Good afternoon. My name is Charlie, and I will be your conference operator today. I would like to welcome everyone to the Teradata Third Quarter 2025 Earnings Call. I will now hand the conference over to your host today, Chad Bennett, Senior Vice President of Investor Relations and Corporate Development. You may begin your conference.

Good afternoon, and welcome to Teradata's 2025 Third 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 September 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. And now I will turn the call over to Steve.

Thanks, Chad, and thanks, everyone, for joining us today. Q3 marked another quarter of solid execution as we beat our revenue and recurring revenue guidance ranges. We delivered non-GAAP earnings per share of $0.72, soundly ahead of our outlook, and we delivered free cash flow ahead of expectations. We posted our second consecutive quarter of total ARR growth ahead of our initial target of the fourth quarter. With a return to total ARR growth ahead of schedule, we have strong conviction in our durable growth path and expect this growth to continue in 2026. We also expect that the return to positive ARR growth, combined with the cost savings and productivity measures we've taken will result in meaningful free cash flow growth. Whether in cloud or on-prem, we are helping organizations build the data foundation and are delivering the enterprise context required for AI solutions. And we see the shift in our business from classic EDW towards the autonomous AI and knowledge platform. We see enterprises reevaluating how to cost-effectively deploy Agentic AI. As we have noted for the past several quarters, we are seeing a resurgence of hybrid environments, which reflects a growing understanding of how enterprises can best leverage both on-prem and cloud capabilities. It isn't just about choosing between environments anymore. It's about effectively operating across both to meet diverse business needs. Our platform is designed to give customers the opportunity to run Agentic AI at scale, wherever that data resides in their business in public cloud, on-prem or private cloud. Interest in AI and in particular, Agentic AI continues to grow in virtually all industries. However, most companies are still in the early stages of deploying this technology, and Teradata sits squarely at the center of this revolution. We believe we provide the enterprise context that AI agents need to deliver trusted, reliable results at scale. Without this knowledge, even the most advanced models can be just plain wrong. This shift also creates a very specific opportunity because Agentic AI with its 24/7 always-on query potential can increase workloads on data platforms by up to 25x and use 50x to 100x the compute resources than what was required by previous modern analytic workloads. Teradata is uniquely built to handle these mixed workloads and high volumes of tactical queries as enterprises deploy potentially thousands of agents and evaluate millions of relationships across thousands of tables to make a single decision. Milliseconds matter. We not only manage the critical enterprise data that powers these AI systems, but we also can deliver the performance required at the level of performance and scale that AI needs. Teradata was built for these types of enormous workloads based on our massively parallel architecture, patented workload management, and query optimization that is designed to provide a high-performance environment with predictable costs that can deliver the most complex AI workloads. Our patented QueryGrid data analytics fabric provides seamless high-performing data access, processing, and movement across multiple data sources. Our industry data models are built on decades of working with the Global 1000. And through these, we bring deep context to language models, another area where we can bring unique benefits to our customers. We believe Teradata is the best autonomous AI and knowledge platform for Agentic workloads and that our platform provides the best price performance, whether on-prem or in the cloud. In the quarter, we were named a leader in the Forrester Wave Data Management for Analytics platforms, and the report noted that Teradata is a good choice for organizations seeking to support hybrid cloud DMA deployments, especially where reliability, scalability, and high availability are essential. We're building the capabilities for the future to enable AI speed and scale. Earlier this year, we announced Enterprise Vector Store, a capability that enables organizations to include unstructured data and their integrated knowledge foundation. We also enhanced ClearScape Analytics with unified ModelOps capabilities designed specifically for Agentic AI. These provide seamless native support for open-source models as well as CSP model APIs. We launched our MCP Server to deliver faster context autonomously, and we've recently taken several more significant steps to further our position. In September, we announced Teradata AgentBuilder, a suite of capabilities designed to accelerate the development and deployment of autonomous contextually intelligent AI agents. Now in private preview, it leverages open-source frameworks, our MCP Server, and deep semantic access to enterprise data across cloud and on-prem environments provided by our knowledge platform. Customers can develop their own agents or use ready-to-deploy Teradata agents to accelerate implementation and deliver rapid impact. Launched at our Possible event last month, Autonomous Customer Intelligence is a software and services offering that embeds Teradata agents across the customer experience or CX journey. These agents can uniquely leverage four decades of Teradata innovation and contextual knowledge from solving mission-critical industry-specific data challenges. Our integrated approach makes sure our agents are extensions of the enterprise data platform and broader knowledge ecosystem rather than generic tools that fail to deliver meaningful impact. To help customers transform AI pilots into production-ready Agentic solutions that deliver significant business value, we also launched new AI services. These new services are intended to make Agentic AI a reality at enterprise scale by combining embedded experts, proven methodology, and Teradata's best-in-class autonomous AI and knowledge platform. Using a sprint-based use case-driven approach, Teradata AI services offer flexible tiered offerings that meet organizations at any stage of their AI journey from initial pilots to enterprise-wide Agentic deployments. Unlike competitors who offer either consulting or technology, we believe Teradata uniquely delivers both, enabling real-time context-aware agent decisioning that leverages our suite of AI tools, trusted data, and decades of industry innovation. Working with our partners in an integrated approach accelerates deployment of autonomous intelligence, CX or otherwise to drive measurable business outcomes. We have forward deployed resources with deep expertise and talent. These AI/ML engineers and data scientists are working with customers across the globe, positioning Teradata as a leading AI/ML player and helping customers move from proof of concepts to production. This team is on track to complete more than 150 AI engagements with customers this year. We're also seeing a significant turn in our pipeline towards AI-fueled projects. Let's look at a few examples of wins from the quarter. These demonstrate the breadth of our offers in hybrid environments, cloud and on-prem. A multinational automotive manufacturer is expanding its Teradata Cloud platform on AWS to support increasing AI/ML workloads as it combats cybersecurity. Executing approximately 10 million SQL statements per day, the customer is moving beyond rule-based approaches and adopting AI/ML technologies to enhance its analytical capabilities. One of the largest U.S. health care providers deepened its strategic alliance with us as it further scaled its Teradata cloud deployment running on Microsoft Azure. This expansion, building on momentum from earlier this year, underscores the provider's continued confidence in our high-performance cloud platform to support mission-critical data and analytics workloads. With this expansion, the organization is further positioned to drive operational excellence and harness complex health care data at scale across its entire system. A leading Japanese heavy industry manufacturer chose Teradata for its on-prem data platform as it transforms to a data-driven manufacturing entity and improves operational efficiency. A Central European financial services company recommitted to us through a seven-year partnership with Teradata as a Service on AWS. This enhances security, provides uninterrupted operations through disaster recovery systems that match production, supports monthly innovation testing, and meets stringent data sovereignty requirements. We recently held our annual customer event named Possible. It was three days of high energy with our people, partners, and customers speaking of what they are doing now with data and analytics and what they are looking ahead to do with AI and Agentic AI. It was our pleasure to recognize VodafoneThree, Ooredoo, and Sicredi at the conference for demonstrating exceptional creativity, technical excellence, and business impact through the use of AI on the Teradata AI and Knowledge platform. VodafoneThree in the U.K. was recognized for deploying an AI-supported fraud detection framework by leveraging AI to detect and mitigate fraud that has strengthened customer trust, improved regulatory compliance, and enhanced operational resilience. Ooredoo Qatar, a leading Doha-based telco, earned this award for its advanced analytical capabilities and AI-powered customer engagement strategy. This strategy is built on Teradata VantageCloud and ClearScape Analytics, which were integrated with and run on GCP native services. Sicredi, Brazil's largest financial cooperative, was honored for its innovative use of ClearScape Analytics and our cloud platform to transform credit risk management as well as support sustainability initiatives. Most recently, Sicredi has also begun developing an AI agent to support provision analysis under Brazilian banking regulations, further strengthening its governance and risk management capabilities. We also held our first AgentBuilder workshop at the Possible event. This hands-on workshop was oversubscribed and packed with customers keen to build AI agents on Teradata. We're in the process of launching an online AgentBuilder experience to help accelerate the development and deployment of autonomous, contextually intelligent AI agents. It will be available from our website in the coming weeks. We held our annual partner forum concurrently with the Possible event, and we had strong year-on-year growth in partner participation. Companies that will win in the Agentic AI future will be the ones that create the most trusted interoperable foundation that lets every other AI innovation flourish. We believe that's our role in the ecosystem. We strive to be the trusted data foundation that makes everyone else's AI work better with the governance layer that lets companies experiment safely. We're partnering across all layers in the ecosystem, and we have strong partner co-sell activity in the third quarter, validating the strength in our ecosystem and identifying and nurturing new opportunities. While at our event, I hosted a fireside chat with one of our partners, ServiceNow. We discussed how together we can power autonomous operations at scale by combining our enterprise-grade analytics with ServiceNow's workflow engine. Our platforms work together to enable seamless integration, governance, and automation. We're collaborating to help customers realize the full potential of their data, delivering intelligence and automation at enterprise scale. This is how we enable AI-native transformation for our customers, empowering organizations to break down silos, unlock real-time intelligence, and transform every part of their business. By combining deep analytics, trusted data, and intelligent workflow automation, we're enabling organizations to move from passive data collection to active Agentic operations, delivering real-time insights, proactive engagement, and measurable business value. Exciting stuff, and that was just one of the leading partners that participated with us. We also hosted a number of industry analysts, and a comment from Constellation Research summarized our focus on helping provide context to AI, noting that we believe there is no AI without context. That context isn't just data. It's the metadata, business logic, and domain know-how that make AI decisions relevant and reliable. Without business context, even the best algorithms can't deliver the accuracy or explainability needed in real-world regulated environments. They also recognized that we are turning our decades of decision analysis experience into domain and industry knowledge models that give AI agents real context. And that our context intelligence framework captures how industries actually operate, so organizations don't have to start from scratch as we help teams build agents faster with enterprise-grade performance, governance, and trust already built in. Our hybrid capabilities are resonating in our customer base with interest in our recent product introductions, AI Factory, MCP Server, and AgentBuilder, giving us further conviction that we offer a unique value proposition. We provide the flexibility to have consistent data, compute models, workloads, outcomes, and experiences across a hybrid environment. We have full confidence in total ARR and are affirming our outlook for 2025. In our recent discussions with customers, we have seen how the Teradata Knowledge platform is ideally suited for AI workloads. AI is always on with ever-increasing agents driving massive complex query volumes. That's Teradata's sweet spot. Our ARR mix may vary as we see customers evaluating between cloud and on-prem for where to deploy the workloads as they build for their AI-enabled future. Regardless of the deployment options they choose, customers can rely on Teradata to run Agentic AI at scale and provide the context needed for trusted results. Thank you very much. Now I'll turn the call over to John.

Thank you for joining us this afternoon. I'm happy with the progress we've made this year, as we have consistently met or exceeded our guidance for three consecutive quarters. We anticipate this trend will continue into Q4, and we are reaffirming our full-year guidance. In the third quarter, our total ARR growth surpassed expectations, marking our second quarter of positive growth. We exceeded our total revenue and recurring revenue guidance. Our gross margin improved compared to Q2, and we reported significant upside in our non-GAAP earnings per share while increasing free cash flow year-over-year for both Q3 and the year-to-date. As mentioned, we are laying a strong foundation this year for continued financial improvement next year. In terms of detailed financial results for Q3, total ARR grew by 1% as reported and remained flat in constant currency. This marks our second consecutive quarter of total ARR growth, driven by better retention and expansion efforts. Our initial goal was to achieve positive total ARR growth by Q4, so we’re pleased to be ahead of schedule. Cloud ARR grew by 11% on both an as-reported and constant currency basis, with a cloud net expansion rate of 109%. We anticipated cloud ARR growth in Q3 would fall below our yearly guidance due to the pull forward of several deals from last quarter. Total revenue for the quarter stood at $416 million, a 5% decline year-over-year as reported and 6% in constant currency, yet it exceeded our outlook due to higher recurring revenue. Recurring revenue was $366 million, down 2% year-over-year as reported and 3% in constant currency, which was again above our expectations. Recurring revenue made up 88% of total revenue, up from 85% in Q3 last year. Our services revenue was consistent with prior performance at $47 million. We are transitioning in our services sector this year, moving from migration projects to delivering AI services, which we believe will enhance performance going forward. Looking at profitability and free cash flow, I will refer to non-GAAP numbers for expenses and margins. For Q3, total gross margin was 62.3%, increasing by 70 basis points year-over-year. Sequentially, gross margin rose by 400 basis points thanks to improvements in both recurring and services gross margins. Recurring revenue gross margin increased to 68.9%, rising by 140 basis points sequentially. We addressed previous cost misalignments in our services segment, resulting in a significant improvement in non-GAAP gross margin from negative 2% in Q2 to positive 8.5% in Q3. The operating margin for Q3 was 23.6%, up 110 basis points year-over-year and up 720 basis points sequentially. Overall, we're witnessing margin improvements due to cost-efficient measures initiated last year. Our non-GAAP diluted earnings per share reached $0.72, surpassing the high end of our outlook by $0.17, driven by better recurring revenue and lower expenses. We generated $88 million in free cash flow during the quarter, reflecting a 28% year-over-year increase, bolstering our confidence in our full-year outlook. Additionally, in Q3, we repurchased around $30 million of our stock, totaling 1.4 million shares, with a goal of returning 50% of our free cash flow to shareholders through buybacks this year. Looking ahead, for the fourth quarter of 2025, we project recurring revenue may decrease by 1% to 3% year-over-year on a constant currency basis. Total revenue is expected to decline by 2% to 4% year-over-year on a constant currency basis. We forecast our non-GAAP diluted earnings per share to range from $0.53 to $0.57. For fiscal 2025, we're reaffirming our prior total ARR growth guidance and maintaining our cloud ARR growth range. We are confident in our total ARR target and still see a pathway to meet our cloud ARR goals for the year, although some deals are still under customer evaluation, which could affect the balance between cloud and on-premise subscription ARR. We also reaffirm our previous guidance for recurring and total revenues. Given our guidance ranges for Q4, we expect recurring and total revenues to land at the midpoint of our fiscal 2025 targets. Based on strong year-to-date performance, we are narrowing the free cash flow projection to the upper end of our outlook, now expecting between $260 million and $280 million. We are also raising our non-GAAP earnings per share forecast to $2.38 to $2.42, reflecting robust Q3 performance. Regarding foreign exchange, we anticipate a 1 to 2 point benefit to our Q4 2025 revenue, while we do not expect significant currency impacts for the full year. Our anticipated non-GAAP tax rate is approximately 23.1%, with a projected weighted average of 96.1 million shares outstanding for the full year. Please refer to our Q3 earnings presentation on our Investor Relations site for a complete overview of our 2025 outlook. In closing, we're taking actions that we believe will enhance shareholder value. Our key steps this year include achieving positive total ARR growth, focusing on cost efficiencies, ensuring consistency in operations, and stabilizing free cash flow. As we plan for next year, we are prioritizing our investments to harness the substantial opportunity for Teradata as a leading AI and knowledge platform within the autonomous enterprise. We are confident that these investments, along with ongoing business optimization, will enable us to achieve profitable growth and increased free cash flow.

Your first question comes from Erik Woodring of Morgan Stanley.

Steve, really nice to see the earnings and free cash flow upside this quarter. I think this was the first time since you began disclosing cloud ARR that we've seen sequentials be negative intrayear for cloud ARR. I know you mentioned that it would dip below the target range this quarter, but I guess I look at the 11% and say it felt a bit below maybe where you would have expected sequentially. But maybe you could just elaborate on how the quarter transpired for cloud ARR, when and where we see that net expansion rate bottom? And maybe why we just aren't derisking Q4 a bit, just given some of your commentary around customers assessing where they're going to be deploying with Teradata. And then a quick follow-up.

Yes, thank you, Erik. I believe we performed as expected in the cloud segment. As noted in our Q2 earnings, we anticipated that performance would be below our full-year outlook. Currently, the market reflects a more thoughtful approach to transitioning to the cloud, with customers carefully considering how they can enhance the value of their AI workloads in their environments. We continue to observe customers leveraging our hybrid capabilities. A significant number of our cloud customers operate both on-premises and in the cloud with us, enabling them to choose where to run their workloads across their extensive data resources. This is evidenced by our total ARR growth being ahead of schedule. We expect to see growth return in the fourth quarter, and our overall customer growth is a positive outcome for us this year. Our net expansion rate is beginning to stabilize, and we're confident about our ARR growth for the year. Looking ahead to 2026, we foresee opportunities for continued ARR growth.

Okay. Just a quick follow-up. Your comment about meaningful free cash flow growth into 2026 was the most confident I've heard you sound on this topic in a while. Can you explain where this confidence comes from? I'm sure it relates to ARR growth and some operational expense initiatives. I know you won't guide to 2026, but can you help us understand what you mean by meaningful free cash flow growth? That's all I have.

Yes. Thanks, Erik. I think you hit the nail on the head with the two points, but I'll just ask John to add any more color.

Yes. I think that's exactly right. I mean I think if you look at how this year is progressing, we've done a nice job on free cash flow relative to where we were at this point last year. And I think we're doing the right things and really focusing on this is a key driver for us. Certainly getting total ARR back to growth territory has had a positive impact. And then the cost actions that we've taken last year and this year as well are also supporting that number. And so we feel like we're putting the right pieces in place to continue that improvement next year.

First for Steve, last quarter, we talked about, I think it was roughly one-third of pipeline, including an AI component. So I guess, first, like how did that track this quarter? You mentioned the agent offerings, MCP Server. Like is there any area in particular within the AI portfolio moving the needle? And then any way to think about how these AI discussions more broadly are impacting competitive win rates?

Yes. Thanks for the question, Radi. Yes, we're continuing to see the AI influence pipeline increase. We saw it increase as we went through Q3, which is really great to see. We have supported that with a fantastic set of innovation and releases from a product perspective. Our new Chief Product Officer, Sumeet, is making a real difference there. In terms of we're measuring our innovation releases in terms of time from concept to press release. And I think as evidenced by the discussions we had with our customers at our most recent marketing event, they're really seeing those innovations as something that Teradata can provide in a holistic way to enable them to deploy Agentic AI workloads, whether it's from our Enterprise Vector store capabilities, our MCP Server, our AgentBuilder capabilities, or ModelOps where we can include language model capabilities. So all of these, I think, are coming together. And one of our customers actually, I think, said it best, where they said, Teradata is one provider in this area who's really putting it all together. But I think the most interesting thing, Radi, from a technology perspective is that we are seeing that the Teradata technology platform is really built for these AI workloads. When you think about an always-on AI agent, essentially that can execute thousands of queries and complex queries, so really large volumes of queries executing concurrently inside an environment with different types of workload. Our architecture inside Teradata, our massively parallel architecture, combined with our workload management and query optimization allows our customers to run those types of queries and the AI agents that they have developed to run those queries more effectively and efficiently than anybody else.

Awesome. And then second for John. You've been in the seat a couple of quarters now, strung together a couple of nice quarters. I guess is it fair to think about your approach to guidance being relatively consistent since you joined? And maybe are there any leading indicators or KPIs in particular that you're looking at that give you confidence in the outlook especially around Q4?

Yes. Thanks for the question. And I would say from an overall standpoint, I guess, in terms of guidance and our philosophy on it, we try to call it as we see it. And so we take a look at our forecast. We do have a number of KPIs that we'll look at from pipeline to our expenses to the revenue model, et cetera. There's a whole bunch of metrics that we'll take a look at and roll all of that up. When you talk about Q4, in particular, you're now getting down to the last few months, and we're literally going deal by deal. And so we've got that kind of granularity in terms of how we ultimately roll up the forecast and then our resulting guidance from it.

Steve, maybe I'll start with you. Great to see everyone in LA. I want to just follow on what Radi was asking, like around the competitive edge, like the Agentic AI strategy with autonomous at Possible and then AgentBuilder like really position Teradata like directly against some of this road map of your larger hyperscaler platform and even competitors like Databricks and Snowflake. Can you kind of help us understand what is really the longer-term durability competitive advantage that you see that Teradata can compete in the space? And is it more the hybrid cloud environment that you've been talking about and then the more enterprise IP within your decades of experience, maybe we can start there.

Thank you for the question, YC. What truly differentiates us is our strong technological foundation, which consists of our patented capabilities that enable us to handle workloads effectively and efficiently, both on-premises and in the cloud. This ability to offer a hybrid environment is a significant advantage for us. Earlier this year, we introduced our AI factory that integrates various capabilities, developed in partnership with NVIDIA. This provides a solid foundation for our upcoming on-prem capabilities. We are eager for the next release of our Teradata technology platform, which will incorporate GPUs for executing workloads. Our customers are currently utilizing the Teradata on-prem platform to run AI workloads reliably. We see this working well in a hybrid context, combining both on-premises and cloud solutions. Ultimately, we believe the competition revolves around the capabilities of the query engine, and we are confident that ours is the best for delivering AI-focused workloads and serving as a knowledge platform that builds enterprise context. This is built on the extensive expertise and solutions we have developed over the past 40 years, encompassing areas such as customer experience and supply chain management across various industries. All these elements come together to create our unique position in the market, and we are enthusiastic about sharing this message and demonstrating our value to customers on a daily basis.

Well, understood. Maybe one for John here. You mentioned the significant improvement in service gross margin to positive territory in the quarter. It's great to see that change. Could you elaborate on some of the actions taken? I know we heard about the team starting to leverage more full-time equivalents or possibly even AI full-time equivalents within the sales process, particularly with these newer AI use cases. Is this something you expect to continue, potentially driving better margins and efficiencies through the use of AI within the company that you briefly mentioned as well?

Yes. There are a few questions mixed in there. Regarding the services business overall, honestly, a lot of it involves adjusting the organization to fit the current revenue levels. This year, we faced some challenges due to increased migration activity last year. In the first few quarters, we lagged behind on the cost structure, but we addressed that in the second quarter, leading to a strong recovery in Q3, and we believe there's still potential for improvement in Q4. Essentially, this is about aligning costs with expected revenue. Regarding your broader inquiry about overall margins and our internal AI initiatives, there’s actually a significant amount happening. I won't convey everything accurately, but I encourage you to look into the presentations from our Possible conference, which highlighted many of our internal efforts. There's a comprehensive work stream in place that affects all aspects of the business, from cost of revenue to operating lines.

I'll just add to that, YC. I think from an AI services perspective, we're seeing customers have a real appetite to deploy real solutions. So with the launch of our customer intelligence framework and also backing that up with real consulting expertise, folks that can actually implement AI solutions inside our customers, we're really pivoting our consulting and services capability to deliver on something that we see as a supply-constrained marketplace in terms of folks that actually know how to deploy these solutions inside our customer base. So our most recent press release in the last couple of weeks around AI services and the capabilities that we have to help enable our customers in this market is super exciting. And obviously, of course, working alongside our partners to deliver those capabilities to the market is super important for us.

I would like to follow up on a previous question regarding the trends in cloud versus on-premises solutions over the next few quarters. Should we focus more on the on-premises segment of the business, and are we seeing a potential slowdown in cloud growth? Additionally, could you share any insights on the related margin and pricing effects?

I'll start, and John can add some thoughts as well. Thank you for the question, Chirag. We're definitely noticing that our on-prem business is stabilizing, and we're seeing improvements. This is due to strong retention and expansion within our on-prem environments. We're pleased with our retention rates, which align with enterprise software norms. We are open to growth wherever it arises. We are positioned to benefit from growth in the hybrid environments that some customers are adopting, and we're also well-prepared to leverage on-prem growth driven by data sovereignty needs and on-prem data gravity. Additionally, we've observed an increase in our cloud expansion rates compared to previous years, and we anticipate this trend will continue. We're confident in our ability to take advantage of the opportunities ahead of us, particularly with the hybrid platform we offer to the market.

Okay. That's really helpful. Maybe just one more. Great to see more of a focus on AI services within consulting. It really speaks to the importance and percolation of this technology. Looking ahead, do you see consulting revenue stabilizing a bit at this point, driven by the focus on delivering AI services? Or is this still a category that you're involved with, but starting to or continuing to shift over to your partner ecosystem?

Yes, at our core, we are a technology company focused on growth in annual recurring revenue. We offer consulting and services to support this growth, and our goal is to maintain a favorable margin profile. We have created opportunities for our partners to succeed alongside us. It is essential for a leading technology organization to have a strong consulting and services capability to enhance its technology value proposition. It is encouraging to see our consulting and services team adapt to provide AI services, which will increase our relevance in the market and assist both our existing and new customers in implementing AI solutions. We see this as a significant competitive advantage. Our go-to-market strategy now includes a forward-deployed engineering model to deliver proofs of concept to clients, while our consulting and services teams and their partners will help transition these concepts into reality and production. We have already achieved success by addressing real business challenges and developing production-ready solutions. Therefore, minimizing the time to value from an AI standpoint is critical, and we believe our AI service capabilities will play a vital role in this.

This is Michael Richards on for Matt. Maybe just double-clicking on that dynamic where customers are assessing the deployment options. Just curious, is that a result of the announcement of the hardware refresh next year where maybe some customers are seeing the transformation you're bringing to the on-prem offering and now it's a bigger decision of whether or not to stay or move to the cloud? And then just any early feedback you've gotten on that decision to have this big refresh?

Thanks, Mike, for the question. No, I wouldn't say it's got anything to do with the technology platform that we're coming out with next. I think the technology that we have in place today is actually enabling some of these decisions, both in terms of things like the AI factory, which are available today on the technology stack that we have. It's actually given our customers exactly what they want. They want the choice of deployment. They want to be able to choose where they put the workloads. And we offer our customers a workload-first deployment model. So they can choose whether they want to run the workload in the cloud or whether they want to run it on-prem. And so that's the decision-making that our customers are going through. And the fact that we offer those technology capabilities in that hybrid environment is essentially given our customers the choice of deployment.

Congrats from me as well on a great quarter. The quick question, Steve, more for you. If you think about the debate of where AI gets that data from, there is a kind of big debate kind of is it coming out of the operational data stores and Oracle, et cetera, is making note more out of like the data warehouses like you guys or more out of the data lakes. Can you speak to that, how you see that playing out? Or is it different use cases will have like a different data foundation?

Raimo, you addressed the question at the end. We are indeed noticing that customers want to maximize the value of their data, regardless of its location. This is why we appreciate QueryGrid as our solution to integrate various data stores. Whether data is sourced from a data lake or an enterprise data warehouse, it can be processed in a highly governed and reliable manner, allowing integration into a language model within a trusted setting. This is the value we provide to our customers. Moreover, with AI solutions, trust and ethics are paramount. It's essential to establish traceability and ensure they operate efficiently. The Teradata platform empowers our customers to achieve this by merging all their data sources.

This is for you, John. You guys had nice outperformance on recurring revenue in Q3. But now for Q4, we had been kind of assuming low single-digit growth implied from your guide last quarter to now low single-digit decline. So was there any kind of pull forward of deals from Q4 into Q3? Or what would you call out on the change in the Q4 growth assumptions? And if I could just squeeze one other in on the cloud ARR having kind of dropped to 109%. Just remind us what the main drags to this number are? And any color on kind of when and where this could start to stabilize and perhaps move back up?

Sure. Yes. Thanks, Derrick. So on the recurring revenue side of things, I think our guidance for the year has actually been fairly consistent on the recurring revenue piece. We did have some variability if you look quarter-to-quarter, and that comes from the upfront portion of the on-premise subscriptions. And so depending on the mix of that in any given quarter, you might have more upfront revenue, which would otherwise throw off your expected linearity. In terms of the net expansion rate, we have seen some consolidation on that. If you look at what we've done historically, and even I think for this year, we're still on track for the same. About 50% of our expansion rate is coming from migration activity, and the remainder is coming from expansions with existing customers. And so we see that continuing into Q4. Right now, you're seeing those rates consolidate. And so the net expansion rate is pretty close to what you're seeing for the cloud ARR growth overall.

I think you mentioned that cost reductions are helping free cash flow for next year. Could you help us understand the overall operating expense trajectory leading into 2026? What is your perspective on the progression from this point? Also, I know that federal is not a significant part of your business, but are you noticing any effects from the government shutdown?

Yes, I'll address the last question first, Wamsi. We are not experiencing any impact on our revenues due to the federal shutdown. From an operational expense standpoint, we have undertaken significant restructuring activities throughout the year, particularly around June and September. We anticipate that these changes will have full-year impacts and benefits, ultimately strengthening our free cash flow as we progress into 2026. We expect that growth in free cash flow will stem from our anticipated ARR growth in 2026, as well as from the operational efficiency and productivity improvements we've implemented in 2025.

John, this one is for you, too. And I know this was a good quarter, but if you divide your free cash flow by the revenue, you get like 21%. Not putting a time frame on it, I think where can that free cash flow margin go?

Yes, that's a good question and it's somewhat related to what Steve just mentioned regarding operating leverage. If we take a step back to consider our performance this year in light of revenue challenges, while we don't provide specific guidance on operating margin, it's reasonable to deduce that the operating margin will remain relatively flat and comparable to last year. This indicates that despite revenue headwinds, we are still managing to maintain that margin percentage. We've implemented various operational and cost efficiency measures that will continue to benefit us in the coming year. While I won't provide a specific number today, I can confidently say that the actions taken this year position us favorably for next year's margin and cash flow.

Thanks, Pat, for the question. And thanks, everyone, for joining us today. We are absolutely committed to show what the AI future holds for our customers and what our differentiated platform and capabilities can deliver. As we continue our focus on execution, we're really confident in our outlook, and we are looking forward to updating you all next quarter. Thank you very much. And operator, you can end the call.

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