Business Challenge
A leading North American home improvement retailer managed millions of product SKUs sourced from thousands of suppliers. Much of the product information was shared via PDF spec sheets, catalogs, and data sheets, creating several challenges:
- Manual extraction was time-consuming and error-prone, delaying item onboarding.
- Incomplete or inconsistent product data reduced catalog quality and discoverability.
- Low data fill rates impacted search relevance, online conversion, and customer experience.
The client needed an automated way to extract structured product attributes from supplier PDFs and validate them against existing item data.
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The Solution
Iksula implemented an AI-powered document extraction and data quality pipeline leveraging computer vision, NLP, and rule-based validation. The solution automated attribute capture, validation, and enrichment — significantly improving catalog completeness and accuracy.
Key Capabilities:
- Automated PDF Extraction: AI models read unstructured PDFs and extract key product attributes (dimensions, material, weight, warranty, etc.)
- Attribute Comparison Engine: Extracted data was matched and compared against existing item master records to identify gaps, mismatches, or missing values.
- Data Enrichment: Missing or incomplete attributes were auto-populated from supplier documents, raising overall data completeness
- Continuous Quality Feedback: Machine learning models improved extraction accuracy over time based on review feedback.
Business Impact
- Data Fill Rate Increased by 45% across thousands of SKUs.
- 80% reduction in manual data entry time and operational effort
- Improved Search & Discovery: Richer product attributes enhanced SEO and conversion rates.
- Data Quality Score Boost: Standardized, validated item data enabled reliable analytics and downstream automation.
Technology Stack
- AI / ML: NLP models (BERT, LayoutLM) for PDF parsing and text extraction
- Computer Vision: OCR + entity recognition for structured attribute mapping
- Data Validation: Rule-based matching engine with similarity scoring
- Integration: Direct sync with PIM/MDM systems and supplier portals
- Automation: ETL pipelines for ingestion, comparison, and enrichment workflows
