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Dynatrace highlighted real-world customer successes at its Perform 2026 conference, demonstrating how its AI-powered observability platform enables organizations to scale AI applications safely, reliably, and cost-effectively. As enterprises shift from AI experimentation to production—driven by predictions that 40% of enterprise apps will integrate task-specific agents—Dynatrace provides the unified visibility, automation, and governance needed to manage complexity, ensure compliance, and deliver tangible business impact.
Canadian technology leader TELUS consolidated multiple monitoring tools into the Dynatrace platform, achieving significant operational gains. By leveraging Dynatrace AI Observability, TELUS reduced onboarding time for new teams by 30%, minimized tooling costs, and accelerated observability deployment through automation and monitoring-as-code capabilities. Incident resolution improved dramatically, enabling faster innovation and greater reliability for critical digital services.
“By combining our Agentic AI initiatives with Dynatrace’s AI Observability capabilities, we’ve successfully optimized our development and operations workflows. This collaboration has enabled us to streamline incident resolution to minutes, from detection to pull requests. Through this integration of AI technologies, we’re driving innovation and delivering measurable business impact while reducing downtime,” states Kulvir Gahunia at TELUS.
Despite widespread AI enthusiasm, most initiatives fail to generate returns due to challenges in scaling to production. Dynatrace counters this with comprehensive observability across the agentic AI stack, providing a single view of internal and external models, orchestration layers, and services. This enables teams to monitor, govern, and optimize AI workloads while mitigating risks such as data leakage, prompt injection, and policy violations.
New capabilities include support for a wide ecosystem of agentic frameworks and services, model versioning with A/B testing for data-driven optimization, and AI-powered forecasting to predict cost and performance trends. These features help organizations move from reactive fixes to proactive management, turning AI into a reliable driver of business outcomes like faster innovation, improved reliability, higher customer satisfaction, and operational efficiency.
“Across industries, our customers are leading the shift from AI experimentation to AI at enterprise scale,” said Steve Tack, Chief Product Officer at Dynatrace. “Their work demonstrates how deep observability of modern AI workloads – using LLMs, agentic AI workflows, and generative AI applications – enables organizations to move faster and more confidently. By combining visibility with automation and intelligent analytics, our customers are turning AI into measurable business outcomes – faster innovation, improved reliability, higher customer satisfaction, and stronger operational efficiency.”
About Dynatrace
Dynatrace is advancing observability for today’s digital businesses, helping to transform the complexity of modern digital ecosystems into powerful business assets. By leveraging AI-powered insights, Dynatrace enables organizations to analyze, automate, and innovate faster to drive their business forward.
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