Dynatrace

Dynatrace's core AI engine, Davis, was designed as a deterministic, causal AI rather than a probabilistic model. It performs real-time root-cause analysis and drives automated remediation based on a unified contextual dataset called Grail, rather than relying on separate logs, metrics, and traces that an LLM must summarize. The company argues this produces actionable answers instead of guesses.

Security is offered as a native capability within the Dynatrace platform, not a separate module requiring data export. It provides vulnerability discovery, prioritization, and shielding in real time, drawing on the same topology model used by the observability and AI operations functions to correlate security risks with application performance.

Published customer evidence points to strong adoption in financial services, aviation, government, and retail. Named logos include SAP, Delta Air Lines, and the U.S. Department of Veterans Affairs. The company's compliance posture and deterministic AI model appeal to organizations where system reliability directly affects revenue or citizen services.

The Grail data lakehouse ingests all observability, security, and business-event data into a single store with retention measured in years rather than days. This architectural choice locks in customers through high switching costs — historical data gets richer over time — and lets Dynatrace charge on a consumption basis rather than per-seat or per-monitored-host.

Dynatrace Intelligence, launched at Perform 2026, coordinates AI agent actions across cloud platforms, developer tools, and IT service management systems. It aims to extend the platform from automated incident response to predictive, cross-tool orchestration that prevents problems before they affect users, representing a push into fully autonomous IT operations.