Rasyn Blog
Unlock unstructured data through custom document workflows and business intelligence
How to Benchmark
Document AI has a leaderboard problem. The IDP Leaderboard is a good place to see it. A benchmark makes a claim to authority. It says: this is what better means, and here is who is better by it. That claim carries obligations, and they aren't optional ones. You have to characterise your noise before you publish an ordering, document what's in your corpus and where it came from, justify why the numbers you're combining can be combined at all, and choose documents difficult enough to separate go
"Fix Your Data First" Is Bad Advice for Document AI
There's a statistic making the rounds in enterprise AI circles: 73% of organizations cite data quality as a barrier to AI success, according to the Hackett Group's 2026 Key Issues Study [1]. The standard advice that follows is always the same. Clean your data first. Set up governance. Then, and only then, bring in AI. For most enterprise AI, that advice is correct. For document AI, maybe not so. The dirty data IS the documents Think about what "data" actually means in a document-heavy enterp
DeepSeek-OCR: Rethinking Document Understanding Through Compression
DeepSeek-OCR takes a different approach to handling documents in language models. Instead of extracting text and sending it as tokens, they keep the document as an image and use vision models for compression.