Blog Articles - Developer

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: What is the best package to read text content from a PDF? Apryse Answers Episode 4 explores PDF data extraction by solving real developer questions from Reddit. Learn how Apryse Smart Data Extraction goes beyond OCR to preserve document structure, extract tables, identify key-value pairs, classify documents, and process scanned PDFs. Discover how to build intelligent extraction workflows using Apryse Server SDK, convert unstructured PDFs into AI-ready JSON, and improve automation, search, compliance, and document processing accuracy.

Summary: When building mobile apps with PDF viewing, native tools like iOS PDFKit and Android PDFRenderer offer free, basic rendering, navigation, and annotation capabilities. However, advanced features, cross-platform consistency, and enterprise-scale performance often require significant custom development. Apryse SDK provides a unified, cross-platform solution with advanced PDF functionality, customizable UI, better performance, and faster development through a single codebase.

Summary: This article demonstrates how to create a highly intuitive tool for generating GoToR links by using two side-by-side instances of Apryse WebViewer. By utilizing a custom button in a dual-viewer setup, developers can enable users to select text and link it directly to a document's current page in a view-only pane, eliminating the need for manual metadata entry.

Summary: Handwriting OCR bridges the gap between old-school paper and digital databases. This beginner guide explains how the tech translates messy handwriting into typed characters, without the confusing technical jargon. We will look at real-world use cases, set honest expectations for accuracy, and compare the top software options out there.

Summary: Handwriting recognition software helps organizations extract data from handwritten documents such as medical forms, insurance claims, checks, shipment records, and government archives. This comparison examines five approaches: Google Document AI, AWS Textract, Azure Document Intelligence, Tesseract OCR, and Apryse Intelligent Character Recognition (ICR). While cloud-based handwriting recognition APIs offer convenience, they often require documents to leave secure environments and charge per page. Open-source OCR tools have limited handwriting support and require a significant developer lift. Apryse ICR provides a dedicated handwriting recognition engine that runs on-premises, in private clouds, or air-gapped environments, enabling secure, scalable extraction of handwritten text into searchable PDFs, JSON, XML, and other structured formats.