Processing sensitive data shouldn't mean compromising privacy. With cloud AI platforms raising trust concerns and compliance hurdles, privacy-centric firms need complete control. LocalPDF lets you analyze legal, medical, and financial documents 100% locally on your device. Zero data leaves your machine, ensuring enterprise-grade security compliance without relying on OpenAI, Gemini or Anthropic.
Hey Product Hunt! 👋
I'll be honest: I don't trust cloud AI platforms. Handing over sensitive legal, medical, or financial documents to third-party servers always felt like an unacceptable security risk to me.
We shouldn't have to choose between using powerful AI tools and keeping our data secure.
I built LocalPDF.io because I wanted a way to process and analyze my documents where I am the only one in control. It operates completely offline, right on your device. Nothing is sent to the cloud. Nothing is used to train someone else's model.
If you work in a privacy-centric firm or you're just protective of your own data like I am, I built this for you.
I'm here all day to answer your questions. Would love to hear your feedback!
A lot of local-document tools break down on real-world PDFs (scanned docs, tables, multi-column layouts, mixed file types). What did you implement to make extraction/indexing reliable in those cases, and what are the failure modes you still see?
Utsav Patel