Langsmith

LangSmith provides a framework‑agnostic platform for observing, evaluating, and deploying AI agents and LLM‑driven applications. It captures full execution traces, allowing developers to debug failures by reviewing each step an agent takes, and offers built‑in assistance to summarize large traces. The observability layer also records cost, latency, error rates, and custom qualitative metrics, which can be visualized on dashboards and used to trigger alerts.

The evaluation component lets teams run automated judges, code‑based checks, or multi‑turn assessments on production traces, calibrate judges to human preferences, and compare results across version changes. Subject‑matter experts can annotate traces, enabling collaborative quality improvement and regression prevention before updates reach production.

Deployment features include a managed runtime that supports human‑in‑the‑loop approvals, background processing, and multi‑agent coordination with exactly‑once execution. Agents are registered centrally with versioning, rollbacks, and organization‑wide rollout, while the infrastructure scales horizontally to handle long‑running or bursty workloads.