Enterprise AI Analysis
A Multimodal Framework for Eurobarometer Data Analysis
This study introduces a novel multimodal framework integrating retrieval-augmented generation (RAG) with multimodal large language models (MLLMs) to enhance the accessibility, interpretability, and analysis of Eurobarometer survey data.
Executive Impact
Our framework delivers measurable improvements in data analysis efficiency and depth for Eurobarometer surveys.
91%
Citizens believe EU humanitarian aid is important
71%
Believe aid is more efficient when coordinated by the EU
€1.5B
Annual EU spending on humanitarian aid (min)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
The study introduces a novel multimodal RAG framework that leverages MLLMs to process diverse data formats, including textual and visual elements from Eurobarometer surveys.
- Enhanced Data Accessibility: Unifies complex data formats into a single, interpretable system.
- Improved Interpretability: Advanced synthesis of insights provides a holistic understanding of public opinion trends.
Offers significant benefits to policymakers, journalists, NGOs, and researchers by enabling data-driven decision-making and efficient knowledge extraction.
- Supports Policymaking: Provides valuable insights for strategic planning and policy development.
- Streamlines Fact-Checking: Enables journalists to communicate accurate and reliable information.
Integrates state-of-the-art AI techniques like MLLMs and RAG with modular design principles for adaptability and scalability.
- Multimodal Indexing: Processes plain text, PDFs, and images for comprehensive data retrieval.
- Agent-Based Q&A: Employs conversational agents with memory for context-aware interactions.
91%
EU citizens believe EU funding for humanitarian aid activities is important.
Enterprise Process Flow
Press Release & PDFs
→
CLIP & Pre-processor
→
Embedding Retriever
→
FAISS Index (Text & Images)
→
RAG Query Stage
| Feature | Text-based RAG | Image-based RAG |
|---|---|---|
| Data Modality |
|
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| Retrieval Mechanism |
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EU Humanitarian Aid Survey Analysis
The framework successfully analyzed the EU Humanitarian Aid survey (Sep-Oct 2023), integrating text and image data. Agents collaborated to provide a comprehensive overview, highlighting public sentiment and financial aspects. This demonstrated its ability to offer in-depth insights from complex, mixed-format datasets, supporting evidence-based decision-making for policymakers and researchers.
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Estimated Annual Savings
$0
Annual Hours Reclaimed
0
Your AI Implementation Roadmap
A strategic, phased approach to integrating advanced AI into your enterprise operations.
Phase 1: Data Ingestion & Indexing
Establish robust pipelines for ingesting and indexing diverse Eurobarometer data formats, including text, PDFs, and images, creating vectorized representations for efficient retrieval.
Phase 2: RAG Pipeline Configuration
Develop and fine-tune simple RAG and image-integrated RAG pipelines, ensuring accurate and contextually relevant data retrieval based on user queries.
Phase 3: Agent-Based Conversational System
Implement and configure conversational agents with memory, enabling dynamic, context-aware interactions and advanced synthesis of insights.
Phase 4: UI Development & User Testing
Design and implement a user-friendly interface for querying and interaction, followed by rigorous user testing to optimize accessibility and effectiveness.
Phase 5: Performance Validation & Iteration
Conduct performance assessments, evaluate the framework against specific business requirements, and gather user feedback for continuous improvement and expanded functionalities.
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