Braintrust Pricing Review: Plans, Usage Costs, and Enterprise Considerations
Review Braintrust pricing, included usage, overage costs, retention, and enterprise features, plus the operating considerations that emerge as AI moves into production.
Quick summary
Braintrust publishes three plans for its evaluation and observability platform:
- Starter: $0 monthly platform fee, with included usage and on-demand overages.
- Pro: $249 per month, with larger allowances and additional production features.
- Enterprise: Custom pricing, limits, deployment options, security, and support.
The practical cost depends on processed trace data, scoring volume, data retention, model usage, and the security features an organization requires. Braintrust can provide a strong evaluation and observability layer. Enterprises should evaluate it alongside the governance, identity, approvals, integration, and business-outcome systems required to operate an AI workforce at scale.
Pricing and plan details below were checked against Braintrust’s published pricing and plans documentation on August 28, 2026.
Braintrust pricing at a glance
| Plan | Platform fee | Included data | Included scores | Retention |
|---|---|---|---|---|
| Starter | $0 per month | 1 GB per month | 10,000 per month | 14 days |
| Pro | $249 per month | 5 GB per month | 50,000 per month | 30 days |
| Enterprise | Custom | Custom | Custom | Custom |
Braintrust includes unlimited users, projects, datasets, playgrounds, and experiments across its published plans. Model credits are included, with token rates applying after those credits are consumed.
Starter plan
Starter has no monthly platform fee and does not require a credit card. It is designed for individual developers and smaller teams beginning with tracing and evaluation.
Published allowances include:
- 1 GB of processed data per month
- 10,000 scores per month
- 14 days of data retention
- $10 in monthly model credits
- Unlimited users, projects, datasets, playgrounds, and experiments
After the included allowance, Braintrust publishes overage rates of $4 per GB of processed data and $2.50 per 1,000 scores.
Starter is a practical entry point for teams learning how much data their applications generate. The short retention window and usage-based overages become important when traces are required for longer investigations, audit support, or sustained production monitoring.
Pro plan
Pro carries a $249 monthly platform fee and is positioned for AI-native teams operating production applications.
Published allowances include:
- 5 GB of processed data per month
- 50,000 scores per month
- 30 days of included retention
- $249 in monthly model credits
- Custom charts, environments, priority support, and role-based access controls
Published overage rates are $3 per GB of processed data and $1.50 per 1,000 scores. Braintrust also lists extended retention at $0.50 per GB per month after the included period.
Pro can make sense when teams need a shared production workspace, stronger access controls, and enough included volume to establish reliable evaluation and observability practices.
Enterprise plan
Enterprise pricing is negotiated. Braintrust lists custom usage limits, custom retention and export, advanced security and compliance capabilities, premium support, and hosted or on-premises deployment options for high-volume or privacy-sensitive environments.
Organizations evaluating Enterprise should ask for a modeled annual cost based on expected trace volume, scoring strategy, retention requirements, model usage, environments, and support expectations.
The cost drivers that matter most
Processed trace data
High-volume applications can generate substantial logs and traces. Estimate the data produced by a representative workflow, then model that volume across environments and expected growth.
Scoring strategy
Automated evaluation is most useful when it runs consistently. Estimate how many outputs will be scored, how frequently evaluations run, and whether each production event requires one scorer or several.
Retention
Short retention can work for active debugging. Regulated operations, longer incident investigations, and trend analysis may require more history.
Model usage
Built-in model usage can consume included credits. Bring-your-own-key arrangements and external model charges should be included in the complete cost model.
Security and deployment
Enterprise identity, private deployment, data residency, support, and compliance requirements can affect packaging. Confirm which capabilities are included and which require a negotiated agreement.
What Braintrust covers well
Braintrust is built around tracing, evaluation, prompt experimentation, datasets, and observability. It helps teams answer questions such as:
- How did an AI application behave on this request?
- Did a prompt or model change improve quality?
- Which evaluations are regressing?
- How do latency, cost, and output quality change over time?
Those are essential production disciplines.
The wider enterprise operating model
As organizations scale from applications to an AI workforce, they also need to answer a different set of questions:
- Which agents exist, and who owns them?
- What tools, data, models, budgets, and authority may each worker use?
- Which actions require human approval?
- How do agents safely interact across internal and external systems?
- What business outcomes are the workers producing?
- How does production intelligence remain controlled by the enterprise?
Evaluation and observability contribute important evidence. The wider operating model connects that evidence to identity, governance, approvals, integrations, and organizational outcomes.
How Ellaworks can fit alongside Braintrust
Ellaworks is an open, governed service platform for operating enterprise AI. It can incorporate evaluation and observability tools such as Braintrust within a broader production foundation.
Ellaworks brings together:
- Governance established at the worker’s inputs and authority
- Approval workflows for actions requiring human oversight
- A Secure Agent Directory for identity, ownership, access, and trust
- Open integrations across models, runtimes, tools, and enterprise systems
- Private AI and enterprise data controls
- Business intelligence from AI activity and outcomes
- Implementation and support from Ellavox engineers
The result is a connected lifecycle from building and evaluating an AI capability to authorizing, operating, and improving it in production.
Questions to ask before selecting a plan
- What trace volume will our representative production workflows generate?
- How many automated scores will run per request or release?
- How long must we retain evidence for operations, security, and audit needs?
- Which identity, deployment, and compliance features are mandatory?
- How will evaluation findings connect to production approvals and governance?
- Who owns the operating model after the first application goes live?
Answering these questions produces a more reliable cost estimate and a clearer production architecture.
Plan for evaluation and operations together
Braintrust offers a clear entry point for tracing and evaluation, with published usage-based pricing and enterprise options. The strongest implementation plans evaluate those capabilities alongside the operating foundation required to manage AI across the enterprise.
Talk with Ellavox about the complete production AI operating model.