Today, we’re thrilled to announce our $7M Seed round led by iAngels, with participation from Y Combinator, F2 Venture Capital, Maverick Ventures, and others. We're also incredibly proud to be backed by an exceptional group of angels at the forefront of AI research and reliability engineering, such as Joel Pobar (AI researcher at Meta Superintelligence Labs, formerly Anthropic), Jeremy Edberg (Founding SRE at Reddit & Netflix), Arash Ferdowski (Co-Founder of Dropbox).
Why We Built Wild Moose
Root cause analysis is one of the hardest problems in engineering.
When production goes down, every second counts. But engineers are forced to hunt through fragmented observability tools, piece together context from Slack threads and dashboards, and make high-stakes decisions under pressure.
When we founded Wild Moose in 2023, we set out to fundamentally change how teams respond to incidents. Even before ChatGPT launched, we knew generative AI could transform this critical workflow, but only if we could deliver accuracy, speed, and trust simultaneously.
Most AI SRE solutions stop at summarization. But in a critical workflow, there's no room for nice-to-have, generic recommendations. Engineers need a tool that understands their system at least as well as they do.
Wild Moose acts as an AI first-responder that conducts structured investigations. When an incident occurs, the platform automatically gathers logs, metrics, traces, recent code changes, and incident history. It cross-references anomalies, validates hypotheses against raw telemetry, determines root causes, and provides the exact steps that need to be taken, all in real time and under one minute.
Instead of creating another dashboard to manage, Wild Moose surfaces results directly in Slack or Teams, where engineers already work. It acts as another team member, continuously learning and codifying tribal knowledge into dynamic playbooks that evolve with every incident.
And because this is enterprise infrastructure handling sensitive production data, we built security and trust into the foundation including SOC 2-compliant controls, read-only integrations, and in-memory processing.
Early customers, including Wix, Redis, GoFundMe, and Lemonade are leveraging Wild Moose to shrink mean time to resolution (MTTR) by up to 80%, while reducing alert fatigue and freeing engineers to focus on building rather than firefighting.
As teams increasingly leverage AI to develop and deploy faster, reliability becomes the foundation of trust between businesses and their customers. We're building the AI member of every R&D team: one that never sleeps, never misses a signal, and ensures consistency and quality at every step.
We're just getting started, and we're deeply grateful to our investors for backing us in this mission.
Wild Moose is led by three technical co-founders: Yasmin Dunsky (CEO), Roei Schuster (CTO), and Tom Tytunovich (VP R&D). CTO Roei Schuster holds a Ph.D. from Cornell University specializing in Large Language Models, bringing cutting-edge academic insight into the design of Wild Moose's intelligent investigation engine. To read publications by Roei Schuster, click here.