What is TradeOps?
TradeOps is an automated document processing pipeline created to ingest scanned, digital, and semi-structured commercial trade invoices. It uses targeted optical pattern recognition and natural language parsing to extract approximately 40 distinct operational and transactional parameters.
What Problem Does It Solve?
Banking and international trade operations manually enter dozens of fields per commercial invoice—such as consignee, consignor, HS codes, port of discharge, currency, invoice total, tax IDs, and bill of lading numbers. This manual entry is prone to high human error rates and operational bottlenecks. TradeOps automates this workflow with sub-second extraction into relational database schemas.
How Does It Work?
- Pre-processing & Normalization: Ingests high-resolution PDF scans, deskews image layers, and normalizes table boundaries.
- Field Identification & Regex Parsing: Employs structured key-value matching algorithms to locate crucial metadata fields regardless of invoice layout variance.
- Database Serialization: Maps extracted entity values into structured schema records in Microsoft SQL Server (SSMS) with audit trail logs.
Technology Stack
Python OCR & Document Parsing Microsoft SQL Server (SSMS) PyODBC Data Validation Pipelines
Ahmed Raza's Contribution
Ahmed Raza implemented the parsing logic and database synchronization scripts, ensuring accurate schema mapping across diverse commercial layout formats.