High Tech — Automated Document Classification for Enhanced Organization

Overview

The purpose of this DAG is to streamline document management in the high-tech industry by utilizing machine learning models to automatically classify incoming documents based on their content. The process begins with the ingestion of documents from various sources, such as email attachments, cloud storage, and internal databases. Once ingested, the documents undergo a series of processing steps where natural language processing (NLP) algorithms analyze the text to determine their appropriate cat

The purpose of this DAG is to streamline document management in the high-tech industry by utilizing machine learning models to automatically classify incoming documents based on their content. The process begins with the ingestion of documents from various sources, such as email attachments, cloud storage, and internal databases. Once ingested, the documents undergo a series of processing steps where natural language processing (NLP) algorithms analyze the text to determine their appropriate categories. Quality control measures are implemented to ensure the accuracy of the classifications, including validation checks and feedback loops that refine model performance over time. The classified results are then integrated into the KM2 portal, which enhances user experience by facilitating easier navigation and search functionalities. Key performance indicators (KPIs) for monitoring the effectiveness of this DAG include classification accuracy rates, processing time per document, and user engagement metrics within the KM2 portal. The business value of this solution lies in its ability to reduce manual sorting efforts, improve operational efficiency, and enhance data accessibility, ultimately leading to better decision-making and resource allocation in high-tech organizations.

Part of the Data & Model Catalog solution for the High Tech industry.

Use cases

• Reduces manual document handling and sorting time
• Improves accuracy in document categorization
• Enhances user experience through better searchability
• Facilitates quicker access to relevant information
• Supports data-driven decision-making processes