DataDog is currently under acquisition. Just a few weeks after snatching Metaprene, an AI-powered observational potential launch, cloud surveillance and security companies have obtained feature flags and experimental platform EPPO.
Eppo will continue to support existing customers and introduce new customers under the brand “Eppo by Datadog.” The terms of the transaction have not been revealed, but a report from Upstarts Media last week suggests that Datadog is planning to pay $220 million.
Despite the demand for tools that allow developers to experiment with different versions of apps, the infrastructure needed for product analysis remains relatively complicated to build. Beyond data pipelines and statistical methods, experimental infrastructure relies on analytical workflows often delivered from challenging cloud environments.
In an interview two years ago, Eppo co-founder and CEO Che Sharma told TechCrunch that Eppo was inspired by experiencing experimental software as a data scientist for website builders Airbnb and Webflow.
Eppo provides what Sharma calls “confidence intervals” to make it easier to understand and interpret the results of randomized APP experiments. The platform supports experiments with AI and machine learning models and utilizes techniques for performing live experiments that show whether one model outperforms another.
While many startups have appeared in recent years, abstracting app experimental infrastructures such as Split, Statsig and Optimizely, Eppo stands out in the crowded field. According to CrunchBase, the San Francisco, California-based company raised $47.5 million from VC companies, including amplifying innovation efforts, MENLO ventures and partners before its exit.
Eppo had around 15 employees as of June 2022, and the startup was valued at $80 million. At the time, Eppo’s customer base included Goldbelly, Netlify, Kumu and others.
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“Eppo wants to bring a high-speed experimental first culture to businesses of all sizes, stages and industries,” Sharma said in a press release. “With DataDog, product analysis, functional management, AI, and experimental capabilities combine experimental capabilities to reduce risk, learn quickly and ship quality products.”
In the case of Datadog, we recently reported better net profit than expected, but revenue forecasts that are below what analysts expected could potentially make EPPO purchases stronger for the company’s current product analytics solution. The sector is big and healthy. According to Fortune Business Insights, the global market for product analytics was worth $9.09 billion last year, potentially reaching $270.1 billion by 2032.
“Using multiple AI models increases the complexity of deploying applications in production,” said Michael Whetten, Vice President of Products at Datadog, in a statement. “Experiments solve this correlation and measurement problem, allowing teams to compare multiple models side by side, determine user engagement for cost trade-offs, and ultimately build AI products that provide measurable values.”
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