Intelligent image tagging, automated by AI
Swiftask integrates with Imagior to automatically analyze and tag your visual assets. Stop sorting through thousands of images manually.
Result:
Drastically reduce file search time and optimize your digital asset management.
AI Agents
imagior
Connector imagior · Secure OAuth 2.0
The organizational chaos of manual tagging
Managing an image library without an effective tagging system is a major time sink. When files are poorly indexed, your teams spend hours looking for the right visual instead of creating.
Main negative impacts:
Time wasted searching
Team members waste precious time navigating unstructured folders, lacking precise metadata.
Database inconsistency
Every user uses their own terminology, making global searches inefficient and complex.
Hidden operational costs
Time spent by skilled resources manually classifying images represents a huge cost for the company.
Swiftask connects Imagior to a specialized AI agent that analyzes the content of each image and automatically applies relevant tags based on your taxonomy.
BEFORE / AFTER
What changes with Swiftask
Without Swiftask
A designer uploads 500 photos from a shoot. They must open each image, analyze its content, and manually enter keywords. The process takes hours and input errors are common.
With Swiftask + Imagior
As soon as files are uploaded to Imagior, your Swiftask agent instantly analyzes the visuals. It identifies objects, colors, context, and applies exact tags in seconds.
4 steps to automate your tagging
1
STEP 1 : Configure your agent in Swiftask
Define the tagging rules and taxonomy specific to your business within the Swiftask interface.
2
STEP 2 : Connect your Imagior account
Link your Imagior space to Swiftask via our secure connector to enable real-time analysis.
3
STEP 3 : Set the automation flow
Choose whether the agent should tag automatically upon upload or after human validation.
4
STEP 4 : Activate and save time
The agent processes every new addition. Your libraries are perfectly organized without effort.
Key AI tagging features
The AI analyzes visual properties (objects, text in image, colors) and business context provided by your reference documents.
- Target connector: The agent performs the right actions in imagior based on event context.
- Automated actions: Automatic tagging based on visual content. Normalization of tags according to your taxonomy. Multilingual tag support. Detection of sector-specific objects.
- Native governance: You keep full control: generated tags are editable and the AI learns from your corrections.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-imagior@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Why choose this automation?
Instant search
Find any asset in seconds thanks to rigorous indexing.
Consistent quality
AI doesn't get tired and applies the same tagging rules for every image.
Increased productivity
Free your teams from repetitive tasks so they can focus on creation.
Unified taxonomy
Ensure perfect consistency across your entire organization.
Scalability
Manage millions of images as easily as a few hundred.
Security and privacy
Swiftask applies enterprise-grade security standards for your imagior automations.
- Protected data: Your images and metadata are processed securely and are never used to train public models.
- Access control: You define precisely who has access to automation configurations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your productivity
| Metric | Before | After |
|---|---|---|
| Tagging time per image | 2-5 minutes | Less than 2 seconds |
| Search time | Several minutes | Instant |
| Indexing error rate | High (human) | Almost zero |
Take action with imagior
Drastically reduce file search time and optimize your digital asset management.