OCR and Data Pipeline for Government Process Automation

Our client processed financial documents the slow way: officers keying figures from bank statements that arrived in dozens of different layouts. Reviews stretched into weeks, and the backlog limited how quickly the agency could act.

The workflow was bottlenecked end to end:

• Wide variation in e-statement formats across Indonesian banks
• Heavy reliance on manual document review and data entry
• Processing cycles that ran for weeks
• Significant human effort for validation, reconciliation, and reporting

Without automation, scalability was capped and downstream analysis always arrived late.

VentureSEA built an end-to-end intelligent document processing pipeline tuned to the agency's formats.

• Built a custom OCR and document-parsing engine in PyTorch, fine-tuned for diverse, noisy bank statement layouts
• Engineered extraction logic to reliably capture transactional and summary-level fields
• Converted unstructured PDFs into clean, structured datasets with automated validation, reconciliation, and a full processing audit log for every document
• Orchestrated the flow in Apache Airflow and served results through a FastAPI service into a PostgreSQL store, with role-based access to protect sensitive financial data
• Fed dashboards for automated reporting and live operational visibility, built to the agency's regulatory and compliance requirements
• Held field-level extraction accuracy above 98 percent on the agency's validation set, with low-confidence documents routed to human review instead of passing through silently