Agent Evaluation

Measure what matters in your agents

Stop shipping agents blind.

LangSmith benchmarks let you systematically evaluate agent quality, compare versions, and identify what actually drives performance improvements. Benchmark against datasets and production traffic.

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LangSmith agent benchmarking interface showing evaluation results

How LangSmith agent benchmarking works

Collect agent traces

Instrument your agents to capture traces. LangSmith records every decision, tool call, and output for evaluation.

Define your benchmarks

Create evaluation datasets and metrics aligned to your agent's goals. Benchmark offline against known examples.

Monitor and improve

Run evals on production traffic to catch quality drops. Use results to iterate and ship better agent versions.

See how it works

LangSmith powers top engineering teams, from AI startups to global enterprises

Built for Systematic Agent Evaluation

Teams trust LangSmith to benchmark and improve their agent performance

50M+

LLM Calls Traced

1B+

Events Ingested per Day

100K+

Monthly active orgs in LangSmith SaaS

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How LangSmith Agent Benchmarking Works

Evaluate agent quality systematically with offline and online evaluations

Agent benchmarking starts with visibility. LangSmith tracing captures every step, tool call, and decision your agent makes. This gives you the raw signal you need to build reliable evaluation datasets and identify what's driving performance.

Connect with our team to see how

LangSmith tracing interface showing agent steps

Built for Enterprise

Security and compliance at scale

LangSmith meets the demanding security, performance, and collaboration requirements of large organizations building AI applications at scale.

Granular permissions

Role-based access control with org-level permissions and project isolation to meet your security and compliance requirements.

SOC 2 Type II

Third-party security certification with comprehensive security controls.

Trust center

Self-hosted deployment

Self-hosting options to maintain full control over your AI data and meet strict compliance requirements.

Why top AI teams choose LangSmith for agent benchmarks

Measure what matters

Define custom evaluation metrics aligned to your agent's actual performance goals. Stop relying on generic benchmarks—create benchmarks specific to your use case.

Compare versions confidently

Run controlled evaluations comparing agent versions side-by-side. See exactly what impact prompt changes, tool additions, and model switches have on quality.

Production benchmarking

Monitor live agent quality with online evaluations on production traffic. Catch regressions immediately instead of hearing about them from users.

Customers

"What we really needed was a more structured way to test new approaches, something better than just shipping and seeing what happened. LangSmith gave us a more scientific, structured way to understand what was actually working, whether that meant running pairwise evaluations or digging into why accuracy jumped from 70% to 80%. Our engineers especially love the intuitive debugging experience, it's saved us a lot of time."

Yusuke Kaji, General Manager of AI for Business Development at Rakuten

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"LangSmith's evaluation capabilities let us systematically improve our agent performance. We went from 70% to 80% accuracy by using LangSmith to identify which agent design choices actually mattered. The ability to benchmark against our production data is critical—we can see exactly what changes drive real improvements."

Customer, Klarna