RunLLM is an AI support engineer that reads logs, code, docs, and telemetry to resolve technical support issues, correlate alerts, and guide through investigations and resolutions.

Who is RunLLM best for?

RunLLM is best for engineering and support teams at tech companies handling complex customer issues, such as those at Databricks, Sourcegraph, and Corelight.

Do I need to install anything to use RunLLM?

No, you do not need to install anything; RunLLM integrates directly with your tools like Slack, Zendesk, Datadog, and GitBook via connectors and widgets.

Does RunLLM have a plan for teams or businesses?

Yes, RunLLM offers plans for teams and businesses with customizable agents, multi-agent support, and enterprise features.

Does RunLLM offer an API or integrations?

Yes, RunLLM offers integrations with tools like Slack, Zendesk, Datadog, Splunk, GCP Logging, Grafana, and GitBook, plus a Python SDK for custom workflows.

How do I contact RunLLM support?

Email info@runllm.com for support.

RunLLM: Reviews, Pricing, Alternatives & Features (2026)

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RunLLM is a web-based AI SRE (Site Reliability Engineering) tool for SREs, support engineers, and technical teams that need faster incident investigation across complex observability stacks.

It connects to telemetry and operational context to investigate alerts automatically and produce actionable outputs:

Rapid RCA and mitigation guidance by correlating alerts with logs, metrics, traces, tickets, code, and documentation, then returning prioritized next steps with verification checks.
Self-teaching investigations that map a team’s stack, learn from incidents and user corrections, and reuse proven investigation steps over time.
Agentic workflows and customization (v2) with a UI for managing suites of agents plus a Python SDK for custom triage, escalation, and support workflows.
Connectors and integrations including Datadog, Splunk, GCP Logging, Grafana, Slack, and Zendesk, with read-only by default, full action logging, and SOC 2 Type II compliance.

Pricing: Contact for pricing.

Notable for combining incident-response automation with multi-agent collaboration, validated code execution, and real-time reasoning, and for being used by vLLM to deflect 99% of 13k+ monthly technical questions.