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).
Product upvotes vs the next 3
Waiting for data. Loading
Product comments vs the next 3
Waiting for data. Loading
Product upvote speed vs the next 3
Waiting for data. Loading
Product upvotes and comments
Waiting for data. Loading
Product vs the next 3
Loading
ContextOCR.dev
OCR for AI: markdown with full context including QR/Barcodes
Convert PDFs, images, and emails into AI-ready Markdown with layout-aware context, decoded QR codes and barcodes, and usage-based OCR billing.
Hey Product Hunt,
I built ContextOCR after running into the same problem across my own products.
OCR is everywhere. But for AI apps, plain text extraction usually isn’t enough. You still need clean markdown, email rendering, attachment handling, QR/barcode decoding, and output that is easy to pass into an agent or RAG pipeline.
ContextOCR is my attempt to make that boring and simple:
Send a file → get back AI-ready markdown.
It handles PDFs, images, and `.eml` files. For emails, it renders them in a headless browser, follows attachments, and keeps the useful context. It also decodes QR codes and barcodes automatically.
I built it first for Passdrop.app and Formslam.com, where it has been working well in production. Now I’m making it available as a standalone API.
Curious to hear what people are building with messy documents, screenshots, labels, emails, and attachments.
About ContextOCR.dev on Product Hunt
“OCR for AI: markdown with full context including QR/Barcodes”
ContextOCR.dev was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #116 on the daily leaderboard. Convert PDFs, images, and emails into AI-ready Markdown with layout-aware context, decoded QR codes and barcodes, and usage-based OCR billing.
On the analytics side, ContextOCR.dev competes within Developer Tools and Artificial Intelligence — topics that collectively have 986.1k followers on Product Hunt. The dashboard above tracks how ContextOCR.dev performed against the three products that launched closest to it on the same day.
Who hunted ContextOCR.dev?
ContextOCR.dev was hunted by Elvijs Untāls. 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 ContextOCR.dev including community comment highlights and product details, visit the product overview.
Elvijs Untāls