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Appligent Redax vs LocalRedact

Appligent Redax

appligent.com

LocalRedact

github.com

Side by side

FigureAppligent RedaxLocalRedact
Price from—Free
Free plan—Yes
Free trialYes—
Open source——
WindowsYesYes
macOS—Yes
Linux—Yes
API—Yes
Self-hosted—Yes
Plans published31
Spec score · Document Redaction Software8.0 (#11)8.4 (#7)
PurposeRedax is an Adobe Acrobat plug-in for permanently removing sensitive text and graphics from PDF files.LocalRedact is a private PDF redaction tool that processes plain-English instructions with deterministic rules.

Plans

Appligent Redax

  • Redax single-desktop license$249, paid once
  • Redax + StampPDF package$319, paid once
  • Redax Five (5) Pack$999, paid once

Appligent Redax pricing →

LocalRedact

  • LocalRedactFree

LocalRedact pricing →

In their own words

Appligent Redax

Appligent Redax has no write-up on Specifiction yet; its figures are above.

Visit appligent.com

LocalRedact

LocalRedact is a free, open-source PDF redaction tool that follows plain-English instructions using deterministic rules. It removes text beneath redacted areas and blanks image pixels where those areas overlap. Detection can target personal, financial, government, health, and credential data, as well as quoted values and selected page or layout instructions. Processing happens locally: the project says it uses no LLM, cloud API, telemetry, or model download, and reads text and coordinates with PyMuPDF. By default, it removes common PDF extras such as metadata, embedded files, JavaScript, links, and saved form state. After saving, it reopens the document and checks whether detected values remain extractable. Interfaces include a Python API, two command-line tools, and an optional HTTP service. Scanned PDFs can use locally installed Tesseract; image-only pages fail closed without OCR by default. The package requires Python 3.10 or later and is available for Windows, macOS, and Linux. The project calls the software alpha and warns that detection is best effort, not a compliance certification. It recommends visually reviewing high-stakes output.

Visit github.com