Teradata Corporation

Teradata third quarter 2025 earnings call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you'd like to ask a question during this time, simply press star followed by the number one on your telephone keypad. If you'd like to withdraw your question, please press star followed by two. I would now 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.

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 FCC filings, including our most recent Form 10-K and in the Form 10-Q for the quarter ended September 30th, 2025. That is expected to be filed with the FCC 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 relation 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 72 cents, 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 re-evaluating 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 by seven always on query potential can increase workloads on data platforms by up to 25 times and use 50 to 100 times the compute resources and 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 query grid 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 model ops 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 Agent Builder, 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 fuel 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 US healthcare 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 healthcare data at scale across its entire system. A leading Japanese heavy industry manufacturer chose Teradata for his 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 Vodafone 3, Uridu, and Sikredi at the conference for demonstrating exceptional creativity, technical excellence, and business impact through the use of AI on the Teradata AI and Knowledge platform. Vodafone 3 in the UK was recognized for deploying an AI-supported fraud detection framework. By leveraging AI to detect and medicate fraud, it has strengthened customer trust, improved regulatory compliance, and enhanced operational resilience. Uridu Qatar, a leading DOLA-based telco, earned this award for its advanced analytical capabilities and AI-powered customer engagement strategy. This strategy is built on Teradata Vantage Cloud and Clearscape Analytics. which were integrated with and run on GCP native services. Secredi, 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, Secredi has also begun developing an AI agent to support provision analysis under Brazilian banking regulations. Further strengthening is governance and risk management capabilities. We also held our first agent builder 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 agent builder 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 and partner participation. Companies that will win in their GenTech 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-sale 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 recognize 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 Agent Builder, 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.