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Multimodal Document Processing

Advanced AI system for processing complex policy documents with text, figures, and tables using cutting-edge multimodal technologies

Year:2025Type:project

Project Overview

Challenge

Processing complex policy documents containing mixed content types (text, figures, tables) while maintaining context and relationships between different elements.

Solution

Implemented advanced multimodal AI processing pipeline that understands and extracts information from text, images, and structured data within documents, integrating everything into a unified knowledge graph.

Key Features

Advanced text extraction from complex PDF documents
Figure and table understanding with computer vision
Multi-format document support (PDF, JSON, Excel, TXT)
Semantic content analysis and knowledge extraction
Knowledge graph integration with Microsoft GraphRAG
Automated document categorization and tagging
Real-time processing pipeline with zero human intervention
Cross-document relationship identification

Results & Impact

Enables comprehensive analysis of complex policy documents, dramatically improving information accessibility and insights extraction for climate policy research.

2025
Project Year
Active
Status
project
Type

Impact & Results

Project Impact

Enables comprehensive analysis of complex policy documents, dramatically improving information accessibility and insights extraction for climate policy research.

Key Achievements:

Future Impact

This project contributes valuable insights to the advancement of AI research and practical applications.

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