Features
Expert-curated supervised fine-tuning data
Reinforcement learning with expert-designed rubrics
Agent environments via API/MCP
Computer-use trajectories (browser/desktop)
Proprietary benchmarks (SpreadsheetBench, IDE-Bench, etc.)
Domain-specific data (finance, coding, UI)
Partnership with The Raine Group
Research publications on data quality
Model evaluation frameworks
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
