Observability and cybersecurity firm Dynatrace Inc. is revamping its artificial intelligence-powered causation engine, Davis AI, converging fact-based causal AI that delivers predictive insights with generative AI to create what it says is the industry’s first-ever “hypermodal AI” engine.

Announced today, the enhanced Dynatrace Davis AI engine is expected to boost productivity for business, development, security and operations teams by delivering generative AI recommendations fueled by the most precise context from the company’s causal and predictive AI systems. It also promises to simplify and accelerate tasks such as creating automations and dashboards, the company said.

Dynatrace is the creator of an intelligence platform that aims to simplify cloud complexity and accelerate digital transformation. Davis AI is at the center of this platform.

It’s a causation engine that provides not just data, but also answers questions about the performance of software applications, the infrastructure they sit on, and the end-user experience. It helps organizations to modernize and automate enterprise cloud operations, push out software updates more frequently, and deliver optimal user experiences for their employees and customers.

Now, Dynatrace is enhancing Davis AI’s capabilities with the latest developments in generative AI, which is the technology that powers conversational chatbots like ChatGPT. Chief Technology Officer Bernd Greifeneder said most people already understand that generative AI has the potential to deliver massive productivity gains. The key to delivering these gains, he said, is to merge generative AI with additional AI techniques, creating what he calls a “hypermodal AI” engine.

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

Davis AI uses predictive AI models to recommend future actions based on data from the past. That includes sales data and customer experience trends, seasonality, cloud application health and other historical behavior.

By leveraging causal AI, it can deliver fact-based, deterministic and precise answers and intelligent automation by analyzing dependencies across large sets of observability and security data while retaining an accurate context. That will help customers to anticipate and remediate future needs and issues related to the performance and security of their applications and the underlying infrastructure before problems occur, Dynatrace said.

Meanwhile, the new generative AI capabilities enhance Davis AI’s creativity by recommending ways in which users can complete and solve specific tasks and problems based on the context of the environment and situation. Dynatrace explained that generative AI works in tandem with causal and predictive AI to automatically deliver recommendations, create new workflows and dashboards. Users can also use natural language to ask questions of and explore their data.

Despite Dynatrace’s claims to be offering something original, Constellation Research Inc. Vice President and Principal Analyst Andy Thurai said the announcement is really just another example of a company “generative AI-washing” an existing solution to keep up with the latest trend. He explained that the forecasting and predictive AI capabilities are already a staple of most AIOps providers, as is the deterministic root cause analysis.

“This is nothing new,” he said. “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.”

Somewhat more kindly, Thurai said that Dynatrace’s use of generative AI to analyze past incidents and offer recommendations based on the customer’s unique situation is new, but even then it’s a use case that many other providers are pursuing. “Dynatrace has a decent observability platform, but these announcements are mostly about playing catch-up with its rivals,” Thurai said.

Gartner Inc. analyst Gregg Siegfried offered a different take, saying that while Dynatrace’s “hypermodal” approach sounds fluffy, it has a legitimate claim that the various AI technologies are better together.

“The ability to leverage the predictive and generative AI engine together to emphasize and potentially stave off an outage or degradation is novel, as is the ability to ‘self-correct’ by using the causal engine in conjunction with the generative AI to enrich, remediate or resolve an active incident,” Siegfried said. “The ability to use both the predictive and causal engines along with the topology data as part of prompt engineering toward a generative AI engine is also novel.”

Dynatrace Vice President of Marketing Bob Wambach also countered Thurai’s assertions, pointing out that Dynatrace generative AI is new code, some of which was previewed on stage at Dynatrace Perform in February of this year, and insisting Davis AI is unique within the industry thanks to using causal AI in addition to predictive and generative AI techniques. “Davis AI root-cause analysis reflects a continuously updated topology, enabling it to pinpoint an issue, whereas others are based upon correlation techniques,” he said.

Image: Dynatrace