Parse, extract, and split your hardest documents with unmatched accuracy. Read any layout with specialized vision models, and ship reliable pipelines in minutes, not months.
Extend already processes millions of pages daily for leading AI teams like @Brex, @Mercury, @Opendoor, and hundreds of others. Now, its even better.
Parse 2.0 is SOTA quality on RealDoc-Bench, our open source benchmark that measures agent success rate on real world docs that agents actually encounter in production.
We trained Parse 2.0 on 1M+ pages of the hardest documents seen in production. Here’s how it stacks up:
#1 in healthcare, real estate, logistics, and financial services
95.7% agent Q&A accuracy on 581 docs (next best: 92%)
The real unlock here isn’t OCR accuracy it’s preserving semantic reading order under structure ambiguity.
Most pipelines break not on extraction, but on downstream assumptions about hierarchy (especially tables/forms where “correct text” ≠ “correct meaning flow”).
Curious how do you handle evaluation when ground truth layout interpretation is subjective (e.g. multi-table docs or mixed narrative/forms)?
How do your specialized vision models handle multi-column layouts, mixed tables, or low-quality scanned PDFs compared to standard LLMs?
Hi everyone! If anyone tells you that PDFs are solved, they probably haven't worked with the PDFs our customers see in production. We're talking bill of lading in shipping and logistics, clinical reports, IRS forms, etc.
Parse 2.0 let's your agents actually work with reliable inputs, no matter how hard the documents are. This allows you to build:
RAG systems that accurately answers questions with precise citation sourcing
Automated workflows to accelerate document workflows
Agents that take action on documents (e.g. routing, classification, extraction, etc)
Parse 2.0 is a SOTA, layout-first document parsing API for agents that need reliable inputs. It features:
A completely rebuilt layout model trained on 1M+ of the hardest docs
New specialized OCR and VLM downstream models to handle specific doc components (e.g. forms, tables, handwriting, etc)
New reading order model to preserve semantic meaning (not every doc should be read left to right, top to bottom)
If you need accurate PDF parsing, check it out and let us know what you think!
About Extend on Product Hunt
“Parse any PDF layout with SOTA accuracy for AI pipelines”
Extend launched on Product Hunt on May 27th, 2026 and earned 88 upvotes and 7 comments, placing #17 on the daily leaderboard. Parse, extract, and split your hardest documents with unmatched accuracy. Read any layout with specialized vision models, and ship reliable pipelines in minutes, not months.
Extend was featured in API (98.3k followers) and Developer Tools (514k followers) on Product Hunt. Together, these topics include over 82.8k products, making this a competitive space to launch in.
Who hunted Extend?
Extend was hunted by fmerian. 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.
Want to see how Extend stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
fmerian
"Over 1 billion PDFs are created every day, and your agents still can't read them reliably."
@Extend announced Parse 2.0, their new document parsing API.
Founder and CEO @kbyatnal on X: