AI/AIZENME
📊 RESEARCH · Deep Research Level: Intermediate ⏱ 30 MIN Free & Open Source

Build a High-Accuracy Knowledge Base over Complex Tables & Scanned PDFs with Open-Source RAGFlow

Stop naive chunking from destroying multi-page financial tables and technical specs. Use open-source RAGFlow with DeepDoc layout recognition and visual citation grounding.

CORE TOOLS RAGFlow (Open Source), DeepSeek / Qwen, BGE-Reranker
BEST FOR Financial analysts, QA/cost engineers, legal compliance teams, knowledge managers
REQUIREMENTS 16GB+ RAM machine running Docker
✦ WHY THIS WORKFLOW

Most RAG failures happen because naive text splitters shred tables and multi-column layouts. RAGFlow solves this at the root with visual layout parsing and bounding-box citations.

✦ Interactive Workflow Animation Preview

Step-by-Step Action Checklist

0 / 4 Completed
READY-TO-USE PROMPT TEMPLATE
Open Official Tool / Repo ↗ 
I am building a knowledge base in open-source RAGFlow for [use case: e.g., IPO prospectuses & annual reports / engineering standards].
Provide:
1) The best built-in RAGFlow chunking template, recommended token size and hybrid search weight ratio (vector vs. full-text) for table-heavy PDFs;
2) A strict anti-hallucination System Prompt requiring the assistant to quote exact table cells before calculating and attach page citations.
Use Cases & Tags:
IPO prospectus & annual report table QAEngineering standard & regulatory code lookupIndustrial equipment manual searchLegal due diligence cross-checking#ragflow
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