The client requested an automated redaction system to overcome the limitations of manual sensitive-data handling in the import declaration processing workflow. The goal was to reduce inefficiency and security risk by accurately identifying and masking multiple forms of sensitive information—such as names, phone numbers, and business identifiers—thereby minimizing repetitive manual work while significantly improving protection levels. Because import declaration documents require both accuracy and strong security, the system needed to reduce human error while accelerating throughput.

In addition, the client emphasized improving operational efficiency and security at the same time. The existing manual approach—reviewing documents one by one and masking data by hand—consumed substantial time and resources and created risk of omissions or incorrect handling. The solution was expected to process high volumes quickly, apply consistent redaction standards, and strengthen organizational capability and trust through reliable protection.

Finally, the client required a hybrid workflow combining automated detection with human verification. Since full automation may not cover every exception case, the system needed to support semi-automatic and fully manual redaction based on auto-detection results. A clear, easy-to-use interface was required so reviewers could validate results, adjust detections, and apply additional masking as needed—leveraging both automation efficiency and human judgment accuracy.

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코드 복사

We developed an intelligent PDF text detection and automated redaction system designed to handle complex and variable import declaration formats. The solution incorporated robust text recognition logic that can adapt to different layouts, fonts, and form variations while maintaining consistent performance. We implemented pattern-based detection algorithms to accurately identify sensitive data types—personal information, contact details, and business numbers—and applied reliable redaction (blinding) to significantly enhance information security. The design was optimized for Korean text characteristics and standardized public-document templates, and it was built with an extensible architecture to accommodate future form changes and new sensitive-data patterns.

To maximize operational efficiency, we implemented flexible masking modes that support automatic, semi-automatic, and manual redaction. Users can review auto-redaction results in real time, adjust or add masking through an intuitive interface, and perform selective redaction on specific areas. We also provided unmask/reprocess options to handle edge cases smoothly, enabling a practical workflow that combines automated speed with human verification accuracy.

We delivered a reviewer-centric UI focused on clarity and productivity. Detection results are visualized clearly by text block so reviewers can immediately understand where sensitive information is located and its current status. Navigation was designed to be intuitive even for complex documents, and one-click actions for masking/unmasking reduced repetitive workload. We also supported precision review with features such as split-view comparison between original and processed output, zoom in/out, page navigation, and real-time progress indicators.

Lastly, we established a secure file handling and audit-ready system appropriate for sensitive-document workflows. We implemented encrypted storage for files before and after processing, enforced access control so only authorized users can view or download outputs, and designed deployment options that can support isolated or internal-only environments when required. We also built an audit trail system to safely log processing activity, strengthening incident prevention and post-event traceability, supported by ongoing security checks and update readiness.