Braintrust Data / braintrustdata.com
AI evaluation platform that enables teams to benchmark, test, and compare LLM application performance systematically through dataset management and scoring.
Free plan
Yes
API access
Yes
Open source
No
Platforms
3
Braintrust is an AI evaluation platform focused on the specific challenge of measuring whether an AI application is actually getting better or worse as prompts, models, and logic change. This problem is harder than it sounds: AI output quality is subjective, variable, and difficult to measure with traditional testing approaches.
The platform provides tools for building and managing evaluation datasets — collections of inputs with expected outputs or scoring criteria. Running an experiment compares the AI application's outputs against these expectations, providing quantitative metrics for quality across dimensions like accuracy, relevance, and tone. Comparing two experiments (old prompt versus new prompt, GPT-4o versus Claude) gives teams objective data for decisions that previously relied on intuition or manual sampling.
The scoring system is flexible: human annotation for subjective quality, LLM-based evaluation where a judge model scores outputs, custom Python functions for domain-specific metrics, or reference answer comparison. This flexibility allows teams to measure what actually matters for their specific application rather than generic metrics.
Braintrust integrates with LangChain, LlamaIndex, and directly with AI model APIs, capturing traces from production for analysis and continuous evaluation. The playground allows testing prompt variations interactively before committing to formal experiments.
Braintrust runs as ml platform software built around text and code workflows. Users typically start with a prompt, upload, or connected data source, and the underlying model handles the heavy lifting before returning a result you can refine or export. It's available on web, python, and api, with API access for teams that want to embed it into their own products.
The capabilities that matter most for teams evaluating Braintrust.
Version-controlled collections of input-output test cases for reproducible AI application quality evaluation across experiments.
Uses a judge model to score AI application outputs against quality criteria, providing quantitative evaluation without manual annotation at scale.
Side-by-side comparison of AI application performance across different models, prompts, or pipeline versions.
Free plan with 100,000 rows of data. Usage-based on Pro with $0.00006/row logged. Enterprise custom pricing. Open source eval library available.
Model
Freemium
Starting price
Free
Free trial
No
Langfuse provides observability with evaluation features in one tool. LangSmith is tightly integrated with LangChain for evaluation. Vellum includes evaluation within a broader AI application platform. RAGAS is an open source evaluation framework for RAG applications.
A side-by-side look at the closest alternative in this category.
Braintrust
Braintrust Data
Langfuse
Langfuse
Key facts about model providers, platforms, and team support.
Model Provider
Agnostic
Platforms
Web, Python, API
Deployment
SaaS, Open Source
Integrations
LangChain, LlamaIndex, OpenAI, Anthropic, GitHub
Team Collaboration
No
Launch Year
2023
Compliance signals and data-handling notes as reported by the vendor.
Review Braintrust's data handling policy. Dataset and production trace data is processed on Braintrust's infrastructure. Enterprise includes data handling agreements.
Review Braintrust's privacy policy before uploading production traces containing sensitive user data. Enterprise includes comprehensive data handling agreements.
Editorial Verdict
Braintrust is well-suited for AI product teams that want systematic quality evaluation rather than ad hoc testing. Teams earlier in their AI product journey may start with simpler Langfuse observability before adding structured evaluation.
Last verified July 24, 2026.
The open source `autoevals` library provides reusable evaluation functions that teams can run locally or within Braintrust, reducing the setup overhead for common evaluation patterns.
For AI product teams that take quality seriously and want systematic rather than ad hoc evaluation, Braintrust provides the infrastructure that transforms AI quality assessment from a subjective discussion into a measurable practice.
Free plan with 100,000 rows of data. Usage-based on Pro with $0.00006/row logged. Enterprise custom pricing. Open source eval library available.
Free self-hosted (open source). Hobby cloud plan free. Pro cloud $59/month. Team $399/month. Enterprise custom pricing.
Review Braintrust's data handling policy. Dataset and production trace data is processed on Braintrust's infrastructure. Enterprise includes data handling agreements.
Self-hosted: complete data control. Cloud: review Langfuse's data handling policy. Enterprise includes data processing agreements.
Review Braintrust's privacy policy before uploading production traces containing sensitive user data. Enterprise includes comprehensive data handling agreements.
Self-hosted Langfuse keeps all trace data within your infrastructure. Cloud version processes trace data on Langfuse's servers. Review privacy policy for applications with sensitive user data.
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