yeah, that's a great question. In fact, we are seeing customers deploy small language models like Hugging Face to, you know, give specialized results. It could be in terms of looking at customer feedback or call center interactions. Instead of putting that through a large language model, using a really specialized small language model, the really exciting thing for us is our massively parallel architecture that we deploy on-prem and in the cloud is really well suited to running these small language models. In some tests with one of the banks in the U.S., we actually ran the Hugging Face model on our parallel CPU architecture, and it actually ran better than running it on an NVIDIA GPU. This was clearly very exciting for our customer in terms of utilizing a small language model in the Teradata environment very effectively and efficiently to get some really great business outcomes.

We absolutely see the small language models as being a good opportunity for us, and it really emphasizes the words I used were open and connected. We don't want to be locked into any one particular language model as some of our competitors have done. We want to be able to enable our customers to have a full deployment choice and to use the language models in the right place, whether that's behind the firewall or in the cloud. They can choose which language model to use both in terms of size, but also in terms of what brand to use. That's the great thing about having that open and connected ecosystem.

Fantastic. That's super interesting. One follow-up, John, for you. It's been around three months since you were appointed as Chief Financial Officer. What is one thing that's gone better than you expected and one thing that's been more challenging than you expected?

Speaker 3

Sure. I'll start on the positive side of things. I think that, you know, you look at the Q2 results, and we obviously started off with a solid quarter, so that makes my job a little bit easier coming in. On the other side of the coin, it's just a matter of getting to know a new business. There's a lot to learn when you come into any new company. I do think there are some complexities to what we do here at Teradata, both from a technology standpoint as well as from a business model standpoint. Getting up to speed on all of those elements.

Speaker 4

Something that I've been very focused on in the last few months.

Speaker 0

Great. Thank you guys so much.

Speaker 4

Thank you.

Speaker 3

Thank you. I can confirm that does conclude the Q&A session, and I would like to hand it back to Steve McMillan for his final remarks.

Speaker 0

Thank you very much, operator, and thanks everyone for joining us today. We remain absolutely focused on profitable revenue growth, and we believe that our differentiated hybrid analytics capabilities are going to deliver that for us. We're super excited about the opportunities ahead as companies move into production with AI and agentic AI initiatives. It's a real additional opportunity for us. We're looking forward to executing. Thanks again all for joining us today.

Speaker 3

Thank you. This concludes today's conference call. You may now disconnect.