Dynatrace is expanding its Davis AI engine to create the hypermodal artificial intelligence (AI), converging fact-based, predictive- and causal-AI insights with new generative-AI capabilities. The expanded Davis AI will boost productivity across business, development, security, and operations teams by delivering generative-AI recommendations fueled by precise context from predictive- and causal-AI techniques that reflect the unique attributes of each organization’s hybrid and multicloud ecosystem.

It will also simplify and accelerate tasks, such as creating automations and dashboards, to enable people to focus on higher-value activities for faster, better, and more secure innovation.

Dynatrace Davis AI provides these capabilities:

• Davis predictive-AI models and dynamic machine learning anticipate future behavior based on past data and observed patterns. This capability allows customers to anticipate and remediate future needs and issues related to the performance and security of their software.
• Davis causal AI analyzes real-time and context-rich observability, security, and business data within the Grail data lakehouse and causal dependencies from Smartscape topology to provide the precise answers and intelligent automation that are necessary for issue prevention, deterministic root-cause analysis, and automated risk remediation.
• Davis CoPilot generative AI works with Dynatrace predictive and causal AI to automatically provide recommendations, create suggested workflows and dashboards, or let people use natural language to explore, solve, and complete tasks.

Bernd Greifeneder, CTO at Dynatrace, said: “We expect Davis AI will enable our customers to achieve substantial productivity gains year-over-year as they drive transformation initiatives related to observability and security.”

Davis predictive and causal AI are available now for all customers, while the expansion to include Davis CoPilot will be available later in 2023 and accessible to all customers as a core technology within the Dynatrace platform.