Enterprise Document Intelligence [Vol.1 #B2] - The FAQ inverts every brick of the standard RAG pipeline. Parsing is trivial, retrieval doubles as a cache, and few-shot prompting becomes a retrieval problem too

The post FAQ as RAG: When You Get to Design the Corpus appeared first on Towards Data Science.

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.

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.