LangSmith
Tracing, evals and monitoring for LLM apps
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LangSmith provides tracing, monitoring, and evaluation for LLM applications and AI agents.
- for
- Developers and teams building LLM-based agents and applications.
- pricing
- freemium
Key features
- Tracing SDKs — Native tracing for popular agent frameworks via Python, TypeScript, Go, and Java SDKs.
- Real-time Monitoring — Dashboards show latency, cost, token usage and support alerts via webhooks or PagerDuty.
- Insights & Clustering — Unsupervised topic clustering and error-analysis templates automatically surface usage patterns.
- SmithDB Query Engine — Purpose-built database for fast, random-access queries, full-text search and JSON-path filtering.
- Self-hosted Options — Managed cloud, BYOC, or fully self-hosted deployments keep data inside your VPC.
- Online Eval as LLM-as-Judge — Run code and response evaluations in real time to score quality.
- Cost Tracking — Track token usage and LSUs, with pay-as-you-go pricing per trace volume.
- Alert Integrations — Webhook and PagerDuty alerts trigger on custom metric thresholds.
Use cases
- Debugging a multi-turn agent to locate latency spikes
- Monitoring production agents for cost overruns and error rates
- Automatically clustering trace data to discover common failure modes
- Running online LLM-as-judge evaluations to improve response quality
- Self-hosting observability for compliance-restricted enterprises
LangSmith pricing
- Developer$0/seat per month1 seat · 5k base traces/mo · Community support
- Plus$39/seat per monthUnlimited seats · 10k base traces/mo · 1 free small serverless deployment
LangSmith vs alternatives
 LangSmith |  Moda |  Better Stack |  Datadog |  New Relic | |
|---|---|---|---|---|---|
| Best for | LLM app observability | AI agent production monitoring | General app uptime | Full-stack cloud monitoring | App & infra observability |
| Pricing | Freemium | Subscription | Subscription | Subscription | Subscription |
| DevHunt upvotes | 0 | 0 | 0 | 0 | 0 |
| Launched | — | — | — | — | — |
- LangSmith vs Moda: Moda focuses on production monitoring and evals for AI agents, while LangSmith adds full tracing, SmithDB query engine and self-hosted deployment options.
- LangSmith vs Better Stack: Better Stack provides general uptime, logs and incident tracking, not specialized LLM trace analysis.
- LangSmith vs Datadog: Datadog offers broad cloud-app observability but lacks built-in LLM agent tracing and eval features.
- LangSmith vs New Relic: New Relic is an observability platform for apps and infrastructure, not tailored to LLM agent pipelines.
LangSmith FAQ
Why do teams need an LLM observability platform?+
It provides end-to-end visibility into agent behavior, tracks cost and latency, and helps debug failures and hallucinations.
What metrics can be tracked in LangSmith monitoring?+
Token usage, latency (P50, P99), error rates, cost breakdowns and feedback scores, with webhook or PagerDuty alerts.
Does LangSmith support OpenTelemetry?+
Yes, it can ingest OpenTelemetry data and integrate with existing observability pipelines.
Can I self-host LangSmith?+
Yes, managed cloud, BYOC, and fully self-hosted deployments are available for data-residency requirements.
Will LangSmith train on my data?+
No, your data remains private and is not used to train models.
How does pricing work?+
Free Developer tier includes 5k traces/mo; Plus adds 10k traces/mo at $39/seat/mo; Enterprise pricing is custom and includes self-hosted options.
Summarized by DevHunt from langchain.com · Nov 7, 2026. Details may change; check the official site.
About this listing
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