Glossary

This glossary defines key terms and concepts used in our product and documentation.

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Agent

A type of task that can be used in playgrounds. Consists of a chained sequence of prompts that automate complex workflows, where one LLM call’s output feeds into the next. Agents guide

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Alert

An automation that notifies you when a specific condition occurs on your logs in Braintrust. Automations guide

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Automation

A configured workflow that lets you trigger actions based on specific events in Braintrust. For example, sending an alert, or batch exporting data. Automations guide

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Benchmark

An evaluation designed to assess model performance across specific capabilities or against industry standards.

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Brainstore

The high-performance data engine backing logs, search, and tables. Brainstore blog post

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BTQL

Braintrust Query Language: a SQL-like syntax for querying eval results, logs, and metrics. BTQL reference

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Configuration

Project-level settings that define behavior for evals, experiments, and integrations. Project configuration guide

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Dataset

A versioned collection of pairs of inputs and (optional) expected outputs. Datasets guide A versioned collection of pairs of inputs and (optional) expected outputs.

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Evaluation / Eval

An eval consists of a task, dataset, and scorer(s). Evaluations can be:

• Offline: run a task on a static dataset with scoring functions.
• Online: real-time scoring on production or test requests.

Evals guide

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Experiment

An instance of an offline eval run. Scores a specific task run on a given dataset. Experiment guide

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Human review

An option to route evaluations or tasks to human reviewers instead of, or in addition to, automated scorers. Human review guide

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Log

An instance of a live production or test interaction. Logs can include inputs, outputs, expected values, metadata, errors, scores, and tags. Scorers can also be applied to live logs to conduct online evaluations. Logs guide

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Loop

An AI assistant in the Braintrust UI that can help you with evaluation-related tasks, like optimizing prompts and generating dataset rows. Loop guide

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Metric

A quantitative measure of model performance (for example, accuracy, latency, or cost) tracked over time and across experiments.

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Model

An AI system (typically an LLM) that can be evaluated or monitored with Braintrust. Models can be first-party, third-party, or open-source.

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Organization

Your company or team “home” in Braintrust. It holds all your projects, members, and settings. Organizations reference

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OTEL

OpenTelemetry: the instrumentation standard Braintrust uses to collect and export trace and span data from integrations. OpenTelemetry guide

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Playground

An interactive space where you can prototype, iterate on, and compare multiple prompts and models against a dataset in real time. A playground can be saved as an experiment. Playgrounds guide

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Project

A container for related experiments, datasets, and logs. Use projects to segment work by feature, environment (dev/prod), or team. Projects guide

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Prompt

The instruction given to an AI model. Prompts are editable objects you can version and reuse across experiments and playgrounds. Prompts guide

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Prompt engineering

The practice of designing, optimizing, and refining prompts to improve AI model outputs and performance.

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Regression testing

Evaluations that ensure new model or prompt configurations maintain or improve upon previous performance benchmarks.

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Remote eval

An evaluation that is executed on external or third-party systems or services, allowing you to evaluate tasks in environments outside Braintrust. Remote evals guide

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Scorer

The component responsible for judging the quality of AI outputs. Scorers may be:

• Rule-based code
• LLM-based prompts as judges
• Human reviewers

Scorers guide

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Setting

An organization-level preference or control, including user management, billing, and global integrations. Organizations reference

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Span

A single segment within a trace, representing one operation (for example, a model call or tool execution) with its timing and metadata. Traces guide

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Structured output

A defined format (for example, JSON or XML) that models must follow, enabling consistent parsing and scoring of responses. Structured output guide

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Task

A single unit of work, typically composed of an input, output, expected result, and evaluation. Tasks often appear within dataset or eval detail screens.

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Trace

An individual recorded session detailing each step of an interaction: model calls, tool invocations, and intermediate outputs. Traces aid debugging and root-cause analysis. Traces guide

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User feedback

End-user inputs and ratings collected from production that inform model performance tracking and future evals. User feedback guide