NotebookLM
Imprecise document grounding
Limited layout awareness
No document editing
See MoDora in Action
From raw documents to grounded answers. MoDora parses, structures, and reasons over your data.
1
Upload2
Parse3
Tree Build4
Retrieval5
AnswerWhy MoDora for Document QA?
MoDora
Structured document tree
Multimodal reasoning
Precise PDF grounding
Editable document structure
OpenClaw
Manual document referencing
Tool call errors
Not specialized for document QA
Key Features
Built for depth and accuracy. MoDora goes beyond simple text matching.
Multimodal Understanding
Seamlessly processes text, tables, and figures from complex documents (PDFs, Papers, Reports).
Tree-Structured Reasoning
Organizes document content into a hierarchical tree to preserve context and structural relationships.
Grounded Citation
Every answer is backed by precise citations pointing to the specific source node in the document tree.
Knowledge Base Integration
Build a comprehensive knowledge base from your document collection for cross-document reasoning.
How It Works
The MoDora Pipeline
Upload Document
User uploads a PDF or document file.
Parse Components
System identifies text blocks, tables, and images.
Build Document Tree
Components are organized into a hierarchical structure.
Tree-Based Retrieval
Relevant nodes are retrieved based on query and structure.
Grounded Generation
LLM generates an answer with citations from retrieved nodes.
Component-Correlation Tree
Unlike traditional RAG that chunks text blindly, MoDora parses documents into a structured tree.
- 1Hierarchical Organization: Sections, subsections, and paragraphs are nodes in a tree.
- 2Multimodal Nodes: Images and tables are treated as first-class citizens, linked to their context.
- 3Contextual Retrieval: Retrieving a node can automatically pull in parent context or child details.
TREE VIEW