Client -
Confidential
Industry -
FinTech
Delivery -
~1 year
Region -
Germany
25-35%
Extraction Accuracy Improvement
15-25%
Manual Review Reduction
<2 min
Processing Time per Invoice
AI Invoice Data Extraction Platform
Table of contents
The client needed a smart invoice data extraction system to process invoices from multiple suppliers across jurisdictions and formats. Manual extraction was slow and error-prone, creating bottlenecks in payment cycles. They required a solution to accurately handle both tabular structures and unstructured text across diverse document types.
Challenge
- Manual invoice processing was slow, error-prone, and unable to scale across multiple suppliers and formats
- Complex invoice structures with mixed tabular and unstructured data were difficult to extract accurately
- Multiple jurisdictions and supplier formats required flexible document handling
- Processing delays created critical bottlenecks in payment approval cycles
Solution
- Automated invoice data extraction platform using OCR and NLP technologies
- Rule-based logic and algorithms to improve accuracy in table and field matching
- Machine learning models for intelligent document type classification and routing
- Training data pipeline enabling continuous model improvement and adaptation
Architecture
Architecture diagram withheld under client confidentiality agreement.
Outcome
- 25-35% improvement in extraction accuracy replacing manual document review
- 15-25% reduction in manual invoice processing effort through automation
- Sub-2 minute processing time per invoice enabling faster payment cycles
- Platform handles multiple formats and jurisdictions without manual configuration
Tech Stack
- AI/ML: OCR, NLP, Machine Learning
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