Wild Moose emerges from stealth mode with site reliability platform

Wild Moose, a startup that recently exited stealth mode, has secured $7 million in seed funding for its AI-powered site reliability engineering (SRE) platform. The platform acts as an SRE copilot, helping IT teams investigate incidents and reduce mean time to repair (MTTR).

Wild Moose says its platform works as an AI “first responder” and copilot for SREs—automating investigations, identifying root causes, and recommending resolution next steps in less than one minute. Early adopters of the Wild Moose platform include Wix, Redis, GoFundMe, and Lemonade, and the funding round was led by iAngels, with participation from Y Combinator, F2 Venture Capital, Maverick Ventures, and others. Wild Moose CEO and co-founder Yasmin Dunsky explains how the platform evolves root-cause analysis beyond passive input to proactive resolution.

“For AI to truly serve as a first responder, it can’t stop at passively providing context, such as relevant runbooks, dashboards, or related past incidents. It does need to do all this, but then, also handling the much more challenging—and valuable—task of using this context to autonomously conduct the investigation itself: analyze diverse data sources such as metrics, logs, traces, and code, and reason holistically about the evidence at the root cause,” Dunsky says. “This is the new layer in the stack, AI that operationalizes reliability by closing the gap between ‘you’ve been paged’ and ‘you know what happened.’”

Beyond AIOps and observability

Wild Moose is positioning itself as a new category of AI investigator that is able to go beyond AIOps and observability platforms.

The SRE platform continuously works in the background to learn from logs, metrics, traces, recent code changes, and incident history. Powered by large language models (LLMs) specifically designed to efficiently handle large volumes of contextual data related to incidents, and the system collects telemetry data from multiple sources via API integrations. The platform is designed to be agnostic, working with observability tools such as Datadog, Snowflake, and New Relic.

“We built Wild Moose to live where engineers already work. It’s a SaaS solution that connects with platforms like Datadog, Grafana, New Relic, Coralogix, and Splunk through secure, read-only integrations—using each tool’s standard APIs to pull the same metrics, logs, and traces teams already rely on,” Dunsky explains. “There’s no need to install agents or grant direct access to production systems.”

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.”

The Wild Moose SRE platform captures and validates insights from every incident. Over time, it learns which investigative steps consistently lead to resolution.

“I’ve spent enough time in the trenches at Reddit and Netflix to know what actually matters when things are on fire. Most observability tools just throw more dashboards at you, but Wild Moose actually learns how your systems work and acts like having another senior engineer on call,” said Jeremy Edberg, angel investor in Wild Moose and founding SRE at Reddit and Netflix, in a statement. “It’s not just summarizing logs, it’s connecting the dots between your code changes, your metrics, and that weird spike at 3 am. When you’re trying to keep a site up for millions of users, you need tools that think like engineers, not just tools that generate pretty graphs. That’s what Wild Moose gets right.”

Next-gen SRE

Founded in 2023 by Dunsky, Roei Schuster (CTO), and Tom Tytunovich (vice president of R&D), the company brings deep expertise in AI and reliability. Schuster, who holds a Ph.D. from Cornell University specializing in large language models, helped design the system’s explainable reasoning engine.

“Before Wild Moose, we had a boring name and wanted something with more character. At first, we thought of Wild Goose Chase because that represents finding the root cause. But then one day we switched up the goose for a moose, put Wild Moose on our name tags at a Y-Combinator event, and the response was overwhelming, so we went with it!” Dunsky says.

Now, with fresh funding, the team plans to scale its go-to-market efforts and expand the platform’s capabilities beyond incident response. “The next generation of reliability engineering will be AI-augmented: humans setting strategy, AI handling the noise,” Dunsky says. “At Wild Moose, we see this as empowerment, not replacement: world-class reliability without burnout, powered by systems that learn from every incident.”

Wild Moose competes with the likes of PagerDuty, BigPanda. And others that offer cloud-based incident management software as well as observability platforms with which it integrates, such as Datadog and New Relic.