Who is doing the best Word/PDF RAG tool with deep research?

Question

Hi HN, which SaaS providers are you eyeing up these days for your RAG needs with thousands of PDFs or Word docs and with a agent that can take its time and give well researched, cited answers? TIA!

randomname4325 · Accepted Answer

checkout www.Airwave.us. They are focused on field services where techs comb through thousands of pages of manuals/documentation for part numbers or specific instructions that have to be 100% accurate.

Norcim133 · Answer

I spent the last 2 months trying out RAG/parsing plays. My use-case required high accuracy on complex tables and figures.Ranking: 1. LlamaCloud/LlamaParse 2. GroundX 3. Unstructured.io 4. Google RAG Engine 5. Docling ... capability gap... 6. Azure - Document Intelligence 7. AWS - Textract 8. LlamaIndex (DIY)

TXTOS · Answer

I've been working on something that directly targets this problem: WFGY — a reasoning engine built for RAG on large-scale PDF/Word documents, especially when you're doing deep research, not just shallow QA.
Instead of just chunking text and throwing it into an embedding model, WFGY builds a persistent semantic resonance layer — meaning it tracks context through formatting breaks, footnotes, diagram captions, even corrupted OCR sections.
The engine applies multiple self-correcting pathways (we call them BBMC and BBPF) so even when parsing is incomplete or wrong, reasoning still holds. That’s crucial if your source materials are academic papers, messy reports, or 1000+ page archives.
It’s open source. No tuning. Works with any LLM. No tricks.
Backed by the creator of tesseract.js (36k) — who gets why document mess is the real challenge.
Check it out: https://github.com/onestardao/WFGY