RunLLM

RunLLM is an advanced AI-powered support tool designed to resolve complex technical issues efficiently and accurately. Developed leveraging over a decade of UC Berkeley research, it combines fine-tuned language models (LLMs), knowledge graphs, and search mechanisms to deliver precise, context-rich answers. RunLLM reads and analyzes logs, code, and documentation to reduce mean time to resolution (MTTR) by 50%, deflect up to 99% of tickets, and save over 30% of engineering time.

The platform is built for technical products, offering capabilities such as agentic reasoning, debugging log analysis, validated code generation, and proactive follow-ups. It learns from your documentation, codebase, and customer interactions to create a unified knowledge graph that powers accurate, multimodal responses. RunLLM integrates seamlessly with popular tools like Slack, Zendesk, and Docs, ensuring support is accessible across various channels.

RunLLM enables businesses to scale their support operations without compromising quality by training dedicated AI agents tailored to their product terminology and edge cases. These agents can be customized for tone, behavior, and output, whether for technical support or business-level responses. The tool also provides continuous insights from support interactions, helping teams identify documentation gaps and improve product offerings.

Trusted by companies like Databricks, Sourcegraph, and Corelight, RunLLM delivers reliable, validated answers that instill user confidence. Its rapid onboarding process allows businesses to ingest their knowledge base, validate the trained AI agent, and deploy it across multiple channels in minutes. By automating routine inquiries and improving response accuracy, RunLLM enhances customer satisfaction (CSAT) and loyalty while freeing teams to focus on strategic initiatives.