• Dynatrace simplifies cloud complexity and accelerates digital transformation with its intelligent platform, with Davis AI at its core.
  • The causation engine delivers answers about software application performance, underlying infrastructure, and user experience, not just data.

Dynatrace Inc., a company specializing in observability and cybersecurity, is transforming its artificial intelligence-powered causation engine, Davis AI. This evolution merges fact-based causal AI, which provides predictive insights, with generative AI. According to the company, the result is the industry’s first “hypermodal AI” engine.

The newly unveiled enhanced Dynatrace Davis AI engine is anticipated to improve productivity for business, development, security, and operations teams. It achieves this by providing generative AI recommendations fueled by the most accurate context extracted from the company’s causal and predictive AI systems. According to the company, it will simplify and accelerate tasks such as creating automation and dashboards.

Dynatrace developed an intelligence platform to streamline cloud complexity and expedite digital transformation, with Davis AI at its core.

It’s a causation engine that provides data and answers questions about software application performance, infrastructure, and end-user experience. It enables organizations to modernize and automate enterprise cloud operations, deliver more frequent software updates, and provide optimal user experiences to their employees and customers.

Dynatrace is now enhancing Davis AI’s capabilities with the most recent advances in generative AI, which power conversational chatbots like ChatGPT. According to Bernd Greifeneder, Chief Technology Officer, most people understand that generative AI can potentially deliver massive productivity gains. He believes that combining generative AI with other AI techniques will result in what he refers to as a “hypermodal AI” engine.

Greifeneder explained, “This is because only causal AI can deterministically know the root cause of an issue, only predictive AI can see into the future reliably. And only generative AI can tailor recommendations and solutions to specific problems using advanced probabilistic algorithms.”

Davis AI employs predictive AI models to suggest future actions based on historical data. Sales data and customer experience trends, seasonality, the state of cloud applications, and other historical behaviors are all included.

Utilizing causal AI enables it to offer fact-based, deterministic, and precise responses. It intelligently analyzes dependencies across extensive observability and security data, ensuring accurate context retention. This empowers customers to proactively anticipate and address potential performance and security concerns for their applications and infrastructure, preventing problems before they arise, as stated by Dynatrace.

Meanwhile, Davis AI’s new generative AI capabilities boost its creativity by recommending ways for users to complete and solve specific tasks and problems based on the context of the environment and situation. According to Dynatrace, generative AI collaborates with causal and predictive AI to automatically deliver recommendations and create new workflows and dashboards. Users can also ask and explore their data using natural language.

Although Dynatrace asserts that it’s introducing something novel, Constellation Research Inc. Vice President and Principal Analyst Andy Thurai believes the announcement is merely another instance of a company “generative AI-washing” an existing solution to align with current trends. He explained that most AIOps providers already have forecasting and predictive AI capabilities, as well as deterministic root cause analysis.

He said, “This is nothing new. Many observability firms have offered these precise deterministic casual answers for years already. Some vendors, such as Splunk, even offer these capabilities across both observability and security data. Intelligent automation and autoremediation are also not new.”

According to Thurai, Dynatrace’s use of generative AI to assess historical incidents and make recommendations based on the customer’s particular scenario is novel. However, it’s a use case that many other companies are investigating. Thurai said, “Dynatrace has a decent observability platform, but these announcements are mostly about playing catch-up with its rivals.”

As a response, Dynatrace’s Vice President of Marketing, Bob Wambach, refuted Thurai’s claims, emphasizing that Davis AI stands out in the industry due to its utilization of causal AI. He said, “It’s reflective of a continuously updated topology that enables Davis AI to pinpoint the root cause of an issue, whereas others use machine learning-based AI to predict outcomes based on a probalistic root-cause analysis. These two approaches are radically different.”