Datadog has acquired Eppo, a feature-flagging and experimentation platform. Despite the demand for tools that let developers experiment with different versions of apps, the infrastructure required for product analytics remains relatively complex to build. Beyond data pipelines and statistical methods, experimentation infrastructure relies on analytics workflows often sourced from difficult-to-configure cloud environments. Eppo will continue supporting existing customers and bringing on new ones under the brand “Eppo by Datadog.” Eppo offers “confidence intervals” to make it easier to understand and interpret the results of a randomized app experiment. The platform supports experimentation with AI and machine learning models, leveraging techniques to perform live experiments that show whether one model is outperforming another. Eppo co-founder and CEO Che Sharma said “With Datadog, we are uniting product analytics, feature management, AI, and experimentation capabilities for businesses to reduce risk, learn quickly, and ship high-quality products.” For Datadog, the Eppo buy could bolster the company’s current product analytics solutions. “The use of multiple AI models increases the complexity of deploying applications in production,” Michael Whetten, VP of Product at Datadog, said. “Experimentation solves this correlation and measurement problem, enabling teams to compare multiple models side-by-side, determine user engagement against cost tradeoffs, and ultimately build AI products that deliver measurable value.”