Life Science — User Intent Classification for Query Automation

Free

This DAG automates the classification of user intents to streamline responses to frequent queries. By leveraging data from ticketing systems and CRM platforms, it enhances knowledge management efficiency in the life sciences sector.

Weeki Logo

Overview

The purpose of this DAG is to classify user intents to automate responses to common queries, thereby improving operational efficiency and user satisfaction in the life sciences industry. It ingests data from various sources, including ticketing systems and customer relationship management (CRM) platforms, which provide insights into user inquiries. The ingestion pipeline begins with data extraction from these systems, followed by preprocessing steps that clean and normalize the data for analysis

The purpose of this DAG is to classify user intents to automate responses to common queries, thereby improving operational efficiency and user satisfaction in the life sciences industry. It ingests data from various sources, including ticketing systems and customer relationship management (CRM) platforms, which provide insights into user inquiries. The ingestion pipeline begins with data extraction from these systems, followed by preprocessing steps that clean and normalize the data for analysis. The core processing involves applying advanced classification models to categorize user intents accurately. Once classified, the responses are integrated into a knowledge management system, ensuring that users receive timely and relevant information. Quality control measures are implemented through manual reviews of classifications, ensuring accuracy and reliability. In cases where the classification fails or requires further intervention, alert mechanisms are triggered for prompt resolution. Key performance indicators (KPIs) include classification accuracy, response time, and user satisfaction metrics, which are monitored to assess the effectiveness of the automation process. This DAG not only streamlines query handling but also enhances the overall knowledge management capabilities within the life sciences sector, leading to improved operational efficiencies and better resource allocation.

Part of the Literature Review solution for the Life Science industry.

Use cases

  • Reduces response time for user queries
  • Enhances accuracy of information provided to users
  • Improves resource allocation through automation
  • Increases user satisfaction and engagement
  • Supports compliance with industry regulations

Technical Specifications

Inputs

  • User query data from ticketing systems
  • Customer interaction logs from CRM platforms
  • Historical classification data for model training

Outputs

  • Classified user intents for automated responses
  • Updated knowledge base with integrated responses
  • Quality control reports on classification accuracy

Processing Steps

  1. 1. Extract data from ticketing systems and CRM
  2. 2. Preprocess and clean user query data
  3. 3. Apply classification models to categorize intents
  4. 4. Integrate classified responses into knowledge management system
  5. 5. Conduct manual reviews for quality assurance
  6. 6. Trigger alerts for classification failures

Additional Information

DAG ID

WK-1439

Last Updated

2025-09-08

Downloads

79

Tags