Towards Data Science July 17, 2026 By angela shi

One RAG Pipeline, Four Very Different PDFs: Same Four Bricks, Every Answer Typed and Cited

Read the original on Towards Data Science →

Enterprise Document Intelligence [Vol. 1 #9B] - One call wires the four upgraded bricks together, run on a paper, a NIST standard, and a report with a broken TOC The post One RAG Pipeline, Four Very Different PDFs: Same Four Bricks, Every Answer Typed and Cited appeared first on Towards Data Science .

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Towards Data Science

Jul 17

A Production RAG Pipeline in Action: Every Answer Typed and Cited

Enterprise Document Intelligence [Vol. 1 #9B] - One call wires the four upgraded bricks together, run on a paper, a NIST standard, and a report with a broken TOC The post A Production RAG Pipeline in Action: Every Answer Typed and Cited appeared first on Towards Data Science .

By angela shi

rag

Towards Data Science

Jul 7

A Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers

Enterprise Document Intelligence [Vol. 1 #9A] - Same paper, same question as Article 1.

By angela shi

rag

Towards Data Science

Jun 9

10 Common RAG Mistakes We Keep Seeing in Production

Enterprise Document Intelligence [Vol. 1 #4bis] - A coauthor note on the brick-by-brick pitfalls that justified the four-brick split, before Part II walks the fixes The post 10 Common RAG Mistakes We Keep Seeing in Production appeared first on Towards Data Science .

By Kezhan Shi

rag

Towards Data Science

Aug 6

Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.2’ Instead of the Actual Answer

Enterprise Document Intelligence [Vol. 1 #11] - When the first answer points elsewhere in the document, the pipeline loops back to fetch the linked context The post Loop Engineering for Cross-References: When RAG Answers ‘see Section 7.

By angela shi

rag

Towards Data Science

May 29

Baseline Enterprise RAG, From PDF to Highlighted Answer

Enterprise Document Intelligence [Vol. 1 #1] The smallest version of RAG that actually works, on a real PDF, with grounded answers and the source lines highlighted.

By angela shi

rag

Towards Data Science

Sep 2

A RAG That Says “Not in This Document” Has to Show Four Kinds of Evidence

The article discusses the importance of a Retrieval-Augmented Generation (RAG) system providing clear evidence when it states that information is not present in a document. It outlines four distinct types of evidence that should accompany such a claim to avoid presenting a confident but incorrect answer or an unsupported “no answer.” The piece emphasizes that each evidence type serves as a safeguard against misinformation in enterprise document intelligence.

By Kezhan Shi

rag

One email a morning, machine-written

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