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

# Auto Annotation

> Use models to speed up data annotation

# Auto Annotation Overview

Auto Annotation streamlines the labeling process on Foundry by leveraging state-of-the-art models,
significantly reducing manual effort and potential for human error.

## Manual Annotation Challenges

We identified several challenges in manual annotation:

* Laborious and monotonous task execution
* Higher potential for human error
* Increased number of Issues during review stage --> Time-consuming correction processes
* Reduced annotation efficiency at scale

<Note>
  These challenges become particularly significant when dealing with thousands of frames,
  making automated assistance essential for maintaining both speed and quality.
</Note>

## Our Solution

You can now:

* Create a completely auto-labelled job OR
* Autolabel specific frames right on the Canvas using the new Agent tool

Both approaches leverage classical machine learning methods and state-of-the-art models (Grounding Dino, Grounding SAM) and
provide an intuitive interface for annotation review and adjustment.

<Check>
  Ready to start using Auto Annotation? Check out our guides on [Autolabel Job Creation](/annotation/kanban-board/job-creation)
  and [Canvas Agent](/annotation/auto-annotation/canvas-agent) to begin.
</Check>