AI agents for Elastic
An AI agent for Elastic is a configured assistant that can gather context from Elastic data, reason over the results, and produce a summary, recommendation, or next action for human review. It is more than a one-off prompt because it follows a repeatable operating pattern.
Why use AI agents with Elastic?
Manual alert triage and incident context gathering can take many minutes. An agent with clear limits can query Elasticsearch, inspect related events, summarize evidence, and help analysts focus on decisions instead of copy-paste work.
Who benefits from AI agents?
SOC analysts use agents for SIEM alert triage. SRE teams use them during observability incidents. Elastic Cloud administrators use them for routine health checks and operational summaries.
How do you get started?
Start with a bounded task. Define the trigger, allowed data sources, queries, reasoning steps, output format, and human approval point. Then test the agent on non-production data.
How this differs from related AI resources
Agents execute or guide work. AI tools are the software they may call. AI workflows document the process the agent follows. AI skills provide reusable instructions inside the agent.
Browse Elastic AI agents
Network Engineering Topology for Kibana
Import a clickable Kibana topology dashboard with Vega zone and adjacency views, plus an Agent Builder readiness agent that checks whether discovered devices have enough evidence for reliable map placement.
Network Analyzer Agents for Elastic
Use three Elastic Agent Builder agents and supporting ES|QL tools to analyze network health, packet evidence, Suricata findings, DNS/TLS risks, HTTP failures, and top conversations.
Related Elastic resources
Continue with Elastic Security downloads, Elastic Observability examples, ES|QL examples, and runtime field examples.