The startup designed its architecture to meet enterprise-grade security requirements. The platform is SOC 2–compliant, processes all data in memory, and doesn’t store customer logs or telemetry. That approach, the company says, allows adoption even in highly regulated industries where data control is critical. The company says the transparency is intentional to also avoid AI hallucinations: the system operates within customer-defined boundaries and uses read-only integrations with third-party platforms, avoiding any need to access production environments directly.
“Every Wild Moose insight is traceable back to its evidence,” Dunsky says. “Our AI doesn’t invent signals—it cites them. Engineers stay in control, able to see the reasoning chain and supporting data at any time.”
Early adopters report wins
Wild Moose customers report using the platform to accelerate problem resolution across sophisticated environments.
At Wix, which runs more than 4,000 microservices supporting hundreds of millions of users, Wild Moose has become part of the daily reliability workflow, according to Dunsky. Within three weeks of integration, the company achieved more than 80% root-cause accuracy and now enriches more than 30,000 alerts per month.
At Redis, the CloudOps team uses Wild Moose to automate root-cause analysis across thousands of distributed databases. What once took around 20 minutes of manual investigation now takes less than one minute, with more than 90% accuracy, according to the Wild Moose.
“Every incident teaches something, but that knowledge usually stays in chat threads or postmortems,” Dunsky says. “Wild Moose captures those insights automatically, verifies them against outcomes, and converts them into dynamic playbooks that update themselves.”
