Project Purpose
Develop a system that automatically categorizes incoming support tickets based on their content, improving ticket resolution efficiency.
Goals
- Design a system that utilizes NLP techniques to extract meaning from support ticket text.
- Automate ticket classification by assigning relevant tags and routing tickets to appropriate support teams.
- Reduce support resolution times by ensuring tickets reach the specialists best equipped to handle them.
Challenges
- Natural language ambiguity: Interpreting the intent and meaning behind different writing styles and terminology.
- Handling unstructured data: Support tickets can contain informal language, typos, and varying formats.
- Evolving customer language: The system needs to adapt to new terminology and phrasing used in support requests.
Achievements
- Developed a support ticket categorization system with high accuracy in classifying incoming tickets.
- Leveraged large language models and transformers to extract key information and assign relevant tags to tickets.
- Designed the system to be scalable and adaptable to evolving customer language patterns.
