AI Config Considerations and Limitations

Summary

To help you get the most value from AI Configurations in the PIM, we strongly recommend following the guides below:

Overview

AI Configurations in Akeneo PIM are designed for performance, reliability, and scalability. Because AI generation involves analyzing structured product data, assets, and prompts simultaneously, a few technical and practical limits apply.

These limits help ensure a consistent experience for all customers while maintaining data integrity and predictable performance across large catalogs.

This page explains:

  • The maximum supported configuration sizes
  • File type and asset restrictions
  • Attribute option limits
  • General performance and reliability considerations

Configuration limits

The following limits apply to AI Configurations in your Akeneo PIM environment.

Type Limit Description
AI Configurations per environment 500 You can create up to 500 AI Configurations in a single Akeneo PIM environment. For higher requirements, contact your Customer Success Manager.
Legacy family-level prompts Supported but not centralized Family-level prompts created before the introduction of AI Configurations remain functional, but they are not managed from the AI Configurations page.
Active AI Configurations Unlimited within the 500 cap You can enable as many AI Configurations as needed within the 500 limit, but each consumes processing resources when executed.

Recommendation: If you manage multiple teams or product lines, organize configurations by purpose (for example, "Enrichment," "Translation," "Audit") rather than creating one configuration per attribute. This keeps the total number manageable.

Attribute option limits

AI Configurations can generate values for select-type Attributes such as Simple Select or Multi Select. These Attributes have a maximum option limit.

Attribute type Limit Description
Simple Select / Multi Select 500 options AI Configurations can only process up to 500 options per Attribute. Any options beyond this number are ignored during generation.
Reference Entity Single / Multi Link 500 records AI Configurations include up to 500 Reference Entity records as context. Records beyond this number are excluded.

Best practice: If you have a large list of select options, consider grouping or filtering them in advance to keep the set below 500.

Supported asset types

When assets (images or documents) are included in an AI Configuration, Akeneo PIM automatically analyzes them to extract contextual data — for example, product color, certifications, or logos. Only certain file types are supported.

Asset type Supported formats Notes
Images JPG, JPEG, PNG, WEBP, TIFF, single-frame GIF Used for visual analysis such as identifying dominant color, shape, or logos.
Documents PDF Only the first 20 pages are analyzed. Used for extracting structured text or key sections from technical sheets or certificates.

Unsupported files (for example, videos, multi-frame GIFs, or PSDs) are skipped automatically during processing. You can still store them in the Asset Manager, but they won't be used by AI Configurations.

Asset quantity and size limits

Each product can include a limited number of assets when running an AI Configuration, to maintain performance consistency.

Asset type Maximum count Per-file size limit Notes
Images 5 50 MB per file Akeneo PIM automatically resizes large images before sending them for analysis.
Documents (PDF) 2 50 MB per file Only the first 20 pages of each PDF are processed.

The total AI request payload — including all images and documents — must stay under 32 MB. If you exceed this limit, you will see the error: Your request exceeds the 32MB limit. If you use assets, please reduce the size of your files. Compress or optimize your assets before upload to avoid this.

If a product contains more than the maximum number of assets, only the first ones found in the selected Asset collection are used.

Asset collection requirements

AI Configurations only process assets stored in collections that include a main media Attribute. This ensures that each asset has a defined primary image or document for analysis.

If you include a collection without a main media reference, it is skipped during execution.

To verify, open your Asset Manager and confirm that each relevant collection has a defined main media Attribute.

Processing order for assets

When multiple assets are available, the AI processes them in the following order:

  1. Images from the selected Asset collection (up to 5, in collection order)
  2. PDF documents from the selected Asset collection (up to 2, in collection order)

This order helps ensure the AI uses the most relevant visuals first — for example, product packshots or hero images — before supplemental documentation.

Reference Entity context limitations

When a Reference Entity Single Link or Multi Link Attribute is used as an input source in an AI Configuration, Akeneo PIM automatically includes the linked record's attributes in the prompt payload, scoped to the selected Channel and Locale.

The following attribute types within the Reference Entity record are supported:

  • Text
  • Text Area
  • Simple Select
  • Multi Select
  • Number

The following attribute types within the Reference Entity record are not sent to the AI:

  • Images and Assets
  • Reference Entity Single Link / Multi Link

Text Area attributes in Reference Entities (for example, brand guidelines or glossaries) are injected directly into the AI prompt. Excessively long text consumes a large portion of available tokens. Keep Reference Entity guidelines concise and formatted as clear bullet points to ensure optimal AI Configuration performance.

Fair usage and performance management

Akeneo monitors AI feature usage to ensure equitable access and performance for all customers. There are currently no hard usage limits, but usage is tracked internally to prevent abuse and manage costs.

If your team consistently runs large-scale automation, contact your Akeneo representative to evaluate suitable scaling or quota options.

Recommendations:

  • Run enrichment rules in batches rather than simultaneously.
  • Schedule heavy automation during off-peak hours.
  • Use Preview and manual runs to test configurations before scaling.

Data privacy and security

All AI enrichment runs through Akeneo's enterprise AI infrastructure. Your data is never used to train AI models, never shared with third parties, and never stored after processing. All data is transmitted over encrypted channels.

For full details on how your data is protected, see AI Configuration Security & Data Privacy.

Key considerations for reliable performance

Category Recommendation
Prompt size Keep prompts concise and structured. Long or repetitive text degrades output quality.
Attribute selection Limit source Attributes to those directly relevant to the task.
Rule frequency Avoid triggering many AI Configurations simultaneously (for example, 10–20 within a single rule).
Asset size Compress or optimize images and PDFs before upload to stay within the 32 MB total request limit.
Parallel rules Run complex AI rules sequentially when possible to improve reliability.

Troubleshooting common limit issues

Problem Likely cause Suggested fix
Missing output for a product Too many assets or unsupported file type Reduce the number of images or use a supported format (JPG, PNG, WEBP, TIFF, PDF).
Error: Your request exceeds the 32MB limit. If you use assets, please reduce the size of your files Total asset payload exceeds 32 MB Compress or reduce the number of assets included in the AI Configuration.
AI Configuration not listed in the Rules Engine Configuration disabled or missing code Check that the configuration is enabled and saved correctly under Settings → AI Configurations.
Incomplete AI output Prompt exceeds token limit, or attribute context is too large Simplify the prompt or reduce the number of source Attributes.
Inconsistent enrichment times Large data scope or high concurrency Schedule smaller, staggered rule executions.

Summary

Understanding AI Configuration limits in Akeneo PIM helps you:

  • Design efficient configurations
  • Avoid data overload
  • Maintain high enrichment performance
  • Scale confidently across your entire catalog

For detailed recommendations on AI output behavior and realistic expectations, see Understanding AI Behavior and Realistic Use Cases.