Features
Automatic alert investigation triggered by Slack alerts
Root cause analysis across logs, traces, metrics, and code
2–3 minute average time to root cause with citations
Natural language chat in Slack and web app for follow-ups
Auto-generated pull requests for fixes
Runbook and documentation updates
Linear ticket creation with full context
Rule-based alert noise reduction
Automatic priority ranking by business impact
Related alerts grouped into single incidents
Living knowledge graph mapping system architecture in real-time
Cross-references logs, traces, metrics, and code
Learns over time from feedback and past investigations
20+ integrations with observability and collaboration tools
No code changes required to integrate
Trace agent executions step by step
Monitor real-time dashboards with cost tracking
Online LLM-as-judge evals for quality scoring
Automated insights with unsupervised topic clustering
SmithDB purpose-built for agent traces
Sub-second query performance across millions of traces
Full-text search with inverted index
JSON key-path filtering and trajectory queries
Self-host SmithDB inside your VPC
LangSmith Engine for autonomous issue detection and fixes
Deploy and scale agents with LangSmith Deployment
Sandboxes for safe agent-generated code execution
Fleet agents for no-code agent creation
Supports Python, TypeScript, Go, Java SDKs
