AI Workflows allow you to automate repetitive catalog tasks in Elovate using AI powered actions and rule based triggers.
Instead of manually running separate enrichment, translation or validation jobs, AI Workflows let you build automated pipelines that process products continuously or in batches.
A workflow starts with a trigger. Once products match the configured rules, one or multiple AI actions are executed automatically.
Examples of actions include:
Attribute Extraction
Content Enrichment
Translation
Category Mapping
Content Validation
Quality Scoring
This makes it possible to automate large parts of your product data operations directly inside Elovate.
How AI Workflows work
An AI Workflow consists of two main parts:
Trigger
The trigger determines which products should enter the workflow.
You can define this using rules and filters such as:
Category equals Shoes
Description is empty
Status is enabled
Brand equals Nike
This ensures only relevant products are processed.
Actions
Actions are the AI powered steps executed after a trigger is activated.
Actions run sequentially, creating a waterfall effect where one action can continue based on the output of a previous action.
Example workflow:
Extract missing attributes
Generate optimized shopping descriptions
Translate content to German
Validate content quality
Synchronize data to your platform
This allows you to fully automate enrichment pipelines.
Why use AI Workflows?
AI Workflows help you:
Reduce repetitive manual work
Automate product enrichment
Generate structured attribute data
Improve catalog consistency
Scale multilingual content
Build automated publishing pipelines
Improve data quality control
Manage AI generation in a single overview
Instead of managing disconnected AI jobs, workflows centralize your automation into one scalable system.
Workflow execution types
AI Workflows currently support different execution methods.
One-time workflows
A one-time workflow processes the products that currently match your rules once.
This is useful for:
Initial catalog enrichment
Bulk translations
Large cleanup projects
Supplier data enrichment
Continuous workflows
Continuous workflows continuously monitor your catalog and automatically process new matching products over time.
This is useful for:
Automatically enriching new products
Ongoing translation pipelines
Automated quality control
Continuous synchronization flows
Workflow moderation
AI Workflows include moderation capabilities to help maintain content quality.
Depending on your configuration:
editors can review generated output
moderators can approve changes
AI reasoning can be inspected
confidence scores can be reviewed before synchronization
This gives teams more control over AI generated data before publishing.
AI Workflows replace old enrichment jobs
Previous Content Enrichment and Translation jobs are migrated into the new AI Workflow system.
The new workflow system provides:
a centralized overview
chained AI actions
clearer execution visibility
moderation improvements
scalable automation pipelines
Existing jobs are automatically converted into workflows where possible.
Common AI Workflow use cases
AI Workflows can be used for many catalog automation scenarios.
Examples include:
Extracting product attributes from descriptions
Generating Google Shopping content
Translating product content automatically
Validating missing catalog data
Assigning categories with AI
Creating multilingual enrichment pipelines
Improving incomplete supplier content