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CaseGuard vs LocalRedact

CaseGuard

caseguard.com

LocalRedact

github.com

Side by side

FigureCaseGuardLocalRedact
Price from$23.25/moFree
Free plan—Yes
Free trial——
Open source——
WindowsYesYes
macOS—Yes
Linux—Yes
API—Yes
Self-hostedYesYes
Plans published41
Spec score · Document Redaction Software7.9 (#12)8.4 (#7)
ComplianceThe pricing page describes the product as supporting HIPAA, FOIA, CJIS, and GDPR compliance and says metadata is scrubbed and redactions are permanent.The project describes its detection as best effort and says it is not a compliance certification.
IntegrationsCaseGuard documents integrations with Axon Evidence and Box, and its project guide also lists Amazon S3 as an import source.The base package depends on PyMuPDF, and the optional HTTP service can be installed with the server extra.
PurposeCaseGuard automates redaction of sensitive information in video, audio, documents, and images for organizations handling evidence and records.LocalRedact is a private PDF redaction tool that processes plain-English instructions with deterministic rules.

Plans

CaseGuard

  • Doc Suite$279 a year
  • Media Suite$299 a year
  • Ultimate Suite$379 a year
  • EnterprisePriced on request

CaseGuard pricing →

LocalRedact

  • LocalRedactFree

LocalRedact pricing →

In their own words

CaseGuard

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

Visit caseguard.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