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About Aqueduct

RunLLM is an AI Site Reliability Engineer (SRE) that automates and accelerates incident resolution by integrating with existing observability tools, code repositories, ticketing systems, and chat platforms. It acts as an always-on agent, correlating alerts, logs, metrics, traces, and tickets to provide evidence-backed investigations and clear next steps for mitigation and root cause analysis (RCA). Designed for SRE teams, on-call engineers, and anyone responsible for system uptime, RunLLM aims to reduce alert fatigue, improve uptime, and prevent repeat incidents. It continuously learns from every investigation and user correction, adapting to specific environments and capturing tribal knowledge to provide veteran-level guidance during live incidents. The platform is built for rapid deployment, offering day-one value by connecting to existing tools without complex setup. RunLLM leverages advanced AI and LLM research from UC Berkeley, employing sophisticated data engineering, model specialization, and decision intelligence to understand complex technical data. It provides transparent reasoning, starting in read-only mode for safety, and allows for human-in-the-loop approvals for any actions, ensuring trust and control.