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AI-Powered Historical Document Analysis Platform for Museums

teacode.io

Education

Cultural Heritage

Tourism

Challenge: Inefficient Historical Research

The Polish National Museum System faces the challenge of efficiently researching and extracting valuable insights from its vast and growing collection of historical documents, particularly those related to industries like coal mining. Manual review is time-consuming, labor-intensive, and limits the ability to quickly identify key research topics and connections across documents. The need for multilingual document processing adds to the complexity.

About the Client

A national institution responsible for the preservation and research of Poland's cultural and historical heritage, including extensive archival collections.

Objectives

Develop an AI-powered platform to automate the identification of key research topics within historical documents.
Enable researchers to quickly browse and explore relevant topics and associated source materials.
Reduce the time and effort required for historical research by at least 75%.
Provide multilingual support for document processing and analysis (Polish, German, Russian, Chinese, etc.).
Generate structured reports summarizing research topics and supporting source material citations.

Functional Requirements

Document ingestion from various sources (e.g., Snowflake, file uploads).
Multilingual document processing and analysis.
AI-powered topic clustering and identification.
LLM-based topic refinement and summarization.
Automated report generation in Excel format.
User-friendly web interface for browsing and exploring topics.
Ability to add new documents dynamically.
Page-level citation referencing.

Preferred Technologies

Large Language Models (LLMs)

Clustering Algorithms (e.g., DBSCAN)

Natural Language Processing (NLP)

Embedding Vectors

Streamlit (for user interface)

Snowflake (data storage and processing)

Required Integrations

Snowflake (for data storage and access)
Potential integration with existing museum document management systems.

Non-Functional Requirements

Scalability to handle a growing volume of documents.
Performance to ensure rapid topic identification and report generation.
Data security and privacy compliance.
High availability and reliability.

Expected Business Impact

This project is expected to significantly improve the efficiency and effectiveness of historical research at the Polish National Museum System. By automating key aspects of the research process, the platform will free up researchers' time, enable them to explore new research avenues, and ultimately contribute to a deeper understanding and preservation of Poland's cultural heritage. The multilingual capabilities will broaden the scope of research and facilitate collaboration with international partners.