Generative AI enables teams to write and ship code faster than ever. But current methods for testing and quality assurance have not evolved to match the new pace and scale of deployments. Manual and deterministic testing paths quickly become obsolete when new features are released, and they fundamentally can’t test AI outputs, leaving a massive untested surface area. To keep up, teams need new testing methods that can define what goals users have, and ensure that their outcomes match. That’s why we’re thrilled to announce that Propolis is joining Datadog.

What is Propolis?

Propolis is an autonomous QA testing platform that specifically tackles goal- and output-oriented testing. Propolis’s agents explore your application and automatically identify real user journeys and goals. Using swarms of synthetic users to test and verify successful outcomes across complex, nondeterministic, or even agentic user journeys and dynamic environments, Propolis can catch errors that traditional tools miss. It then autonomously self-heals these tests and keeps coverage up to date via subsequent runs and continuous test generation, removing the need for human intervention.

Datadog + Propolis

By combining Propolis with Datadog’s deep production context – including traces, logs, and Real User Monitoring (RUM) data – we are creating the first solution to truly automate testing end-to-end. By integrating Propolis and Datadog, agents can infer user intent from how applications are actually used, not just how they were designed. Quality shifts from a slow pre-release gate to a continuous signal embedded in CI/CD and runtime.

Stay tuned for future updates on our progress as we work to bring Propolis’s features into Datadog.