Electronic Document Management (EDM) AI Application

Description:

This project aims to develop a sophisticated Electronic Document Management (EDM) application with AI features to enhance research and indexing capabilities. The application focuses on indexing and uploading media to improve search functionalities, utilizing both keyword and semantic search techniques.

Key Features:

- AI-Enhanced Search: Implementing machine learning algorithms to improve the accuracy and relevance of search results, allowing users to find information more effectively.

- Media Indexing: Efficiently indexing various media types (images, documents, etc.) to facilitate fast and comprehensive retrieval.

- Object Storage Integration: Storing indexed media in an object storage solution to ensure scalability and reliability.

- Kafka Integration: Utilizing Kafka for real-time data streaming and processing, allowing for the efficient handling of large volumes of data.

- Modular Architecture: Building the application with a modular architecture to support easy enhancements and the addition of new features in the future.

Technologies Used:

- Backend: FastAPI for building a robust and performant backend.

- AI: Integrating machine learning models for semantic search capabilities.

- Data Streaming: Apache Kafka for managing data flow and ensuring scalability.

- Storage: Object storage solutions for efficient media handling and indexing.

- Containerization: Docker and Docker Compose for local development and deployment.

Use Cases:

- Academic research institutions seeking improved indexing and retrieval of research materials.

- Businesses requiring efficient media management and search capabilities for their digital assets.

- Developers looking for a scalable solution to integrate AI search functionalities into existing applications.