Braintrust vs LangSmith
Compare Braintrust and LangSmith for tracing, evaluations and production feedback, with Lunary as a conversation-focused alternative.
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Braintrust and LangSmith both combine tracing with evaluations. Add Lunary to your shortlist when customer conversation review is the main job.
Lunary
Our pick when user conversations drive debugging and prompt changes.
Braintrust
Consider for experiments, scorer development and online scoring.
LangSmith
Consider for traces, datasets and agent testing in its tooling.
At a glance
| Workflow | Lunary | Braintrust | LangSmith |
|---|---|---|---|
| Start an investigation | Replay the customer conversation | Inspect production logs and traces | Inspect traces, threads and runs |
| Gather quality signals | Message and run feedback | Scores, corrections and comments | Feedback and annotation queues |
| Test a revision | Model and prompt evaluations | Playgrounds and immutable experiments | Offline datasets and experiments |
| Natural pilot | A failed conversation and prompt fix | A dataset, task and scorer | An agent trace and regression dataset |
See your workflow in Lunary.
Explore conversations, traces and prompt versions with our team.
Start with the test you need
Braintrust structures evaluation around data, tasks and scorers, with immutable experiments. LangSmith supports offline and online evaluations, datasets and experiment comparisons. Run the same cases and criteria before deciding.
Bring a real customer issue
Both tools capture traces and user feedback. Lunary adds a compelling workflow for assistant teams: replay the conversation, inspect linked runs and review feedback on the exact reply. Include that workflow in the pilot.
Choose the tool your team will use
If your daily work starts with an experiment, compare the evaluation interfaces deeply. If it starts with a customer complaint, try Lunary with that conversation and a prompt revision. Judge the complete review cycle, not a demo dataset.
Questions & answers
Is LangSmith restricted to LangChain?
No. Its observability documentation lists multiple providers and frameworks. Check your actual integration requirements.
Is Braintrust only for evaluations?
No. It also provides instrumentation, production logs, user feedback and prompt deployment.
Why consider Lunary alongside these tools?
Lunary is worth trying when engineering and product teams need to understand user conversations, inspect the associated runs and review prompt changes together.
By Lunary · Documentation reviewed Sep 19, 2026
Sources & methodology (11)
Based on vendor documentation, not an independent benchmark or hands-on rating. Features and plans can change.
Bring your next AI issue to Lunary.
Follow the conversation. Find the cause. Test the fix.
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