Browsing: Document

, I built a fully automated intelligent document processing (IDP) system that ran in the cloud on Amazon Web Services. The system was designed to allow…

Loop engineering for hierarchical retrieval: reading a long document by its table of contents – gif by author of Part II of Enterprise Document Intelligence, a…

in Enterprise Document Intelligence, the series that builds an enterprise RAG system from four bricks. Article 5 (document parsing) built the parser with PyMuPDF (fitz), which…

def create_demo_image(path): img = Image.new(“RGB”, (320, 180), “white”) draw = ImageDraw.Draw(img) draw.rectangle([20, 20, 300, 160], outline=”black”, width=3) draw.ellipse([55, 45, 145, 135], outline=”black”, width=4) draw.line([180, 140, 285,…

def normalize(data): return {“text”: (data.get(“text”) or “”).strip().lower()} def tokenize(data): text = data.get(“text”, “”) cleaned = “”.join(c if (c.isalnum() or c.isspace()) else ” ” for c in…

, generative AI took off and RAG showed up as the standard answer for “we have documents, we want to ask questions.” The pitch sounded miraculous.…

situation: You work in the operations team of a medium-sized company. Every day, your team processes order forms from different B2B customers. All of them arrive…

the most important AI use cases of an enterprise today, document comparison ranks alongside conversational chatbots. Organizations spend a vast number of person-hours comparing contracts, policies,…

In this tutorial, we explore how to use Google’s LangExtract library to transform unstructured text into structured, machine-readable information. We begin by installing the required dependencies…

and asked if I could help extract revision numbers from over 4,700 engineering drawing PDFs. They were migrating to a new asset-management system and needed every…