# Workspaces, Projects, and Models Everything in Roboflow follows this structure: Workspace → Projects → Dataset Versions → Models ### **Workspaces** A [Workspace](https://docs.roboflow.com/workspaces/roboflow-workspaces) is the top-level container. * It's where you and your team collaborate. * All Projects live inside a Workspace * Billing and [subscription plans](https://roboflow.com/pricing) are managed at the Workspace level Think of it like a company folder that holds all your computer vision work. ### Projects A [Project](https://docs.roboflow.com/datasets/create-a-project) lives inside a Workspace. Each Project is built around a computer vision dataset. This is where you manage: * Images * Annotations * Dataset updates over time When you create a Project, you have to choose the Project type - one of the computer vision task type: * Object detection * Classification * Instance segmentation * Keypoint detection * Semantic segmentation * Multimodal This determines how your data is structured and which model architectures you can train. ### **Dataset Versions** A [Dataset Version](https://docs.roboflow.com/datasets/dataset-versions) is a snapshot of your dataset at a specific moment in time. * You create a Version from the current state of your Project * Once created, it does not change * Any future edits to images or annotations will not affect existing Versions Which ensures reproducibility, clear tracking, and helps with model comparison. ### Models [Models](https://docs.roboflow.com/train/train) are trained using Dataset Versions. * You select a specific Dataset Version which will be used to train a model * That model is permanently linked to that version * Available model architectures for training will depend on your Project type You can also [upload trained models to Roboflow](https://docs.roboflow.com/deploy/upload-custom-weights). --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.roboflow.com/workspaces/key-concepts.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.