This project aims to develop a React-based web application that leverages fine-tuned Large Language Models (LLMs) to assist customer service teams in generating professional email responses. The system integrates with existing customer service platforms to provide AI-generated, contextually relevant responses to customer inquiries, significantly reducing response times while maintaining high-quality communications.
The AI-generated responses are designed to be reviewed and edited by customer service agents, allowing for human oversight and ensuring appropriateness. The project also incorporates a feedback mechanism where users can rate the AI’s suggestions, improving the model's performance over time.
| Folder | Description |
|---|---|
| Documentation | all documentation the project team has created to describe the architecture, design, installation, and configuration of the project |
| Notes and Research | Relevant helpful information to understand the tools and techniques used in the project |
| Project Deliverables | Folder that contains final pdf versions of all Fall and Spring Major Deliverables |
| Status Reports | Project management documentation - weekly reports, milestones, etc. |
| scr | Source code - create as many subdirectories as needed |
- Keroles Hakem - CoStar Group - Mentor
- Preetam Ghosh - Computer Science - Faculty Advisor
- Sohil Marreddi - Computer Science - Student Team Member
- Cameron Clyde - Computer Science - Student Team Member
- Emma Smith - Computer Science - Student Team Member
- Angela Harris - Computer Science - Student Team Member