Tags are keywords or labels that you can assign to your files to organize and manage them more effectively. Tags help you quickly find files.
Add tags on files
You can add tags to files at the time of upload or after uploading them. Tags can only be added to files and not to folders or collections.
To add/edit tags on a file, right-click to open the context menu and select the "Tags" option. You can add, edit, or delete tags from the file.
While adding tags, as you type, you will see suggestions based on the tags already present in the Media Library. You can select from the suggestions or add a new tag. Learn more about managing suggested tags. Suggestions are shown to minimize the chance of team members creating similar tags with different spellings or capitalization.
AI-powered auto-tagging
ImageKit DAM provides AI-powered auto-tagging that automatically assigns tags to your files based on their content. The auto-tagging feature uses machine-learning algorithms to analyze the file's content and assign relevant tags. This feature helps you organize and search for files more effectively.
This operation consumes extension units. To learn more about extension unit pricing, refer to this documentation.
To add tags using AI, click the "Add auto tags" option from the image's context menu or detail page. To view the AI tags, open the asset detail page and look under the "Tags" section.
ImageKit leverages powerful label detection APIs by Google Cloud Vision and Amazon Rekognition to provide accurate and relevant tags for your files. Select the maximum number of tags you want to add to the file and click the "Add auto tags" button.
Once the tags are added, you can view them in the tags section of the asset detail page.
Watch and learn how to add AI tags to your files
Business-specific tagging using AI tasks
ImageKit offers AI tasks to use modern LLMs to automate media management at scale. You can use these AI tasks to apply tags that are relevant to your business and workflows, using natural-language instructions and predefined vocabularies.
For example, you can get tags for answers to questions like “Is there a male or a female model in this image?”, “What is the kind of collar of this t-shirt - round, polo, or v-neck?, “Is this a full sleeve or a half sleeve t-shirt?”
Auto-tagging vs AI tasks
| Feature | Auto-tagging | AI tasks |
|---|---|---|
| Tag source | Google/Amazon vision APIs suggest generic tags | You control the kind of information for which tags need to be generated |
| What it sets | Tags only | Tags AND custom metadata fields |
| Control | No control over tags added | Complete control via controlled vocabularies |
| Best for | Quick discovery and general categorization | Product catalogs, compliance, structured data |
Example difference:
Auto-tagging gives: ["clothing", "fashion", "outdoor"], which only provides generic classification
AI tasks allow you to extract a specific piece of information with your pre-defined vocabulary:
{
"type": "select_tags",
"instruction": "What is the kind of collar of this t-shirt?",
"vocabulary": ["round collar", "polo collar", "v-neck collar"]
}
// Returns only values from YOUR list: ["polo collar"]
Common use cases
- E-commerce product catalogs: Categorize by product type, color, season; set metadata fields like
colororstyle_categoryfrom your controlled vocabulary list. - Brand compliance: Check images against brand guidelines and set approval status automatically based on your business rules.
- Editorial workflows: Prioritize content by quality assessment and manage rights metadata with yes/no conditional logic.
Learn more about AI tasks for tagging with controlled vocabularies →
Searching using tags
As you type in the search bar, ImageKit automatically shows assets with one or more tags matching the search query.
Learn more about searching in ImageKit DAM.
Managing suggested tags
You can manage suggested tags in the Media Library settings. You can see the list and delete any suggested tags you don't want to use.