Teradata (TDC) Q3 2026 Earnings Call Transcript

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DATE

Thursday, Nov. 5, 2026

CALL PARTICIPANTS

• Senior Vice President of Investor Relations and Corporate Development - Chad Bennett
• President and Chief Executive Officer - Stephen McMillan
• Chief Financial Officer - John Ederer

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TAKEAWAYS

• Total ARR -- $1.512 billion, representing an increase of 1% as reported and 2% in constant currency.
• Public Cloud ARR -- $700 million, growing 11% as reported and in constant currency.
• Non-GAAP Diluted EPS -- $0.70, exceeding the top end of the guidance range by $0.11 due to lower operating expenses and revenue performance.
• Adjusted Free Cash Flow -- $96 million, increasing from $88 million in the prior year.
• Year-to-Date Adjusted Free Cash Flow -- $254 million, rising from $134 million during the first nine months of the previous fiscal year.
• Recurring Revenue -- $359 million, finishing at the high end of the company's outlook range despite a 2% year-over-year decrease.
• Total Revenue -- $399 million, representing 4% year-over-year decline but reaching the high end of management's guidance.
• Non-GAAP Operating Margin -- 21.8% for the quarter, while year-to-date margin improved by 300 basis points to 24%.
• FY 2026 Non-GAAP EPS Guidance -- $2.86 to $2.90, raised from the initial midpoint of $2.60 to reflect improved operating margin expansion.
• FY 2026 Revenue Guidance -- Narrowed to the high end of previous ranges, with recurring revenue growth of 1% to 2% and total revenue between -1% and 0%.
• Q4 2026 Revenue Guidance -- Total revenue is expected to decline 4% to 6% year over year, impacted by the timing of upfront revenue recognition in earlier quarters.
• Share Repurchases -- $57 million, consisting of approximately 2 million common shares repurchased during the quarter.
• Tera Token Efficiency -- 73% fewer tokens used than a leading AI coding agent while achieving 42% faster task completion in internal testing.
• Data Engineering Cost Performance -- 53% lower cost per reliably solved task than Snowflake Cortex code based on internal testing of public benchmarks.
• Consulting Revenue -- $37 million, declining 21% as the company transitions its services toward advanced AI implementation.
• FY 2026 Operating Margin Expansion -- 200 basis points, doubling the initial full-year improvement target of 100 basis points.
• Non-GAAP Tax Rate -- 26% expected for the fourth quarter, with fiscal 2026 other expenses anticipated to be $17 million.
• Cash from Operations -- $665 million to $685 million for the full year, including a $315 million after-tax benefit related to the SAP settlement.
• Recurring Revenue Gross Margin -- 67%, down compared to the prior year primarily due to revenue linearity and recognition timing.

SUMMARY

Teradata Corporation (NYSE:TDC) reported its third quarter results, highlighting a strategic shift toward Agentic AI and sovereign deployment models while raising its full-year earnings guidance. Management noted that the fourth quarter remains the largest selling period, with a significant government expansion deal in the Pacific region already closed in Oct. 2026. The company focused investments on its product pipeline, particularly the Autonomous Knowledge Platform and the Tera Agentic Coworker, to facilitate moving AI from experimentation into production. Financial performance for the period was characterized by disciplined expense management and expansion in adjusted free cash flow, supported by year-to-date recurring revenue growth.

• The company evolved Tera into an agentic coworker designed to perform data engineering and infrastructure automation through natural language, aiming to bridge the business understanding and execution gaps in enterprise AI.
• CEO Stephen McMillan noted, "Organizations also have varied deployment requirements that are often shaped by regulatory and sovereign considerations," driving demand for the company's hybrid and sovereign cloud offerings.
• Management launched Teradata Factory in partnership with Dell, a unified environment that brings data, models, and agents into on-premises infrastructure to provide physical control over AI execution.
• A new integration with Microsoft OneLake allows customers to run AI on data stored in OneLake without duplicating or migrating it, supporting multicloud flexibility.
• The company reported its first product built mostly using agentic development, reflecting internal efforts to use AI to accelerate product delivery while strengthening security.
• The sales organization is utilizing agentic tooling to generate proposals and improve business value propositions, contributing to the acquisition of new logos such as a multinational electronics firm in Japan.

INDUSTRY GLOSSARY

• Autonomous Knowledge Platform: The unified multicloud data environment designed by Teradata to integrate data, models, and agents for enterprise AI production.
• Tera: An agentic coworker developed by Teradata that enables users to perform data engineering and analysis using natural language.
• Agentic AI: A form of artificial intelligence involving autonomous agents that can plan and execute tasks to achieve specific goals.
• Sovereign AI: AI infrastructure and data management that prioritize national or organizational control over data residency, operations, and model independence.
• Teradata Factory: A unified environment bringing data, models, and agents into on-premises infrastructure, often in partnership with Dell.
• OneLake: A unified, logical data lake for an entire organization, serving as a single place for all data.
• ARR (Annual Recurring Revenue): The annual contract value for all active and contractually binding term-based contracts at the end of a period.
• Constant Currency: A financial calculation that eliminates the effects of foreign exchange rate fluctuations to compare performance across periods.

Full Conference Call Transcript

Operator: Good afternoon. My name is Percy, and I will be your conference operator today. At this time, I would like to welcome everyone to the Teradata 2026 Third Quarter Earnings Call. [Operator Instructions] 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.

Chad Bennett: Good afternoon, and welcome to Teradata's Third Quarter 2026 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. Please note that Teradata intends to file the Form 10-Q for the quarter ended September 30, 2026, 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, adjusted free cash flow and constant currency comparisons. 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.

Stephen McMillan: Thanks, Chad, and thanks to everyone who's joining us today. Teradata delivered a solid third quarter, performing as we expected across our operating metrics. We delivered another strong quarter of adjusted free cash flow growth, up year-over-year and year-to-date. And we saw growth in recurring revenue, up 4% year-to-date, maintained strong operating leverage and exceeded our non-GAAP earnings per share range. We are well positioned as we enter the fourth quarter. As in every year, the fourth quarter is our largest selling quarter, and we've already closed the largest expansion deal in our Q4 plan. We remain confident in our total ARR guidance of 2% to 4%.

Today, I'll focus on the broad set of products and capabilities we are bringing forth as a result of the investments we made in our innovation pipeline. This was done with one goal in mind, helping customers leverage all of their enterprise data and get their Agentic AI initiatives into production. This is an imperative in order for AI to deliver durable value. Organizations around the world face the challenge of accelerating AI and moving from experimentation into production. We believe that for AI to work autonomously, it needs to be trusted, ethical and effective and it needs the enterprise context to be accurate. Organizations also have varied deployment requirements that are often shaped by regulatory and sovereign considerations.

We're seeing increased interest in our hybrid capabilities from customers running Teradata on-prem in the cloud or in a combination of both. As enterprises move from asking questions of the data to delegating work to AI agents, the platform underneath has to do more than it ever has before. Agents use data far more intensively and very differently than people do. We built the autonomous knowledge platform to meet these challenges. And it is that backdrop for the announcements I will cover next, many of which are already available and being trialed by customers. In September, we announced a major evolution of Tera, our Agentic Coworker for enterprise data work.

It is designed so that everyone from business analysts to database administrators can describe what they need in plain language and see the work carried through without deep Teradata expertise. I personally use Tera in my daily work, so it can attest that even business leaders can ask natural language questions and get the answers they need. We built Tera to close two gaps that limit what enterprise AI delivers today. The first is business understanding. A model can be highly capable and still not know what a company's own terms, relationships and policies mean. The second is execution, which has to be reliable, governed and economical as agent activity grows.

Tera is generally available today, and we are extending it to take on both gaps through Tera Context Engine, Tera Harness and Agent Skills, all expected to arrive before the end of the year. Tera Context Engine addresses the first gap by giving agents governed business meaning to work from. Our industry knowledge models are designed to add expertise validated with some of the world's most complex enterprises, so agents start with meaning rather than starting from scratch. The second component is Tera Harness, which addresses the execution gap.

It is designed to coordinate the right skills, tools, data and models at each step of the workflow with guardrails and human approvals built in to solve high-risk actions before they run. The third Tera element is agent skills, which take what Teradata has learned over decades and package it into functions that any agent can call and that people can request in plain language. Supporting all three components is our AI services team, which helps customers choose and implement the use cases where governed context will create measurable value. We are very pleased with how Tera performed on Suite Bench Pro, a widely used software engineering benchmark.

Using the same model for our internal testing, Tera used 73% fewer tokens than one of the leading AI coding agents while achieving higher task completion rates and completing work 42% faster. On data engineering bench, a public benchmark Snowflake Labs and bespoke labs developed for data pipeline engineering, Tera delivered 53% lower cost per reliably sold task than Snowflake Cortex code. This result is based on our internal testing using the benchmark compared to Snowflake's own published results. Tera also earned the highest accuracy score on the benchmark in the same comparison.

For customers, this level of efficiency reduces cost as a constraint on scaling AI, which gives them greater confidence to move more of their workloads into production on Teradata. We're already seeing strong interest in Tera with customers asking for proposals to utilize Tera across their entire environment for coding and data engineering. We also released Tera internally to all employees so they can utilize its power, bringing a specific language model that they want to use in their own roles. Our internal usage helps our teams gain AI fluency and efficiencies and provides near real-time feedback to our product organization on future enhancements to consider.

Additionally, all of our engineering is now augmented by Agentic development, and we've launched our first product built mostly using Agentic development. We continue to expand how we use AI to accelerate how we deliver product capabilities while strengthening the quality and security of what we ship. Two other recent announcements reflect our belief that AI should run for data already sets. In October, we announced the general availability of Elastic Python compute and AI Studio. It gives data science teams a managed Python environment for scaling AI workloads in parallel directly inside the Teradata platform.

This offering is available on AWS and Azure today as well as on-prem with Teradata Factory, so customers get the same capability in whichever environment holds the data. In September, we announced an integration between our Teradata Autonomous Knowledge platform and Microsoft OneLake. When running AI on Teradata, customers are able to use AI directly on data stored in OneLake without duplicating or migrating it. For some customers, AI has to run entirely inside their own boundary and interest in sovereign and AI continues to grow.

We think about sovereignty in three parts: control over where data lives and who can reach it, control over who operates the environment and freedom to choose the models and technology an organization depends on. At our most recent customer event in London, we expanded our sovereign offerings with two complementary deployment models. The first is Teradata Factory with AI Studio, a unified environment that brings data, vectors, models and agents into on-prem infrastructure. This is designed to give customers direct physical control over their AI execution. The second is Teradata Sovereign Cloud on Google Distributed Cloud's Adapt environment for customers who want a cloud operating model inside an isolated boundary.

There's no connection to the public Internet, is operated by the customer and is designed for governments, defense organizations and regulated industries. Control over where AI runs goes hand-in-hand with protecting the data itself. To this end, we also recently announced new privacy, security and resiliency capabilities. They reflect how enterprise AI requires sensitive data to move between users, applications, models and agents. This increases risk, and we believe protection has to work as a single system to safeguard the intelligence behind AI without diminishing what makes it valuable. With these new capabilities, customers can protect the identities behind their data while keeping the relationships that AI and analytics depend on.

Post-quantum security and readiness strengthen protection against emerging quantum error threats and immutable backup protection keeps mission-critical operations available and recoverable. These are available now on Teradata Cloud across AWS, Azure and Google Cloud and masking and classification are also available on Teradata Factory and on-prem. With the increased investment in our product pipeline, we've announced many new offerings that are already available, plus more are arriving this quarter and into early 2027. As agents take on more work, customers will need context, governance and performance together in whichever environment the data sets. Technology alone doesn't get AI into production, so we pair our platform with AI services.

Our teams work alongside customers starting from their data, their governance requirements and their business priorities. We take use cases from prototype to production against clear business outcomes. We're seeing this across industries from banking and aviation to telecommunications and pharmaceuticals. In each case, our teams are helping customers get AI into production and see value they can measure. This year, we brought our new technology to the market at events around the world. These events encompass product announcements, customer use cases like workshops and demos. All showing how Teradata can help move customers' AI initiatives into production. Attendance beat our goals, and our teams are now following up with customers.

In addition, the workshops were oversubscribed, and we're bringing the workshops online to extend the reach. Now I'll walk through some customer examples that reflect the breadth of our offerings. A multinational electronics company in Japan is a new logo for us. It selected Teradata for our hybrid capabilities as the firm required both high-performance analytics across trillions of records and the stability of on-prem operations. Running on our on-prem platform and Teradata on AWS, this next-gen analytical environment will provide quality insights on its fast-growing manufacturing operations. Our team won by demonstrating superior query performance and a robust data foundation.

A EMEA public sector new account has selected Teradata to support a multimodal AI and analytics program for operational readiness and asset protection. This win reflects growing demand for trusted governed AI platforms, platforms that can run mission-critical workloads on sovereign infrastructure and highly secure on-prem environments. Federal transportation agency in Latin America selected Teradata on AWS, AI Studio and Elastic Compute to integrate fragmented traffic conditions, accident and weather data. Teradata is also supporting AI-driven predictive infrastructure decision-making. This win reinforces our role as a trusted data and AI foundation at scale. And finally, a utility company in the Americas chose our AI services and AI Studio to help turn its trusted enterprise data into business value through AI.

Building on its existing Teradata investment in governed intelligence and business context, it can reuse trusted data, metadata, business rules and analytical assets rather than creating a separate foundation for AI. This is to accelerate customer time to value with natural language experiences while supporting scalable governed AI adoption across the organization. As we started the year, we said we would continue to drive top line growth, improve profitability and maintain healthy free cash flow. And we'd invest to advance our products and helping customers drive value from AI, and we've done just that. We are receiving positive feedback from customers on their AI initiatives with Teradata.

Our more aggressive technology pipeline, coupled with the enthusiastic response we've seen from customers, underpins our confidence in our annual outlook. Now I'll turn the call over to John.

John Ederer: Thank you, Steve, and good afternoon, everyone. Q3 marked another quarter of progress against the goals we set at the start of the year. More specifically, entering the year, we are focused on driving total ARR growth, continued operating margin improvement and delivering strong free cash flow. On a year-to-date basis, we have had positive total ARR growth every quarter this year. We have increased operating margin by 300 basis points, and we have grown adjusted free cash flow by 90%. We also noted that we are focusing investments on product development this year. These investments are starting to pay off, and we are pleased with the accelerated pace of innovation this year.

As Steve just discussed, we have advanced many elements of our Autonomous Knowledge platform, and we are encouraged by the early response from customers. We believe these solutions position us well to capitalize on the market opportunity for Agentic AI as we head into next year. In terms of our detailed financial results for the third quarter, total ARR grew 1% as reported and 2% in constant currency, while cloud ARR grew 11% as reported and in constant currency. As we mentioned throughout the year, we continue to anticipate the majority of our ARR expansion will come in Q4. Third quarter total revenue was $399 million and at the high end of our outlook range, driven by recurring revenue.

Third quarter recurring revenue was $359 million, which was also at the high end of our outlook range. As we've discussed for several quarters, our revenue linearity this year has been skewed to the first half of the year due to upfront revenue recognition for on-premise subscriptions. So while reported Q3 recurring revenue was down year-over-year, on a year-to-date basis, our recurring revenue is up 4% versus the comparable period last year. The timing of revenue this year has also had an impact on our quarterly margin performance, which I will highlight in a minute.

Third quarter consulting services revenue was $37 million, which was down year-over-year as we transition this part of our business from cloud migration work to more advanced AI services. During this transition, we have continued to optimize this part of our business to safeguard profitability. Looking at profitability and cash flow, please note that I will be referencing non-GAAP numbers for expenses and margins and a full reconciliation to GAAP results is provided in our press release. For the third quarter, total gross margin was 61%, which was down slightly versus Q3 last year. However, on a year-to-date basis, gross margin has improved by 140 basis points due to a higher mix of recurring revenue.

Recurring revenue gross margin was 67%, down versus Q3 last year, primarily due to revenue linearity this year. Consulting services gross margin was 5%, up slightly from Q1 and Q2 as recent actions that we have taken are expected to have a bigger impact in Q4. Operating margin was 22%, down versus Q3 last year, again, primarily due to revenue linearity. On a year-to-date basis, operating margin is 24%, up approximately 300 basis points versus the first 9 months of 2025. Total operating expenses declined year-to-date, driven by lower SG&A, partially offset by higher investments in R&D to drive innovation. Non-GAAP diluted earnings per share were $0.70, exceeding the top end of our outlook range by $0.11.

The outperformance was primarily driven by lower operating expenses, along with revenue at the high end of our outlook. We generated $96 million of adjusted free cash flow in the quarter, up 9% from $88 million a year ago. Year-to-date adjusted free cash flow is at $254 million versus $134 million for the first three quarters of 2025. As a reminder, adjusted free cash flow excludes all impacts related to the SAP settlement earlier this year.

Finally, we continue to return value to shareholders, repurchasing $57 million or approximately 2 million shares in the third quarter, bringing us to $131 million on a year-to-date basis, which is slightly ahead of our target of using 50% of our adjusted free cash flow for stock repurchases. Now turning to our annual outlook for 2026. We reaffirm our ranges for total ARR and adjusted free cash flow. Given the year-to-date performance, we are narrowing our ranges for total revenue and recurring revenue to the high end of our previous ranges. Total revenue is now expected to be in the range of minus 1% to 0% year-over-year.

Recurring revenue is now anticipated to be in the range of 1% to 2% growth year-over-year. For non-GAAP earnings per share, we are increasing the range to $2.86 to $2.90. For the fourth quarter of 2026, recurring revenue is expected to be in the range of minus 2% to minus 4% year-over-year. Total revenue is expected to be in the range of minus 4% to minus 6% year-over-year, and non-GAAP diluted earnings per share is expected to be in the range of $0.58 to $0.62. As we've discussed on prior calls, recurring revenue and total revenue growth rates in the fourth quarter are being impacted by the timing of upfront revenue recognition that occurred earlier this year.

We believe our annual targets for fiscal '26 recurring revenue and total revenue are more reflective of the general trends in the business. In terms of some of the other modeling assumptions, for the fourth quarter, we expect the non-GAAP tax rate to be approximately 26% and the weighted average shares outstanding to be about 94.8 million. Also, we now anticipate FY '26 other expenses to be approximately $17 million. In summary, we are pleased with the financial and operational progress we have made over the first three quarters of this year, and we remain confident in our ability to achieve our full year objectives. We also remain very focused on driving operating margin improvement.

We now see operating margin expansion of approximately 200 basis points for the year, which is double the 100 basis point improvement that we had anticipated at the beginning of the year. The operating margin expansion has driven our increased outlooks for both non-GAAP EPS and adjusted free cash flow this year, with non-GAAP EPS increasing from a midpoint of $2.60 at the start of the year to the current midpoint of $2.88 and the midpoint of our adjusted free cash flow range from $320 million at the start of the year to our current midpoint of $340 million. Thank you all very much for your time today. Now let's open up the call for questions.

Operator: [Operator Instructions] Your first question comes from the line of Eric Woodring with Morgan Stanley.

Erik Woodring: Maybe just to start, Steve, your ability to support customers on-prem in the cloud and hybrid environment is clearly differentiated. I'm wondering, does that flexibility also mean customers might have less urgency to migrate and expand their cloud commitments? And maybe my question is just like how should investors think about the trade-off between offering kind of like deployment flexibility versus thinking about faster public cloud ARR growth? And then just a quick follow-up, please.

Stephen McMillan: Thanks, Eric. Yes, that's a great question. I think what we're seeing is we're in the business of growing our total ARR. And that's really why we guided at the start of the year that we would grow total ARR between 2% and 4%. I think as we've discussed on prior earnings calls, the mix between cloud and on-prem is more of a customer choice. And we've said that we've seen kind of decline in the headlong rush to the cloud -- and customers are being more strategic in terms of what assets and workloads to deploy on-prem and which workloads they want to deploy in the cloud.

What I'm really excited about, though, Eric, is the fact that our new AI stack and the Autonomous Knowledge platform is something that we can deploy on-prem for our existing customers and new customers and give them a complete AI stack that they can use on top of the data platform that they have from Teradata. And so I think as we look and as we look at Q3, we certainly saw on-prem deals getting closed and hybrid deals getting closed and customers making deliberate choices about that deployment model. And in all of the cases, they led to some growth for us, which is great.

Erik Woodring: Okay. Awesome. And then just maybe a follow-up to that, Steve, I'm not asking for 2027 guidance. But as you think about entering 2027, what are, call it, the two or three most important drivers that you think could lead to maybe like a reacceleration in ARR growth into next year? Is that new customer acquisition? Is that expansion in the installed base? Is that monetization of some of the new tools that you discussed earlier in your prepared remarks? And just like the visibility that you kind of have into those drivers today. Just whatever flavor you can give us for next year would be incredibly helpful.

Stephen McMillan: Yes, that's great. Thanks, Erik. We -- as I spoke about in my prepared remarks, we talked a lot about context. and how our Tera, our Agent can develop context for our customers. That is a discussion which is resonating across all industries. And that manifests for us in terms of the deployment of all of the new capabilities I spoke about. So AI Studio, our Elastic compute capability, the fact that we can develop context autonomously, the partnerships that we have with folks like unstructured and Wisdom AI. So that's definitely going to be one growth area for us. The other growth area is definitely going to be Teradata Factory, the partnership that we have with Dell.

And that's going to manifest in terms of increased sovereign deployments and increased on-prem deployments. And I think that's going to be the other growth element for us. And we're very excited about the early signs that we have from a Teradata factory perspective and the opportunity that, that presents as we get into 2027.

Operator: Your next question comes from the line of Yitchuin Wong with Citi.

Yitchuin Wong: Steve, I'd like to start on the Sovereign AI opportunity. You spent some time discussing the GA of Teradata factory along with AI Studio as well as the expanded offering of Sovereign Cloud with Google. Palantir highlighted multiple 8-figure sovereign AI contract in their earnings call earlier this week. Can you talk a little bit about what you're seeing with customer demand today for Soren AI and how you think about this opportunity longer term for Teradata?

Stephen McMillan: Yes. Thanks, YC. Yes, sovereign is certainly something that's capturing the industry interest just now, especially in the international marketplace, but also highly regulated industries in the U.S., governments across the world thinking about how they're going to deploy. And also, we see telco operators throughout the world developing private cloud solutions that can act as an alternative to some of the U.S. public cloud solutions. The great thing about Teradata technology is we can deploy in all of those environments. It was very easy for us, as an example, to partner with Google in their Google Distributed Cloud, which is their on-prem capability targeted at sovereign environments.

And I think we see a lot of players talking about sovereign as an alternative because it really gives the customers control over where they can put their data. And they don't need to release that data into large general purpose language models. The benefit of Teradata Factory with GPUs right inside means that customers can utilize the language models that they want right next to the data that they've got in a completely controlled and well-governed environment. And that is resonating very much in terms of the deployment choice for our customers. And that's why I pointed to that as one of the key growth areas for 2027. So thanks for that question.

Yitchuin Wong: Great. And then I have a quick follow-up for John. Like Steve noted the largest expansion deal in the Q4 that you guys closed. Could we get a little bit more detail on the deal? Is there a sovereign AI in there? Or like what are the products or upsell in the contract that was closed?

Stephen McMillan: YC, I'll take that. I'll go into the details of what the customer was. And it was actually a government customer in the Pacific region that chose this technology, and that's going to start off with a hybrid deployment. And as I said, the great thing about our technology is that they see the ability to actually move between on-prem and the cloud. And that's something that they're going to be very deliberate about in terms of how they're deploying that capability. They're certainly going to take advantage of all of our new capabilities in the cloud.

And I know that the sales team has actually started showing them Tera or Agentic workplace in terms of how they can use Tera to actually interrogate that data. massive data sets involved there, very secure environment required, and it was a super win that we closed early in Q4.

Operator: Your next question comes from the line of Patrick Walravens with Citizens JMP.

Unknown Analyst: This is Nick on for Pat. Steve, one for you to start. Following all these product announcements this year, how are you balancing your go-to-market resources between winning new logos and expanding within the installed base?

Stephen McMillan: Yes. Thanks for the question. We are, as we're looking at '27, looking at how we can actually -- while keeping our operating expense envelopes flat to maybe slightly down to improve our operating income, how we can invest more inside our sales teams and sales organizations. And that's going to essentially give us the capability to have more of a focus on new logo. We've already seen good logo traction. I mentioned the Japanese multinational electronics company is a new logo that we've got in Q3. These are really coming from the capabilities that we've been building and we've deployed and our ability to demonstrate that to our customer base.

So we expect as we go through '27 an increase in the proportion of new logos that we'll be able to tell you about. But we certainly see a tremendous opportunity with some of the largest customers in the world that are inside our installed base. They are very excited about the new capabilities that we're bringing to bear, and we've certainly got some great expansion opportunities in there. Awesome.

Unknown Analyst: And as a follow-up, maybe for you, John. With memory and component and spot prices moving higher, how is that affecting the pricing commitments you can make to customers on factory?

John Ederer: Yes. So on that front, we've actually seen a little bit of stabilization in the market more recently. So I would say earlier this year, much more of an inflationary environment for those types of components. I would say in Q3, we started to see a little bit more stabilization. Now when you look at our business, keep in mind, for the current platform, we actually were able to buy ahead last year in terms of inventory. So we're in great shape on that front. And then in terms of the new Teradata factory going forward, our partnership with Dell really gives us a lot of support there.

Operator: Your next question comes from the line of Matt Hedberg with RBC Capital Markets.

Unknown Analyst: This is Simran on for Matt Hedberg. Just one for me. You mentioned your customer events had oversubscribed workshops. Can you talk a bit about how that pipeline could be converting into deal activity heading into Q4? And just thinking more broadly, like the Q4 ARR ramp is a big piece of that full year guide. So just any sense around the visibility in the pipeline, especially given that you've already closed the expansion deal? Any color on that would be great.

Stephen McMillan: Yes, that's great. I'll start off with actually Q4 and some color around that. Q4 is certainly our largest renewal quarter, and it gives us the most opportunities for expansion. And that certainly drives pipeline that is actionable in quarter as well as that in Q4, we tend to see Q4 is a big deal for us. A lot of the large opportunities for the year are actually focused in Q4. So closing one of the largest in October and getting that in early gives us confidence in the execution in the quarter. And we've got a strong pipeline and coverage for that 2% to 4% guidance range.

So we're confident in the execution for Q4 and committing to that range of 2% to 4%. What I would say in terms of the customer event, we demonstrated to customers how they could take their selected business use cases and get them into production very, very rapidly. What I said at that conference is customers shouldn't be thinking about POCs. These technologies have proven themselves out. and they should go for implementation. And we have an AI services capability that can help customers do that. So that services capability, combined with all of these new announcements is really building up a pipeline for us to execute on as we move into FY '27.

So that's -- it's an exciting time to be an AI player and being able to really demonstrate how a data platform and a scalable data platform can put these solutions into production very effectively.

Operator: Your next question comes from the line of Derrick Wood with TD.

Jared Jungjohann: John, this is Jared on for Derek. It was encouraging to hear you talk about some of the net new logos you landed in the quarter. And off of this, I was wondering if you could give us a sort of directional update on trends you've been seeing in your net new logo business. Has this been improving recently?

Stephen McMillan: Jared, thanks for the question. Yes, I think the whole opportunity around sovereign is opening up real opportunities for Teradata. Regulated industries that want to control where their data is, but still want to take advantage of AI capabilities are certainly starting to use it. When you've got organizations like the Japanese organization I was talking about that like to use on-prem technology. They don't want to move trillions of records between their on-prem implementation up into the cloud where it could be more expensive. So we are seeing good growth in the interest in our hybrid capabilities globally.

Sovereign capabilities, especially across Europe and the Middle East are very, very interesting for us, and we're seeing our pipeline growing there. And we certainly expect an increase in our new logo activity, especially with the partnership with Dell, where they've actually committed to us that they will bring new logo opportunities for Teradata factory. So being able to leverage that Dell sales force is going to be great for us as we move into 2027.

Jared Jungjohann: I appreciate all that color. Just one follow-up. Can you talk to any go-to-market retooling you have done for the factory rollout? Is this a materially different selling motion than your reps have traditionally had gone through?

Stephen McMillan: Yes. I think one of the things that I've been really proud from the growth and the development of the sales team is how they're using Agentic tooling to improve execution. That comes from helping them develop the overall business value proposition. It comes from how they are learning about our new offerings and capabilities, how they can customize that Teradata factory offer specifically to the customer requirements and customer environment. And we're seeing the ability to really get our sales teams and new sales folks that we're bringing into the organization based on our faith and the growth that we'll be able to get up to speed much quicker.

So, I think we've got a great transformation that's been undergoing in our sales organization. Everybody inside Teradata is now using Tera, and they can use Tera and the Agentic tools that we've built to really generate proposals and just to execute better. So it's a great story.

Operator: Your next question comes from the line of Wamsi Mollen with Bank of America.

Wamsi Mohan: This operating margin performance has been pretty strong this year. How are you thinking about -- given some of the things that you've said about your pipeline and growth, and obviously, you're investing a lot into your new product portfolio. How should we think about rate and pace of op margin expansion as we look into 2027? And I have a follow-up, please.

Stephen McMillan: Wamsi, I'll start out and then maybe John can add a little bit of color from a numbers perspective. We are seeing a good transition in terms of the offers and the capabilities that we've got. One of the things I did want to point out is as organizations are looking for sovereign deployments or deployment in their cloud environment, it means that we have the ability to focus on shipping software. So not just shipping appliances with the software on it or an end-to-end cloud solution, we're actually seeing opportunities where we can have much more of a software motion, which is great for setting the overall environment.

Now in terms of operating margin and gross margin, I'll let John talk to some of the details.

John Ederer: Yes, sure. I think I would sum it up by saying that from a philosophical standpoint, we're dedicated to profitable growth. And so what that means for us is that while we're certainly investing for growth opportunities, we also want to do that in a responsible way and make sure that we're dropping incremental benefit to the bottom line. And so when you step back and take a look at what we've done this year, 2026, as we said numerous times, has really been about product innovation. And so we've taken the -- every available resource that we can. We've reinvested in R&D.

As we look ahead to '27, we'll look to monetize that, and we'll look for ways to invest on the go-to-market side to be able to capitalize on the product innovation of this year.

Wamsi Mohan: Okay. And maybe, Steve, just you mentioned sort of AI services a bunch of times. And I'm just curious, has your thought process around services changed at all? Do you see AI services being a profit center by itself? Or do you see it more of customer acquisition and sort of driving incremental Teradata usage in the core platform and expansion over there as the primary way in which you're approaching it?

Stephen McMillan: Yes. At our core, Wamsi, we are a technology company, and we're absolutely focused on the technology differentiation that we can deliver in the marketplace. All the best technology companies have software as part of their nature and all the best technology companies have a platform that they can grow upon. And that's really the focus for us. Our AI services is really all about helping our customers get to value quicker and then being able to run those AI environments into the future so that the guardrails, the governance, the security, the privacy, the resiliency can be managed and implemented for our customers as they move through time.

So that -- our services business is certainly operating in support of our technology mission.

Operator: That concludes today's Q&A session. I will now turn the call back over to Steve McMillan for his final remarks.

Stephen McMillan: Thank you very much, operator. And as I stated earlier, we are really well positioned with our new technology. And that technology is all about delivering real measurable business value using AI. And we're certainly pleased with all of the initial interest that we've seen from our customers in this area. Our hybrid and sovereign capabilities have an unmatched advantage in the marketplace, and we remain really confident in our annual outlook. Thank you very much for your time.

Operator: This concludes today's conference call. You may now disconnect.

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