Dynatrace launches intelligence system combining AI approaches

Dynatrace (NYSE: DT) announced Dynatrace Intelligence at its Perform conference in Las Vegas, introducing what the company describes as a system that combines deterministic and agentic artificial intelligence for observability operations.

The system aims to provide visibility into AI workloads and enable automated responses to system issues. Dynatrace Intelligence builds on the company's existing platform components, including Grail, a data lakehouse that stores various types of operational data, and Smartscape, which maps system dependencies.

According to the company's internal benchmarking, when an external site reliability engineering agent worked with Dynatrace's deterministic agents, problems were resolved 12 times more often, three times faster, and at half the cost compared to tests without deterministic agents.

The system includes integrations with platforms from ServiceNow, Amazon Web Services, Microsoft Azure, Google Cloud, Atlassian, GitHub, and Red Hat. Dynatrace positions the technology as supporting a progression from reactive monitoring to autonomous operations.

"Agentic AI offers enormous potential, but many businesses still struggle to ensure it operates reliably, securely, and with consistent performance in real-world environments," said Bernd Greifeneder, chief technology officer and founder at Dynatrace. "Dynatrace Intelligence fuses deterministic and agentic AI, removing the guesswork and delivering AI-powered observability organizations can trust."

The announcement comes as global AI investment is projected to reach nearly $2 trillion in 2026, according to Gartner data cited by the company. Organizations face increasing pressure to demonstrate returns on AI investments while managing the complexity of AI systems.

Dynatrace Intelligence is designed to allow organizations to progress through phases of automation adoption, from AI-driven insights to supervised operations and ultimately autonomous operations with oversight controls.

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