Capability · Framework — evals

Braintrust

Braintrust is the 'evals-first' commercial platform: you bring datasets, it runs scored experiments across prompt and model variations, and tracks regressions over time. It also captures production logs so you can build datasets from real traffic. Popular with US AI startups and labs that treat evals as a first-class engineering discipline rather than an afterthought.

Framework facts

Category: evals
Language: TypeScript + Python SDKs
License: commercial
Repository: https://github.com/braintrustdata/braintrust-sdk

Install

pip install braintrust
# or
npm install braintrust

Quickstart

from braintrust import Eval
from autoevals import Factuality

Eval(
    'Geography eval',
    data=lambda: [
        {'input': 'Capital of Japan?', 'expected': 'Tokyo'}
    ],
    task=lambda q: my_llm(q),
    scores=[Factuality]
)

Alternatives

LangSmith — LangChain-native, similar feature set
Langfuse — open-source alternative
Helicone — observability-focused
DeepEval — OSS pytest-first evals

Frequently asked questions

Braintrust or LangSmith?

Both cover evals + observability. LangSmith integrates tightly with the LangChain/LangGraph ecosystem. Braintrust is framework-agnostic and has a stronger dataset + experiment surface. If you're all-in on LangChain, LangSmith is frictionless. Otherwise Braintrust often wins on eval UX.

Is there a free tier?

Yes — Braintrust has a free hobby tier suitable for individuals and small projects. Team and enterprise tiers add collaboration, SSO, and higher limits.

Sources

Braintrust — docs — accessed 2026-04-20