Braintrust

Paid

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Inputs: text, codeOutputs: text, code

Type

Saas

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About Braintrust

Braintrust is an AI observability platform designed to help teams build, monitor, and improve AI applications at scale. It provides a unified environment for tracing production behavior, evaluating outputs, and automating quality improvements. The platform is framework-agnostic and integrates with any AI stack, making it suitable for engineering and product teams alike. Braintrust emphasizes catching silent failures and regressions that are common in AI systems, offering tools to inspect traces, score outputs, and block bad releases before they reach production.

Key Features

Real-time trace inspection for prompts, responses, and tool calls

Eval system with LLM-based, code-based, or human scoring

Automatic pattern discovery via Topics (task, issue, sentiment clustering)

Continuous online scoring and quality gates to block bad releases

Custom facets and annotation interfaces tailored to team workflows

One-click conversion of production traces into eval datasets

MCP server for querying logs, running evals, and updating prompts from an IDE

Framework-agnostic integration with existing AI stacks

Pros & Cons

Pros

Comprehensive observability covering traces, evals, and automation in one platform
Automatic pattern discovery helps surface issues without manual effort
Framework-agnostic design works with any AI stack
Supports multiple scoring methods (LLM, code, human) for flexible evaluation
Quality gates can block bad releases before they hit production

Cons

Pricing requires contacting sales; no publicly listed starting price
Free tier availability and limits are not specified on the homepage
Platform complexity may require initial setup and learning for teams new to observability
Dependence on internet connectivity for cloud-based features

Best For

Monitoring production AI applications for drift and regressionsRunning experiments to compare prompts and models side-by-sideBuilding regression tests from real production failuresAutomating quality gates to prevent bad releasesCollaborating across engineering and product teams on AI qualityOptimizing evals and prompts with agent-assisted improvement (Loop)

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FAQ

What types of AI models does Braintrust support?

Based on available information, Braintrust is framework-agnostic and appears to work with any AI stack, including LLMs and agents. Specific model support should be verified on the product's documentation.

Is there a free tier or trial available?

The homepage does not mention a free tier. Pricing is listed as 'contact sales,' so interested users should inquire directly about trial options.

Can Braintrust be used with non-LLM AI models?

The platform focuses on AI observability and mentions traces, prompts, and tool calls, which suggests it is designed for LLM-based applications. Support for other AI model types should be confirmed with the vendor.

How does Braintrust handle data privacy and security?

The homepage does not detail security or data privacy features. Users should review Braintrust's security documentation or contact sales for specifics.

Does Braintrust integrate with existing monitoring tools?

Braintrust is described as framework-agnostic and offers an MCP server for IDE integration. Specific integrations with other monitoring tools should be checked in the documentation.

What is the Loop agent AI feature?

Loop is described as an agent that helps improve AI by generating better prompts, scorers, and datasets automatically based on user-defined optimization goals. Details on its capabilities should be verified.