This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Respond to DSARs in half the time. Auto-detect NHS numbers, NI numbers, postcodes, names and 12 UK PII types in PDFs and Word docs. 100% local. Built for UK DPOs.
I built DesktopRedact after seeing how painful document redaction still is for UK legal and compliance teams. The options are either Adobe Acrobat (slow, entirely manual you're squinting at pages looking for names you might have missed), or cloud tools that mean uploading privileged client documents to someone else's server. For anyone handling DSARs, disclosure bundles, or patient records, neither is really acceptable.
So I built the thing I thought should exist:
• Open a PDF or Word doc and it auto-detects PII — names, NHS/NI numbers, UK postcodes, sort codes, passport numbers, emails, addresses, the lot • Review each detection with one keypress (approve, dismiss, next) • OCR built in for scanned PDFs Apple Vision on macOS, Tesseract on Windows/Linux • Export with a plain-text audit log alongside every file — SHA-256 chain-of-custody hash, DSAR exemption reason codes, reviewer sign-off, UTC timestamps • Runs 100% locally on macOS, Windows, and Linux. No uploads, no account required, works offline
The stack: Tauri 2 + Vue 3 on the front, Python sidecar with spaCy + Microsoft Presidio for detection. Free tier for occasional use, paid tiers unlock batch processing and higher page quotas licence verified locally with Ed25519, no phone-home.
Would love feedback — especially from anyone who's dealt with DSARs, disclosure, or redacting sensitive records. What's the most painful part of your current workflow? And what PII types or languages should I prioritise next?
— Marcin
About DesktopRedact — DSAR Response Automation on Product Hunt
DesktopRedact — DSAR Response Automation was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #160 on the daily leaderboard. Respond to DSARs in half the time. Auto-detect NHS numbers, NI numbers, postcodes, names and 12 UK PII types in PDFs and Word docs. 100% local. Built for UK DPOs.
On the analytics side, DesktopRedact — DSAR Response Automation competes within Productivity, Privacy and Legal — topics that collectively have 668.9k followers on Product Hunt. The dashboard above tracks how DesktopRedact — DSAR Response Automation performed against the three products that launched closest to it on the same day.
Who hunted DesktopRedact — DSAR Response Automation?
DesktopRedact — DSAR Response Automation was hunted by Marcin Walczak. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of DesktopRedact — DSAR Response Automation including community comment highlights and product details, visit the product overview.
Marcin Walczak
⏺ Hey Product Hunt 👋
I built DesktopRedact after seeing how painful document redaction still is for UK legal and compliance teams. The options are either Adobe Acrobat (slow, entirely manual you're squinting at pages looking for names you might have missed), or cloud tools that mean uploading privileged client documents to someone else's server. For anyone handling DSARs, disclosure bundles, or patient records, neither is really acceptable.
So I built the thing I thought should exist:
• Open a PDF or Word doc and it auto-detects PII — names, NHS/NI numbers, UK postcodes, sort codes, passport numbers, emails, addresses, the lot
• Review each detection with one keypress (approve, dismiss, next)
• OCR built in for scanned PDFs Apple Vision on macOS, Tesseract on Windows/Linux
• Export with a plain-text audit log alongside every file — SHA-256 chain-of-custody hash, DSAR exemption reason codes, reviewer sign-off, UTC timestamps
• Runs 100% locally on macOS, Windows, and Linux. No uploads, no account required, works offline
The stack: Tauri 2 + Vue 3 on the front, Python sidecar with spaCy + Microsoft Presidio for detection. Free tier for occasional use, paid tiers unlock batch processing and higher page quotas licence verified locally with Ed25519, no phone-home.
Would love feedback — especially from anyone who's dealt with DSARs, disclosure, or redacting sensitive records. What's the most painful part of your current workflow?
And what PII types or languages should I prioritise next?
— Marcin