> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openlayer.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Glossary

> Definitions of terms used in Openlayer

Here, we define some terms used in Openlayer.

## Workspace

When you [create an account](https://app.openlayer.com/), you are given a workspace. A workspace is
your **home in Openlayer**, where all your projects live and where your team collaborates.
Your [plan](https://docs.openlayer.com/workspace-and-projects/plans-and-usage.md) applies to the whole workspace.

## Project

A project lives inside a workspace. It represents **an AI system or initiative** and houses its
data, tests, and compliance work. You can [create multiple projects](https://docs.openlayer.com/workspace-and-projects/creating-and-loading-projects.md)
in your workspace.

A project can use offline testing, observability, or both.

### Offline testing

Offline testing is also called **development mode**. You test each version of your AI system on a
dataset you curate, usually as part of CI/CD, to catch regressions before you ship. Refer to the
[Offline testing overview](https://docs.openlayer.com/development/overview.md) for details.

### Observability

Observability is also called **monitoring mode**. Openlayer receives your production data, runs
your tests on it at a regular cadence, and notifies you when tests fail. Refer to the
[Observability overview](https://docs.openlayer.com/monitoring/overview.md) for details.

## Tests

Tests codify **expectations for your AI system and data**. Offline tests run on the datasets you
push in development mode. Monitoring tests run on production data from your data sources.
Refer to the [Tests overview](https://docs.openlayer.com/tests/overview.md) for details.

## Data source

A data source brings production data into a project. It is either a stream of requests from your
app, sent with the [SDKs](https://docs.openlayer.com/api-reference/sdk/overview.md) or OpenTelemetry, or a
[table in your warehouse](https://docs.openlayer.com/data-quality-monitoring/connect-data-source.md). Many teams use one data
source per environment, such as `staging` and `production`.

In the REST API, SDKs, and CLI, a data source is called an **inference pipeline**. For example,
you send data with an `inference_pipeline_id`.

## Trace

A trace is the full record of one request your AI system handles. It holds the inputs, outputs,
intermediate steps, and metadata. You see traces on the **Data** page of your project. Refer to
[Instrument your code](https://docs.openlayer.com/monitoring/instrument.md) for details.

## Request

A request is one trace sent to Openlayer. Usage and [plan limits](https://docs.openlayer.com/workspace-and-projects/plans-and-usage.md)
count requests: each trace counts as one request.

## Session

A session groups related traces, such as the turns of a chatbot conversation. You identify it
with a `session_id`. Refer to [Track users and sessions](https://docs.openlayer.com/monitoring/sessions-and-users.md) for details.

## Scorer run

A scorer run is one LLM-judge test, such as [LLM-as-a-judge](https://docs.openlayer.com/tests/catalog/l-l-m-rubric-threshold.md),
evaluated on one request. Usage counts scorer runs per year.

## Framework

A framework is a set of governance requirements, such as the EU AI Act or ISO 42001, that you
activate for some or all of your projects. Openlayer provides pre-built frameworks, and you can
[build a custom one](https://docs.openlayer.com/governance/build-custom-framework.md). Refer to the
[Governance overview](https://docs.openlayer.com/governance/overview.md) for details.

## Rule

A rule is one requirement inside a framework. [Platform rules](https://docs.openlayer.com/governance/platform-rules.md) are
satisfied automatically as your team uses Openlayer.
[Evidence-based rules](https://docs.openlayer.com/governance/evidence-based-rules.md) need a document or link as proof.

## Gateway

The Openlayer Gateway is a single endpoint between your apps and your LLM providers. It enforces
budgets, model access, and guardrails on every request, and traces each request to your project.
Refer to the [Gateway overview](https://docs.openlayer.com/gateway/overview.md) for details.


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