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Projects organize AI features in your application. Each project contains logs, experiments, datasets, prompts, and other functions. Configure project-specific settings to customize behavior for your use case.

Create a project

  1. Navigate to your organization’s project list
  2. Click + Project
  3. Enter a project name
  4. Optionally add a description
  5. Click Create

Configure AI providers

Project-level AI provider keys override organization-level keys. Use project-level keys when:
  • Different projects need separate billing or rate limits
  • You want to isolate API usage by project
  • Projects require different provider accounts or credentials
To configure project-level AI providers:
  1. Navigate to your project.
  2. Go to Configuration.
  3. Under Project, select Project AI providers.
  4. Click the provider you want to configure.
  5. Enter your API key for that provider.
  6. Click Save.
Project-level providers are available in a project’s playgrounds, experiments, and when using the AI Proxy with the project’s context.
Secrets are encrypted at rest using transparent data encryption with a unique 256-bit key and nonce.

Add custom providers

Braintrust supports custom AI providers at both the organization and project level. See Custom providers for details on configuring custom endpoints.

Add tags

Tags help organize and filter logs, datasets, and experiments:
  1. Go to Settings.
  2. Under Project, select Tags.
  3. Click Add tag.
  4. Enter tag details:
    • Name: Tag identifier.
    • Color: Visual indicator.
    • Description: Optional explanation.
  5. Click Save.
Use tags to track data by user type, feature, environment, or any custom category. Filter by tags in logs, experiments, and datasets. For more information about using tags, see View logs.

Configure human review

Define scores for manual review by users or your team:
  1. Go to Settings.
  2. Under Project, select Human review.
  3. Click + Human review score.
  4. Enter a name and description for your score. Descriptions support Markdown.
  5. Select a score type:
    • Categorical score: Predefined options with assigned scores. Each option gets a unique percentage value between 0% and 100% (stored as 0 to 1). Use for classification tasks like sentiment or correctness categories. Also supports writing to the exptected field instead of creating a score.
    • Continuous score: Numeric values between 0% and 100% with a slider input control. Use for subjective quality assessments like helpfulness or tone.
    • Free-form input: String values written to the metadata field at a specified path. Use for explanations, corrections, or structured feedback.
  6. Click Save.
Review scores appear in all logs and experiments in the project. Use them for quality control, data labeling, or feedback collection. For more information, see Collect human feedback. For more information, see Collect human feedback.

Create aggregate scores

Combine multiple scores into a single metric:
  1. Go to Settings.
  2. Under Project, select Aggregate scores.
  3. Click Add aggregate score.
  4. Define the aggregation:
    • Name: Score identifier.
    • Type: Weighted average, minimum, or maximum.
    • Selected scores: Scores to aggregate.
    • Weights: For weighted averages, set score weights.
    • Description: Optional explanation.
  5. Click Save.
Aggregate scores appear in experiment summaries and comparisons. Use them to create composite quality metrics or overall performance indicators. For more information, see Interpret evaluation results.

Set up online scoring

Define project-level scoring rules that automatically evaluate production logs as they arrive. These rules can be created here or when creating and editing scorers.
  1. Go to Settings.
  2. Under Project, select Online scoring.
  3. Click Add rule.
  4. Configure the rule:
    • Name: Rule identifier.
    • Scorers: Select which scorers to run.
    • Sampling rate: Percentage of logs to evaluate (1-100%).
    • Filter: Optional SQL query to select specific logs.
    • Span type: Apply to root spans or all spans.
  5. Click Save.
Online scoring rules run asynchronously in the background. View results in the logs page alongside other scores. Rules can also be created and managed when working with individual scorers. For more information, see Create scoring rules.

Configure span iframes

Customize how specific span fields render in the UI:
  1. Go to Settings.
  2. Under Project, select Span iframes.
  3. Click Add iframe.
  4. Configure rendering:
    • Field path: Which field to render (e.g., output.html).
    • iframe URL: Template for the iframe src attribute.
  5. Click Save.
Use span iframes to render HTML, charts, or custom visualizations directly in trace views. For more information, see Extend traces.

Set comparison key

Customize how experiments match test cases:
  1. Go to Settings.
  2. Under Project, select Advanced.
  3. Enter a SQL expression (default: input).
  4. Click Save.
Examples:
  • input.question - Match by question field only.
  • input.user_id - Match by user.
  • [input.query, metadata.category] - Match by multiple fields.
The comparison key determines which test cases are considered the same across experiments. For more information, see Compare experiments.

Edit project details

Update project name and description:
  1. Navigate to your project.
  2. Click Edit project in the top-right.
  3. Modify name and description.
  4. Click Save.

Delete a project

Deleting a project permanently removes all logs, experiments, datasets, and functions. This cannot be undone.
  1. Navigate to Configuration.
  2. Scroll to the bottom of the page.
  3. Click Delete project.
  4. Confirm by typing the project name.
  5. Click Delete.

Next steps