Enterprise Document Intelligence [Vol.1 #B1] - Three sources of one problem. User typos, fast-typing transcription noise, OCR character errors. Classical spell-check handles one of them. Embeddings carry the rest
The post Noisy Text in RAG: Typos, OCR, and the Gap Classical Spell-Check Leaves appeared first on Towards Data Science.
Learn where which coding agent is best
The post When to Use Claude Code and When to Use Codex appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #B00] - Retrieval answers one kind of question. Classifying a request, matching free text to a reference list, reading a table, cleaning OCR noise: each has a cheaper method that works, and the engineering is knowing which one to reach for
The post RAG Is Not the Whole Toolkit: The NLP Techniques Real Problems Still Need appeared first on Towards Data Science.
How we stopped reviewing every agent action and started routing human attention where it actually mattered
The post Human-in-the-Loop Without Killing Throughput appeared first on Towards Data Science.
Be a better communicator with LLM programming
The post Why Claude Code Time Estimates Are Poor appeared first on Towards Data Science.
What happens when you stop feeding a model context and let it go find its own, walking a knowledge graph within strict limits, and what four models and one wrong prediction revealed about whether that is worth doing.
The post Stop Giving Your AI Agent a Search Box and Start Giving It Typed Tools, Hard Bounds, and a Gate It Cannot Talk Past appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #2D] - What data scientists say when asked, what the model actually does under the hood, and why the honest answer changes your architecture decisions in enterprise RAG
The post How Does a RAG Reranker Really Work? appeared first on Towards Data Science.
Work more effectively with your coding agents
The post How to Effectively Solve 100+ Tasks with Claude Code appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #14C] - One hour with two people, six to ten fields, and the two signals that separate a real column from one that will break a filter later
The post One Document Type, a Million Files: Structured Extraction into the SQL Table RAG Queries appeared first on Towards Data Science.
Understanding Codex hooks
The post Put Your Own Logic Inside the Codex Agentic Loop appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #M3] - The ten positions the series argues from, and the map of every article that argues them
The post 10 Positions for Enterprise RAG That Mainstream Tutorials Get Wrong appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #14D] - The index lists what the case type demands before any folder is opened, and the two questions worth building for are not retrieval questions at all
The post Parse the Folder, Not Just the PDFs: The Relational Tables RAG Needs on a Case File appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #14B] - No shared fields means no index to build. One summary line per file plus each file’s own table of contents, and retrieval routes down two levels
The post Multi-Document RAG: A Folder of Unrelated PDFs Is One Long Document with a Nested Outline appeared first on Towards Data Science.
Turning Codex from an interactive assistant into a programmable automation component
The post Running Codex as a Headless Agent appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #7sexies] - The unit of retrieval doesn’t have to be a page or a paragraph. When the corpus carries tables, each body row with its column headers is a chunk in its own right, and it’s often the one row the reader asked about
The post Retrieve One Row from a Table, Not the Whole Table: Row-Level Chunks for RAG appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #14C] - One hour with two people, six to ten fields, and the two signals that separate a real column from one that will break a filter later
The post One Document Type, a Million Files: Structured Extraction into the SQL Table RAG Queries appeared first on Towards Data Science.
Understanding Codex hooks
The post Put Your Own Logic Inside the Codex Agentic Loop appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #M3] - The ten positions the series argues from, and the map of every article that argues them
The post 10 Positions for Enterprise RAG That Mainstream Tutorials Get Wrong appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #14D] - The index lists what the case type demands before any folder is opened, and the two questions worth building for are not retrieval questions at all
The post Parse the Folder, Not Just the PDFs: The Relational Tables RAG Needs on a Case File appeared first on Towards Data Science.
Enterprise Document Intelligence [Vol.1 #14B] - No shared fields means no index to build. One summary line per file plus each file’s own table of contents, and retrieval routes down two levels
The post Multi-Document RAG: A Folder of Unrelated PDFs Is One Long Document with a Nested Outline appeared first on Towards Data Science.
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