Using AI Tagging to Speed Up Search
BrandLife’s AI tagging feature is designed to help your team find assets faster, reduce manual organization, and improve overall productivity. With AI-powered tags, your assets become searchable instantly, so you spend less time hunting for files and more time creating. This guide explains how AI tagging works and how to use it effectively.
1. What is AI Tagging?
AI tagging uses advanced machine learning algorithms to automatically analyze your assets—images, videos, and documents—and assign relevant tags based on their content.
- For images and videos: The AI detects objects, colors, text, and context to generate descriptive tags.
- For documents: The AI analyzes content, headings, and keywords to suggest metadata tags.
These tags are searchable and can be combined with manual tags, providing a robust, organized system for finding assets quickly.
2. Benefits of Using AI Tagging
- Faster Search: AI-generated tags make it easy to locate assets without manually naming every file.
- Improved Organization: Assets are automatically categorized, reducing the need for constant manual sorting.
- Consistency: AI applies standardized tags across your library, ensuring uniform searchability.
- Time Savings: Spend less time on tagging and more on creating and collaborating.
- Enhanced Collaboration: Teams can find the right assets faster, reducing bottlenecks in workflows.
3. How to Enable AI Tagging in BrandLife
Step 1: Log In to BrandLife
- Navigate to your library or collection where you want to apply AI tagging.
Step 2: Upload Assets
- Upload new assets or select existing assets in your library.
- AI tagging works automatically for supported file types (images, videos, and documents).
Step 3: Review AI Tags
- Click on an asset to view its AI-generated tags.
- Tags are automatically suggested and can include objects, colors, text, or content-specific descriptors.
Step 4: Edit or Add Custom Tags
- You can add your own tags or edit AI-generated tags for more accuracy.
- Combining AI and manual tagging ensures precision while maintaining search speed.
4. Best Practices for Using AI Tagging
- Combine AI and Manual Tags: AI is powerful, but manual input helps capture brand-specific terminology or internal project codes.
- Standardize Tagging Guidelines: Define rules for naming, abbreviations, and hierarchical tags to maintain consistency.
- Use Descriptive Tags: Avoid generic terms like “image” or “file.” Instead, use tags like “product shot,” “summer campaign,” or “social media ad.”
- Regularly Review AI Tags: Occasionally check AI-generated tags for accuracy, especially for new types of assets.
- Leverage Collections: Use AI tags alongside collections to create multiple ways of finding the same asset.
5. Troubleshooting AI Tagging
- Missing Tags: Ensure the asset is a supported file type (JPG, PNG, MP4, PDF, etc.).
- Incorrect Tags: Edit tags manually and add notes for AI learning improvement.
- Slow Tagging: Large files or videos may take a few moments to process—refresh or check back later.
6. Combining AI Tagging with Search
- Use the search bar to find assets by AI-generated tags, manual tags, or a combination of both.
- Apply filters like file type, date, or collection to narrow search results further.
- AI tagging works across collections, so assets are discoverable regardless of where they are stored.
Key Takeaways
- AI tagging automates asset categorization, making search faster and more efficient.
- Combining AI and manual tagging ensures accuracy and consistency.
- Use AI tags along with collections and filters to maximize asset discoverability.
- Regularly review AI-generated tags to maintain quality and relevance.
