Braintrust

Braintrust is an observability platform for teams working to improve AI agents in production. It lets users inspect agent traces and tool calls while monitoring latency, cost, and quality in real time. Teams can run evaluations on datasets, compare prompts and models, and score outputs with LLMs, code, or human reviewers. Discovery tools help identify patterns in production traces, and the Loop agent can run evaluations, generate test cases, and revise prompts autonomously. Braintrust describes its product as framework agnostic and lists native SDKs for Python, TypeScript, Go, Ruby, C#, and more. Its MCP server lets coding agents query logs, run evaluations, and update prompts from an IDE. Braintrust states it is SOC 2 Type II certified and GDPR and HIPAA compliant, with SSO, RBAC, and hybrid deployment options. The free Starter plan includes 1 GB of processed data, 10,000 scores, and 14-day retention. Pro costs $249 a month, with further charges beyond some included usage limits. Enterprise pricing is custom.

Braintrust combines production observability with evaluation and prompt iteration workflows. The free Starter plan has defined data, score, and retention limits; Pro starts at $249 a month.

Braintrust is intended for teams running AI agents in production, from early-stage projects to enterprise deployments. It may suit teams that need to inspect traces and evaluate prompts, models, or outputs.

Braintrust brings production monitoring and agent-quality improvement into one workflow for teams operating AI agents. It suits builders who need to connect live behavior to repeatable evaluations; teams seeking only a local testing framework may prefer a narrower tool. Its breadth is a strength, but usage caps and paid overages deserve attention as activity grows.

Overview

Braintrust combines inspection of agent traces and tool calls with experiments on datasets, prompts, and models. Teams can track latency, cost, and quality in real time, then score outputs with LLMs, code, or human reviewers. The appeal is the link between production behavior and evaluation rather than either capability alone; teams that will not build that feedback loop may not use the platform’s full range.

Key features

Tracing and discovery help teams investigate agent behavior: Braintrust identifies patterns in production traces, while trace views expose tool calls and real-time latency, cost, and quality. Those capabilities support diagnosis, though the product description does not establish that discovery automatically resolves issues.

Evaluation experiments compare prompts and models against datasets. Scoring can use LLMs, code, or people, with custom metrics, safety evaluations, and human-review workflows also supported. Prompt versioning and CI/CD integration suit teams that want evaluation to accompany prompt changes. The Loop agent can run evaluations, create test cases, and iterate on prompts autonomously, while the MCP server lets coding agents query logs, run evaluations, and update prompts from an IDE.

Braintrust describes the platform as framework agnostic, with native SDKs for Python, TypeScript, Go, Ruby, C#, and other languages. It states that it is SOC 2 Type II certified and GDPR- and HIPAA-compliant, and offers SSO, RBAC, and hybrid deployment options. These controls broaden its fit for organizations with security and deployment requirements; custom retention policies and S3 trace export are reserved for Enterprise.

Pricing

Starter costs nothing, billed monthly. It includes 1 GB of processed data, 10,000 scores, 14-day retention, unlimited users and projects, and unlimited datasets. That is a useful starting allowance for small or early production workloads, but the plan permits only one human review score per project.

Pro costs $249 a month and includes $100 credits plus token rates. It raises the allowance to 5 GB of processed data and 50k scores; additional data costs +$3/GB, and additional scores cost $1.50/1k. Retention is 30 days, with further retention at $0.50/GB/mo. Pro adds custom charts, environments, priority support, RBAC, and unlimited human review scores. It fits teams that need those capabilities and can monitor usage-based charges, but the listed quotas make cost less predictable at higher volumes.

Enterprise has custom pricing, with custom retention and export, RBAC, premium support, and on-prem or hosted deployment. It is the relevant tier for organizations needing those deployment or data controls; the plan details do not provide a fixed price. Support spans community, priority, and shared Slack channel support across the plans.

Platforms

Braintrust is available through API, self-hosted, and web options. That range gives teams flexibility in how they integrate and deploy it, including an on-premises or hosted Enterprise option.

Who it's for

Braintrust is aimed at teams running agents in production, from early-stage builders to enterprises. It is strongest for teams that want observability, dataset-based evaluation, and prompt iteration connected in one system. The free Starter tier can support an initial workload, while Pro is a more natural fit when unlimited human review scores, RBAC, or longer retention matter.

Pros and cons

• Pro: Traces, evaluation, and prompt iteration sit in one workflow, helping teams connect observed behavior with tests and changes.
• Pro: SDKs across several languages, API access, and self-hosted options give teams multiple integration and deployment paths.
• Con: Starter’s 1 GB processed-data allowance, 10,000 scores, 14-day retention, and one human review score per project constrain sustained or people-heavy evaluation.
• Con: Pro’s overage charges for data, scores, and retention can add to its monthly price as usage rises.
• Con: Custom retention and S3 trace export are Enterprise features, putting those data controls behind custom pricing.

Alternatives

For a hosted evaluation-and-observability option with a low-cost entry point, Confident AI offers a free tier limited to 2 user seats, 1 project, 5 test runs per week, and 1 GB-month of trace spans. Choose it when those tighter caps suit the workload and Braintrust’s Pro price is not justified.

DeepEval is a free, Apache 2.0-licensed open-source evaluation framework with a local and CI/CD test runner. It is a better fit for teams focused on evaluation in local or CI workflows rather than Braintrust’s combined production observability and prompt iteration.

Galileo has a Pro plan at $100 a month, billed yearly, with 50,000 traces per month, standard RBAC, advanced analytics and insights, and dedicated Slack support. Consider it when that stated trace allowance and yearly billing fit better than Braintrust’s Pro pricing and overage structure.

Giskard offers a free open-source library for local deployment, including a basic LLM vulnerability scan using adversarial techniques from 2024 and a basic RAG evaluation report. It suits teams whose priority is local vulnerability scanning or RAG evaluation.

HELM is a free, open-source Python framework with no paid plans listed, a straightforward option for teams seeking that framework approach.

Maxim AI has a free Developer plan with up to 3 seats, 1 workspace, up to 10k logs per month, 3-day data retention, and email support. It may suit a small team that can work within those limits.

Parea AI offers a free plan for up to 2 team members, 3k logs per month with one-month retention, 10 deployed prompts, and Discord community support; its Team plan costs $150 a month. It is worth considering when those stated team and log limits or the lower Team price better match the workload.

Promptfoo offers a free Community plan with 10k red-team probes per month, LLM evaluation features, model-provider integrations, and local or self-hosted runs. It is a fit for teams prioritizing those evaluation and red-teaming capabilities.

For broader browsing, compare the LLM Evaluation Tools, AI LLM Evaluation Tools, AI Agent Evaluation Tools, AI Agent Observability Tools, AI Prompt Management Software, and Model Monitoring Software lists.

Verdict

Choose Braintrust if your team runs agents in production and wants to connect trace investigation with dataset-based evaluation and prompt iteration. Its breadth, flexible integrations, and deployment choices make that combination compelling; look elsewhere if you need a free local evaluation runner or cannot accommodate Pro’s monthly price and usage-based overages.