Dynatrace, Inc.

Greetings and welcome to the Dynatrace fourth quarter and full year fiscal 2026 earnings call. At this time, all participants are in a listen-only mode. A question and answer session will follow the formal presentation. If anyone should require operator assistance during the conference, please press star zero on your telephone keypad. As a reminder, this conference is being recorded. I would now like to turn the call over to your host, Noelle Farris, Vice President of Investor Relations. Thank you. You may begin.

Good morning, and thank you for joining Dynatrace's fourth quarter and full year fiscal 2026 earnings conference call. Joining me today are Rick McConnell, Chief Executive Officer, and Jim Benson, Chief Financial Officer. Before we get started, please note that today's comments include forward-looking statements, such as statements regarding revenue, earnings guidance, and economic conditions. Actual results may differ materially from expectations due to a number of risk and uncertainties discussed in Dynatrace's SEC filings, including our most recent quarterly report on Form 10-Q and our upcoming annual report on Form 10-K that we plan to file later this month. The forward-looking statements contained in this call represent the company's views on May 13, 2026. We assume no obligation to update these statements as a result of new information, future events, or circumstances. Unless otherwise noted, the growth rates we discussed today are year-over-year and non-GAAP, reflecting constant currency growth. And per share amounts are on a diluted basis. We will also discuss other non-GAAP financial measures on today's call. To see reconciliations between non-GAAP and GAAP measures, please refer to today's earnings press release and supplemental presentation, which are both posted in the financial results section of our IR website. And with that, let me turn the call over to our Chief Executive Officer, Rick McConnell.

Thanks, Noelle, and good morning, everyone. Thank you for joining us for today's call. Danny Trace delivered a strong finish to fiscal 2026 marked by meaningful scale, durable execution, and continued innovation. In particular, we surpassed $2 billion in ARR and delivered our fourth consecutive quarter of 16% ARR growth. We drove continued traction in logs, now well over $100 million in annualized consumption, growing more than 100% per year. We launched major platform innovations, including Dynatrace Intelligence and domain-specific AI agents. We advanced our cloud-native integrations across AWS, Azure, and GCP, moving operations from reactive monitoring to autonomous action. We extended our agentic AI ecosystem with native connectivity to Anthropix Cloud Code, deepened our integration with ServiceNow, and broadened developer workflow integrations with GitHub Copilot. We acquired DevCycle, a feature management company, as well as BindPlane, an open standards-based telemetry pipeline company, as we entered the new fiscal year. We maintained a leadership position in all major third-party analyst reports for observability and AIOps. and we delivered robust operating and pre-tax free cash flow margins. Our consistent performance in fiscal 2026 underscores the growing criticality of observability, the strength of our strategy, and the value of our platform to customers. Jim will share more details about our Q4 financial performance and fiscal 2027 guidance in a moment. In the meantime, I'd like to cover four topics. how AI is reshaping the observability market, why we believe Dynatrace is unique, Q4 customer highlights, and the growth opportunity ahead. To begin, observability is entering a new era, one in which observability is more mission critical than ever. But a new set of demands is reshaping what observability must deliver. Observability has already become foundational for enterprises, looking to deliver business resilience amidst growing workload complexity and data volumes. And increasingly, organizations are looking to leverage their observability solution to evolve toward autonomous operations, enabling software to auto-prevent, auto-remediate and auto-optimize. Adopting this approach requires organizations to trust the accuracy of the data that fuels agents to take action. Deterministic and causal insights from Dynatrace allow our platform to become the system of record so that development and SRE teams and increasingly AI agents can act with confidence to deliver what we refer to as answers, not guesses. Beyond business resilience, organizations now need observability for reliable AI. The former addresses the question of, is it working? The latter addresses the question of, is it accurate? Namely, is the content coming from AI models trustworthy in driving action and or credible in providing recommendations to end users? AI also adds yet another layer to the software stack, increasing the need for more observability. Enterprises are deploying new agents, models, orchestration layers, and agentic architectures that behave differently than traditional systems. Their environments generate dramatically more telemetry, connect decisions across agents, and introduce probabilistic behavior that must still operate safely, securely, and at enterprise scale. Organizations now require continuous validation of system and agent behavior, governance and auditability of autonomous decisions, cost control across GPU-intensive infrastructure and strong security management. As a result, software development life cycles are evolving as well, requiring organizations to operate in two modes. The first is human-led, with development teams building and operating resilient systems. These teams are increasingly augmented by AI-powered observability that drives intelligent automation, agentic workflows, and progressively more autonomous operations. We continue to invest to expand our reach in this area by extending left to provide development teams, platform engineers, and SREs with the observability functionality needed to put workloads into production faster. Second mode is agent-led, resulting in AI-first environments in which agents themselves are primarily acting as the builders and operators. In this environment, observability insights are consumed directly by the agents in the creation and oversight of delivered software. And those insights are crucial to the effective and trustworthy operation of the environment. We believe the winner in observability will be the provider that can meet the needs of both human led and agent led environments with a shared system of truth that spans both modes across AI, cloud native and traditional workloads. This is the moment for which the Dynatrace platform has been built. Serving customers in both modes with the trust and accuracy that autonomous operations demand and the reliability that AI-driven initiatives require is exactly what the Dynatrace platform was built to do. So why do we believe Dynatrace is unique? It is because our advantage is architectural, not feature-based. Dynatrace is built as a real-time context engine that operates at massive scale. across millions of monitored entities and exabytes of data, all connected and all in real time. By combining deterministic AI with agentic capabilities, we deliver faster, more accurate insights than approaches that rely on agentic AI alone. This level of intelligence, speed, and efficiency cannot be achieved with point solutions that offer visibility without causality. And this is why so many of the largest organizations in the world rely on Dynatrace. As enterprises increasingly operate in agent-led environments, this architectural advantage compounds. Every new workload, AI service, and agent added to the Dynatrace platform deepens causal context, strengthens autonomous reasoning, and extends the gap between fragmented visibility and the unified intelligence that only Dynatrace delivers. That intelligence is built on three integrated components of our third-generation platform. GRAIL has an extensible AI data lakehouse that connects every signal across an enterprise's digital environment. SmartScape has a real-time integrated topology graph. And Dynatrace Intelligence delivering both answers as well as action. Together, these three elements provide durable competitive differentiation. For other providers that add capabilities across stitched data stores, it's difficult to reproduce a unified data foundation with real-time causality plus trustworthy automation in the most complex mission-critical environments, and certainly extremely difficult to do so in the timeframe AI demands. We've now delivered agents across three domains, and customers are already using them in production to coordinate agents to take end-to-end actions. Our SRE agent handles tasks such as Kubernetes troubleshooting, infrastructure optimization, and automated incident resolution. Our developer agent supports use cases that surface production contacts during deployment, validate changes, and prevent issues before they reach customers. And our security agent identifies vulnerabilities, triaging threats, and accelerating security response, all in real time. That intelligence extends beyond the Dynatrace platform itself. Ecosystem integrations then enable agentic interactions to extend Dynatrace intelligence into third-party tools from ServiceNow and GitHub to the hyperscalers to drive autonomous actions across development, SRE, ITSM, and ITOps workflows. What separates Dynatrace's agents from others is the deterministic foundation underneath. Real root cause analysis, anomaly detection, and forecasting grounded in GRAIL. That's not AI that guesses. It's AI that reasons from facts. More than 500 customers are deploying a Dynatrace's agentic capabilities to run operations autonomously and extend that intelligence into AI development tools like QuadCode and GitHub Copilot. At the same time, more than 850 customers are using Dynatrace to observe and trust AI and LLM workloads in production today. Enterprises aren't just managing their environments with the Dynatrace platform. They're using it as the intelligent foundation for AI agents across their ecosystem, creating a critical role for Dynatrace as AI adoption accelerates. This momentum is increasingly evident in customer wins across multiple buying personas. Highlighting four examples from Q4. One of the largest banks in Brazil signed a seven-figure expansion and is standardizing on Dynatrace with 100% open telemetry data flowing into Grail. Choosing Dynatrace for an open, scalable architecture with a clear runway for broader platform expansion. Another large US-based airline selected Dynatrace as a seven-figure new logo through a partner-originated opportunity. They chose Dynatrace to consolidate a complex multi-vendor environment to improve business observability outcomes and reduce operational disruption. A leading hospitality SaaS provider consolidated onto Dynatrace as a seven-figure new logo. displacing legacy tooling and invoking end-to-end visibility across their cloud-native platform. And an AI-native security platform selected Dynatrace as a seven-figure new logo to deliver end-to-end observability across AWS. Together, these wins reflect increasing demand for an end-to-end AI-powered observability platform in the most complex environments. Looking ahead, our strategy is to win with both human-led and agent-led operating modes on a single platform. Our product and go-to-market approaches reflect this dual reality, combining enterprise engagement focused on business outcomes with a strong developer motion that enables agentic workflows to expand at scale. This strategy leads us to an expanded set of growth drivers for FY27. First, our go-to-market investments in both direct sales and partner enablement have improved productivity and deal quality. End-to-end platform deals are getting larger and more strategic with Q4 annual contract value of anchor deals up 60%, with a record 22 deals with incremental annual contract value over $1 million. PPS, which now represents greater than 75% of ARR, also continues to produce double the platform adoption and consumption of non-DPS customers. Second, cloud growth is an accelerating tailwind, with the major hyperscalers now growing at 40% annually. As customers scale hybrid and multi-cloud architectures across AWS, Azure, and Google Cloud, Dynatrace's expanding cloud-native integrations and automation drive sustained platform usage as complexity and scale increase. Third, logs and telemetry pipelines represent a meaningful consumption and displacement opportunity. With our bind plane acquisition now complete and resulting in expanded ingest from open telemetry, we're simplifying telemetry collection and routing at scale, reducing friction for customers to bring more data into Dynatrace, and we are accelerating time to value plus consumption growth. Fourth, agentic AI itself is an expansion driver. As agentic development accelerates, customers need more context, precise answers, governance, and closed-loop automation, areas in which Dynatrace is structurally advantaged. And finally, developers are a long-term growth engine through the integration of Dynatrace observability into AI development life cycles, including support for Cloud Code, Purser, and GitHub Copilot. With our Dev Cycle acquisition, we extend this opportunity even further, expanding Dynatrace's footprint earlier in the lifecycle and driving durable usage over time. To close, observability is already mission-critical infrastructure for AI-driven enterprises. Context and domain knowledge make Dynatrace not only durable but essential in an AI-first world. We believe we are uniquely positioned with a differentiated end-to-end platform. providing the intelligence engine and AI control plane that produced both insights as well as autonomous action. With tailwinds in cloud and AI, plus Dynastrate-specific growth drivers, we are focused on accelerating ARR growth in fiscal 2027 and enthusiastic about the year ahead. Jim, over to you.