RunLLM is an AI Site Reliability Engineer (SRE) designed to streamline incident response by integrating with existing tech stacks. It helps teams quickly understand and resolve alerts, cutting through the noise of traditional observability tools. With its ability to correlate alerts, logs, metrics, and tickets, RunLLM offers actionable insights within minutes, which can significantly improve response times and reduce alert fatigue. The platform starts in a read-only mode, ensuring safety as it investigates incidents without making changes until trust is established. It connects with various observability tools and provides a Slack-first interface for ease of use. RunLLM continuously learns from each incident, improving its responses and reducing Mean Time to Recovery (MTTR) over time. This feature allows teams to prevent recurring issues by identifying risks early and leveraging past incident data for future investigations. Founded by experts from UC Berkeley, RunLLM combines cutting-edge research with practical applications in AI and large language models. The goal is to empower engineers with veteran-level guidance during live incidents, enabling them to act confidently even if they're new to on-call duties. The system ramps up new team members quickly, helping them gain the necessary experience without lengthy onboarding processes.