Blog Articles - redaction

Summary: This article introduces a new Apryse code sample that leverages LangChain and LLMs directly within WebViewer to automatically detect PII and create redaction annotations to streamline the document security workflow. By integrating AI-powered detection, users can efficiently identify sensitive data while retaining necessary human oversight for final redaction approval.

Summary: Protecting sensitive data in industries like healthcare, law, and insurance is vital for compliance and risk reduction. This article demonstrates how to use the Apryse SDK to automate the detection of sensitive content inside a PDF within the browser. You will learn how to automatically scan and identify sensitive keywords, names, and addresses upon document load, programmatically generate redaction annotations using text coordinates (quads), and customize redaction styles by adding descriptive overlay text like replacing a name with "Witness A".