Medianonymizer's answer:

It handles all four media types — documents, images, audio and video — in one tool, where most alternatives only blur faces in video or images. The AI only locates sensitive data; deterministic code does the actual removal (solid boxes, pixelation, audio beeps, metadata stripping), so results are irreversible, auditable and reproducible instead of a soft, reversible blur overlay. And you review and adjust every detected region before you pay.

Medianonymizer's answer:

Three reasons: - Coverage — it redacts documents and spoken audio PII too, not just faces in video or images. - Control — you see the exact price and can edit every detected region (rectangle or lasso) before paying, with no account and no subscription. - Compliance — redaction is irreversible by design (which supports taking data out of GDPR scope), files upload encrypted straight to storage, originals self-delete after processing, and nothing is ever used to train AI.

Medianonymizer's answer:

Teams that need to share, publish or archive media without exposing personal data: legal and compliance, healthcare and research, HR and recruitment, journalists and media, customer support (call and chat recordings), and public sector / CCTV operators. It's built for EU and GDPR-conscious users, and available in English, Spanish, German, French, Italian and Portuguese.

Medianonymizer's answer:

Anonymizing media properly is tedious and error-prone. Manual blurring in video editors is slow, and most automated tools either handle only one media type or use a reversible blur that isn't truly compliant. Medianonymizer was built to make irreversible, auditable anonymization across documents, images, audio and video fast and self-serve: upload a file, let the AI find the sensitive data, review and adjust it, then pay per job and download — no account, no subscription.

Medianonymizer's answer:

A Next.js and TypeScript frontend (deployed on Vercel), and a Python processing worker that does the heavy lifting: computer-vision face and license-plate detection, spaCy-based PII and named-entity detection for text, and ffmpeg for audio/video redaction and re-encoding. Files use object storage with presigned, encrypted uploads, and payments run through Stripe on a pay-per-job basis.