Model releases, benchmarks, and research notes
How we build and evaluate the models behind Nanonets agents — from the Nanonets-OCR family to our work on complex instruction following.
A deep dive into building fully automated document processing workflows — no human in the loop, no manual exceptions, no fallback queues.
The latest generation of our document OCR model — converting pages into structured, LLM-ready markdown with stronger layout, table, and equation understanding.
The second-generation Nanonets-OCR model, extending image-to-markdown extraction across more document types and languages.
Our open image-to-markdown OCR model — turning documents into structured text with tables, equations, and reading order preserved.
How Nanonets performs on Surge AI's ComplexConstraints benchmark for entangled instruction following — conditional, implicit, multistep, and negative constraints.
An open leaderboard tracking OCR model performance across document types, languages, and layout complexity — updated as new models are evaluated.
The industry benchmark for intelligent document processing — ranking models on real-world extraction tasks across invoices, forms, contracts, and more.
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