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Airgap
Local document AI for confidential files
Ask questions about your PDFs, Markdown, and text files entirely on your Mac. Local retrieval, local models, and citations down to the paragraph.
Top comment
Document RAG without handing documents to a service. Airgap builds a private vector index for each vault on your Mac. It parses documents, retrieves the relevant chunks, runs a local language model, and links answers back to the original source pages. It is designed for local research workflows where precision, provenance, and data residency matter more than cloud convenience.
About Airgap on Product Hunt
“Local document AI for confidential files”
Airgap was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #41 on the daily leaderboard. Ask questions about your PDFs, Markdown, and text files entirely on your Mac. Local retrieval, local models, and citations down to the paragraph.
On the analytics side, Airgap competes within Productivity and Artificial Intelligence — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Airgap performed against the three products that launched closest to it on the same day.
Who hunted Airgap?
Airgap was hunted by Nedim. 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 Airgap including community comment highlights and product details, visit the product overview.