AI tool

LangSmith

Visit website

Trace multi-step agents and compare evaluation runs while keeping seat fees separate from execution and model costs.

Starting price
Plus USD 39/seat/month
Free access
One seat; 5k base traces/month
Billing unit
Seats, traces and service meters
Platform
Cloud; enterprise hosting options
Verified
26 Oct 2026

Overview

What you provide

  • Instrument agent calls and provide evaluation examples that capture the task success criteria.

What you get

  • LangSmith exposes execution traces, datasets and evaluation results for debugging agent behavior.

Choosing this tool

LangSmith is a fit when tracing, evaluation and agent operations need to be reviewed together. The Plus trace pool is a total allowance, so adding seats should not be assumed to add another 10,000 traces each. Braintrust offers a data-and-score model with unlimited users; PromptLayer concentrates on prompt lifecycle and transaction quotas.

A decision worked through

Two Plus seats cost USD 78/month before usage. At 12,000 base traces, the displayed 10,000 total allowance leaves 2,000 additional traces; at 0.005 LSU each that adds USD 10, giving USD 88 for seats and that trace usage alone. Hosting, model calls and other services remain outside the calculation.

LangSmith alternatives for agent observability and evaluation

Compare LangSmith with Braintrust, PromptLayer for agent observability and evaluation. Compare the published operating scope as well as the billing unit.

ProductPrice / unitFree allowanceInput → outputKey limit
LangSmithRead profileOfficial source ↗Plus USD 39/seat/mo plus usage5k base traces and one seatAgent runs become inspected traces.Plus includes 10k traces total.
BraintrustRead profileOfficial source ↗Pro USD 249/mo plus usage1 GB; 10k scores monthlyTraces become scored experiments.Starter retention is 14 days.
PromptLayerRead profileOfficial source ↗Pro USD 49/mo plus transactionsFive users; one workspacePrompts become versioned tests.Pro keeps 2,500 included requests.

Setup & workflow

  1. Instrument one representative agent workflow.
  2. Evaluate it against a stable dataset and inspect the failing steps.
  3. Track service usage as well as quality before expanding deployment.
Requirements & installation
  • Start with an instrumentable application and define which traces may contain user data before enabling collection.

Limits & review

  • A successful trace is not evidence of a correct answer. Resource-based deployment and model-gateway charges can dominate a small seat fee, so estimate each enabled service rather than relying on the starter headline.

Your part

  • Check nested tool calls and scoring failures before deciding that a run is ready for production.
Sources & verification5

This profile is based on official sources, not a hands-on product test.

Vendor descriptions and demos document advertised features. Editorial guidance is based on these sources.