AI Compliance Vendors

LangSmith

AI Agent & LLM Observability Platform

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Last verified April 24, 2026

Quick facts: LangSmith is an AI compliance vendor founded in 2023 and headquartered in San Francisco, US. Pricing is tiered. Profile last verified April 24, 2026, with every claim traceable to a cited public source.

About LangSmith

LangSmith is an LLM observability platform that provides tracing, monitoring, and evaluation for AI agents and LLM applications. It offers native tracing for agent frameworks, cost and latency tracking, online LLM-as-judge evals, custom dashboards, and alerts via webhooks or PagerDuty. Framework-agnostic with SDKs for Python, TypeScript, Go, Java, and OpenTelemetry support, it works with OpenAI, Anthropic, LlamaIndex, and custom stacks. Typical buyers are engineering teams building production LLM apps needing visibility into agent behavior, debugging failures, and performance optimization. Enterprise plans include self-hosted and BYOC options for data residency.LangSmith homepage Pricing

Featured in

LangSmith is ranked in the following independent collection.

Framework coverage

Not yet catalogued. We only list frameworks when LangSmith publicly documents coverage in their own materials. If you work at LangSmith and want to add citations, use the correction link at the bottom of this page.

LangSmith features

Capabilities LangSmith markets publicly. Inclusion means the feature is documented on the vendor's site — not that it's best-in-class. Last verified April 24, 2026.

LLM Evaluation

Systematic testing of LLM outputs for correctness, relevance, safety, and consistency using automated scorers, rubrics, or human review.

Model Monitoring

Production monitoring for performance, drift, data quality, and fairness regressions.

Agent Tracing

End-to-end visibility into multi-step LLM agent runs: tool calls, intermediate reasoning, token usage, latency, and errors at each step.

Prompt Management

Versioning, templating, A/B testing, and deployment workflows for LLM prompts treated as production artifacts.

Drift Detection

Automated detection of distribution shift, feature drift, prediction drift, and performance degradation in deployed ML/AI models.

Industries served

Integrations

Documented by LangSmith in public product materials.

  • OpenAI API
  • Anthropic API
  • OpenTelemetry
  • LlamaIndex

LangSmith pricing

Contact for pricing

Developer free (1 seat, 5k base traces/mo); Plus $39/seat/mo (unlimited seats, 10k base traces/mo); traces $2.50/1k base (14d), $5/1k extended (400d); Enterprise custom with self-hosting.Pricing page

Pros and cons of LangSmith

Pros

  • Framework-agnostic tracing with multiple SDKs and OpenTelemetry support.
  • Built-in LLM evals, cost/latency monitoring, and production alerts.
  • Enterprise self-hosted/BYOC options for data control.

Cons

  • Pricing per-seat plus usage can scale quickly for large teams/high volume.
  • Primary positioning tied to LangChain ecosystem despite agnostic claims.
  • No explicit regulatory framework coverage documented on site.

Frequently asked

Is there a free tier?+

Yes, Developer plan free with 1 seat and 5k base traces/month.

Does it support self-hosting?+

Yes, Enterprise plan offers self-hosted and BYOC deployment.

What integrations are available?+

SDKs for Python/TS/Go/Java, OpenAI/Anthropic/Vercel AI/LlamaIndex, OpenTelemetry.

How are traces priced?+

Base traces $2.50/1k (14-day retention); extended $5/1k (400 days).

Sources

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