Document Processing & OCR for Government Data
The Challenge
A government agency accumulated large volumes of digital documents containing critical operational and legal data. This information was locked in unstructured formats — PDFs, scanned documents, and mixed-language files — making it impossible to query, analyze, or visualize without extensive manual effort. The agency needed to convert this data into structured database records suitable for Power BI dashboards and analytical reporting.
Our Approach
Neural AI developed a comprehensive Document AI and OCR pipeline:
- Advanced OCR processing handling both digital-native and scanned documents with high accuracy, including handwritten elements
- Maltese language support enabling accurate extraction from bilingual documents that mix Maltese and English text
- Intelligent data extraction identifying and structuring key fields such as dates, names, amounts, reference numbers, and categorizations from diverse document types
- Comparison engine cross-referencing extracted data against existing records to identify duplicates, discrepancies, and data quality issues
- Structured output transforming raw document content into clean, normalized database records ready for direct import into Power BI
- Summarisation generating document summaries and metadata tags for improved search and categorization
"Turning mountains of government documents into structured, analyzable data unlocks insights that were previously impossible to extract at scale."
Key Results
- Automated extraction from thousands of documents
- Bilingual Maltese and English document processing
- Structured data output ready for Power BI analysis
- Reduced manual data entry by over 75%
- Improved data accuracy and consistency
- Scalable pipeline for ongoing document processing
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