Wild Moose: Solve production incidents faster with Gen AI

Wild Moose: Helping On-Call Devs Tame Production Chaos with Generative AI

The tech industry has been growing at a rapid pace, and so are the demands and expectations of the consumers. As a result, developers spend over 30% of their time solving production issues, which often lead to millions in lost revenue. Debugging in production can be an arduous task, and it can take hours, if not days, to identify the root cause of an issue. Fortunately, Wild Moose is here to help on-call developers tame production chaos with Generative AI. In this article, we will explore the company's background, its founders, the problem it solves, its solution, how it works, and its technology.

Introducing Wild Moose

Wild Moose is a San Francisco-based start-up that was founded in 2022. The company's mission is to help on-call developers more quickly identify the source of production incidents. They do this by providing a conversational AI trained on their environment. They feed observability data into a Large-Language Model. Then, when something breaks, they can just ask the moose a question and get an answer.

The Challenge of Production Debugging

With developers spending over 30% of their time on production issues, and incidents leading to millions in lost revenue, there’s no need to say much about the headache that is production debugging. The traditional debugging process can be tedious, time-consuming, and frustrating. Moreover, it is often done in a reactive manner, which can lead to prolonged downtime, missed SLAs, and poor user experience.

Faster Incident Resolution with Wild Moose

Wild Moose's solution is to help on-call developers more quickly identify the source of production incidents. The company's Generative AI allows developers to solve issues in minutes instead of hours, reducing MTTR 100x. It helps developers avoid costly downtime, save time, and keep their SLAs in check. With Wild Moose, developers can navigate through heaps of logs, metrics, and other people's code, build queries like a pro for any observability tool (Elastic, Datadog, SQL DBs, etc.), and get next-step recommendations so they stay on track when the pressure is on and they're flooded with data.

The Power of Conversational AI for Debugging in Production

When you sign up for Wild Moose, their team will help you integrate their conversational AI into your observability stack. Once you’re set up, the AI will begin to learn the ins and outs of your system, your code, and your team’s past incidents.

When something goes wrong, you can simply ask the moose a question, and it will provide an answer based on the data it has gathered. The answer may include specific code snippets, log entries, or other relevant data points that can help you identify the root cause of the problem.

One of the advantages of using Wild Moose is that the AI is always on-call and ready to help, even in the middle of the night. This can be a huge relief for on-call developers who might otherwise have to wake up and spend hours sifting through logs to find the source of an incident.

In addition to providing quick answers, Wild Moose can also help you navigate through heaps of logs, metrics, and other people’s code. It can build queries for any observability tool, including Elastic, Datadog, SQL databases, and more. And, it can even give you next-step recommendations so you can stay on track when the pressure is on and you’re flooded with data.

Overall, Wild Moose can help you solve production incidents faster and with more accuracy, reducing your MTTR 100x. This can save you time and money, and help you keep your SLAs in check.

Innovative AI Techniques that Power Wild Moose's Debugging Solution

Behind the conversational AI experience lies Wild Moose's special-purpose Large Language Models (LLMs). The LLMs have been designed to efficiently ingest massive contextual data about a given incident, including code, logs, and other relevant data points.

The LLMs are fed with observability data from your environment, and they learn the patterns of your system over time. They use this knowledge to provide quick and accurate answers when you have a question.

One of the key features of Wild Moose's technology is that it validates the produced answers against the original sources of truth, giving you trustworthy information when you need it the most. This ensures that the AI is providing accurate answers that you can rely on.

In addition, Wild Moose automates your postmortem generation, helping you learn from incidents and improve your system over time. This can help you avoid future incidents and reduce the time it takes to resolve them when they do occur.

Meet the Founders of Wild Moose

Yasmin Dunsky holds an MBA from Stanford and has a successful track record in founding and leading ventures, including an ecosystem that trains thousands of female software developers across Israel. She served as an analyst for the Israeli Special Forces Intelligence and holds a BSc in Computer Science from The Hebrew University.

Roei Schuster is the CTO of Wild Moose. Before co-founding the company, he was a post-doc at the Vector Institute of AI, after completing a PhD at Cornell and Tel Aviv University. His research focused on security and privacy of AI, and particularly NLP. Before that, he did his undergrad at the Technion and served in the IDF's 8200 alongside his co-founder Tom.

Tom Tytunovich has been building software since 2002. He has worked as a software developer, architect, and engineering manager in both tiny startups and large corporations. He also served as CTO of a nonprofit building technology with people who are homeless in NY. With Wild Moose, Tom is using his expertise to help on-call developers solve production incidents faster and with more accuracy.


Wild Moose is a promising startup that offers a unique solution to a common problem faced by on-call developers in today's fast-paced software development world. By leveraging generative AI and large language models, Wild Moose provides a conversational AI experience that helps developers quickly identify the source of production incidents, saving valuable time, reducing MTTR, and avoiding costly downtime.

With its impressive founding team and innovative technology, Wild Moose is poised to disrupt the observability and incident response market. Its ability to learn from incidents and automate postmortem generation also provides added value to customers, helping them improve their overall incident management process.

As Wild Moose continues to grow and expand its offerings, it will be interesting to see how it evolves and adapts to the ever-changing needs of the software development industry. One thing is for sure: with the backing of its talented team and cutting-edge technology, Wild Moose has the potential to become a major player in the observability and incident response space.

If you're an on-call developer looking to tame the chaos of production incidents, Wild Moose is definitely worth checking out. With its conversational AI experience and ability to quickly provide accurate and trustworthy answers, it may just become your new best friend in the world of incident response.