Dynatrace is seeing significant business growth right now. Many companies are moving their AI projects from small tests into full production. This growth happens because organizations need better ways to keep their AI reliable and cost-effective. Dynatrace AI Observability gives these teams the data they nee d to stay in control. It helps them track exactly how much their AI costs and how well it actually performs. Without these insights, many firms struggle to show that their AI investments are worth the money.
The platform makes it easier to manage agentic AI, where software agents make decisions on their own. Dynatrace provides the visibility needed to make sure these agents do not make mistakes or leak data. This is a major fact or for big companies that cannot afford security slips or slow apps. By catching technical bottlenecks early, teams can keep their services running fast for their customers. This kind of oversight is quickly becoming a requirement for any large company using modern AI tools.
Making AI Work Better for Real Companies
Proving that AI actually helps the bottom line is a major challenge for many leaders today. Dynatrace AI Observability provides the clear evidence they need to justify their technology spending. For instance, the Canadian company TELUS has been using the platform to improve how it handles technical workloads. They managed to reduce the effort to deploy observability from 600 minutes down to just 20 minutes. This efficiency lets their developers focus on building new things instead of just fixing old problems.
Dynatrace is also making sure its tools work across all big cloud providers like AWS and Google. This means companies can grow their AI systems without getting stuck with just one vendor. As more businesses turn to autonomous software, the need for a steady control plane only gets bigger. Dynatrace is positioning itself as that foundation to help brands innovate faster. Their recent success shows that the market is hungry for tools that make AI both safe and smart.
“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,” said Steve Tack, Chief Product Officer at Dynatrace.
“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,” said Kulvir Gahunia, Director of the Site Reliability Office at TELUS.
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News Source: Businesswire.com
