PDFRedaction vs Philter

PDFRedaction is a browser-based tool for detecting and permanently removing sensitive information from documents. Its AI detection, analysis, and redaction run locally in an isolated browser context, and document content, extracted text, PII values, and redacted output are not transmitted to its servers. The service detects more than 50 types of personally identifiable information, including names, contact details, financial identifiers, and medical IDs. OCR covers scanned PDFs and image-based documents, with layout preserved in PDF output. Redaction removes sensitive text and covers it with solid black rectangles. The tool also scans PDFs for malicious elements and strips them during export. Users can add a signature image or sign on screen, then position and resize signatures or stamps in the browser. It supports PDF, image, text, and data formats. Registered users can process up to 10 documents per day on the free plan; processing pauses when the quota is reached. Professional and Enterprise plans are not currently available for purchase.

Philter is open-source software for finding and redacting personally identifiable information and protected health information in text. For detected entities, users can choose to mask, encrypt, replace with synthetic values, remove, or pass them through. Policies, custom dictionaries, and identifier patterns such as medical record numbers and transaction IDs let teams configure what to detect and how to handle it. General Purpose, Healthcare, and COVID-19 NLP lenses address different types of text. Philter provides an HTTP REST API, a Java SDK, and an OpenAPI specification for generating clients in other languages. It can run in a private environment or through AWS, Google Cloud, and Microsoft Azure marketplaces. The maker says text stays in the customer’s environment, including firewalled or air-gapped deployments. Redaction requests are recorded in a tamper-evident, hash-chained audit log that can be queried and exported to CSV. Detection is probabilistic, so results should be checked against an organization’s own data before production use. The open-source toolkit has community support; commercial licenses include direct support.