Artificial intelligence firms are racing to solve the long‑standing challenge of extracting reliable information from PDF documents. While PDFs dominate high‑quality data sources such as government reports and academic papers, their visual‑centric format thwarts traditional OCR and language models, leading to errors, hallucinations, and costly processing. Startups like Reducto are experimenting with multi‑stage visual models that segment pages into headers, tables, and charts before applying specialized parsers. Researchers at the Allen Institute and Hugging Face are also building dedicated PDF‑reading models, yet even the best systems still miss a small but critical portion of content. The continued proliferation of PDFs ensures the problem will persist, keeping it a hot focus for AI developers. Read more →