> For the complete documentation index, see [llms.txt](https://docs.unitlab.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.unitlab.ai/documentation/start-here.md).

# Unitlab Product Documentation

Operate Unitlab from source ingestion through governed multimodal annotation and reproducible delivery.

This documentation is organized around the objects and responsibilities a production team operates: data, datasets, projects, annotations, multimodal context, ontologies, workflows, queues, releases, collaboration, security, and workspaces.

## Watch Unitlab AI in action

Unitlab helps AI teams curate, annotate, manage, version, and prepare multimodal training data at enterprise scale. This overview shows connected video, document, audio, image, workflow, review, and versioned dataset operations in one enterprise platform.

{% embed url="<https://cdn.prod.website-files.com/651fc1beafe23dfe4999151d/6a7610b174ee3346f6af02c1_unitlab-multimodal-data-platform-explainer-1080p.mp4>" %}

[Open the full-screen Unitlab AI explainer](https://cdn.prod.website-files.com/651fc1beafe23dfe4999151d/6a7610b174ee3346f6af02c1_unitlab-multimodal-data-platform-explainer-1080p.mp4).

## Follow the production lifecycle

```mermaid
flowchart LR
  A["Workspace"]
  B["Data"]
  C["Dataset version"]
  D["Project"]
  E["Annotate + review"]
  F["Release"]
  A --> B
  B --> C
  C --> D
  D --> E
  E --> F
```

## Upload and prepare your data

* [Upload files and folders](/documentation/data/data-upload.md): choose a destination, prepare supported files, and check processing.
* [Import local annotations](/documentation/data/import-local-annotations.md): upload media and labels together, or add labels to existing data.
* [Create Data Groups and layouts](/documentation/data/data-groups-and-layouts.md): prepare related filenames and present them as one work item.
* [Automate uploads with the SDK and CLI](https://docs.unitlab.ai/api-sdk-cli/sdks/project-uploads): use files, folders, and scripts that process a local file list.

## Try a small example first

1. Start with two supported images and follow [Data upload](/documentation/data/data-upload.md).
2. Confirm both files open in [Project Data](/documentation/projects/project-data.md).
3. If you have model predictions, use [Import local annotations](/documentation/data/import-local-annotations.md) to match the label JSON to those images.
4. Follow [Review, rework, and escalation](/documentation/workflows/review-rework-and-escalation.md) to correct and review the labels.
5. [Create a release](/documentation/releases/create-a-release.md) when the intended work is ready for export.

For S3-hosted images, begin with [Cloud providers](/documentation/data/cloud-providers.md). For related camera views or modalities, prepare [Data Groups and layouts](/documentation/data/data-groups-and-layouts.md) before assigning work.

## Documentation map

| Area                   | Use it to                                                                                                                                    |
| ---------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- |
| Get Started            | Orient the team, understand the object model, and prove one end-to-end cycle.                                                                |
| Data                   | Ingest, organize, curate, group, and explore durable source data.                                                                            |
| Datasets               | Publish reusable membership versions and control project attachments.                                                                        |
| Projects               | Configure the operating boundary for policy, work, quality, and delivery.                                                                    |
| Annotations            | Use the shared Workbench and modality-native editors, including [LiDAR and 3D point clouds](/documentation/annotations/lidar-annotation.md). |
| Multimodal Annotations | Preserve multiple views or modalities as one contextual work unit.                                                                           |
| Ontologies             | Govern classes, geometry, properties, relations, validation, and schema versions.                                                            |
| Workflows              | Design human, model, review, rework, and completion routes.                                                                                  |
| Queues                 | Allocate, prioritize, monitor, and recover individual and batch work.                                                                        |
| Releases               | Create an export snapshot and validate its content downstream.                                                                               |
| Collaboration          | Coordinate members, roles, assignments, feedback, and ownership.                                                                             |
| Security               | Protect identities, credentials, sensitive data, and privileged operations.                                                                  |
| Workspaces             | Govern the top-level resource, identity, storage, and capacity boundary.                                                                     |

{% hint style="warning" %}
Unitlab configuration is connected. Changes to source membership, Data Groups, ontology, workflow, permissions, models, or export mapping can affect active work and downstream data. Validate material changes on a controlled cohort and retain an operational record.
{% endhint %}

***

> **Related Unitlab capability guides:** [enterprise data annotation workflows](https://unitlab.ai/en/data-annotation)