
PDF2Emails
Extract & verify emails from PDFs in-browser. 100% private.
What it does
PDF2Emails is a privacy-first lead extractor that pulls, verifies, and enriches contacts from any PDF directly in your browser. Unlike cloud tools, your PDF never touches a server—100% client-side processing using local OCR. Key Features: • OCR for scanned PDFs • Real SMTP email verification • AI name formatting & title/company enrichment • Export clean lists to CSV, TXT, or Excel (.xlsx) • Pay-as-you-go flexibility (Free for ≤3 pages)
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- PFPrivacy friendly suite of PDF tools2023 · pdfux.com · ▲99
Hi HN, I have been working on a set of PDF tools that does all the processing directly in the web browser. From time to time I needed to do some simple PDF manipulations like merging PDF files. Sometimes the files contain my personal data and I was not comfortable using other online services where the file usually is uploaded to a remote server. Behind the scenes there is a small library written in C++ doing the changes to the PDF files. I am using the Emscripten compiler to compile it to WebAssembly that is running in the browser. It was a very good learning for me and it was easier than I…
- PEPDFx – Extract Metadata and URLs from PDFs, and Download Referenced PDFs2015 · metachris.com · ▲93
More growth this month
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AstraPixels▲267A pixel-art solar system at its real current positions.
Growth · 29d ago · astrapixels.com

Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com