AI Data Enrichment
Transform incomplete product data into sales-ready items: Our AI solution automatically enriches descriptions, attributes, and technical specifications - with direct PIM and ERP integration.
What is AI Data Enrichment?
Data Enrichment refers to the systematic enrichment and completion of product data through artificial intelligence.
Structured Data
Raw data from suppliers or ERP systems is transformed into structured, sales-ready product information - with all required attributes and categories.
Automatic Completion
Missing product information is derived from existing data, images, and external sources. The AI recognizes patterns and completes consistently.
Improve Data Quality
Inconsistencies are detected and corrected, duplicates cleaned up, and formats standardized - for uniform, high-quality product data across your entire range.
Automatic Data Enrichment
From individual attributes to complete product data transformation - our AI modules cover all enrichment requirements.
Complete Descriptions
Missing or inadequate product descriptions are automatically generated from existing data. The AI creates sales-promoting texts that cover all relevant product features.
- Short and long descriptions
- Bullet points from features
- Generate usage instructions
- Prepare technical details
Attribute Extraction
The AI extracts structured attributes from free text, product names, and descriptions. Dimensions, weights, materials, and technical values are automatically recognized and written to the correct fields.
- Recognize dimensions and weights
- Classify materials
- Parse technical values
- Normalize properties
Image Recognition & Tagging
Computer Vision analyzes product images and extracts visual attributes: Colors, shapes, styles, and product categories are automatically recognized and stored as tags.
- Color analysis and assignment
- Shape recognition
- Style classification
- Automatic alt text
Multilingual Enrichment
Product data is enriched in over 30 languages - not just translated, but localized with country-specific units of measurement, terms, and cultural adaptations.
- Contextual translation
- Local units of measurement
- Cultural adaptation
- SEO in target language
Categorization & Mapping
Products are automatically assigned to the correct categories, Google Product Categories, and marketplace taxonomies. Perfect for multi-channel commerce.
- Assign shop categories
- Google Product Category
- Amazon categories
- Cross-selling groups
Quality Assurance & Validation
Multi-level validation checks all enriched data for plausibility, completeness, and consistency. Confidence scores and approval workflows ensure high data quality.
- Plausibility check
- Confidence scoring
- Approval workflows
- Audit trail
PIM and ERP Integration
Seamless integration into your existing system landscape - from Akeneo to SAP.
Akeneo PIM
Bidirectional connection to Akeneo PIM. Incomplete products are detected, enriched, and written back with change history.
Pimcore
Native Pimcore integration with support for Data Objects, Assets, and complex data structures. Workflows and versioning included.
SAP Business One
Master data from SAP is enriched and synchronized. Mapping to SAP material masters and batch processing for mass imports.
Microsoft Dynamics
Integration with Dynamics NAV/365 Business Central. Item master data is automatically enriched and shop exports optimized.
Shopware 6
Direct shop integration for enrichment in the shop backend. Products are automatically checked and completed before publication.
REST & GraphQL API
Flexible API access for custom integrations. Batch processing, webhooks, and streaming endpoints for real-time enrichment.
Data Enrichment in Practice
Concrete scenarios where our AI data enrichment makes the difference.
Supplier Imports
Sparse supplier data (only item number, name, price) becomes complete product pages with descriptions, attributes, and categories.
Legacy Data Migration
During shop relaunch or PIM introduction, historical data is automatically cleaned, standardized, and enriched.
Attribute Completion
Missing filter attributes for faceted navigation are extracted from texts and images - for better product discoverability.
Cross-Selling Recommendations
Based on product attributes, the AI automatically generates matching accessory and complementary product links.
Marketplace Export
Product data is automatically adapted and completed for Amazon, eBay, and other marketplace requirements.
Internationalization
Existing product data is localized for new country markets - including units of measurement, standards, and country-specific attributes.
The Enrichment Process
Data Analysis & Mapping
We analyze your existing data structures, identify gaps, and define the target schema for enrichment.
AI Configuration
The enrichment AI is trained on your product categories and industry. Rule sets for validation and quality assurance are defined.
Pilot Enrichment
Test with 100-500 products for fine-tuning results. Feedback loops optimize output quality.
Full Automation
Integration into your systems for continuous enrichment. New products are automatically processed, changes synchronized.
Frequently Asked Questions About Data Enrichment
Data Enrichment focuses on the structured completion of product data: adding missing attributes, extracting technical specifications, assigning categories. Product text generation, on the other hand, creates flowing text descriptions. Both processes complement each other optimally - first the data is enriched, then high-quality texts are generated from it.
Our AI solution connects directly to your PIM system (Akeneo, Pimcore, etc.) via API interfaces. Incomplete products are automatically detected, enriched by AI, and written back to the PIM. The process runs fully automatically or with a manual review step - depending on your requirements for control and speed.
The AI recognizes dimensions, weights, materials, colors, technical specifications, application areas, and many other attributes. Visual features such as color, shape, and style are additionally extracted from product images. Recognition accuracy is over 95% - with continuous improvement through feedback learning.
Yes, this is actually a main use case. The AI can enrich product data in over 30 languages while considering language-specific characteristics. Existing data in one language is used as a basis and translated or localized with high quality - including country-specific units of measurement and standards.
We rely on multi-level quality assurance: Rule-based validation checks plausibility (e.g., dimension ratios), confidence scores show the reliability of AI results, and optional manual approval workflows enable control for critical data. Additionally, the system learns from corrections and continuously improves.